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1

Value of Wind Power Forecasting  

DOE Green Energy (OSTI)

This study, building on the extensive models developed for the Western Wind and Solar Integration Study (WWSIS), uses these WECC models to evaluate the operating cost impacts of improved day-ahead wind forecasts.

Lew, D.; Milligan, M.; Jordan, G.; Piwko, R.

2011-04-01T23:59:59.000Z

2

Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations  

E-Print Network (OSTI)

Power Forecasting in Five U.S. Electricity Markets MISO NYISO PJM ERCOT CAISO Peak load 109,157 MW (7 ........................................................................................... 18 4 WIND POWER FORECASTING AND ELECTRICITY MARKET OPERATIONS............................................................ 18 4-1 Market Operation and Wind Power Forecasting in Five U.S. Electricity Markets .......... 21 #12

Kemner, Ken

3

Wind Speed Forecasting for Power System Operation  

E-Print Network (OSTI)

In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system operation in terms of the efficiency of the system. The goal of this dissertation is to develop advanced statistical wind speed predictive models to reduce the uncertainties in wind, especially the short-term future wind speed. Moreover, a criterion is proposed to evaluate the performance of models. Cost reduction in power system operation, as proposed, is more realistic than prevalent criteria, such as, root mean square error (RMSE) and absolute mean error (MAE). Two advanced space-time statistical models are introduced for short-term wind speed forecasting. One is a modified regime-switching, space-time wind speed fore- casting model, which allows the forecast regimes to vary according to the dominant wind direction and seasons. Thus, it avoids a subjective choice of regimes. The other one is a novel model that incorporates a new variable, geostrophic wind, which has strong influence on the surface wind, into one of the advanced space-time statistical forecasting models. This model is motivated by the lack of improvement in forecast accuracy when using air pressure and temperature directly. Using geostrophic wind in the model is not only critical, it also has a meaningful geophysical interpretation. The importance of model evaluation is emphasized in the dissertation as well. Rather than using RMSE or MAE, the performance of both wind forecasting models mentioned above are assessed by economic benefits with real wind farm data from Pacific Northwest of the U.S and West Texas. Wind forecasts are incorporated into power system economic dispatch models, and the power system operation cost is used as a loss measure for the performance of the forecasting models. From another perspective, the new criterion leads to cost-effective scheduling of system-wide wind generation with potential economic benefits arising from the system-wide generation of cost savings and ancillary services cost savings. As an illustration, the integrated forecasts and economic dispatch framework are applied to the Electric Reliability Council of Texas (ERCOT) equivalent 24- bus system. Compared with persistence and autoregressive models, the first model suggests that cost savings from integration of wind power could be on the scale of tens of millions of dollars. For the second model, numerical simulations suggest that the overall generation cost can be reduced by up to 6.6% using look-ahead dispatch coupled with spatio-temporal wind forecast as compared with dispatch with persistent wind forecast model.

Zhu, Xinxin

2013-08-01T23:59:59.000Z

4

Distribution of Wind Power Forecasting Errors from Operational Systems (Presentation)  

SciTech Connect

This presentation offers new data and statistical analysis of wind power forecasting errors in operational systems.

Hodge, B. M.; Ela, E.; Milligan, M.

2011-10-01T23:59:59.000Z

5

A survey on wind power ramp forecasting.  

DOE Green Energy (OSTI)

The increasing use of wind power as a source of electricity poses new challenges with regard to both power production and load balance in the electricity grid. This new source of energy is volatile and highly variable. The only way to integrate such power into the grid is to develop reliable and accurate wind power forecasting systems. Electricity generated from wind power can be highly variable at several different timescales: sub-hourly, hourly, daily, and seasonally. Wind energy, like other electricity sources, must be scheduled. Although wind power forecasting methods are used, the ability to predict wind plant output remains relatively low for short-term operation. Because instantaneous electrical generation and consumption must remain in balance to maintain grid stability, wind power's variability can present substantial challenges when large amounts of wind power are incorporated into a grid system. A critical issue is ramp events, which are sudden and large changes (increases or decreases) in wind power. This report presents an overview of current ramp definitions and state-of-the-art approaches in ramp event forecasting.

Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J. (Decision and Information Sciences); (INESC Porto)

2011-02-23T23:59:59.000Z

6

Managing Wind Power Forecast Uncertainty in Electric Grids.  

E-Print Network (OSTI)

??Electricity generated from wind power is both variable and uncertain. Wind forecasts provide valuable information for wind farm management, but they are not perfect. Chapter… (more)

Mauch, Brandon Keith

2012-01-01T23:59:59.000Z

7

ANL Wind Power Forecasting and Electricity Markets | Open Energy  

Open Energy Info (EERE)

ANL Wind Power Forecasting and Electricity Markets ANL Wind Power Forecasting and Electricity Markets Jump to: navigation, search Logo: Wind Power Forecasting and Electricity Markets Name Wind Power Forecasting and Electricity Markets Agency/Company /Organization Argonne National Laboratory Partner Institute for Systems and Computer Engineering of Porto (INESC Porto) in Portugal, Midwest Independent System Operator and Horizon Wind Energy LLC, funded by U.S. Department of Energy Sector Energy Focus Area Wind Topics Pathways analysis, Technology characterizations Resource Type Software/modeling tools Website http://www.dis.anl.gov/project References Argonne National Laboratory: Wind Power Forecasting and Electricity Markets[1] Abstract To improve wind power forecasting and its use in power system and electricity market operations Argonne National Laboratory has assembled a team of experts in wind power forecasting, electricity market modeling, wind farm development, and power system operations.

8

Wind Power Forecasting Error Distributions over Multiple Timescales (Presentation)  

DOE Green Energy (OSTI)

This presentation presents some statistical analysis of wind power forecast errors and error distributions, with examples using ERCOT data.

Hodge, B. M.; Milligan, M.

2011-07-01T23:59:59.000Z

9

Optimal Bidding Strategies for Wind Power Producers with Meteorological Forecasts  

E-Print Network (OSTI)

bid is computed by exploiting the forecast energy price for the day ahead market, the historical windOptimal Bidding Strategies for Wind Power Producers with Meteorological Forecasts Antonio statistics at the plant site and the day-ahead wind speed forecasts provided by a meteorological service. We

Giannitrapani, Antonello

10

Impact of Wind PowerImpact of Wind Power Forecasting on Unit  

E-Print Network (OSTI)

Impact of Wind PowerImpact of Wind Power Forecasting on Unit Commitment and Dispatchp Jianhui Wang and University of Porto, Portugal 8th Int. Wind Integration Workshop, Bremen, Germany, Oct. 14 2009 #12;Outline of the information in wind power forecasts in system and market operationsin system and market operations Stochastic

Hudson, Randy

11

Short-Term Wind Speed Forecasting for Power System Operations  

E-Print Network (OSTI)

Global large scale penetration of wind energy is accompanied by significant challenges due to the intermittent and unstable nature of wind. High quality short-term wind speed forecasting is critical to reliable and secure power system operations. This paper gives an overview of the current status of worldwide wind power developments and future trends, and reviews some statistical short-term wind speed forecasting models, including traditional time series models and advanced space-time statistical models. It also discusses the evaluation of forecast accuracy, in particular the need for realistic loss functions. New challenges in wind speed forecasting regarding ramp events and offshore wind farms are also presented.

Xinxin Zhu; Marc G. Genton

2011-01-01T23:59:59.000Z

12

Short term wind power forecasting using time series neural networks  

Science Conference Proceedings (OSTI)

Forecasting wind power energy is very important issue in a liberalized market and the prediction tools can make wind energy be competitive in these kinds of markets. This paper will study an application of time-series and neural network for predicting ... Keywords: neural networks, time series, wind power forecasting

Mohammadsaleh Zakerinia; Seyed Farid Ghaderi

2011-04-01T23:59:59.000Z

13

A Short-Term Ensemble Wind Speed Forecasting System for Wind Power Applications  

Science Conference Proceedings (OSTI)

This study develops an adaptive, blended forecasting system to provide accurate wind speed forecasts 1 h ahead of time for wind power applications. The system consists of an ensemble of 21 forecasts with different configurations of the Weather ...

Justin J. Traiteur; David J. Callicutt; Maxwell Smith; Somnath Baidya Roy

2012-10-01T23:59:59.000Z

14

Wind power forecasting in U.S. electricity markets.  

Science Conference Proceedings (OSTI)

Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts.

Botterud, A.; Wang, J.; Miranda, V.; Bessa, R. J.; Decision and Information Sciences; INESC Porto

2010-04-01T23:59:59.000Z

15

Wind power forecasting in U.S. Electricity markets  

Science Conference Proceedings (OSTI)

Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts. (author)

Botterud, Audun; Wang, Jianhui; Miranda, Vladimiro; Bessa, Ricardo J.

2010-04-15T23:59:59.000Z

16

Wind Power Forecasting Error Distributions: An International Comparison; Preprint  

DOE Green Energy (OSTI)

Wind power forecasting is expected to be an important enabler for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that do occur can be critical to system operation functions, such as the setting of operating reserve levels. This paper provides an international comparison of the distribution of wind power forecasting errors from operational systems, based on real forecast data. The paper concludes with an assessment of similarities and differences between the errors observed in different locations.

Hodge, B. M.; Lew, D.; Milligan, M.; Holttinen, H.; Sillanpaa, S.; Gomez-Lazaro, E.; Scharff, R.; Soder, L.; Larsen, X. G.; Giebel, G.; Flynn, D.; Dobschinski, J.

2012-09-01T23:59:59.000Z

17

Comparison of Wind Power and Load Forecasting Error Distributions: Preprint  

DOE Green Energy (OSTI)

The introduction of large amounts of variable and uncertain power sources, such as wind power, into the electricity grid presents a number of challenges for system operations. One issue involves the uncertainty associated with scheduling power that wind will supply in future timeframes. However, this is not an entirely new challenge; load is also variable and uncertain, and is strongly influenced by weather patterns. In this work we make a comparison between the day-ahead forecasting errors encountered in wind power forecasting and load forecasting. The study examines the distribution of errors from operational forecasting systems in two different Independent System Operator (ISO) regions for both wind power and load forecasts at the day-ahead timeframe. The day-ahead timescale is critical in power system operations because it serves the unit commitment function for slow-starting conventional generators.

Hodge, B. M.; Florita, A.; Orwig, K.; Lew, D.; Milligan, M.

2012-07-01T23:59:59.000Z

18

Use of wind power forecasting in operational decisions.  

DOE Green Energy (OSTI)

The rapid expansion of wind power gives rise to a number of challenges for power system operators and electricity market participants. The key operational challenge is to efficiently handle the uncertainty and variability of wind power when balancing supply and demand in ths system. In this report, we analyze how wind power forecasting can serve as an efficient tool toward this end. We discuss the current status of wind power forecasting in U.S. electricity markets and develop several methodologies and modeling tools for the use of wind power forecasting in operational decisions, from the perspectives of the system operator as well as the wind power producer. In particular, we focus on the use of probabilistic forecasts in operational decisions. Driven by increasing prices for fossil fuels and concerns about greenhouse gas (GHG) emissions, wind power, as a renewable and clean source of energy, is rapidly being introduced into the existing electricity supply portfolio in many parts of the world. The U.S. Department of Energy (DOE) has analyzed a scenario in which wind power meets 20% of the U.S. electricity demand by 2030, which means that the U.S. wind power capacity would have to reach more than 300 gigawatts (GW). The European Union is pursuing a target of 20/20/20, which aims to reduce greenhouse gas (GHG) emissions by 20%, increase the amount of renewable energy to 20% of the energy supply, and improve energy efficiency by 20% by 2020 as compared to 1990. Meanwhile, China is the leading country in terms of installed wind capacity, and had 45 GW of installed wind power capacity out of about 200 GW on a global level at the end of 2010. The rapid increase in the penetration of wind power into power systems introduces more variability and uncertainty in the electricity generation portfolio, and these factors are the key challenges when it comes to integrating wind power into the electric power grid. Wind power forecasting (WPF) is an important tool to help efficiently address this challenge, and significant efforts have been invested in developing more accurate wind power forecasts. In this report, we document our work on the use of wind power forecasting in operational decisions.

Botterud, A.; Zhi, Z.; Wang, J.; Bessa, R.J.; Keko, H.; Mendes, J.; Sumaili, J.; Miranda, V. (Decision and Information Sciences); (INESC Porto)

2011-11-29T23:59:59.000Z

19

New Concepts in Wind Power Forecasting Models  

E-Print Network (OSTI)

of the motivations behind the project led by ANL ­ Argonne National Laboratory, together with INESC Porto from a manageable procedure to compute the solution. IV. ENTROPY AND PARZEN WINDOW PDF ESTIMATION The most well into the substation connecting it to the electric power network. Other model's input variables include forecasts

Kemner, Ken

20

Development and testing of improved statistical wind power forecasting methods.  

DOE Green Energy (OSTI)

Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios (with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.

Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J. (Decision and Information Sciences); (INESC Porto)

2011-12-06T23:59:59.000Z

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

Managing Wind Power Forecast Uncertainty in Electric Brandon Keith Mauch  

E-Print Network (OSTI)

i Managing Wind Power Forecast Uncertainty in Electric Grids Brandon Keith Mauch Co in Electric Grids Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy for aggregated wind farms are often modeled with Gaussian distributions. However, data from several studies have

22

Status of Centralized Wind Power Forecasting in North America: May 2009-May 2010  

SciTech Connect

Report surveys grid wind power forecasts for all wind generators, which are administered by utilities or regional transmission organizations (RTOs), typically with the assistance of one or more wind power forecasting companies.

Porter, K.; Rogers, J.

2010-04-01T23:59:59.000Z

23

Powering up with space-time wind forecasting  

E-Print Network (OSTI)

The technology to harvest electricity from wind energy is now advanced enough to make entire cities powered by it a reality. High-quality short-term forecasts of wind speed are vital to making this a more reliable energy source. Gneiting et al. (2006) have introduced a model for the average wind speed two hours ahead based on both spatial and temporal information. The forecasts produced by this model are accurate, and subject to accuracy, the predictive distribution is sharp, i.e., highly concentrated around its center. However, this model is split into nonunique regimes based on the wind direction at an off-site location. This paper both generalizes and improves upon this model by treating wind direction as a circular variable and including it in the model. It is robust in many experiments, such as predicting at new locations. We compare this with the more common approach of modeling wind speeds and directions in the Cartesian space and use a skew-t distribution for the errors. The quality of the predictions from all of these models can be more realistically assessed with a loss measure that depends upon the power curve relating wind speed to power output. This proposed loss measure yields more insight into the true value of each model’s predictions. Some key words: Circular variable, power curve, skew-t distribution, wind direction, wind speed.

A S. Hering; Marc G. Genton

2009-01-01T23:59:59.000Z

24

European Wind Energy Conference -Brussels, Belgium, April 2008 Data mining for wind power forecasting  

E-Print Network (OSTI)

European Wind Energy Conference - Brussels, Belgium, April 2008 Data mining for wind power-term forecasting of wind energy produc- tion up to 2-3 days ahead is recognized as a major contribution the improvement of predic- tion systems performance is recognised as one of the priorities in wind energy research

Paris-Sud XI, Université de

25

Central Wind Power Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities  

DOE Green Energy (OSTI)

The report addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America.

Porter, K.; Rogers, J.

2009-12-01T23:59:59.000Z

26

Statistical Wind Power Forecasting Models: Results for U.S. Wind Farms; Preprint  

DOE Green Energy (OSTI)

Electricity markets in the United States are evolving. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast makes it possible for grid operators to schedule the economically efficient generation to meet the demand of electrical customers. In the evolving markets, some form of auction is held for various forward markets, such as hour ahead or day ahead. This paper develops several statistical forecasting models that can be useful in hour-ahead markets that have a similar tariff. Although longer-term forecasting relies on numerical weather models, the statistical models used here focus on the short-term forecasts that can be useful in the hour-ahead markets. We investigate the extent to which time-series analysis can improve on simplistic persistence forecasts. This project applied a class of models known as autoregressive moving average (ARMA) models to both wind speed and wind power output.

Milligan, M.; Schwartz, M.; Wan, Y.

2003-05-01T23:59:59.000Z

27

Statistical Wind Power Forecasting for U.S. Wind Farms: Preprint  

DOE Green Energy (OSTI)

Electricity markets in the United States are evolving. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast allows grid operators to schedule economically efficient generation to meet the demand of electrical customers. The evolving markets hold some form of auction for various forward markets, such as hour ahead or day ahead. This paper describes several statistical forecasting models that can be useful in hour-ahead markets. Although longer-term forecasting relies on numerical weather models, the statistical models used here focus on the short-term forecasts that can be useful in the hour-ahead markets. The purpose of the paper is not to develop forecasting models that can compete with commercially available models. Instead, we investigate the extent to which time-series analysis can improve simplistic persistence forecasts. This project applied a class of models known as autoregressive moving average (A RMA) models to both wind speed and wind power output. The results from wind farms in Minnesota, Iowa, and along the Washington-Oregon border indicate that statistical modeling can provide a significant improvement in wind forecasts compared to persistence forecasts.

Milligan, M.; Schwartz, M. N.; Wan, Y.

2003-11-01T23:59:59.000Z

28

Impacts of Improved Day-Ahead Wind Forecasts on Power Grid Operations: September 2011  

DOE Green Energy (OSTI)

This study analyzed the potential benefits of improving the accuracy (reducing the error) of day-ahead wind forecasts on power system operations, assuming that wind forecasts were used for day ahead security constrained unit commitment.

Piwko, R.; Jordan, G.

2011-11-01T23:59:59.000Z

29

Wind Power Forecasting Error Frequency Analyses for Operational Power System Studies: Preprint  

DOE Green Energy (OSTI)

The examination of wind power forecasting errors is crucial for optimal unit commitment and economic dispatch of power systems with significant wind power penetrations. This scheduling process includes both renewable and nonrenewable generators, and the incorporation of wind power forecasts will become increasingly important as wind fleets constitute a larger portion of generation portfolios. This research considers the Western Wind and Solar Integration Study database of wind power forecasts and numerical actualizations. This database comprises more than 30,000 locations spread over the western United States, with a total wind power capacity of 960 GW. Error analyses for individual sites and for specific balancing areas are performed using the database, quantifying the fit to theoretical distributions through goodness-of-fit metrics. Insights into wind-power forecasting error distributions are established for various levels of temporal and spatial resolution, contrasts made among the frequency distribution alternatives, and recommendations put forth for harnessing the results. Empirical data are used to produce more realistic site-level forecasts than previously employed, such that higher resolution operational studies are possible. This research feeds into a larger work of renewable integration through the links wind power forecasting has with various operational issues, such as stochastic unit commitment and flexible reserve level determination.

Florita, A.; Hodge, B. M.; Milligan, M.

2012-08-01T23:59:59.000Z

30

A Quick Guide to Wind Power Forecasting: State-of-the-Art 2009  

E-Print Network (OSTI)

challenges with regard to both power production and load balance in the electricity grid. This new source reliable and accurate wind power forecasting systems. Electricity generated from wind power can be highly other electricity sources, must be scheduled. Although wind power forecasting methods are used

Kemner, Ken

31

Wind power forecasting : state-of-the-art 2009.  

DOE Green Energy (OSTI)

Many countries and regions are introducing policies aimed at reducing the environmental footprint from the energy sector and increasing the use of renewable energy. In the United States, a number of initiatives have been taken at the state level, from renewable portfolio standards (RPSs) and renewable energy certificates (RECs), to regional greenhouse gas emission control schemes. Within the U.S. Federal government, new energy and environmental policies and goals are also being crafted, and these are likely to increase the use of renewable energy substantially. The European Union is pursuing implementation of its ambitious 20/20/20 targets, which aim (by 2020) to reduce greenhouse gas emissions by 20% (as compared to 1990), increase the amount of renewable energy to 20% of the energy supply, and reduce the overall energy consumption by 20% through energy efficiency. With the current focus on energy and the environment, efficient integration of renewable energy into the electric power system is becoming increasingly important. In a recent report, the U.S. Department of Energy (DOE) describes a model-based scenario, in which wind energy provides 20% of the U.S. electricity demand in 2030. The report discusses a set of technical and economic challenges that have to be overcome for this scenario to unfold. In Europe, several countries already have a high penetration of wind power (i.e., in the range of 7 to 20% of electricity consumption in countries such as Germany, Spain, Portugal, and Denmark). The rapid growth in installed wind power capacity is expected to continue in the United States as well as in Europe. A large-scale introduction of wind power causes a number of challenges for electricity market and power system operators who will have to deal with the variability and uncertainty in wind power generation when making their scheduling and dispatch decisions. Wind power forecasting (WPF) is frequently identified as an important tool to address the variability and uncertainty in wind power and to more efficiently operate power systems with large wind power penetrations. Moreover, in a market environment, the wind power contribution to the generation portofolio becomes important in determining the daily and hourly prices, as variations in the estimated wind power will influence the clearing prices for both energy and operating reserves. With the increasing penetration of wind power, WPF is quickly becoming an important topic for the electric power industry. System operators (SOs), generating companies (GENCOs), and regulators all support efforts to develop better, more reliable and accurate forecasting models. Wind farm owners and operators also benefit from better wind power prediction to support competitive participation in electricity markets against more stable and dispatchable energy sources. In general, WPF can be used for a number of purposes, such as: generation and transmission maintenance planning, determination of operating reserve requirements, unit commitment, economic dispatch, energy storage optimization (e.g., pumped hydro storage), and energy trading. The objective of this report is to review and analyze state-of-the-art WPF models and their application to power systems operations. We first give a detailed description of the methodologies underlying state-of-the-art WPF models. We then look at how WPF can be integrated into power system operations, with specific focus on the unit commitment problem.

Monteiro, C.; Bessa, R.; Miranda, V.; Botterud, A.; Wang, J.; Conzelmann, G.; Decision and Information Sciences; INESC Porto

2009-11-20T23:59:59.000Z

32

Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison (Presentation)  

Science Conference Proceedings (OSTI)

This presentation summarizes the work to investigate the uncertainty in wind forecasting at different times of year and compare wind forecast errors in different power systems using large-scale wind power prediction data from six countries: the United States, Finland, Spain, Denmark, Norway, and Germany.

Zhang, J.; Hodge, B.; Miettinen, J.; Holttinen, H.; Gomez-Lozaro, E.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Lovholm, A.; Berge, E.; Dobschinski, J.

2013-10-01T23:59:59.000Z

33

The wind power probability density forecast problem can be formulated as: forecast the wind power pdf at time step t for each look-ahead time step t+k of a given time-horizon  

E-Print Network (OSTI)

The wind power probability density forecast problem can be formulated as: forecast the wind power forecasted for look-ahead time t+k, xt is a set of explanatory variables available at time step t, fP,x is the joint density function of the forecasted wind power and explanatory variables, fX is the density

Kemner, Ken

34

Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison: Preprint  

DOE Green Energy (OSTI)

One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer.

Zhang, J.; Hodge, B. M.; Gomez-Lazaro, E.; Lovholm, A. L.; Berge, E.; Miettinen, J.; Holttinen, H.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Dobschinski, J.

2013-10-01T23:59:59.000Z

35

Investigating the Correlation Between Wind and Solar Power Forecast Errors in the Western Interconnection: Preprint  

DOE Green Energy (OSTI)

Wind and solar power generations differ from conventional energy generation because of the variable and uncertain nature of their power output. This variability and uncertainty can have significant impacts on grid operations. Thus, short-term forecasting of wind and solar generation is uniquely helpful for power system operations to balance supply and demand in an electricity system. This paper investigates the correlation between wind and solar power forecasting errors.

Zhang, J.; Hodge, B. M.; Florita, A.

2013-05-01T23:59:59.000Z

36

Economic Evaluation of Short-Term Wind Power Forecasts in ERCOT: Preliminary Results; Preprint  

DOE Green Energy (OSTI)

Historically, a number of wind energy integration studies have investigated the value of using day-ahead wind power forecasts for grid operational decisions. These studies have shown that there could be large cost savings gained by grid operators implementing the forecasts in their system operations. To date, none of these studies have investigated the value of shorter-term (0 to 6-hour-ahead) wind power forecasts. In 2010, the Department of Energy and National Oceanic and Atmospheric Administration partnered to fund improvements in short-term wind forecasts and to determine the economic value of these improvements to grid operators, hereafter referred to as the Wind Forecasting Improvement Project (WFIP). In this work, we discuss the preliminary results of the economic benefit analysis portion of the WFIP for the Electric Reliability Council of Texas. The improvements seen in the wind forecasts are examined, then the economic results of a production cost model simulation are analyzed.

Orwig, K.; Hodge, B. M.; Brinkman, G.; Ela, E.; Milligan, M.; Banunarayanan, V.; Nasir, S.; Freedman, J.

2012-09-01T23:59:59.000Z

37

Unit commitment with wind power generation: integrating wind forecast uncertainty and stochastic programming.  

DOE Green Energy (OSTI)

We present a computational framework for integrating the state-of-the-art Weather Research and Forecasting (WRF) model in stochastic unit commitment/energy dispatch formulations that account for wind power uncertainty. We first enhance the WRF model with adjoint sensitivity analysis capabilities and a sampling technique implemented in a distributed-memory parallel computing architecture. We use these capabilities through an ensemble approach to model the uncertainty of the forecast errors. The wind power realizations are exploited through a closed-loop stochastic unit commitment/energy dispatch formulation. We discuss computational issues arising in the implementation of the framework. In addition, we validate the framework using real wind speed data obtained from a set of meteorological stations. We also build a simulated power system to demonstrate the developments.

Constantinescu, E. M.; Zavala, V. M.; Rocklin, M.; Lee, S.; Anitescu, M. (Mathematics and Computer Science); (Univ. of Chicago); (New York Univ.)

2009-10-09T23:59:59.000Z

38

Space-Time Wind Speed Forecasting for Improved Power System Dispatch  

E-Print Network (OSTI)

In order to support large scale integration of wind power, state-of-the-art wind speed forecasting methods should provide accurate and adequate information to enable efficient scheduling of wind power in electric energy systems. In this article, space-time wind forecasts are incorporated into power system economic dispatch models. First, we proposed a new space-time wind forecasting model, which generalizes and improves upon a so-called regime-switching space-time model by allowing the forecast regimes to vary with the dominant wind direction and with the seasons. Then, results from the new wind forecasting model are implemented into a power system economic dispatch model, which takes into account both spatial and temporal wind speed correlations. This, in turn, leads to an overall more cost-effective scheduling of system-wide wind generation portfolio. The potential economic benefits arise in the system-wide generation cost savings and in the ancillary service cost savings. This is illustrated in a test system in the northwest region of the U.S. Compared with persistent and autoregressive models, our proposed method could lead to annual integration cost savings on the scale of tens of millions of dollars in regions with high wind penetration, such as Texas and the Northwest. Key words: Power system economic dispatch; Power system operation; Space-time statistical model; Wind data; Wind speed forecasting.

Xinxin Zhu; Marc G. Genton; Yingzhong Gu; Le Xie

2012-01-01T23:59:59.000Z

39

MPC for Wind Power Gradients --Utilizing Forecasts, Rotor Inertia, and Central Energy Storage  

E-Print Network (OSTI)

MPC for Wind Power Gradients -- Utilizing Forecasts, Rotor Inertia, and Central Energy Storage iterations. We demonstrate our method in simulations with various wind scenarios and prices for energy. INTRODUCTION Today, wind power is the most important renewable energy source. For the years to come, many

40

Examining Information Entropy Approaches as Wind Power Forecasting Performance Metrics: Preprint  

DOE Green Energy (OSTI)

In this paper, we examine the parameters associated with the calculation of the Renyi entropy in order to further the understanding of its application to assessing wind power forecasting errors.

Hodge, B. M.; Orwig, K.; Milligan, M.

2012-06-01T23:59:59.000Z

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

The ANEMOS Project: Next Generation Forecasting of Wind Power. G.Kariniotakis*  

E-Print Network (OSTI)

integration of wind energy in the developing liberalized electricity markets. Keywords - Wind power, short-resolution meteorological forecasts. For the offshore case, marine meteorology is considered as well as information will allow validation of the models and an analysis of the value of wind prediction for a competitive

Heinemann, Detlev

42

1) INTRODUCTION The accuracy of short-term wind power forecasts is besides  

E-Print Network (OSTI)

unconsidered outages of single turbines reflect a higher forecast error than expected from NWP. Wind power. The wind farm was in the commissioning phase in early 2001, when gradually more and more turbines became due to turbine wakes in the wind park and vi) accounting the availability of turbines with respect

Heinemann, Detlev

43

Wind Power Forecasting: State-of-the-Art 2009  

E-Print Network (OSTI)

operator (ISO) ­ Generate electricity to meet loads ­ Strive to maximize profits Independent system rules ­ Post next-day weather and load forecasts ­ Compute and post market clearing prices ­ Post unitElectric Power Market Simulations Using Individuals as Agents Guenter Conzelmann Argonne National

Kemner, Ken

44

Time Series Models to Simulate and Forecast Wind Speed and Wind Power  

Science Conference Proceedings (OSTI)

A general approach for modeling wind speed and wind power is described. Because wind power is a function of wind speed, the methodology is based on the development of a model of wind speed. Values of wind power are estimated by applying the ...

Barbara G. Brown; Richard W. Katz; Allan H. Murphy

1984-08-01T23:59:59.000Z

45

Scanning Doppler Lidar for Input into Short-Term Wind Power Forecasts  

Science Conference Proceedings (OSTI)

Scanning Doppler lidar is a promising technology for improvements in short-term wind power forecasts since it can scan close to the surface and produce wind profiles at a large distance upstream (15–30 km) if the atmosphere has sufficient aerosol ...

Rod Frehlich

2013-02-01T23:59:59.000Z

46

Wind Power Forecasting Error Distributions over Multiple Timescales: Preprint  

DOE Green Energy (OSTI)

In this paper, we examine the shape of the persistence model error distribution for ten different wind plants in the ERCOT system over multiple timescales. Comparisons are made between the experimental distribution shape and that of the normal distribution.

Hodge, B. M.; Milligan, M.

2011-03-01T23:59:59.000Z

47

Enhanced Short-Term Wind Power Forecasting and Value to Grid Operations: Preprint  

DOE Green Energy (OSTI)

The current state of the art of wind power forecasting in the 0- to 6-hour time frame has levels of uncertainty that are adding increased costs and risk on the U.S. electrical grid. It is widely recognized within the electrical grid community that improvements to these forecasts could greatly reduce the costs and risks associated with integrating higher penetrations of wind energy. The U.S. Department of Energy has sponsored a research campaign in partnership with the National Oceanic and Atmospheric Administration (NOAA) and private industry to foster improvements in wind power forecasting. The research campaign involves a three-pronged approach: 1) a 1-year field measurement campaign within two regions; 2) enhancement of NOAA's experimental 3-km High-Resolution Rapid Refresh (HRRR) model by assimilating the data from the field campaign; and 3) evaluation of the economic and reliability benefits of improved forecasts to grid operators. This paper and presentation provides an overview of the regions selected, instrumentation deployed, data quality and control, assimilation of data into HRRR, and preliminary results of HRRR performance analysis.

Orwig, K.; Clark, C.; Cline, J.; Benjamin, S.; Wilczak, J.; Marquis, M.; Finley, C.; Stern, A.; Freedman, J.

2012-09-01T23:59:59.000Z

48

Updated Eastern Interconnect Wind Power Output and Forecasts for ERGIS: July 2012  

DOE Green Energy (OSTI)

AWS Truepower, LLC (AWST) was retained by the National Renewable Energy Laboratory (NREL) to update wind resource, plant output, and wind power forecasts originally produced by the Eastern Wind Integration and Transmission Study (EWITS). The new data set was to incorporate AWST's updated 200-m wind speed map, additional tall towers that were not included in the original study, and new turbine power curves. Additionally, a primary objective of this new study was to employ new data synthesis techniques developed for the PJM Renewable Integration Study (PRIS) to eliminate diurnal discontinuities resulting from the assimilation of observations into mesoscale model runs. The updated data set covers the same geographic area, 10-minute time resolution, and 2004?2006 study period for the same onshore and offshore (Great Lakes and Atlantic coast) sites as the original EWITS data set.

Pennock, K.

2012-10-01T23:59:59.000Z

49

Updated Eastern Interconnect Wind Power Output and Forecasts for ERGIS: July 2012  

SciTech Connect

AWS Truepower, LLC (AWST) was retained by the National Renewable Energy Laboratory (NREL) to update wind resource, plant output, and wind power forecasts originally produced by the Eastern Wind Integration and Transmission Study (EWITS). The new data set was to incorporate AWST's updated 200-m wind speed map, additional tall towers that were not included in the original study, and new turbine power curves. Additionally, a primary objective of this new study was to employ new data synthesis techniques developed for the PJM Renewable Integration Study (PRIS) to eliminate diurnal discontinuities resulting from the assimilation of observations into mesoscale model runs. The updated data set covers the same geographic area, 10-minute time resolution, and 2004?2006 study period for the same onshore and offshore (Great Lakes and Atlantic coast) sites as the original EWITS data set.

Pennock, K.

2012-10-01T23:59:59.000Z

50

Wind Energy Management System EMS Integration Project: Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations  

SciTech Connect

The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. Currently, uncertainties associated with wind and load forecasts, as well as uncertainties associated with random generator outages and unexpected disconnection of supply lines, are not taken into account in power grid operation. Thus, operators have little means to weigh the likelihood and magnitude of upcoming events of power imbalance. In this project, funded by the U.S. Department of Energy (DOE), a framework has been developed for incorporating uncertainties associated with wind and load forecast errors, unpredicted ramps, and forced generation disconnections into the energy management system (EMS) as well as generation dispatch and commitment applications. A new approach to evaluate the uncertainty ranges for the required generation performance envelope including balancing capacity, ramping capability, and ramp duration has been proposed. The approach includes three stages: forecast and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence levels. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis, incorporating all sources of uncertainties of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the “flying brick” technique has been developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation algorithm has been developed to validate the accuracy of the confidence intervals.

Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

2010-01-01T23:59:59.000Z

51

Wind Energy Management System Integration Project Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations  

SciTech Connect

The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation) and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. In order to improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively, by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. In this report, a new methodology to predict the uncertainty ranges for the required balancing capacity, ramping capability and ramp duration is presented. Uncertainties created by system load forecast errors, wind and solar forecast errors, generation forced outages are taken into account. The uncertainty ranges are evaluated for different confidence levels of having the actual generation requirements within the corresponding limits. The methodology helps to identify system balancing reserve requirement based on a desired system performance levels, identify system “breaking points”, where the generation system becomes unable to follow the generation requirement curve with the user-specified probability level, and determine the time remaining to these potential events. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (California ISO) real life data have shown the effectiveness of the proposed approach. A tool developed based on the new methodology described in this report will be integrated with the California ISO systems. Contractual work is currently in place to integrate the tool with the AREVA EMS system.

Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

2010-09-01T23:59:59.000Z

52

The effects of energy storage properties and forecast accuracy on mitigating variability in wind power generation  

E-Print Network (OSTI)

Electricity generation from wind power is increasing worldwide. Wind power can offset traditional fossil fuel generators which is beneficial to the environment. However, wind generation is unpredictable. Wind speeds have ...

Jaworsky, Christina A

2013-01-01T23:59:59.000Z

53

Incorporating Uncertainty of Wind Power Generation Forecast into Power System Operation, Dispatch, and Unit Commitment Procedures  

Science Conference Proceedings (OSTI)

An approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. An assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty - both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures). A new method called the 'flying-brick' technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through EMS integration illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems in control rooms.

Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian; Huang, Zhenyu; Subbarao, Krishnappa

2011-06-23T23:59:59.000Z

54

Today's Forecast: Improved Wind Predictions | Department of Energy  

NLE Websites -- All DOE Office Websites (Extended Search)

in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar --...

55

Evaluation of Advanced Wind Power Forecasting Models Results of the Anemos Project  

E-Print Network (OSTI)

capacity of 33.09 MW distributed on 49 Gamesa G47-660 wind turbines and one Lagerwey LW750 turbine. The RIX (digital terrain maps with elevation and roughness, wind farm layout, wind turbine power and thrust curves of the Baltic Sea. The wind farm consists of 2 Nordtank NTK500/41 turbines with a total rated capacity of 1.0 MW

Paris-Sud XI, Université de

56

Powering Up With Space-Time Wind Forecasting Amanda S. HERING and Marc G. GENTON  

E-Print Network (OSTI)

to harvest electricity from wind energy is now advanced enough to make entire cities powered by it a reality of a kilowatt (kW) of wind-powered electricity is now nearly the same as a kW produced by coal or nuclear energy

Genton, Marc G.

57

Subhourly wind forecasting techniques for wind turbine operations  

DOE Green Energy (OSTI)

Three models for making automated forecasts of subhourly wind and wind power fluctuations were examined to determine the models' appropriateness, accuracy, and reliability in wind forecasting for wind turbine operation. Such automated forecasts appear to have value not only in wind turbine control and operating strategies, but also in improving individual wind turbine control and operating strategies, but also in improving individual wind turbine operating strategies (such as determining when to attempt startup). A simple persistence model, an autoregressive model, and a generalized equivalent Markhov (GEM) model were developed and tested using spring season data from the WKY television tower located near Oklahoma City, Oklahoma. The three models represent a pure measurement approach, a pure statistical method and a statistical-dynamical model, respectively. Forecasting models of wind speed means and measures of deviations about the mean were developed and tested for all three forecasting techniques for the 45-meter level and for the 10-, 30- and 60-minute time intervals. The results of this exploratory study indicate that a persistence-based approach, using onsite measurements, will probably be superior in the 10-minute time frame. The GEM model appears to have the most potential in 30-minute and longer time frames, particularly when forecasting wind speed fluctuations. However, several improvements to the GEM model are suggested. In comparison to the other models, the autoregressive model performed poorly at all time frames; but, it is recommended that this model be upgraded to an autoregressive moving average (ARMA or ARIMA) model. The primary constraint in adapting the forecasting models to the production of wind turbine cluster power output forecasts is the lack of either actual data, or suitable models, for simulating wind turbine cluster performance.

Wegley, H.L.; Kosorok, M.R.; Formica, W.J.

1984-08-01T23:59:59.000Z

58

Today's Forecast: Improved Wind Predictions | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable. These forecasts also play an important role in reducing the cost of renewable energy by allowing electricity grid operators to make timely decisions on what reserve generation they need to operate their systems.

59

Today's Forecast: Improved Wind Predictions | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable. These forecasts also play an important role in reducing the cost of renewable energy by allowing electricity grid operators to make timely decisions on what reserve generation they need to operate their systems.

60

Integration of Wind Generation and Load Forecast Uncertainties into Power Grid Operations  

Science Conference Proceedings (OSTI)

In this paper, a new approach to evaluate the uncertainty ranges for the required generation performance envelope, including the balancing capacity, ramping capability and ramp duration is presented. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (CAISO) real life data have shown the effectiveness and efficiency of the proposed approach.

Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Chakrabarti, Bhujanga B.; Subbarao, Krishnappa; Loutan, Clyde; Guttromson, Ross T.

2010-04-20T23:59:59.000Z

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

European Union Wind Energy Forecasting Model Development and Testing: U.S. Department of Energy -- EPRI Wind Turbine Verification Pr ogram  

Science Conference Proceedings (OSTI)

Wind forecasting can increase the strategic and market values of wind power from large wind facilities. This report summarizes the results of the European Union (EU) wind energy forecasting project and performance testing of the EU wind forecasting model. The testing compared forecast and observed wind speed and generation data from U.S. wind facilities.

1999-12-15T23:59:59.000Z

62

Short-term wind power forecast based on cluster analysis and artificial neural networks  

Science Conference Proceedings (OSTI)

In this paper an architecture for an estimator of short-term wind farm power is proposed. The estimator is made up of a Linear Machine classifier and a set of k Multilayer Perceptrons, training each one for a specific subspace of the input space. ...

Javier Lorenzo; Juan Méndez; Modesto Castrillón; Daniel Hernández

2011-06-01T23:59:59.000Z

63

Incorporating Wind Generation Forecast Uncertainty into Power System Operation, Dispatch, and Unit Commitment Procedures  

DOE Green Energy (OSTI)

In this paper, an approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the "flying-brick" technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through integration with an EMS system illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems from other vendors.

Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Subbarao, Krishnappa

2010-10-19T23:59:59.000Z

64

Solar and wind power advancing  

U.S. Energy Information Administration (EIA) Indexed Site

Solar and wind power advancing U.S. electricity generation from wind and solar energy show no signs of slowing down. In its new monthly forecast, the U.S. Energy Information...

65

Forecasting Wind Markets  

U.S. Energy Information Administration (EIA)

Emerging Technologies, Data, and NEM Modeling Issues in Wind Resource Supply Data and Modeling Chris Namovicz ASA Committee on Energy Statistics

66

The use of real-time off-site observations as a methodology for increasing forecast skill in prediction of large wind power ramps one or more hours ahead of their impact on a wind plant.  

SciTech Connect

ABSTRACT Application of Real-Time Offsite Measurements in Improved Short-Term Wind Ramp Prediction Skill Improved forecasting performance immediately preceding wind ramp events is of preeminent concern to most wind energy companies, system operators, and balancing authorities. The value of near real-time hub height-level wind data and more general meteorological measurements to short-term wind power forecasting is well understood. For some sites, access to onsite measured wind data - even historical - can reduce forecast error in the short-range to medium-range horizons by as much as 50%. Unfortunately, valuable free-stream wind measurements at tall tower are not typically available at most wind plants, thereby forcing wind forecasters to rely upon wind measurements below hub height and/or turbine nacelle anemometry. Free-stream measurements can be appropriately scaled to hub-height levels, using existing empirically-derived relationships that account for surface roughness and turbulence. But there is large uncertainty in these relationships for a given time of day and state of the boundary layer. Alternatively, forecasts can rely entirely on turbine anemometry measurements, though such measurements are themselves subject to wake effects that are not stationary. The void in free-stream hub-height level measurements of wind can be filled by remote sensing (e.g., sodar, lidar, and radar). However, the expense of such equipment may not be sustainable. There is a growing market for traditional anemometry on tall tower networks, maintained by third parties to the forecasting process (i.e., independent of forecasters and the forecast users). This study examines the value of offsite tall-tower data from the WINDataNOW Technology network for short-horizon wind power predictions at a wind farm in northern Montana. The presentation shall describe successful physical and statistical techniques for its application and the practicality of its application in an operational setting. It shall be demonstrated that when used properly, the real-time offsite measurements materially improve wind ramp capture and prediction statistics, when compared to traditional wind forecasting techniques and to a simple persistence model.

Martin Wilde, Principal Investigator

2012-12-31T23:59:59.000Z

67

Wind Power  

NLE Websites -- All DOE Office Websites (Extended Search)

Power As the accompanying map of New Mexico shows, the best wind power generation potential near WIPP is along the Delaware Mountain ridge line of the southern Guadalupe Mountains,...

68

Short-term wind speed forecasting based on a hybrid model  

Science Conference Proceedings (OSTI)

Wind power is currently one of the types of renewable energy with a large generation capacity. However, operation of wind power generation is very challenging because of the intermittent and stochastic nature of the wind speed. Wind speed forecasting ... Keywords: Forecasting, RBF neural networks, Seasonal adjustment, Wavelet transform, Wind speed

Wenyu Zhang, Jujie Wang, Jianzhou Wang, Zengbao Zhao, Meng Tian

2013-07-01T23:59:59.000Z

69

Wind forecasting objectives for utility schedulers and energy traders  

DOE Green Energy (OSTI)

The wind energy industry and electricity producers can benefit in a number of ways from increased wind forecast accuracy. Higher confidence in the reliability of wind forecasts can help persuade an electric utility to increase the penetration of wind energy into its operating system and to augment the capacity value of wind electric generation. Reliable forecasts can also assist daily energy traders employed by utilities in marketing the available and anticipated wind energy to power pools and other energy users. As the number of utilities with wind energy experience grows, and wind energy penetration levels increase, the need for reliable wind forecasts will likely grow as well. This period of wind energy growth also coincides with advances in computer weather prediction technology that could lead to more accurate wind forecasts. Thus, it is important to identify the type of forecast information needed by utility schedulers and energy traders. This step will help develop approaches to the challenge of wind forecasting that will result in useful products being supplied to utilities or other energy generating entities. This paper presents the objectives, approach, and current findings of a US Department of Energy National Renewable Energy Laboratory (DOE/NREL) initiative to develop useful wind forecasting tools for utilities involved with wind energy generation. The focus of this initiative thus far has been to learn about the needs of prospective utility users. NREL representatives conducted a series of onsite interviews with key utility staff, usually schedulers and research planners, at seven US utilities. The purpose was to ascertain information on actual scheduling and trading procedures, and how utilities could integrate wind forecasting into these activities.

Schwartz, M.N. [National Renewable Energy Lab., Golden, CO (United States); Bailey, B.H. [AWS Scientific, Inc., Albany, NY (United States)

1998-05-01T23:59:59.000Z

70

Review of Wind Energy Forecasting Methods for Modeling Ramping Events  

DOE Green Energy (OSTI)

Tall onshore wind turbines, with hub heights between 80 m and 100 m, can extract large amounts of energy from the atmosphere since they generally encounter higher wind speeds, but they face challenges given the complexity of boundary layer flows. This complexity of the lowest layers of the atmosphere, where wind turbines reside, has made conventional modeling efforts less than ideal. To meet the nation's goal of increasing wind power into the U.S. electrical grid, the accuracy of wind power forecasts must be improved. In this report, the Lawrence Livermore National Laboratory, in collaboration with the University of Colorado at Boulder, University of California at Berkeley, and Colorado School of Mines, evaluates innovative approaches to forecasting sudden changes in wind speed or 'ramping events' at an onshore, multimegawatt wind farm. The forecast simulations are compared to observations of wind speed and direction from tall meteorological towers and a remote-sensing Sound Detection and Ranging (SODAR) instrument. Ramping events, i.e., sudden increases or decreases in wind speed and hence, power generated by a turbine, are especially problematic for wind farm operators. Sudden changes in wind speed or direction can lead to large power generation differences across a wind farm and are very difficult to predict with current forecasting tools. Here, we quantify the ability of three models, mesoscale WRF, WRF-LES, and PF.WRF, which vary in sophistication and required user expertise, to predict three ramping events at a North American wind farm.

Wharton, S; Lundquist, J K; Marjanovic, N; Williams, J L; Rhodes, M; Chow, T K; Maxwell, R

2011-03-28T23:59:59.000Z

71

Forecasting Solar Wind Speeds  

E-Print Network (OSTI)

By explicitly taking into account effects of Alfven waves, I derive from a simple energetics argument a fundamental relation which predicts solar wind (SW) speeds in the vicinity of the earth from physical properties on the sun. Kojima et al. recently found from their observations that a ratio of surface magnetic field strength to an expansion factor of open magnetic flux tubes is a good indicator of the SW speed. I show by using the derived relation that this nice correlation is an evidence of the Alfven wave which accelerates SW in expanding flux tubes. The observations further require that fluctuation amplitudes of magnetic field lines at the surface should be almost universal in different coronal holes, which needs to be tested by future observations.

Takeru K. Suzuki

2006-02-03T23:59:59.000Z

72

California Wind Energy Forecasting System Development and Testing, Phase 1: Initial Testing  

Science Conference Proceedings (OSTI)

Wind energy forecasting uses sophisticated numerical weather forecasting and wind plant power generation models to predict the hourly energy generation of a wind power plant up to 48 hours in advance. As a result, it has great potential to address the needs of the California Independent System Operator (ISO) and the wind plant operators, as well as power marketers and buyers and utility system dispatch personnel. This report gives the results of 28 days of testing of wind energy forecasting at a Californ...

2003-01-31T23:59:59.000Z

73

Wind Energy Forecasting Technology Update: 2004  

Science Conference Proceedings (OSTI)

This report describes the status of wind energy forecasting technology for predicting wind speed and energy generation of wind energy facilities short-term (minutes to hours), intermediate-term (hours to days), and long-term (months to years) average wind speed and energy generation. The information should be useful to companies that are evaluating or planning to incorporate wind energy forecasting into their operations.

2005-04-26T23:59:59.000Z

74

Reference wind farm selection for regional wind power prediction models  

E-Print Network (OSTI)

1 Reference wind farm selection for regional wind power prediction models Nils Siebert George.siebert@ensmp.fr, georges.kariniotakis@ensmp.fr Abstract Short-term wind power forecasting is recognized today as a major requirement for a secure and economic integration of wind generation in power systems. This paper deals

Paris-Sud XI, Université de

75

Wind Energy Forecasting Technology Update: 2006  

Science Conference Proceedings (OSTI)

The worldwide installed wind generation capacity increased by 25 and reached almost 60,000 MW worldwide during 2005. As wind capacity continues to grow and large regional concentrations of wind generation emerge, utilities and regional transmission organizations will increasingly need accurate same-day and next-day forecasts of wind energy generation to dispatch system generation and transmission resource and anticipate rapid changes of wind generation.

2006-12-05T23:59:59.000Z

76

Wind Energy Forecasting Technology Update: 2005  

Science Conference Proceedings (OSTI)

The worldwide installed wind generation capacity increased by 25 and reached almost 60,000 MW worldwide during 2005. As wind capacity continues to grow and large regional concentrations of wind generation emerge, utilities and regional transmission organizations will increasingly need accurate same-day and next-day forecasts of wind energy generation to dispatch system generation and transmission resource and anticipate rapid changes of wind generation. The project objective is to summarize the results o...

2006-03-31T23:59:59.000Z

77

Central Wind Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities: Revised Edition  

DOE Green Energy (OSTI)

The report and accompanying table addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America. The first part of the table focuses on electric utilities and regional transmission organizations that have central wind power forecasting in place; the second part focuses on electric utilities and regional transmission organizations that plan to adopt central wind power forecasting in 2010. This is an update of the December 2009 report, NREL/SR-550-46763.

Rogers, J.; Porter, K.

2011-03-01T23:59:59.000Z

78

Final Report on California Regional Wind Energy Forecasting Project:Application of NARAC Wind Prediction System  

DOE Green Energy (OSTI)

Wind power is the fastest growing renewable energy technology and electric power source (AWEA, 2004a). This renewable energy has demonstrated its readiness to become a more significant contributor to the electricity supply in the western U.S. and help ease the power shortage (AWEA, 2000). The practical exercise of this alternative energy supply also showed its function in stabilizing electricity prices and reducing the emissions of pollution and greenhouse gases from other natural gas-fired power plants. According to the U.S. Department of Energy (DOE), the world's winds could theoretically supply the equivalent of 5800 quadrillion BTUs of energy each year, which is 15 times current world energy demand (AWEA, 2004b). Archer and Jacobson (2005) also reported an estimation of the global wind energy potential with the magnitude near half of DOE's quote. Wind energy has been widely used in Europe; it currently supplies 20% and 6% of Denmark's and Germany's electric power, respectively, while less than 1% of U.S. electricity is generated from wind (AWEA, 2004a). The production of wind energy in California ({approx}1.2% of total power) is slightly higher than the national average (CEC & EPRI, 2003). With the recently enacted Renewable Portfolio Standards calling for 20% of renewables in California's power generation mix by 2010, the growth of wind energy would become an important resource on the electricity network. Based on recent wind energy research (Roulston et al., 2003), accurate weather forecasting has been recognized as an important factor to further improve the wind energy forecast for effective power management. To this end, UC-Davis (UCD) and LLNL proposed a joint effort through the use of UCD's wind tunnel facility and LLNL's real-time weather forecasting capability to develop an improved regional wind energy forecasting system. The current effort of UC-Davis is aimed at developing a database of wind turbine power curves as a function of wind speed and direction, using its wind tunnel facility at the windmill farm at the Altamont Pass. The main objective of LLNL's involvement is to provide UC-Davis with improved wind forecasts to drive the parameterization scheme of turbine power curves developed from the wind tunnel facility. Another objective of LLNL's effort is to support the windmill farm operation with real-time wind forecasts for the effective energy management. The forecast skill in capturing the situation to meet the cut-in and cutout speed of given turbines would help reduce the operation cost in low and strong wind scenarios, respectively. The main focus of this report is to evaluate the wind forecast errors of LLNL's three-dimensional real-time weather forecast model at the location with the complex terrain. The assessment of weather forecast accuracy would help quantify the source of wind energy forecast errors from the atmospheric forecast model and/or wind-tunnel module for further improvement in the wind energy forecasting system.

Chin, H S

2005-07-26T23:59:59.000Z

79

Development of Wind Speed Forecasting Model Based on the Weibull Probability Distribution  

Science Conference Proceedings (OSTI)

Wind is a variable energy source. The power output of a wind turbine generator (WTG) unit, therefore, fluctuates with wind speed variations. Accurate models reflecting the variability of wind speed is hence required in both reliability evaluation of ... Keywords: Wind Energy, Wind Speed Forecasting Model, Weibull Distribution, Maximum Likelihood Method, Time Series Model

Ruigang Wang; Wenyi Li; B. Bagen

2011-02-01T23:59:59.000Z

80

Test application of a semi-objective approach to wind forecasting for wind energy applications  

SciTech Connect

The test application of the semi-objective (S-O) wind forecasting technique at three locations is described. The forecasting sites are described as well as site-specific forecasting procedures. Verification of the S-O wind forecasts is presented, and the observed verification results are interpreted. Comparisons are made between S-O wind forecasting accuracy and that of two previous forecasting efforts that used subjective wind forecasts and model output statistics. (LEW)

Wegley, H.L.; Formica, W.J.

1983-07-01T23:59:59.000Z

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

Balancing of Wind Power.  

E-Print Network (OSTI)

?? In the future, renewable energy share, especially wind power share, in electricity generation is expected to increase. Due to nature of the wind, wind… (more)

Ülker, Muhammed Akif

2011-01-01T23:59:59.000Z

82

Wind and Load Forecast Error Model for Multiple Geographically Distributed Forecasts  

Science Conference Proceedings (OSTI)

The impact of wind and load forecast errors on power grid operations is frequently evaluated by conducting multi-variant studies, where these errors are simulated repeatedly as random processes based on their known statistical characteristics. To generate these errors correctly, we need to reflect their distributions (which do not necessarily follow a known distribution law), standard deviations, auto- and cross-correlations. For instance, load and wind forecast errors can be closely correlated in different zones of the system. This paper introduces a new methodology for generating multiple cross-correlated random processes to simulate forecast error curves based on a transition probability matrix computed from an empirical error distribution function. The matrix will be used to generate new error time series with statistical features similar to observed errors. We present the derivation of the method and present some experimental results by generating new error forecasts together with their statistics.

Makarov, Yuri V.; Reyes Spindola, Jorge F.; Samaan, Nader A.; Diao, Ruisheng; Hafen, Ryan P.

2010-11-02T23:59:59.000Z

83

Probabilistic Wind Vector Forecasting Using Ensembles and Bayesian Model Averaging  

Science Conference Proceedings (OSTI)

Probabilistic forecasts of wind vectors are becoming critical as interest grows in wind as a clean and renewable source of energy, in addition to a wide range of other uses, from aviation to recreational boating. Unlike other common forecasting ...

J. McLean Sloughter; Tilmann Gneiting; Adrian E. Raftery

2013-06-01T23:59:59.000Z

84

Emerging challenges in wind energy forecasting for Australia  

E-Print Network (OSTI)

Growing concern about climate change has led to significant interest in renewable energy resources such as wind energy. However, such non-storable energy sources present a significant issue – how to maintain continuity of supply in the event of possible disturbances to power production. For example, in the case of wind energy, such disturbances can result from extreme weather events due to frontal systems or rapidly evolving low pressure systems. Such events cannot be avoided, but if they can be accurately forecast, their impact can be minimized by ensuring that alternative sources are available to make up any power shortfalls. Thus as wind energy makes up an ever greater component of our energy supply, there is greater interest in developing models to produce accurate, local scale, wind-focused forecasts for wind farm sites that push the boundaries of current weather prediction techniques. In this article we present a case study focusing on the Woolnorth wind farm on the northwest tip of Tasmania, to highlight some of the key challenges that will be involved in developing such forecasts.

Merlinde J. Kay; Nicholas Cutler; Adam Micolich; Iain Macgill; Hugh Outhred Centre For Energy; Environmental Markets; South Wales

2008-01-01T23:59:59.000Z

85

Solar Wind Forecasting with Coronal Holes  

E-Print Network (OSTI)

An empirical model for forecasting solar wind speed related geomagnetic events is presented here. The model is based on the estimated location and size of solar coronal holes. This method differs from models that are based on photospheric magnetograms (e.g., Wang-Sheeley model) to estimate the open field line configuration. Rather than requiring the use of a full magnetic synoptic map, the method presented here can be used to forecast solar wind velocities and magnetic polarity from a single coronal hole image, along with a single magnetic full-disk image. The coronal hole parameters used in this study are estimated with Kitt Peak Vacuum Telescope He I 1083 nm spectrograms and photospheric magnetograms. Solar wind and coronal hole data for the period between May 1992 and September 2003 are investigated. The new model is found to be accurate to within 10% of observed solar wind measurements for its best one-month periods, and it has a linear correlation coefficient of ~0.38 for the full 11 years studied. Using a single estimated coronal hole map, the model can forecast the Earth directed solar wind velocity up to 8.5 days in advance. In addition, this method can be used with any source of coronal hole area and location data.

S. Robbins; C. J. Henney; J. W. Harvey

2007-01-09T23:59:59.000Z

86

Wind Powering America: Wind Events  

Wind Powering America (EERE)

calendar.asp Lists upcoming wind calendar.asp Lists upcoming wind power-related events. en-us julie.jones@nrel.gov (Julie Jones) http://www.windpoweringamerica.gov/images/wpa_logo_sm.jpg Wind Powering America: Wind Events http://www.windpoweringamerica.gov/calendar.asp Pennsylvania Wind for Schools Educator Workshop https://www.regonline.com/builder/site/Default.aspx?EventID=1352684 http://www.windpoweringamerica.gov/filter_detail.asp?itemid=4068 Wed, 4 Dec 2013 00:00:00 MST 2014 Joint Action Workshop http://www.windpoweringamerica.gov/filter_detail.asp?itemid=3996 http://www.windpoweringamerica.gov/filter_detail.asp?itemid=3996 Mon, 21 Oct 2013 00:00:00 MST AWEA Wind Project Operations and Maintenance and Safety Seminar http://www.windpoweringamerica.gov/filter_detail.asp?itemid=4009 http://www.windpoweringamerica.gov/filter_detail.asp?itemid=4009 Mon, 21

87

Wind Power Today  

DOE Green Energy (OSTI)

Wind Power Today is an annual publication that provides an overview of the wind energy research conducted by the U.S. Department of Energy Wind and Hydropower Technologies Program.

Not Available

2007-05-01T23:59:59.000Z

88

Wind Power Today  

SciTech Connect

Wind Power Today is an annual publication that provides an overview of the wind energy research conducted by the U.S. Department of Energy Wind and Hydropower Technologies Program.

2006-05-01T23:59:59.000Z

89

Wind Powering America Webinar: Wind Power Economics: Past, Present...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Power Economics: Past, Present, and Future Trends Wind Powering America Webinar: Wind Power Economics: Past, Present, and Future Trends November 23, 2011 - 1:43pm Addthis Wind...

90

Wind Powering America  

Wind Powering America (EERE)

These news items are notable additions These news items are notable additions to the Wind Powering America Web site. The Wind Powering America Web site reports recent national and state wind market changes by cataloging wind activities such as wind resource maps, small wind consumer's guides, local wind workshops, news articles, and publications in the areas of policy, public power, small wind, Native Americans, agricultural sector, economic development, public lands, and schools. en-us julie.jones@nrel.gov (Julie Jones) http://www.windpoweringamerica.gov/images/wpa_logo_sm.jpg Wind Powering America http://www.windpoweringamerica.gov/ Nominate an Electric Cooperative for Wind Power Leadership Award by January 15 http://www.windpoweringamerica.gov/filter_detail.asp?itemid=4076 http://www.windpoweringamerica.gov/filter_detail.asp?itemid=4076 Mon, 16

91

Survey of Wind Power Integration Studies  

Science Conference Proceedings (OSTI)

The worldwide installed wind generation capacity increased by 25% and reached almost 60,000 MW worldwide and 9150 MW in the United States during 2005, and the high growth rate is forecast to continue for several years. Wind generation is an intermittent resource and can't be dispatched. Therefore, large blocks of wind generation concentrated in a region can affect the operation of the electricity grid with regard to ancillary service requirements and cost. Because the numerous wind power integration stud...

2006-03-31T23:59:59.000Z

92

Wind powering America: Colorado  

DOE Green Energy (OSTI)

This fact sheet contains information about green power programs in Colorado and a description of the Ponnequin Wind Farm.

O'Dell, K.

2000-04-03T23:59:59.000Z

93

Solar Wind Forecast by Using Interplanetary Scintillation Observations  

Science Conference Proceedings (OSTI)

Interplanetary scintillation (IPS) allows us to determine solar wind velocity and density structures over a relatively short time by employing computer assisted tomography. This method can be applied to forecast solar wind changes for a few days prior to its reaching Earth. We have been attempting solar wind forecasting by using IPS data observed at Solar?Terrestrial Environment Laboratory (STELab)

Ken’ichi Fujiki; Hiroaki Ito; Munetoshi Tokumaru

2010-01-01T23:59:59.000Z

94

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center  

E-Print Network (OSTI)

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at wind energy sites are becoming paramount. Regime-switching space-time (RST) models merge meteorological forecast regimes at the wind energy site and fits a conditional predictive model for each regime

Washington at Seattle, University of

95

Development of an Equivalent Wind Plant Power-Curve: Preprint  

SciTech Connect

Development of an equivalent wind plant power-curve becomes highly desirable and useful in predicting plant output for a given wind forecast. Such a development is described and summarized in this paper.

Wan, Y. H.; Ela, E.; Orwig, K.

2010-06-01T23:59:59.000Z

96

Modelling and forecasting wind speed intensity for weather risk management  

Science Conference Proceedings (OSTI)

The main interest of the wind speed modelling is on the short-term forecast of wind speed intensity and direction. Recently, its relationship with electricity production by wind farms has been studied. In fact, electricity producers are interested in ... Keywords: ARFIMA-FIGARCH, Auto Regressive Gamma, Gamma Auto Regressive, Weather risk management, Wind speed modelling, Wind speed simulation

Massimiliano Caporin; Juliusz Pre

2012-11-01T23:59:59.000Z

97

Energy Basics: Wind Power Animation  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Energy Basics Renewable Energy Printable Version Share this resource Biomass Geothermal Hydrogen Hydropower Ocean Solar Wind Wind Turbines Wind Resources Wind Power...

98

Stakeholder Engagement and Outreach: Where Is Wind Power?  

Wind Powering America (EERE)

Where Is Wind Power? Where Is Wind Power? Wind Powering America offers maps to help you visualize the wind resource at a local level and to show how much wind power has been installed in the United States. How much wind power is on my land? Go to the wind resource maps. Go to the wind resource maps. Go to the wind resource maps. If you want to know how much wind power is in a particular area, these wind resource maps can give you a visual indication of the average wind speeds to a local level such as a neighborhood. These maps have been developed using the same mathematical models that are used by weather forecasters and are even used to estimate the wind energy potential-or how much wind energy could potentially be produced at the state level, if wind power were developed there.

99

DOE Science Showcase - Wind Power  

Office of Scientific and Technical Information (OSTI)

Power Testing and Data in General Wind and Turbine Dynamics Wind Stresses Control, the Power Grid, and the Grids Economics Environmental Effects Energy101: Wind Turbines...

100

Chronological Reliability Model Incorporating Wind Forecasts to Assess Wind Plant Reserve Allocation: Preprint  

DOE Green Energy (OSTI)

Over the past several years, there has been considerable development and application of wind forecasting models. The main purpose of these models is to provide grid operators with the best information available so that conventional power generators can be scheduled as efficiently and as cost-effectively as possible. One of the important ancillary services is reserves, which involves scheduling additional capacity to guard against shortfalls. In a recent paper, Strbac and Kirschen[1] proposed a method to allocate the reserve burden to generators. Although Milligan adapted this technique to wind plants[2], neither of these papers accounts for the wind forecast in the reliability calculation. That omission is rectified here. For the system studied in this paper, we found that a reserve allocation scheme using 1-hour forecasts results in a small allocation of system reserve relative to the rated capacity of the wind power plant. This reserve allocation is even smaller when geographically dispersed wind sites are used instead of a large single site.

Milligan, M. R.

2002-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

Wind Power Outlook 2004  

DOE Green Energy (OSTI)

The brochure, expected to be updated annually, provides the American Wind Energy Association's (AWAE's) up-to-date assessment of the wind industry. It provides a summary of the state of wind power in the U.S., including the challenges and opportunities facing the industry. It provides summary information on the growth of the industry, policy-related factors such as the federal wind energy production tax credit status, comparisons with natural gas, and public views on wind energy.

anon.

2004-01-01T23:59:59.000Z

102

Estimating the economic value of wind forecasting to utilities  

SciTech Connect

Utilities are sometimes reluctant to assign capacity value to wind plants because they are an intermittent resource. One of the potential difficulties is that the output of a wind plant may not be known in advance, thereby making it difficult for the utility to consider wind output as firm. In this paper, we examine the economics of an accurate wind forecast, and provide a range of estimates calculated by a production cost model and real utility data. We discuss how an accurate forecast will affect resource scheduling and the mechanism by which resource scheduling can benefit from an accurate wind forecast.

Milligan, M.R.; Miller, A.H. [National Renewable Energy Lab., Golden, CO (United States); Chapman, F. [Environmental Defense Fund, Oakland, CA (United States)

1995-05-01T23:59:59.000Z

103

Wind power today  

DOE Green Energy (OSTI)

This publication highlights initiatives of the US DOE`s Wind Energy Program. 1997 yearly activities are also very briefly summarized. The first article describes a 6-megawatt wind power plant installed in Vermont. Another article summarizes technical advances in wind turbine technology, and describes next-generation utility and small wind turbines in the planning stages. A village power project in Alaska using three 50-kilowatt turbines is described. Very brief summaries of the Federal Wind Energy Program and the National Wind Technology Center are also included in the publication.

NONE

1998-04-01T23:59:59.000Z

104

New England Wind Forum: Wind Power Technology  

Wind Powering America (EERE)

Wind Power Technology Wind Power Technology Modern wind turbines have become sophisticated power plants while the concept of converting wind energy to electrical energy remains quite simple. Follow these links to learn more about the science behind wind turbine technology. Wind Power Animation An image of a scene from the wind power animation. The animation shows how moving air rotates a wind turbine's blades and describes how the internal components work to produce electricity. It shows small and large wind turbines and the differences between how they are used, as stand alone or connected to the utility grid. How Wind Turbines Work Learn how wind turbines make electricity; what are the types, sizes, and applications of wind turbines; and see an illustration of the components inside a wind turbine.

105

Wind Power in Paradise  

Science Conference Proceedings (OSTI)

The paper discusses how an international team of engineers brought wind power to the Galapagos Islands. The san cristobal system is a wind-diesel hybrid. The electricity generated by the wind turbines and by three diesel generators converges at the substation ...

E. Guizzo

2008-03-01T23:59:59.000Z

106

Wind Power Career Chat  

DOE Green Energy (OSTI)

This document will teach students about careers in the wind energy industry. Wind energy, both land-based and offshore, is expected to provide thousands of new jobs in the next several decades. Wind energy companies are growing rapidly to meet America's demand for clean, renewable, and domestic energy. These companies need skilled professionals. Wind power careers will require educated people from a variety of areas. Trained and qualified workers manufacture, construct, operate, and manage wind energy facilities. The nation will also need skilled researchers, scientists, and engineers to plan and develop the next generation of wind energy technologies.

Not Available

2011-01-01T23:59:59.000Z

107

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty  

Science Conference Proceedings (OSTI)

This paper presents four algorithms to generate random forecast error time series. The performance of four algorithms is compared. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets used in power grid operation to study the net load balancing need in variable generation integration studies. The four algorithms are truncated-normal distribution models, state-space based Markov models, seasonal autoregressive moving average (ARMA) models, and a stochastic-optimization based approach. The comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics (i.e., mean, standard deviation, autocorrelation, and cross-correlation). The results show that all methods generate satisfactory results. One method may preserve one or two required statistical characteristics better the other methods, but may not preserve other statistical characteristics as well compared with the other methods. Because the wind and load forecast error generators are used in wind integration studies to produce wind and load forecasts time series for stochastic planning processes, it is sometimes critical to use multiple methods to generate the error time series to obtain a statistically robust result. Therefore, this paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.

Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.; Samaan, Nader A.; Makarov, Yuri V.

2013-07-25T23:59:59.000Z

108

Wind powering America: Vermont  

DOE Green Energy (OSTI)

Wind resources in the state of Vermont show great potential for wind energy development according to the wind resource assessment conducted by the state, its utilities, and NREL. This fact sheet provides a brief description of the resource assessment and a link to the resulting wind resource map produced by NREL. The fact sheet also provides a description of the state's net metering program, its financial incentives, and green power programs as well as a list of contacts for more information.

NREL

2000-04-11T23:59:59.000Z

109

Wind powering America: Kansas  

DOE Green Energy (OSTI)

Wind resources in the state of Kansas show great potential for wind energy development according to the wind resource assessment conducted by the Kansas Electric Utilities Research Program, UWIG, and DOE. This fact sheet provides a brief description of the resource assessment and description of the state's new educational wind kiosk as well as its green power program and financial incentives available for the development of renewable energy technologies. A list of contacts for more information is also included.

NREL

2000-04-11T23:59:59.000Z

110

Wind Powering the Government  

DOE Green Energy (OSTI)

There are more than half a million Federal buildings with electric bills totaling about $3.5 billion per year. The Wind Powering America Initiative challenges the Federal government to reduce its use of energy produced by fossil fuels by obtaining at least 5% of its electricity from wind by 2010. As part of the current efforts to achieve the initiative's goal, NREL's Technical Information Services published Wind Powering the Government, a brochure that encourages the use of wind energy on Federal properties and the purchase of green power or green tags by Federal property managers.

Pitchford, P.

2000-08-02T23:59:59.000Z

111

Energy Basics: Wind Power Animation  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

EERE: Energy Basics Wind Power Animation This animation discusses the advantages of wind power, the workings of a wind turbine, and wind resources in the United States. It also...

112

Evaluating a Hybrid Prognostic–Diagnostic Model That Improves Wind Forecast Resolution in Complex Coastal Topography  

Science Conference Proceedings (OSTI)

The results from a hybrid approach that combines the forecasts of a mesoscale model with a diagnostic wind model to produce high-resolution wind forecasts in complex coastal orography are evaluated. The simple diagnostic wind model [Winds on ...

Francis L. Ludwig; Douglas K. Miller; Shawn G. Gallaher

2006-01-01T23:59:59.000Z

113

Wind Powering America: New England Wind Forum  

Wind Powering America (EERE)

About the New England Wind Forum About the New England Wind Forum New England Wind Energy Education Project Historic Wind Development in New England State Activities Projects in New England Building Wind Energy in New England Wind Resource Wind Power Technology Economics Markets Siting Policy Technical Challenges Issues Small Wind Large Wind Newsletter Perspectives Events Quick Links to States CT MA ME NH RI VT Bookmark and Share The New England Wind Forum was conceived in 2005 as a platform to provide a single, comprehensive and objective source of up-to-date, Web-based information on a broad array of wind-energy-related issues pertaining to New England. The New England Wind Forum provides information to wind energy stakeholders through Web site features, periodic newsletters, and outreach activities. The New England Wind Forum covers the most frequently discussed wind energy topics.

114

New England Wind Forum: Wind Power Economics  

Wind Powering America (EERE)

State Activities Projects in New England Building Wind Energy in New England Wind Resource Wind Power Technology Economics Cost Components Determining Factors Influencing Wind Economics in New England How does wind compare to the cost of other electricity options? Markets Siting Policy Technical Challenges Issues Small Wind Large Wind Newsletter Perspectives Events Quick Links to States CT MA ME NH RI VT Bookmark and Share Wind Power Economics Long-Term Cost Trends Since the first major installations of commercial-scale wind turbines in the 1980s, the cost of energy from wind power projects has decreased substantially due to larger turbine generators, towers, and rotor lengths; scale economies associated with larger projects; improvements in manufacturing efficiency, and technological advances in turbine generator and blade design. These technological advances have allowed for higher generating capacities per turbine and more efficient capture of wind, especially at lower wind speeds.

115

Availability of wind power  

DOE Green Energy (OSTI)

Meteorological studies of available wind power were begun at Sandia in 1973 to support the development of a vertical-axis wind turbine (VAWT, ''egg-beater''). This presentation reviews work to date. Copies of seven source reports were provided to ELETROBRAS; Scientia, Ltda., has included them in an extensive bibliography that was distributed at the seminar. This report summarizes those climatological studies that are needed to assist and promote wind energy exploitation in Brazil.

Reed, J.W.

1978-01-01T23:59:59.000Z

116

Wind Energy Technology Trends: Comparing and Contrasting Recent Cost and Performance Forecasts (Poster)  

DOE Green Energy (OSTI)

Poster depicts wind energy technology trends, comparing and contrasting recent cost and performance forecasts.

Lantz, E.; Hand, M.

2010-05-01T23:59:59.000Z

118

A quick guide to wind power forecating : state-of-the-art 2009.  

DOE Green Energy (OSTI)

This document contains a summary of the main findings from our full report entitled 'Wind Power Forecasting: State-of-the-Art 2009'. The aims of this document are to provide guidelines and a quick overview of the current state-of-the-art in wind power forecasting (WPF) and to point out lines of research in the future development of forecasting systems.

Monteiro, C.; Keko, H.; Bessa, R.; Miranda, V.; Botterud, A.; Wang, J.; Conzelmann, G.; Decision and Information Sciences; INESC Porto

2009-11-20T23:59:59.000Z

119

DOE Science Showcase - Wind Power  

Office of Scientific and Technical Information (OSTI)

DOE Science Showcase - Wind Power DOE Science Showcase - Wind Power Wind Powering America Wind Powering America is a nationwide initiative of the U.S. Department of Energy's Wind Program designed to educate, engage, and enable critical stakeholders to make informed decisions about how wind energy contributes to the U.S. electricity supply. Wind Power Research Results in DOE Databases IEA Wind Task 26: The Past and Future Cost of Wind Energy, Work Package 2, Energy Citations Database NREL Triples Previous Estimates of U.S. Wind Power Potential, Energy Citations Database Dynamic Models for Wind Turbines and Wind Power Plants, DOE Information Bridge 2012 ARPA-E Energy Innovation Summit: Profiling General Compression: A River of Wind, ScienceCinema, multimedia Solar and Wind Energy Resource Assessment (SWERA) Data from the

120

Wind powering America - Texas  

DOE Green Energy (OSTI)

This fact sheet contains a description of the wind energy resources in the state of Texas and the state's efforts to develop wind energy production, green power, and net metering programs. The fact sheet also includes a list of contacts for those interested in obtaining more information.

O'Dell, K.

2000-04-13T23:59:59.000Z

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

Wind powering America: Massachusetts  

DOE Green Energy (OSTI)

This fact sheet provides a brief description of the wind resources in Massachusetts, the state financial incentives to develop wind systems and its net metering and green power programs. The fact sheet also provides a list of contacts for more information.

NREL

2000-04-11T23:59:59.000Z

122

Wind Power Today, 2010, Wind and Water Power Program (WWPP)  

SciTech Connect

Wind Power Today is an annual publication that provides an overview of the wind energy research conducted by the U.S. Department of Energy Wind and Water Power Program.

2010-05-01T23:59:59.000Z

123

Wind powering America: Wyoming  

DOE Green Energy (OSTI)

This fact sheet contains a description of the green power programs in Wyoming, the state's efforts to promote wind energy, and a list of contacts for those interested in obtaining more information.

NREL

2000-04-10T23:59:59.000Z

124

Wind powering America: Nebraska  

DOE Green Energy (OSTI)

This fact sheet contains a description of Nebraska's wind energy resources and the state's green power programs. The fact sheet includes a list of contacts for those interested in obtaining more information.

NREL

2000-04-10T23:59:59.000Z

125

Wind Speeds at Heights Crucial for Wind Energy: Measurements and Verification of Forecasts  

Science Conference Proceedings (OSTI)

Wind speed measurements from one year from meteorological towers and wind turbines at heights between 20 and 250 m for various European sites are analyzed and are compared with operational short-term forecasts of the global ECMWF model. The ...

Susanne Drechsel; Georg J. Mayr; Jakob W. Messner; Reto Stauffer

2012-09-01T23:59:59.000Z

126

California Regional Wind Energy Forecasting System Development, Vol. 3  

Science Conference Proceedings (OSTI)

The rated capacity of wind generation in California is expected to grow rapidly in the future beyond the approximately 2100 MW in place at the end of 2005. The main drivers are the state's 20 percent Renewable Portfolio Standard requirement in 2010 and the low cost of wind energy relative to other renewable energy sources. As wind is an intermittent generation resource and weather changes can cause large and rapid changes in output, system operators will need accurate and robust wind energy forecasting ...

2006-11-15T23:59:59.000Z

127

Crownbutte Wind Power LLC | Open Energy Information  

Open Energy Info (EERE)

Crownbutte Wind Power LLC Jump to: navigation, search Name Crownbutte Wind Power LLC Place Mandan, North Dakota Zip 58554 Sector Wind energy Product North Dakota wind power company...

128

Wind Power | Open Energy Information  

Open Energy Info (EERE)

Wind Power Wind Power Jump to: navigation, search Wind Power WIndfarm.Sunset.jpg Wind power is a form of solar energy.[1] Wind is caused by the uneven heating of the atmosphere by the sun, variations in the earth's surface, and rotation of the earth. Mountains, bodies of water, and vegetation all influence wind flow patterns[2], [3]. Wind energy (or wind power) describes the process by which wind is used to generate electricity. Wind turbines convert the energy in wind to electricity by rotating propeller-like blades around a rotor. The rotor turns the drive shaft, which turns an electric generator.[2] Three key factors affect the amount of energy a turbine can harness from the wind: wind speed, air density, and swept area.[4] Mechanical power can also be utilized directly for specific tasks such as

129

Evaluation of a Wind-Wave System for Ensemble Tropical Cyclone Wave Forecasting. Part II: Waves  

Science Conference Proceedings (OSTI)

A wind-wave forecast system, designed with the intention of generating unbiased ensemble wave forecasts for extreme wind events, is assessed. Wave hindcasts for 12 tropical cyclones (TCs) are forced using a wind analysis produced from a ...

Steven M. Lazarus; Samuel T. Wilson; Michael E. Splitt; Gary A. Zarillo

2013-04-01T23:59:59.000Z

130

2009 Wind Technologies Market Report  

E-Print Network (OSTI)

2010. Status of Centralized Wind Power Forecasting in NorthInterconnection Policies and Wind Power: A Discussion ofs first utility-scale wind power project. Credit: Klaus

Wiser, Ryan

2010-01-01T23:59:59.000Z

131

Wind Powering America Webinar Series (Postcard), Wind Powering...  

Wind Powering America (EERE)

Wind Powering America webinar series provides expert information on today's key wind energy topics. * Webinars are presented on the third Wednesday of every month. * Recordings...

132

Power load forecasting Organization: Huizhou Electric Power, P. R. China  

E-Print Network (OSTI)

, regression, artificial intelligence. 1. Introduction Accurate models for electric power load forecasting are essential to the operation and planning of a utility company. Load forecasting helps an electric utility as electric load forecasting. In particular, ARMA (autoregressive moving average), ARIMA (autore- gressive

133

Short term wind speed forecasting with evolved neural networks  

Science Conference Proceedings (OSTI)

Concerns about climate change, energy security and the volatility of the price of fossil fuels has led to an increased demand for renewable energy. With wind turbines being one of the most mature renewable energy technologies available, the global use ... Keywords: forecasting, renewable energy, wind-speed

David Corne; Alan Reynolds; Stuart Galloway; Edward Owens; Andrew Peacock

2013-07-01T23:59:59.000Z

134

Wind Energy Forecasting: A Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy  

DOE Green Energy (OSTI)

The focus of this report is the wind forecasting system developed during this contract period with results of performance through the end of 2010. The report is intentionally high-level, with technical details disseminated at various conferences and academic papers. At the end of 2010, Xcel Energy managed the output of 3372 megawatts of installed wind energy. The wind plants span three operating companies1, serving customers in eight states2, and three market structures3. The great majority of the wind energy is contracted through power purchase agreements (PPAs). The remainder is utility owned, Qualifying Facilities (QF), distributed resources (i.e., 'behind the meter'), or merchant entities within Xcel Energy's Balancing Authority footprints. Regardless of the contractual or ownership arrangements, the output of the wind energy is balanced by Xcel Energy's generation resources that include fossil, nuclear, and hydro based facilities that are owned or contracted via PPAs. These facilities are committed and dispatched or bid into day-ahead and real-time markets by Xcel Energy's Commercial Operations department. Wind energy complicates the short and long-term planning goals of least-cost, reliable operations. Due to the uncertainty of wind energy production, inherent suboptimal commitment and dispatch associated with imperfect wind forecasts drives up costs. For example, a gas combined cycle unit may be turned on, or committed, in anticipation of low winds. The reality is winds stayed high, forcing this unit and others to run, or be dispatched, to sub-optimal loading positions. In addition, commitment decisions are frequently irreversible due to minimum up and down time constraints. That is, a dispatcher lives with inefficient decisions made in prior periods. In general, uncertainty contributes to conservative operations - committing more units and keeping them on longer than may have been necessary for purposes of maintaining reliability. The downside is costs are higher. In organized electricity markets, units that are committed for reliability reasons are paid their offer price even when prevailing market prices are lower. Often, these uplift charges are allocated to market participants that caused the inefficient dispatch in the first place. Thus, wind energy facilities are burdened with their share of costs proportional to their forecast errors. For Xcel Energy, wind energy uncertainty costs manifest depending on specific market structures. In the Public Service of Colorado (PSCo), inefficient commitment and dispatch caused by wind uncertainty increases fuel costs. Wind resources participating in the Midwest Independent System Operator (MISO) footprint make substantial payments in the real-time markets to true-up their day-ahead positions and are additionally burdened with deviation charges called a Revenue Sufficiency Guarantee (RSG) to cover out of market costs associated with operations. Southwest Public Service (SPS) wind plants cause both commitment inefficiencies and are charged Southwest Power Pool (SPP) imbalance payments due to wind uncertainty and variability. Wind energy forecasting helps mitigate these costs. Wind integration studies for the PSCo and Northern States Power (NSP) operating companies have projected increasing costs as more wind is installed on the system due to forecast error. It follows that reducing forecast error would reduce these costs. This is echoed by large scale studies in neighboring regions and states that have recommended adoption of state-of-the-art wind forecasting tools in day-ahead and real-time planning and operations. Further, Xcel Energy concluded reduction of the normalized mean absolute error by one percent would have reduced costs in 2008 by over $1 million annually in PSCo alone. The value of reducing forecast error prompted Xcel Energy to make substantial investments in wind energy forecasting research and development.

Parks, K.; Wan, Y. H.; Wiener, G.; Liu, Y.

2011-10-01T23:59:59.000Z

135

Heilongjiang Lishu Wind Power | Open Energy Information  

Open Energy Info (EERE)

Lishu Wind Power Jump to: navigation, search Name Heilongjiang Lishu Wind Power Place Heilongjiang Province, China Sector Wind energy Product China-based wind project developer...

136

Daqing Longjiang Wind Power | Open Energy Information  

Open Energy Info (EERE)

Longjiang Wind Power Jump to: navigation, search Name Daqing Longjiang Wind Power Place Daqing, Heilongjiang Province, China Zip 163316 Sector Wind energy Product Local wind...

137

Gansu Xinhui Wind Power | Open Energy Information  

Open Energy Info (EERE)

Xinhui Wind Power Jump to: navigation, search Name Gansu Xinhui Wind Power Place China Sector Wind energy Product China-based joint venture engaged in developing wind projects....

138

Metrics for Evaluating the Accuracy of Solar Power Forecasting (Presentation)  

DOE Green Energy (OSTI)

This presentation proposes a suite of metrics for evaluating the performance of solar power forecasting.

Zhang, J.; Hodge, B.; Florita, A.; Lu, S.; Hamann, H.; Banunarayanan, V.

2013-10-01T23:59:59.000Z

139

Wind Power Today: Federal Wind Program Highlights  

DOE Green Energy (OSTI)

Wind Power Today is an annual publication that provides an overview of the wind research conducted under the U.S. Department of Energy's Wind and Hydropower Technologies Program. The purpose of Wind Power Today is to show how DOE supports wind turbine research and deployment in hopes of furthering the advancement of wind technologies that produce clean, low-cost, reliable energy. Content objectives include: educate readers about the advantages and potential for widespread deployment of wind energy; explain the program's objectives and goals; describe the program's accomplishments in research and application; examine the barriers to widespread deployment; describe the benefits of continued research and development; facilitate technology transfer; and attract cooperative wind energy projects with industry.

Not Available

2005-04-01T23:59:59.000Z

140

Wind powering America: Minnesota  

DOE Green Energy (OSTI)

This fact sheet contains a description of Minnesota's wind energy resources, and the state's green power and net metering programs as well as financial incentives that support the programs. The fact sheet includes a list of contacts for those interested in obtaining more information.

NREL

2000-04-10T23:59:59.000Z

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

Wind powering America: Montana  

DOE Green Energy (OSTI)

This fact sheet contains a description of Montana's wind energy resources, and the state's green power and net metering programs as well as financial incentives that support the programs. The fact sheet includes a list of contacts for those interested in obtaining more information.

NREL

2000-04-10T23:59:59.000Z

142

Sinomatech Wind Power Blade aka Sinoma Science Technology Wind...  

Open Energy Info (EERE)

Sinomatech Wind Power Blade aka Sinoma Science Technology Wind Turbine Blade Co Ltd Jump to: navigation, search Name Sinomatech Wind Power Blade (aka Sinoma Science & Technology...

143

New England Wind Forum: Buying Wind Power  

Wind Powering America (EERE)

Buying Wind Power Buying Wind Power On this page find information about: Green Marketing Renewable Energy Certificates Green Pricing Green Marketing Green power marketing refers to selling green power in the competitive marketplace, in which multiple suppliers and service offerings exist. In states that have established retail competition, customers may be able to purchase green power from a competitive supplier. Connecticut Connecticut Clean Energy Options Beginning in April 2005, Connecticut's two investor-owned utilities, Connecticut Light and Power and United Illuminating, began to offer a simple, affordable program to their customers for purchasing clean energy such as wind power. In late 2006, stakeholders started to explore a new offering that would convey the price stability of wind energy (and other renewable energy resources) to Connecticut consumers. This new offering is still under development.

144

Wind Powering America - New Jersey  

DOE Green Energy (OSTI)

This fact sheet describes the wind energy deployment efforts and green power programs in the state of New Jersey.

O'Dell, K.

2000-10-13T23:59:59.000Z

145

Wind Powering America Webinar: Wind Power Economics: Past, Present, and  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Wind Powering America Webinar: Wind Power Economics: Past, Present, Wind Powering America Webinar: Wind Power Economics: Past, Present, and Future Trends Wind Powering America Webinar: Wind Power Economics: Past, Present, and Future Trends November 23, 2011 - 1:43pm Addthis Wind turbine prices in the United States have declined, on average, by nearly one-third since 2008, after doubling from 2002 through 2008. Over this entire period, the average nameplate capacity rating, hub height, and rotor swept area of turbines installed in the United States have increased significantly, while other design improvements have also boosted turbine energy production. In combination, these various trends have had a significant-and sometimes surprising-impact on the levelized cost of energy delivered by wind projects. This webinar will feature three related presentations that explore these

146

A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height  

Science Conference Proceedings (OSTI)

The Weather Research and Forecasting Model (WRF) with 10-km horizontal grid spacing was used to explore improvements in wind speed forecasts at a typical wind turbine hub height (80 m). An ensemble consisting of WRF model simulations with ...

Adam J. Deppe; William A. Gallus Jr.; Eugene S. Takle

2013-02-01T23:59:59.000Z

147

Wind Powering America  

DOE Green Energy (OSTI)

At the June 1999 Windpower Conference, the Secretary of Energy launched the Office of Energy Efficiency and Renewable Energy's Wind Powering America (WPA) initiative. The goals of the initiative are to meet 5% of the nation's energy needs with wind energy by 2020 (i.e., 80,000 megawatts installed), to double the number of states that have more than 20 megawatts (MW) of wind capacity to 16 by 2005 and triple it to 24 by 2010, and to increase wind's contribution to Federal electricity use to 5% by 2010. To achieve the Federal government's goal, DOE would take the leadership position and work with its Federal partners. Subsequently, the Secretary accelerated the DOE 5% commitment to 2005. Achieving the 80,000 MW goal would result in approximately $60 billion investment and $1.5 billion of economic development in our rural areas (where the wind resources are the greatest). The purpose of this paper is to provide an update on DOE's strategy for achieving its goals and the activities it has undertaken since the initiative was announced.

Flowers, L. (NREL); Dougherty, P. J. (DOE)

2001-07-07T23:59:59.000Z

148

Texas Wind Energy Forecasting System Development and Testing, Phase 1: Initial Testing  

Science Conference Proceedings (OSTI)

This report describes initial results from the Texas Wind Energy Forecasting System Development and Testing Project at a 75-MW wind project in west Texas.

2003-12-31T23:59:59.000Z

149

California Wind Energy Forecasting System Development and Testing Phase 2: 12-Month Testing  

Science Conference Proceedings (OSTI)

This report describes results from the second phase of the California Wind Energy Forecasting System Development and Testing Project.

2003-07-22T23:59:59.000Z

150

European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. Forecasting of Regional Wind Generation by a Dynamic  

E-Print Network (OSTI)

European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. Forecasting of Regional Wind forecasting. I. INTRODUCTION HE actual large-scale integration of wind energy in several European countries enhance the position of wind energy compared to other dispatchable forms of generation. Predicting

Paris-Sud XI, Université de

151

Online short-term solar power forecasting  

SciTech Connect

This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 h. The data used is 15-min observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques. Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to 2 h ahead the most important input is the available observations of solar power, while for longer horizons NWPs are the most important input. A root mean square error improvement of around 35% is achieved by the ARX model compared to a proposed reference model. (author)

Bacher, Peder; Madsen, Henrik [Informatics and Mathematical Modelling, Richard Pedersens Plads, Technical University of Denmark, Building 321, DK-2800 Lyngby (Denmark); Nielsen, Henrik Aalborg [ENFOR A/S, Lyngsoe Alle 3, DK-2970 Hoersholm (Denmark)

2009-10-15T23:59:59.000Z

152

Wind Power Today and Tomorrow  

DOE Green Energy (OSTI)

Wind Power Today and Tomorrow is an annual publication that provides an overview of the wind research conducted under the U.S. Department of Energy's Wind and Hydropower Technologies Program. The purpose of Wind Power Today and Tomorrow is to show how DOE supports wind turbine research and deployment in hopes of furthering the advancement of wind technologies that produce clean, low-cost, reliable energy. Content objectives include: educate readers about the advantages and potential for widespread deployment of wind energy; explain the program's objectives and goals; describe the program's accomplishments in research and application; examine the barriers to widespread deployment; describe the benefits of continued research and development; facilitate technology transfer; and attract cooperative wind energy projects with industry. This 2003 edition of the program overview also includes discussions about wind industry growth in 2003, how DOE is taking advantage of low wind speed region s through advancing technology, and distributed applications for small wind turbines.

Not Available

2004-03-01T23:59:59.000Z

153

Energy Basics: Wind Power Animation (Text Version)  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Energy Basics Renewable Energy Printable Version Share this resource Biomass Geothermal Hydrogen Hydropower Ocean Solar Wind Wind Turbines Wind Resources Wind Power...

154

Wind Powering America: Wind Energy Videos  

DOE Data Explorer (OSTI)

Wind Powering America is a nationwide initiative designed to increase the use of wind energy across the United States by working with regional stakeholders. A list of videos developed by and for the program includes interviews, short news clips, and documentary-like programs.

155

Wind Powering America Webinar Series (Postcard), Wind Powering America (WPA)  

DOE Green Energy (OSTI)

Wind Powering America offers a free monthly webinar series that provides expert information on today?s key wind energy topics. This postcard is an outreach tool that provides a brief description of the webinars as well as the URL.

Not Available

2012-02-01T23:59:59.000Z

156

Analysis and Forecasting of the Low-Level Wind during the Sydney 2000 Forecast Demonstration Project  

Science Conference Proceedings (OSTI)

During the Sydney 2000 Forecast Demonstration Project (FDP) a four-dimensional variational assimilation (4DVAR) scheme was run to analyze the low-level wind field with high spatial and temporal resolution. The 4DVAR scheme finds an optimal fit to ...

N. Andrew Crook; Juanzhen Sun

2004-02-01T23:59:59.000Z

157

Wind Powering America Podcasts, Wind Powering America (WPA)  

SciTech Connect

Wind Powering America and the National Association of Farm Broadcasters produce a series of radio interviews featuring experts discussing wind energy topics. The interviews are aimed at a rural stakeholder audience and are available as podcasts. On the Wind Powering America website, you can access past interviews on topics such as: Keys to Local Wind Energy Development Success, What to Know about Installing a Wind Energy System on Your Farm, and Wind Energy Development Can Revitalize Rural America. This postcard is a marketing piece that stakeholders can provide to interested parties; it will guide them to this online resource for podcast episodes.

Not Available

2012-04-01T23:59:59.000Z

158

Guohua Hulunbeier Wind Power | Open Energy Information  

Open Energy Info (EERE)

Hulunbeier Wind Power Jump to: navigation, search Name Guohua (Hulunbeier) Wind Power Place Hulunbeier, Inner Mongolia Autonomous Region, China Zip 21300 Sector Wind energy Product...

159

Guohua Qiqihaer Wind Power | Open Energy Information  

Open Energy Info (EERE)

Qiqihaer Wind Power Jump to: navigation, search Name Guohua (Qiqihaer) Wind Power Place Qiqihaer, Heilongjiang Province, China Zip 161005 Sector Wind energy Product Guohua...

160

Wind Power Ltd | Open Energy Information  

Open Energy Info (EERE)

Power Ltd Place Wickam Market, United Kingdom Sector Wind energy Product Conducting research into alternative, large scale wind turbine design. References Wind Power Ltd1...

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Empirical Solar Wind Forecasting from the Chromosphere  

E-Print Network (OSTI)

Recently, we correlated the inferred structure of the solar chromospheric plasma topography with solar wind velocity and composition data measured at 1AU. We now offer a physical justification of these relationships and present initial results of a empirical prediction model based on them. While still limited by the fundamentally complex physics behind the origins of the solar wind and how its structure develops in the magnetic photosphere and expands into the heliosphere, our model provides a near continuous range of solar wind speeds and composition quantities that are simply estimated from the inferred structure of the chromosphere. We suggest that the derived quantities may provide input to other, more sophisticated, prediction tools or models such as those to study Coronal Mass Ejections (CME) propagation and Solar Energetic Particle (SEP) generation.

Leamon, Robert J; 10.1086/511777

2009-01-01T23:59:59.000Z

162

Surface wind speed distributions| Implications for climate and wind power.  

E-Print Network (OSTI)

?? Surface constituent and energy fluxes, and wind power depend non-linearly on wind speed and are sensitive to the tails of the wind distribution. Until… (more)

Capps, Scott Blair

2010-01-01T23:59:59.000Z

163

Wind powering America: New York  

DOE Green Energy (OSTI)

This fact sheet contains a description of New York's wind energy resources, the state's efforts to development wind energy production, and its green power programs. The fact sheet includes a list of contacts for those interested in obtaining more information.

NREL

2000-04-10T23:59:59.000Z

164

Cielo Wind Power LLC | Open Energy Information  

Open Energy Info (EERE)

Cielo Wind Power LLC Jump to: navigation, search Name Cielo Wind Power LLC Place Austin, Texas Zip 78701 2459 Sector Wind energy Product Currently the largest wind power developer...

165

Texas Wind Energy Forecasting System Development and Testing: Phase 2: 12-Month Testing  

Science Conference Proceedings (OSTI)

Wind energy forecasting systems are expected to support system operation in cases where wind generation contributes more than a few percent of total generating capacity. This report presents final results from the Texas Wind Energy Forecasting System Development and Testing Project at a 75-MW wind project in west Texas.

2004-09-30T23:59:59.000Z

166

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime-Switching  

E-Print Network (OSTI)

Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at a wind energy site and fits a conditional predictive model for each regime. Geographically dispersed was applied to 2-hour-ahead forecasts of hourly average wind speed near the Stateline wind energy center

Genton, Marc G.

167

NREL: Wind Research - Re-Powering a Wind Farm: Wind Powering...  

NLE Websites -- All DOE Office Websites (Extended Search)

Re-Powering a Wind Farm: Wind Powering America Lessons Learned August 12, 2013 Some wind farms in the United States are nearing the end of their 20-plus-year lifetimes, increasing...

168

Comparison of post-processing methods for the calibration of 100 m wind ensemble forecasts at off- and onshore sites  

Science Conference Proceedings (OSTI)

Ensemble forecasts are a valuable addition to deterministic wind forecasts since they allow the quantification of forecast uncertainties. To remove common deficiencies of ensemble forecasts such as biases and ensemble spread deficits, various post-...

Constantin Junk; Lueder von Bremen; Martin Kühn; Stephan Späth; Detlev Heinemann

169

New England Wind Forum: Selling Wind Power  

Wind Powering America (EERE)

Selling Wind Power Selling Wind Power Markets are either well-developed or developing for each of the 'products' produced by wind generators. These include electricity products and generation attributes. Electricity Electricity can be used in two ways: on-site (interconnected behind a retail customer's meter) of for sales of electricity over the electric grid. On-site generation can displace a portion of a customer's purchases of electricity from the grid. In addition, net metering rules are in place at the state level that in some cases allow generation in excess of on-site load to be sold back to the local utility (see state pages for net metering specifics). For sales over the electricity grid, the Independent System Operator of New England (ISO New England) creates and manages a wholesale market for electric energy, capacity, and ancillary services within the New England Power Pool (NEPOOL). Wind generators may sell their electric energy and capacity in spot markets organized by the ISO, or they may contract with wholesale buyers to sell these products for any term to buyers operating in the ISO New England marketplace. Wind generators do not generally produce other marketable ancillary services. The ISO has rules specific to the operation of wind generators reflecting operations, scheduling, calculation of installed capacity credit, and so forth.

170

Wind powering America: Iowa  

DOE Green Energy (OSTI)

Wind resources in the state of Iowa show great potential for wind energy development. This fact sheet provides a brief description of the state's wind resources and the financial incentives available for the development of wind energy systems. It also provides a list of contacts for more information.

NREL

2000-04-11T23:59:59.000Z

171

Missing wind data forecasting with adaptive neuro-fuzzy inference system  

Science Conference Proceedings (OSTI)

In any region, to begin generating electricity from wind energy, it is necessary to determine the 1-year distribution characteristics of wind speed. For this aim, a wind observation station must be constructed and 1-year wind speed and direction data ... Keywords: ANFIS, Back-propagation, Forecasting, Missing data, Wind energy, Wind speed

Fatih O. Hocaoglu; Yusuf Oysal; Mehmet Kurban

2009-02-01T23:59:59.000Z

172

Sixth Northwest Conservation and Electric Power Plan Chapter 3: Electricity Demand Forecast  

E-Print Network (OSTI)

Sixth Northwest Conservation and Electric Power Plan Chapter 3: Electricity Demand Forecast Summary............................................................................................................ 2 Sixth Power Plan Demand Forecast................................................................................................ 4 Demand Forecast Range

173

One-Month Ahead Prediction of Wind Speed and Output Power Based on EMD and LSSVM  

Science Conference Proceedings (OSTI)

Wind speed is a kind of non-stationary time series, it is difficult to construct the model for accurate forecast. The way improving accuracy of the model for predicting wind speed up to one-month ahead has been investigated using measured data recorded ... Keywords: wind speed forecasting, empirical mode decomposition(EMD), least square support vector machine (LSSVM), intrinsic mode function(IFM), wind power

Wang Xiaolan; Li Hui

2009-10-01T23:59:59.000Z

174

Voluntary Green Power Market Forecast through 2015  

NLE Websites -- All DOE Office Websites (Extended Search)

158 158 May 2010 Voluntary Green Power Market Forecast through 2015 Lori Bird National Renewable Energy Laboratory Ed Holt Ed Holt & Associates, Inc. Jenny Sumner and Claire Kreycik National Renewable Energy Laboratory National Renewable Energy Laboratory 1617 Cole Boulevard, Golden, Colorado 80401-3393 303-275-3000 * www.nrel.gov NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Operated by the Alliance for Sustainable Energy, LLC Contract No. DE-AC36-08-GO28308 Technical Report NREL/TP-6A2-48158 May 2010 Voluntary Green Power Market Forecast through 2015 Lori Bird National Renewable Energy Laboratory Ed Holt Ed Holt & Associates, Inc. Jenny Sumner and Claire Kreycik National Renewable Energy Laboratory

175

Application of Ensemble Sensitivity Analysis to Observation Targeting for Short-term Wind Speed Forecasting  

Science Conference Proceedings (OSTI)

The operators of electrical grids, sometimes referred to as Balancing Authorities (BA), typically make critical decisions on how to most reliably and economically balance electrical load and generation in time frames ranging from a few minutes to six hours ahead. At higher levels of wind power generation, there is an increasing need to improve the accuracy of 0- to 6-hour ahead wind power forecasts. Forecasts on this time scale have typically been strongly dependent on short-term trends indicated by the time series of power production and meteorological data from a wind farm. Additional input information is often available from the output of Numerical Weather Prediction (NWP) models and occasionally from off-site meteorological towers in the region surrounding the wind generation facility. A widely proposed approach to improve short-term forecasts is the deployment of off-site meteorological towers at locations upstream from the wind generation facility in order to sense approaching wind perturbations. While conceptually appealing, it turns out that, in practice, it is often very difficult to derive significant benefit in forecast performance from this approach. The difficulty is rooted in the fact that the type, scale, and amplitude of the processes controlling wind variability at a site change from day to day if not from hour to hour. Thus, a location that provides some useful forecast information for one time may not be a useful predictor a few hours later. Indeed, some processes that cause significant changes in wind power production operate predominantly in the vertical direction and thus cannot be monitored by employing a network of sensors at off-site locations. Hence, it is very challenging to determine the type of sensors and deployment locations to get the most benefit for a specific short-term forecast application. Two tools recently developed in the meteorological research community have the potential to help determine the locations and parameters to measure in order to get the maximum positive impact on forecast performance for a particular site and short-term look-ahead period. Both tools rely on the use of NWP models to assess the sensitivity of a forecast for a particular location to measurements made at a prior time (i.e. the look-ahead period) at points surrounding the target location. The fundamental hypothesis is that points and variables with high sensitivity are good candidates for measurements since information at those points are likely to have the most impact on the forecast for the desired parameter, location and look-ahead period. One approach is called the adjoint method (Errico and Vukicevic, 1992; Errico, 1997) and the other newer approach is known as Ensemble Sensitivity Analysis (ESA; Ancell and Hakim 2007; Torn and Hakim 2008). Both approaches have been tested on large-scale atmospheric prediction problems (e.g. forecasting pressure or precipitation over a relatively large region 24 hours ahead) but neither has been applied to mesoscale space-time scales of winds or any other variables near the surface of the earth. A number of factors suggest that ESA is better suited for short-term wind forecasting applications. One of the most significant advantages of this approach is that it is not necessary to linearize the mathematical representation of the processes in the underlying atmospheric model as required by the adjoint approach. Such a linearization may be especially problematic for the application of short-term forecasting of boundary layer winds in complex terrain since non-linear shifts in the structure of boundary layer due to atmospheric stability changes are a critical part of the wind power production forecast problem. The specific objective of work described in this paper is to test the ESA as a tool to identify measurement locations and variables that have the greatest positive impact on the accuracy of wind forecasts in the 0- to 6-hour look-ahead periods for the wind generation area of California's Tehachapi Pass during the warm (high generation) season. The paper is organized

Zack, J; Natenberg, E; Young, S; Manobianco, J; Kamath, C

2010-02-21T23:59:59.000Z

176

Application of Ensemble Sensitivity Analysis to Observation Targeting for Short-term Wind Speed Forecasting  

DOE Green Energy (OSTI)

The operators of electrical grids, sometimes referred to as Balancing Authorities (BA), typically make critical decisions on how to most reliably and economically balance electrical load and generation in time frames ranging from a few minutes to six hours ahead. At higher levels of wind power generation, there is an increasing need to improve the accuracy of 0- to 6-hour ahead wind power forecasts. Forecasts on this time scale have typically been strongly dependent on short-term trends indicated by the time series of power production and meteorological data from a wind farm. Additional input information is often available from the output of Numerical Weather Prediction (NWP) models and occasionally from off-site meteorological towers in the region surrounding the wind generation facility. A widely proposed approach to improve short-term forecasts is the deployment of off-site meteorological towers at locations upstream from the wind generation facility in order to sense approaching wind perturbations. While conceptually appealing, it turns out that, in practice, it is often very difficult to derive significant benefit in forecast performance from this approach. The difficulty is rooted in the fact that the type, scale, and amplitude of the processes controlling wind variability at a site change from day to day if not from hour to hour. Thus, a location that provides some useful forecast information for one time may not be a useful predictor a few hours later. Indeed, some processes that cause significant changes in wind power production operate predominantly in the vertical direction and thus cannot be monitored by employing a network of sensors at off-site locations. Hence, it is very challenging to determine the type of sensors and deployment locations to get the most benefit for a specific short-term forecast application. Two tools recently developed in the meteorological research community have the potential to help determine the locations and parameters to measure in order to get the maximum positive impact on forecast performance for a particular site and short-term look-ahead period. Both tools rely on the use of NWP models to assess the sensitivity of a forecast for a particular location to measurements made at a prior time (i.e. the look-ahead period) at points surrounding the target location. The fundamental hypothesis is that points and variables with high sensitivity are good candidates for measurements since information at those points are likely to have the most impact on the forecast for the desired parameter, location and look-ahead period. One approach is called the adjoint method (Errico and Vukicevic, 1992; Errico, 1997) and the other newer approach is known as Ensemble Sensitivity Analysis (ESA; Ancell and Hakim 2007; Torn and Hakim 2008). Both approaches have been tested on large-scale atmospheric prediction problems (e.g. forecasting pressure or precipitation over a relatively large region 24 hours ahead) but neither has been applied to mesoscale space-time scales of winds or any other variables near the surface of the earth. A number of factors suggest that ESA is better suited for short-term wind forecasting applications. One of the most significant advantages of this approach is that it is not necessary to linearize the mathematical representation of the processes in the underlying atmospheric model as required by the adjoint approach. Such a linearization may be especially problematic for the application of short-term forecasting of boundary layer winds in complex terrain since non-linear shifts in the structure of boundary layer due to atmospheric stability changes are a critical part of the wind power production forecast problem. The specific objective of work described in this paper is to test the ESA as a tool to identify measurement locations and variables that have the greatest positive impact on the accuracy of wind forecasts in the 0- to 6-hour look-ahead periods for the wind generation area of California's Tehachapi Pass during the warm (high generation) season. The paper is organized

Zack, J; Natenberg, E; Young, S; Manobianco, J; Kamath, C

2010-02-21T23:59:59.000Z

177

Devon Wind Power Ltd | Open Energy Information  

Open Energy Info (EERE)

Devon Wind Power Ltd Jump to: navigation, search Name Devon Wind Power Ltd Place Exeter, United Kingdom Zip EX1 1TL Sector Wind energy Product Wind project developer - has proposed...

178

High Horizontal and Vertical Resolution Limited-Area Model: Near-Surface and Wind Energy Forecast Applications  

Science Conference Proceedings (OSTI)

As harvesting of wind energy grows, so does the need for improved forecasts from the surface to the top of wind turbines. To improve mesoscale forecasts of wind, temperature, and dewpoint temperature in this layer, two different approaches are ...

Natacha B. Bernier; Stéphane Bélair

2012-06-01T23:59:59.000Z

179

Active Power Control from Wind Power (Presentation)  

DOE Green Energy (OSTI)

In order to keep the electricity grid stable and the lights on, the power system relies on certain responses from its generating fleet. This presentation evaluates the potential for wind turbines and wind power plants to provide these services and assist the grid during critical times.

Ela, E.; Brooks, D.

2011-04-01T23:59:59.000Z

180

Objective Forecasting of Foehn Winds for a Subgrid-Scale Alpine Valley  

Science Conference Proceedings (OSTI)

Foehn winds often depend on topographical features of a scale that is not sufficiently resolved in numerical models. Consequently, a successful foehn forecast has crucially depended on the experience of bench forecasters. This study provides a ...

Susanne Drechsel; Georg J. Mayr

2008-04-01T23:59:59.000Z

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

An Application of Model Output Statistics to the Development of a Local Wind Regime Forecast Procedure  

Science Conference Proceedings (OSTI)

The Model Output Statistics (MOS) approach is used to develop a procedure for forecasting the occurrence of a local wind regime at Rota, Spain known as the levante. Variables derived solely from surface pressure and 500 mb height forecast fields ...

Robert A. Godfrey

1982-12-01T23:59:59.000Z

182

Wind Power Associates LLC | Open Energy Information  

Open Energy Info (EERE)

Associates LLC Jump to: navigation, search Name Wind Power Associates LLC Place Goldendale, Washington State Sector Wind energy Product Wind farm developer and operater....

183

Short Term Hydro Power Planning Coordinated with Wind Power in Areas with Congestion Problems  

E-Print Network (OSTI)

In this paper a day-ahead planning algorithm for a multi-reservoir hydropower system coordinated with wind power is developed. Coordination applies to real situations, where wind power and hydropower are owned by different utilities, sharing the same transmission lines, though hydropower has priority for transmission capacity. Coordination is thus necessary to minimize wind energy curtailments during congestion situations. The planning algorithm accounts for the uncertainty of wind power forecasts and power market price uncertainty. Planning for the spot market and the regulating market is considered in the algorithm. The planning algorithm is applied to a case study and the results are summarized in the paper.

J. Matevosyan; et al.

2006-01-01T23:59:59.000Z

184

Wind Power Development in the United States: The Perfect (Wind...  

NLE Websites -- All DOE Office Websites (Extended Search)

Wind Power Development in the United States: The Perfect (Wind) Storm? Speaker(s): Mark Bolinger Date: February 25, 2008 - 12:00pm Location: 90-3122 Wind power development is...

185

NREL: Wind Research - Wind Powering America Hosts 12th Annual...  

NLE Websites -- All DOE Office Websites (Extended Search)

Wind Powering America Hosts 12th Annual All-States Summit: A Wind Powering America Success Story May 21, 2013 In 2012, the wind energy industry saw great expansion in capacity as...

186

Definition: Wind power | Open Energy Information  

Open Energy Info (EERE)

Wind power Wind power Jump to: navigation, search Dictionary.png Wind power The amount of power available to a wind turbine depends on: air density, wind speed and the swept area of the rotor. While the power is proportional to air density and swept area, it varies with the cube of wind speed, so small changes in wind speed can have a relatively large impact on wind power.[1] View on Wikipedia Wikipedia Definition Wind power is the conversion of wind energy into a useful form of energy, such as using wind turbines to make electrical power, windmills for mechanical power, windpumps for water pumping or drainage, or sails to propel ships. Large wind farms consist of hundreds of individual wind turbines which are connected to the electric power transmission network. Offshore wind is steadier and stronger than on land, and offshore farms

187

Wind power outlook 2006  

DOE Green Energy (OSTI)

This annual brochure provides the American Wind Energy Association's up-to-date assessment of the wind industry in the United States. This 2006 general assessment shows positive signs of growth, use and acceptance of wind energy as a vital component of the U.S. energy mix.

anon.

2006-04-15T23:59:59.000Z

188

The Political Economy of Wind Power in China  

E-Print Network (OSTI)

of wind power, as the integration of wind power, and thecompany, found that the integration of wind power into the

Swanson, Ryan Landon

2011-01-01T23:59:59.000Z

189

Characterization and Impact of Extreme Forecast Errors on Power Systems  

SciTech Connect

Extreme events in the electrical power system, caused by the load and wind forecasting errors, can impact the power system infrastructure via two main avenues. The first avenue is a sudden and significant power unbalance exceeding reasonable operating reserve capacity. The second is a sudden increase of power flows on the system critical paths causing transmission violations. The challenge in managing these system unbalances is more significant for a standalone balancing area operation. The consolidation of balancing authorities into a single balancing area can offset the operating reserve problem but this strategy enhances incremental power flows on the transmission interfaces, potentially leading to more unpredictable transmission congestion. This paper evaluates the expectancy of occurrence of tail events due to forecast error extremes using California ISO and BPA data. Having this type of information, independent system operators and operating utilities could be better prepared to address the tail events by exploring alternative reserve options such as: wide area control coordination, new operating proce-dures and remedial actions.

Heydt, Gerald T.; Vittal, Vijay; Malhara, Sunita V.; Makarov, Yuri V.; Zhou, Ning; Etingov, Pavel V.

2011-12-15T23:59:59.000Z

190

Voluntary Green Power Market Forecast through 2015  

SciTech Connect

Various factors influence the development of the voluntary 'green' power market--the market in which consumers purchase or produce power from non-polluting, renewable energy sources. These factors include climate policies, renewable portfolio standards (RPS), renewable energy prices, consumers' interest in purchasing green power, and utilities' interest in promoting existing programs and in offering new green options. This report presents estimates of voluntary market demand for green power through 2015 that were made using historical data and three scenarios: low-growth, high-growth, and negative-policy impacts. The resulting forecast projects the total voluntary demand for renewable energy in 2015 to range from 63 million MWh annually in the low case scenario to 157 million MWh annually in the high case scenario, representing an approximately 2.5-fold difference. The negative-policy impacts scenario reflects a market size of 24 million MWh. Several key uncertainties affect the results of this forecast, including uncertainties related to growth assumptions, the impacts that policy may have on the market, the price and competitiveness of renewable generation, and the level of interest that utilities have in offering and promoting green power products.

Bird, L.; Holt, E.; Sumner, J.; Kreycik, C.

2010-05-01T23:59:59.000Z

191

Voluntary Green Power Market Forecast through 2015  

SciTech Connect

Various factors influence the development of the voluntary 'green' power market--the market in which consumers purchase or produce power from non-polluting, renewable energy sources. These factors include climate policies, renewable portfolio standards (RPS), renewable energy prices, consumers' interest in purchasing green power, and utilities' interest in promoting existing programs and in offering new green options. This report presents estimates of voluntary market demand for green power through 2015 that were made using historical data and three scenarios: low-growth, high-growth, and negative-policy impacts. The resulting forecast projects the total voluntary demand for renewable energy in 2015 to range from 63 million MWh annually in the low case scenario to 157 million MWh annually in the high case scenario, representing an approximately 2.5-fold difference. The negative-policy impacts scenario reflects a market size of 24 million MWh. Several key uncertainties affect the results of this forecast, including uncertainties related to growth assumptions, the impacts that policy may have on the market, the price and competitiveness of renewable generation, and the level of interest that utilities have in offering and promoting green power products.

Bird, L.; Holt, E.; Sumner, J.; Kreycik, C.

2010-05-01T23:59:59.000Z

192

Wind Powering America Newsletter (Postcard)  

DOE Green Energy (OSTI)

Wind Powering America is a nationwide initiative of the U.S. Department of Energy's Wind Program designed to educate, engage, and enable critical stakeholders to make informed decisions about how wind energy contributes to the U.S. electricity supply. As part of Wind Powering America's outreach efforts, the team publishes a biweekly e-newsletter. This postcard is a marketing piece that stakeholders can provide to interested parties; it will guide them to the a website page at which they can sign up for the e-newsletter.

Not Available

2012-08-01T23:59:59.000Z

193

Wind powering America: America's wind power...a natural resource  

DOE Green Energy (OSTI)

The Wind Powering America Initiative is a regionally-based effort to increase the use of clean wind energy in the United States over the next two decades. The purpose of this brochure is to provide a brief description of the initiative, its goals, benefits, and strategy as well as a list of contacts for those interested in obtaining more information.

NONE

2000-04-04T23:59:59.000Z

194

Wind Powering America: America's Wind Power...A Natural Resource  

DOE Green Energy (OSTI)

The Wind Powering America Initiative is a regionally-based effort to increase the use of clean wind energy in the United States over the next two decades. The purpose of this brochure is to provide a brief description of the initiative, its goals, benefits, and strategy as well as a list of contacts for those interested in obtaining more information.

Dougherty, P.

2001-05-23T23:59:59.000Z

195

Wind Powering America: Agricultural Podcasts  

Wind Powering America (EERE)

agricultural/podcasts.asp A series of agricultural/podcasts.asp A series of radio interviews on wind energy aimed at a rural stakeholder audience produced by Wind Powering America and the National Association of Farm Broadcasters. en-us julie.jones@nrel.gov (Julie Jones) http://www.windpoweringamerica.gov/images/wpa_logo_sm.jpg Wind Powering America: Agricultural Podcasts http://www.windpoweringamerica.gov/agricultural/podcasts.asp Wind Energy Forum Enhances Positives of Wind Production http://www.windpoweringamerica.gov/filter_detail.asp?itemid=4043 http://www.windpoweringamerica.gov/filter_detail.asp?itemid=4043 Thu, 14 Nov 2013 00:00:00 MST Rural Communities Benefit from Wind Energy's Continued Success http://www.windpoweringamerica.gov/filter_detail.asp?itemid=4021 http://www.windpoweringamerica.gov/filter_detail.asp?itemid=4021 Tue, 29

196

Wind Powering America Webinar: Wind Power Economics: Past, Present, and  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Power Economics: Past, Present, Power Economics: Past, Present, and Future Trends Wind Powering America Webinar: Wind Power Economics: Past, Present, and Future Trends November 23, 2011 - 1:43pm Addthis Wind turbine prices in the United States have declined, on average, by nearly one-third since 2008, after doubling from 2002 through 2008. Over this entire period, the average nameplate capacity rating, hub height, and rotor swept area of turbines installed in the United States have increased significantly, while other design improvements have also boosted turbine energy production. In combination, these various trends have had a significant-and sometimes surprising-impact on the levelized cost of energy delivered by wind projects. This webinar will feature three related presentations that explore these

197

TS Wind Power Developers | Open Energy Information  

Open Energy Info (EERE)

Login | Sign Up Search Page Edit with form History Facebook icon Twitter icon TS Wind Power Developers Jump to: navigation, search Name TS Wind Power Developers Place...

198

Standardized Software for Wind Load Forecast Error Analyses and Predictions Based on Wavelet-ARIMA Models - Applications at Multiple Geographically Distributed Wind Farms  

Science Conference Proceedings (OSTI)

Given the multi-scale variability and uncertainty of wind generation and forecast errors, it is a natural choice to use time-frequency representation (TFR) as a view of the corresponding time series represented over both time and frequency. Here we use wavelet transform (WT) to expand the signal in terms of wavelet functions which are localized in both time and frequency. Each WT component is more stationary and has consistent auto-correlation pattern. We combined wavelet analyses with time series forecast approaches such as ARIMA, and tested the approach at three different wind farms located far away from each other. The prediction capability is satisfactory -- the day-ahead prediction of errors match the original error values very well, including the patterns. The observations are well located within the predictive intervals. Integrating our wavelet-ARIMA (‘stochastic’) model with the weather forecast model (‘deterministic’) will improve our ability significantly to predict wind power generation and reduce predictive uncertainty.

Hou, Zhangshuan; Makarov, Yuri V.; Samaan, Nader A.; Etingov, Pavel V.

2013-03-19T23:59:59.000Z

199

Wind powering America: North Dakota  

DOE Green Energy (OSTI)

This fact sheet contains a description of North Dakota's wind energy resources, the state's efforts to development wind energy production, and its green power and net metering programs. The fact sheet includes a list of contacts for those interested in obtaining more information.

NREL

2000-04-10T23:59:59.000Z

200

Space-time forecasting and evaluation of wind speed with statistical tests for comparing accuracy of spatial predictions  

E-Print Network (OSTI)

High-quality short-term forecasts of wind speed are vital to making wind power a more reliable energy source. Gneiting et al. (2006) have introduced a model for the average wind speed two hours ahead based on both spatial and temporal information. The forecasts produced by this model are accurate, and subject to accuracy, the predictive distribution is sharp, i.e., highly concentrated around its center. However, this model is split into nonunique regimes based on the wind direction at an off-site location. This work both generalizes and improves upon this model by treating wind direction as a circular variable and including it in the model. It is robust in many experiments, such as predicting at new locations. This is compared with the more common approach of modeling wind speeds and directions in the Cartesian space and use a skew-t distribution for the errors. The quality of the predictions from all of these models can be more realistically assessed with a loss measure that depends upon the power curve relating wind speed to power output. This proposed loss measure yields more insight into the true value of each model's predictions. One method of evaluating time series forecasts, such as wind speed forecasts, is to test the null hypothesis of no difference in the accuracy of two competing sets of forecasts. Diebold and Mariano (1995) proposed a test in this setting that has been extended and widely applied. It allows the researcher to specify a wide variety of loss functions, and the forecast errors can be non-Gaussian, nonzero mean, serially correlated, and contemporaneously correlated. In this work, a similar unconditional test of forecast accuracy for spatial data is proposed. The forecast errors are no longer potentially serially correlated but spatially correlated. Simulations will illustrate the properties of this test, and an example with daily average wind speeds measured at over 100 locations in Oklahoma will demonstrate its use. This test is compared with a wavelet-based method introduced by Shen et al. (2002) in which the presence of a spatial signal at each location in the dataset is tested.

Hering, Amanda S.

2009-08-01T23:59:59.000Z

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

2008 Wind Energy Projects, Wind Powering America (Poster)  

SciTech Connect

The Wind Powering America program produces a poster at the end of every calendar year that depicts new U.S. wind energy projects. The 2008 poster includes the following projects: Stetson Wind Farm in Maine; Dutch Hill Wind Farm in New York; Grand Ridge Wind Energy Center in Illinois; Hooper Bay, Alaska; Forestburg, South Dakota; Elbow Creek Wind Project in Texas; Glacier Wind Farm in Montana; Wray, Colorado; Smoky Hills Wind Farm in Kansas; Forbes Park Wind Project in Massachusetts; Spanish Fork, Utah; Goodland Wind Farm in Indiana; and the Tatanka Wind Energy Project on the border of North Dakota and South Dakota.

2009-01-01T23:59:59.000Z

202

Wind and solar powered turbine  

SciTech Connect

A power generating station having a generator driven by solar heat assisted ambient wind is disclosed. A first plurality of radially extending air passages direct ambient wind to a radial flow wind turbine disposed in a centrally located opening in a substantially disc-shaped structure. A solar radiation collecting surface having black bodies is disposed above the first plurality of air passages and in communication with a second plurality of radial air passages. A cover plate enclosing the second plurality of radial air passages is transparent so as to permit solar radiation to effectively reach the black bodies. The second plurality of air passages direct ambient wind and thermal updrafts generated by the black bodies to an axial flow turbine which also derives additional motive power from the air mass exhausted by the radial flow turbine. The rotating shaft of the turbines drive the generator. The solar and wind driven power generating system operates in electrical cogeneration mode with a fuel powered prime mover. The system is particularly adapted to satisfy the power requirements of a relatively small community located in a geographic area having favorable climatic conditions for wind and solar powered power generation.

Wells, I.D.; Holmes, M.; Kohn, J.L.

1984-02-28T23:59:59.000Z

203

Atmospheric Boundary-Layer Properties Affecting Wind Forecasting in Coastal Regions  

Science Conference Proceedings (OSTI)

Atmospheric boundary-layer properties and processes in gulf and coastal regions have special characteristics that are important in forecasting winds and ocean forcing. Accurate coastal-wind predictions require knowledge of local responses to a ...

Kenneth L. Davidson; Patricia J. Boyle; Peter S. Guest

1992-08-01T23:59:59.000Z

204

A Real-Time Hurricane Surface Wind Forecasting Model: Formulation and Verification  

Science Conference Proceedings (OSTI)

A real-time hurricane wind forecast model is developed by 1) incorporating an asymmetric effect into the Holland hurricane wind model; 2) using the National Oceanic and Atmospheric Administration (NOAA)/National Hurricane Center’s (NHC) hurricane ...

Lian Xie; Shaowu Bao; Leonard J. Pietrafesa; Kristen Foley; Montserrat Fuentes

2006-05-01T23:59:59.000Z

205

Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast  

E-Print Network (OSTI)

Sixth Northwest Conservation and Electric Power Plan Appendix C: Demand Forecast Energy Demand................................................................................................................................. 1 Demand Forecast Methodology.................................................................................................. 3 New Demand Forecasting Model for the Sixth Plan

206

Sixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast  

E-Print Network (OSTI)

Sixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast Introduction................................................................................................................................. 3 Price Forecasts............................................................................................................................... 12 Oil Price Forecast Range

207

Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast  

E-Print Network (OSTI)

Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast Role of the Economic Forecast.................................................................................. 19 Forecasting Commercial Floor Space Requirements

208

ANEMOS: Development of a Next Generation Wind Power  

E-Print Network (OSTI)

This paper presents the objectives and the research work carried out in the frame of the ANEMOS project on short-term wind power forecasting. The aim of the project is to develop accurate models that substantially outperform current state-of-the-art methods, for onshore and offshore wind power forecasting, exploiting both statistical and physical modeling approaches. The project focus on prediction horizons up to 48 hours ahead and investigates predictability of wind for higher horizons up to 7 days ahead useful i.e. for maintenance scheduling. Emphasis is given on the integration of highresolution meteorological forecasts. For the offshore case, marine meteorology is considered as well as information by satellite-radar images. An integrated software platform, `ANEMOS', is developed to host the various models. This system will be installed by several utilities for on-line operation at onshore and offshore wind farms for prediction at a local, regional and national scale. The applications include different terrain types and wind climates, on- and offshore cases, and interconnected or island grids. The on-line operation by the utilities will allow validation of the models and an analysis of the value of wind prediction for a competitive integration of wind energy in the developing liberalized electricity markets in the EU.

Forecasting System For; G. Kariniotakis; J. Ottavi; U. Focken; M. Lange; J. Kintxo; J. Usaola; I. Sanchez; D. Mccoy; I. Marti H. Madsen; M. Collmann; A. Gig; G. Gonzales

2003-01-01T23:59:59.000Z

209

Wind powering America: New Mexico  

DOE Green Energy (OSTI)

This fact sheet provides a brief description of the wind resources in New Mexico and the state's net metering and green power programs. The fact sheet also provides a list of contacts for more information.

NREL

2000-04-11T23:59:59.000Z

210

Guodian Linghai Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Linghai Wind Power Co Ltd Jump to: navigation, search Name Guodian Linghai Wind Power Co Ltd Place China Sector Wind energy Product Wind power project developer. References Guodian...

211

Wind Power Overview Windpoweristhefastestgrowingformofrenewableenergy,withpoten-  

E-Print Network (OSTI)

Wind Power Overview · Windpoweristhefastestgrowingformofrenewableenergy Offshore Wind Power for Florida? · AveragehouseholdelectricitycostsforFloridaare expectedtoincreaseby4.7%($7.50/month)each yearoverthenextdecade2 . · Offshore winds are typically stronger and more

212

Offshore Wind Power | Open Energy Information  

Open Energy Info (EERE)

Power Jump to: navigation, search Name Offshore Wind Power Place St Albans, United Kingdom Zip AL1 3AW Sector Wind energy Product Formed to develop offshore wind farms around the...

213

System-wide emissions implications of increased wind power penetration.  

DOE Green Energy (OSTI)

This paper discusses the environmental effects of incorporating wind energy into the electric power system. We present a detailed emissions analysis based on comprehensive modeling of power system operations with unit commitment and economic dispatch for different wind penetration levels. First, by minimizing cost, the unit commitment model decides which thermal power plants will be utilized based on a wind power forecast, and then, the economic dispatch model dictates the level of production for each unit as a function of the realized wind power generation. Finally, knowing the power production from each power plant, the emissions are calculated. The emissions model incorporates the effects of both cycling and start-ups of thermal power plants in analyzing emissions from an electric power system with increasing levels of wind power. Our results for the power system in the state of Illinois show significant emissions effects from increased cycling and particularly start-ups of thermal power plants. However, we conclude that as the wind power penetration increases, pollutant emissions decrease overall due to the replacement of fossil fuels.

Valentino, L.; Valenzuela, V.; Botterud, A.; Zhou, Z.; Conzelmann, G. (Decision and Information Sciences); (Univ. of Illinois, Champaign/Urbana); (Georgia Institute of Technology)

2012-01-01T23:59:59.000Z

214

Comparison of 10-m Wind Forecasts from a Regional Area Model and QuikSCAT Scatterometer Wind Observations over the Mediterranean Sea  

Science Conference Proceedings (OSTI)

Surface wind forecasts from a limited-area model [the Quadrics Bologna Limited-Area Model (QBOLAM)] covering the entire Mediterranean area at 0.1° grid spacing are verified against Quick Scatterometer (QuikSCAT) wind observations. Only forecasts ...

Christophe Accadia; Stefano Zecchetto; Alfredo Lavagnini; Antonio Speranza

2007-05-01T23:59:59.000Z

215

Accuracy of RUC-1 and RUC-2 Wind and Aircraft Trajectory Forecasts by Comparison with ACARS Observations  

Science Conference Proceedings (OSTI)

As part of an investigation into terminal airspace productivity sponsored by the NASA Ames Research Center, a study was performed at the Forecast Systems Laboratory to investigate sources of wind forecast error and to assess differences in wind ...

Barry E. Schwartz; Stanley G. Benjamin; Steven M. Green; Matthew R. Jardin

2000-06-01T23:59:59.000Z

216

ESS 2012 Peer Review - Wind Firming EnergyFarm - Tom Stepien...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

the Bonneville Power Administration area. Forecasting wind is tricky. Plot shows: (forecast - actual)forecast. 5 sec data shown. 9 Modesto currently integrates intermittent...

217

NREL: Wind Research - Wind Powering America - A Credible Source...  

NLE Websites -- All DOE Office Websites (Extended Search)

Wind Powering America - A Credible Source for Information August 6, 2013 The goal of the Wind Powering America (WPA) initiative, established by the U.S. Department of Energy (DOE)...

218

NREL: Wind Research - DOE Releases Wind Powering America Impact...  

NLE Websites -- All DOE Office Websites (Extended Search)

DOE Releases Wind Powering America Impact Study June 3, 2013 The U.S. Department of Energy (DOE) established Wind Powering America (WPA) in 1999 to educate, engage, and enable...

219

NREL: Wind Research - 2013 Public Power Wind Award Nominations  

NLE Websites -- All DOE Office Websites (Extended Search)

The 2013 Public Power Wind Award is sponsored by the U.S. Department of Energy's Wind Powering America initiative in partnership with the APPA. This year marks the eleventh...

220

Wind Powering America: Webinar Podcasts  

Wind Powering America (EERE)

podcasts_webinar.asp A series of podcasts_webinar.asp A series of Webinars about current wind energy issues. en-us julie.jones@nrel.gov (Julie Jones) http://www.windpoweringamerica.gov/images/wpa_logo_sm.jpg Wind Powering America: Webinar Podcasts http://www.windpoweringamerica.gov/podcasts_webinar.asp Stakeholder Engagement and Outreach Webinar: Jobs and Economic Development Impacts of Offshore Wind http://www.windpoweringamerica.gov/filter_detail.asp?itemid=4004 http://www.windpoweringamerica.gov/filter_detail.asp?itemid=4004 Sun, 1 Dec 2013 00:00:00 MST Small Wind Standards and Policy Update: A WPA Webinar http://www.windpoweringamerica.gov/filter_detail.asp?itemid=3976 http://www.windpoweringamerica.gov/filter_detail.asp?itemid=3976 Fri, 20 Sep 2013 00:00:00 MST 2012 Market Report on U.S. Wind Technologies in

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

California Wind Energy Forecasting Program Description and Status - 2000: California Energy Commission--EPRI Wind Energy Forecasting Program  

Science Conference Proceedings (OSTI)

The modern era of wind power began in the early 1980s when the first large installations of modern wind turbines were installed in California. The industry has grown rapidly in recent years and, at the end of 1999, the total installed wind capacity was 13.4 gigawatts (GW) worldwide and 2.5 GW in the U.S., of which about 1.6 GW is operating in California. Deregulation of the California electricity markets in 1998 created a challenge for the California investor-owned utilitiies and the owners and operators...

2000-12-18T23:59:59.000Z

222

Long-Term Wind Power Variability  

DOE Green Energy (OSTI)

The National Renewable Energy Laboratory started collecting wind power data from large commercial wind power plants (WPPs) in southwest Minnesota with dedicated dataloggers and communication links in the spring of 2000. Over the years, additional WPPs in other areas were added to and removed from the data collection effort. The longest data stream of actual wind plant output is more than 10 years. The resulting data have been used to analyze wind power fluctuations, frequency distribution of changes, the effects of spatial diversity, and wind power ancillary services. This report uses the multi-year wind power data to examine long-term wind power variability.

Wan, Y. H.

2012-01-01T23:59:59.000Z

223

Infinity Wind Power Inc | Open Energy Information  

Open Energy Info (EERE)

energy project developer assisting landowners to participate in the renewable energy industry, and more specifically, with wind energy projects. References Infinity Wind Power,...

224

Berkshire Wind Power Cooperative | Open Energy Information  

Open Energy Info (EERE)

Wind Power Cooperative Wind Power Cooperative Jump to: navigation, search Name Berkshire Wind Power Cooperative Place Holyoke, Massachusetts Sector Wind energy Product The Berkshire Wind Power Cooperative Corp. is a municipal cooperative of 14 Massachusetts municipal utilities and the Massachusetts Municipal Wholesale Electric Co. (MMWEC) invovled in the development of wind farms. References Berkshire Wind Power Cooperative[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Berkshire Wind Power Cooperative is a company located in Holyoke, Massachusetts . References ↑ "Berkshire Wind Power Cooperative" Retrieved from "http://en.openei.org/w/index.php?title=Berkshire_Wind_Power_Cooperative&oldid=342679

225

Short-Term Wind Generation Forecasting Using Artificial Neural Networks  

Science Conference Proceedings (OSTI)

Wind power is a highly intermittent power output resource that cannot be bid competitively in a traditional market due to scheduling problems associated with the resource. The California Independent System Operator (CAISO) has proposed a unique market arrangement that makes such bidding possible. The central part of the arrangement is a provision that deviations between metered and scheduled energy for participating intermittent renewable resources will be averaged across a calendar month, and paid or ch...

2003-10-27T23:59:59.000Z

226

Power Quality Aspects in a Wind Power Plant: Preprint  

SciTech Connect

Although many operational aspects affect wind power plant operation, this paper focuses on power quality. Because a wind power plant is connected to the grid, it is very important to understand the sources of disturbances that affect the power quality.

Muljadi, E.; Butterfield, C. P.; Chacon, J.; Romanowitz, H.

2006-01-01T23:59:59.000Z

227

Jilin Tongli Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Jilin Province, China Sector Wind energy Product Jilin-based company focused on wind power generation and development of wind projects. References Jilin Tongli Wind Power Co...

228

Liaoning Kangping Jinshan Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Kangping Jinshan Wind Power Co Ltd Jump to: navigation, search Name Liaoning Kangping Jinshan Wind Power Co Ltd Place Liaoning Province, China Sector Wind energy Product Wind farm...

229

Wind Fins: Novel Lower-Cost Wind Power System  

DOE Green Energy (OSTI)

This project evaluated the technical feasibility of converting energy from the wind with a novel “wind fin” approach. This patent-pending technology has three major components: (1) a mast, (2) a vertical, hinged wind structure or fin, and (3) a power takeoff system. The wing structure responds to the wind with an oscillating motion, generating power. The overall project goal was to determine the basic technical feasibility of the wind fin technology. Specific objectives were the following: (1) to determine the wind energy-conversion performance of the wind fin and the degree to which its performance could be enhanced through basic design improvements; (2) to determine how best to design the wind fin system to survive extreme winds; (3) to determine the cost-effectiveness of the best wind fin designs compared to state-of-the-art wind turbines; and (4) to develop conclusions about the overall technical feasibility of the wind fin system. Project work involved extensive computer modeling, wind-tunnel testing with small models, and testing of bench-scale models in a wind tunnel and outdoors in the wind. This project determined that the wind fin approach is technically feasible and likely to be commercially viable. Project results suggest that this new technology has the potential to harvest wind energy at approximately half the system cost of wind turbines in the 10kW range. Overall, the project demonstrated that the wind fin technology has the potential to increase the economic viability of small wind-power generation. In addition, it has the potential to eliminate lethality to birds and bats, overcome public objections to the aesthetics of wind-power machines, and significantly expand wind-power’s contribution to the national energy supply.

David C. Morris; Dr. Will D. Swearingen

2007-10-08T23:59:59.000Z

230

Evaluation of Wave Forecasts Consistent with Tropical Cyclone Warning Center Wind Forecasts  

Science Conference Proceedings (OSTI)

An algorithm to generate wave fields consistent with forecasts from the official U.S. tropical cyclone forecast centers has been made available in near–real time to forecasters since summer 2007. The algorithm removes the tropical cyclone from ...

Charles R. Sampson; Paul A. Wittmann; Efren A. Serra; Hendrik L. Tolman; Jessica Schauer; Timothy Marchok

2013-02-01T23:59:59.000Z

231

Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint  

Science Conference Proceedings (OSTI)

Forecasting solar energy generation is a challenging task due to the variety of solar power systems and weather regimes encountered. Forecast inaccuracies can result in substantial economic losses and power system reliability issues. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, applications, etc.). In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design of experiments methodology, in conjunction with response surface and sensitivity analysis methods. The results show that the developed metrics can efficiently evaluate the quality of solar forecasts, and assess the economic and reliability impact of improved solar forecasting.

Zhang, J.; Hodge, B. M.; Florita, A.; Lu, S.; Hamann, H. F.; Banunarayanan, V.

2013-10-01T23:59:59.000Z

232

Wind: wind speed and wind power density GIS data at 10m and 50m...  

Open Energy Info (EERE)

data files of wind speed and wind power density at 10 and 50 m heights. Global data of offshore wind resource as generated by NASA's QuikScat SeaWinds scatterometer.

...

233

Wind: wind speed and wind power density maps at 10m and 50m above...  

Open Energy Info (EERE)

data files of wind speed and wind power density at 10 and 50 m heights. Global data of offshore wind resource as generated by NASA's QuikSCAT SeaWinds scatterometer.

...

234

Low-Maintenance Wind Power System  

E-Print Network (OSTI)

with widespread adoption of wind energy. The project hasProject: Low-Maintenance Wind Power System Summary of theImproved Vertical Axis Wind Turbine and Aerodynamic Control

Rasson, Joseph E

2010-01-01T23:59:59.000Z

235

Wind Power Integration: Exploring Impacts and Alternatives  

E-Print Network (OSTI)

Wind Power Integration: Exploring Impacts and Alternatives Assist. Prof. C sustainable sources of energy. The idea of harnessing wind energy has been there have been no less than fifteen in-depth wind integration studies

Walter, M.Todd

236

Wind Powering America Webinar: Wind and Wildlife Interactions | Department  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

and Wildlife Interactions and Wildlife Interactions Wind Powering America Webinar: Wind and Wildlife Interactions November 23, 2011 - 2:08pm Addthis This webinar is part of the U.S. Department of Energy's Wind Powering America 2011 webinar series. This webinar will provide an overview of wind turbine and wildlife issues, including a summary of research plans by the American Wind and Wildlife Institute. Other topics will include an update of the U.S. Fish and Wildlife Service wind regulations and bat/wind turbine interactions. The webinar is free; no registration is required. More Addthis Related Articles Wind Powering America Webinar: Wind Power Economics: Past, Present, and Future Trends DOE Announces Webinar on Tying Energy Efficiency to Compensation and Performance Reviews, and More

237

Wind energy and power system interconnection, control, and operation for high penetration of wind power .  

E-Print Network (OSTI)

??High penetration of wind energy requires innovations in different areas of power engineering. Methods for improving wind energy and power system interconnection, control, and operation… (more)

Liang, Jiaqi

2012-01-01T23:59:59.000Z

238

Department of Energy Bonneville Power Administration  

E-Print Network (OSTI)

Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations Audun Botterud (point forecast ­ 10% quantile forecast) Det. Point R3 Det. UC w/additional reserve (15% of load) Det Stochastic UC w/additional reserve (15% of load) Stoch. Scenarios #12;Wind Power Forecast Day-ahead point

239

The Value of Wind Power Forecasting  

NLE Websites -- All DOE Office Websites (Extended Search)

Preprint Debra Lew and Michael Milligan National Renewable Energy Laboratory Gary Jordan and Richard Piwko GE Energy Presented at the 91 st American Meteorological Society...

240

Wind Powering America Initiative (Fact Sheet)  

DOE Green Energy (OSTI)

The U.S. Department of Energy's Wind Powering America initiative engages in technology market acceptance, barrier reduction, and technology deployment support activities. This fact sheet outlines ways in which the Wind Powering America team works to reduce barriers to appropriate wind energy deployment, primarily by focusing on six program areas: workforce development, communications and outreach, stakeholder analysis and resource assessment, wind technology technical support, wind power for Native Americans, and federal sector support and collaboration.

Not Available

2011-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Wind Powering America Initiative (Fact Sheet)  

SciTech Connect

The U.S. Department of Energy's Wind Powering America initiative engages in technology market acceptance, barrier reduction, and technology deployment support activities. This fact sheet outlines ways in which the Wind Powering America team works to reduce barriers to appropriate wind energy deployment, primarily by focusing on six program areas: workforce development, communications and outreach, stakeholder analysis and resource assessment, wind technology technical support, wind power for Native Americans, and federal sector support and collaboration.

2011-01-01T23:59:59.000Z

242

Wind Power Plant Monitoring Project Annual Report  

DOE Green Energy (OSTI)

The intermittent nature of the wind resource, together with short-term power fluctuations, are the two principal issues facing a utility with wind power plants in its power grid. To mitigate these issues, utilities, wind power plant developers, and operators need to understand the nature of wind power fluctuations and how they affect the electrical power system, as well as to analyze ancillary service requirements with real wind power plant output data. To provide the necessary data, NREL conducted a study to collect at least 2 years of long-term, high-frequency (1-hertz [Hz]) data from several medium- to large-scale wind power plants with different wind resources, terrain features, and turbine types. Researchers then analyzed the data for power fluctuations, frequency distribution of wind power (by deriving a probability distribution function of wind power plant output variations), spatial and temporal diversity of wind power, and wind power capacity credit issues. Results of these analyses can provide data on the potential effects of wind power plants on power system regulation.

Wan, Y.

2001-07-11T23:59:59.000Z

243

Capacity Value of Wind Power  

Science Conference Proceedings (OSTI)

Power systems are planned such that they have adequate generation capacity to meet the load, according to a defined reliability target. The increase in the penetration of wind generation in recent years has led to a number of challenges for the planning and operation of power systems. A key metric for system adequacy is the capacity value of generation. The capacity value of a generator is the contribution that a given generator makes to overall system adequacy. The variable and stochastic nature of wind sets it apart from conventional energy sources. As a result, the modeling of wind generation in the same manner as conventional generation for capacity value calculations is inappropriate. In this paper a preferred method for calculation of the capacity value of wind is described and a discussion of the pertinent issues surrounding it is given. Approximate methods for the calculation are also described with their limitations highlighted. The outcome of recent wind capacity value analyses in Europe and North America are highlighted with a description of open research questions also given.

Keane, Andrew; Milligan, Michael; Dent, Chris; Hasche, Bernhard; DAnnunzio, Claudine; Dragoon, Ken; Holttinen, Hannele; Samaan, Nader A.; Soder, Lennart; O'Malley, Mark J.

2011-05-04T23:59:59.000Z

244

Padoma Wind Power LLC | Open Energy Information  

Open Energy Info (EERE)

Padoma Wind Power LLC Padoma Wind Power LLC Jump to: navigation, search Name Padoma Wind Power LLC Place La Jolla, California Zip 92037 Sector Wind energy Product A wind energy consulting and development company. References Padoma Wind Power LLC[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Padoma Wind Power LLC is a company located in La Jolla, California . References ↑ "Padoma Wind Power LLC" Retrieved from "http://en.openei.org/w/index.php?title=Padoma_Wind_Power_LLC&oldid=349559" Categories: Clean Energy Organizations Companies Organizations Stubs What links here Related changes Special pages Printable version Permanent link Browse properties 429 Throttled (bot load)

245

New England Wind Forum: Wind Power Policy in New England  

Wind Powering America (EERE)

Projects in New England Building Wind Energy in New England Wind Resource Wind Power Technology Economics Markets Siting Policy Renewable Energy Portfolio Standards State Renewable Energy Funds Federal Tax Incentives and Grants Net Metering and Interconnection Standards Pollutant Emission Reduction Policies Awareness Technical Challenges Issues Small Wind Large Wind Newsletter Perspectives Events Quick Links to States CT MA ME NH RI VT Bookmark and Share Wind Power Policy in New England Why Incentives and Policy? Federal and state policies play an important role in encouraging wind energy development by leveling the playing field compared to other energy sources. Many of the substantial benefits of wind power as a domestic, zero-emission part of the energy portfolio - sustainability, displacement of pollutant emissions from other power sources, fuel diversity, price stabilization, keeping a substantial portion of energy expenditures in the local economy - are shared by society as a whole and cannot be readily captured by wind generators directly in the price they charge for their output. In addition, while wind power receives some policy support, the level of federal incentives for wind represents less than 1% of the subsidies and tax breaks given to the fossil fuels and nuclear industries (source: "Wind Power An Increasingly Competitive Source of New Generation." Wind Energy Weekly #1130.).

246

An Optimized Autoregressive Forecast Error Generator for Wind and Load Uncertainty Study  

SciTech Connect

This paper presents a first-order autoregressive algorithm to generate real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast errors. The methodology aims at producing random wind and load forecast time series reflecting the autocorrelation and cross-correlation of historical forecast data sets. Five statistical characteristics are considered: the means, standard deviations, autocorrelations, and cross-correlations. A stochastic optimization routine is developed to minimize the differences between the statistical characteristics of the generated time series and the targeted ones. An optimal set of parameters are obtained and used to produce the RT, HA, and DA forecasts in due order of succession. This method, although implemented as the first-order regressive random forecast error generator, can be extended to higher-order. Results show that the methodology produces random series with desired statistics derived from real data sets provided by the California Independent System Operator (CAISO). The wind and load forecast error generator is currently used in wind integration studies to generate wind and load inputs for stochastic planning processes. Our future studies will focus on reflecting the diurnal and seasonal differences of the wind and load statistics and implementing them in the random forecast generator.

De Mello, Phillip; Lu, Ning; Makarov, Yuri V.

2011-01-17T23:59:59.000Z

247

Wethersfield Wind Power Wind Farm | Open Energy Information  

Open Energy Info (EERE)

Wethersfield Wind Power Wind Farm Wethersfield Wind Power Wind Farm Facility Wethersfield Wind Power Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner Enel North America Developer Western NY Wind Power Partners Energy Purchaser Niagara Mohawk Location WY County NY Coordinates 42.667741°, -78.219803° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":42.667741,"lon":-78.219803,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

248

Wind for Schools: A Wind Powering America Project (Alaska) (Brochure)  

DOE Green Energy (OSTI)

This brochure provides an overview of Wind Powering America's Wind for Schools Project, including a description of the project, the participants, funding sources, the basic configurations, and how interested parties can become involved.

Not Available

2010-02-01T23:59:59.000Z

249

Wind for Schools: A Wind Powering America Project (Brochure)  

DOE Green Energy (OSTI)

This brochure provides an overview of Wind Powering America's Wind for Schools Project, including a description of the project, the participants, funding sources, the basic configurations, and how interested parties can become involved.

Baring-Gould, I.

2009-08-01T23:59:59.000Z

250

Wind for Schools: A Wind Powering America Project  

Science Conference Proceedings (OSTI)

This brochure serves as an introduction to Wind Powering America's Wind for Schools Project, including a description of the project, the participants, funding sources, and the basic configurations of the project.

Not Available

2007-12-01T23:59:59.000Z

251

Primer on Wind Power for Utility Applications  

SciTech Connect

The wind industry still faces many market barriers, some of which stem from utilities' lack of experience with the technology. Utility system operators and planners need to understand the effects of fluctuating wind power on system regulation and stability. Without high-frequency wind power data and realistic wind power plant models to analyze the problem, utilities often rely on conservative assumptions and worst-case scenarios to make engineering decisions. To remedy the situation, the National Renewable Energy Laboratory (NREL) has undertaken a project to record long-term, high-resolution (1-hertz [Hz]) wind power output data from large wind power plants in various regions. The objective is to systematically collect actual wind power data from large commercial wind power plants so that wind power fluctuations, their frequency distribution, the effects of spatial diversity, and the ancillary services of large commercial wind power plants can be analyzed. It also aims to provide the industry with nonproprietary wind power data in different wind regimes for system planning and operating impact studies. This report will summarize the results of data analysis performed at NREL and discuss the wind power characteristics related to power system operation and planning.

Wan, Y.

2005-12-01T23:59:59.000Z

252

Primer on Wind Power for Utility Applications  

DOE Green Energy (OSTI)

The wind industry still faces many market barriers, some of which stem from utilities' lack of experience with the technology. Utility system operators and planners need to understand the effects of fluctuating wind power on system regulation and stability. Without high-frequency wind power data and realistic wind power plant models to analyze the problem, utilities often rely on conservative assumptions and worst-case scenarios to make engineering decisions. To remedy the situation, the National Renewable Energy Laboratory (NREL) has undertaken a project to record long-term, high-resolution (1-hertz [Hz]) wind power output data from large wind power plants in various regions. The objective is to systematically collect actual wind power data from large commercial wind power plants so that wind power fluctuations, their frequency distribution, the effects of spatial diversity, and the ancillary services of large commercial wind power plants can be analyzed. It also aims to provide the industry with nonproprietary wind power data in different wind regimes for system planning and operating impact studies. This report will summarize the results of data analysis performed at NREL and discuss the wind power characteristics related to power system operation and planning.

Wan, Y.

2005-12-01T23:59:59.000Z

253

2011 Grants for Offshore Wind Power | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Offshore Wind Power 2011 Grants for Offshore Wind Power 2011 Grants for Offshore Wind Power Addthis Browse By Topic TOPICS Energy Efficiency ---Home Energy Audits --Design &...

254

Factors driving wind power development in the United States  

E-Print Network (OSTI)

s Largest Purchase of Wind Power,” September 17, 2001.FACTORS DRIVING WIND POWER DEVELOPMENT IN THE UNITED STATESthe United States third in wind power capacity globally,

Bird, Lori A.; Parsons, Brian; Gagliano, Troy; Brown, Matthew H.; Wiser, Ryan H.; Bolinger, Mark

2003-01-01T23:59:59.000Z

255

Projected Partner Funding Table: Wind Power | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Projected Partner Funding Table: Wind Power Projected Partner Funding Table: Wind Power This is a table detailing projected partner funding for several wind power projects....

256

Success Stories (Postcard), Wind Powering America (WPA)  

DOE Green Energy (OSTI)

Wind Powering America shares best practices and lessons learned on the Wind Powering America website. This postcard is an outreach tool that provides a brief description of the success stories as well as the URL.

Not Available

2012-02-01T23:59:59.000Z

257

Langford Wind Power LLC | Open Energy Information  

Open Energy Info (EERE)

Langford Wind Power LLC Jump to: navigation, search Name Langford Wind Power LLC Place Texas Utility Id 56506 References EIA Form EIA-861 Final Data File for 2010 - File220101...

258

To forecast short-term load in electric power system based on FNN  

Science Conference Proceedings (OSTI)

Electric power system load forecasting plays an important part in the Energy Management System (EMS), which has a great effect on the operating, controlling and planning of power system. Accurate load forecasting, especially short-term load forecasting, ...

Yueli Hu; Huijie Ji; Xiaolong Song

2009-08-01T23:59:59.000Z

259

Wind Powering America Program Overview (Fact Sheet)  

DOE Green Energy (OSTI)

This fact sheet provides an overview of the U.S. Department of Energy's Wind Powering America Program.

Not Available

2008-04-01T23:59:59.000Z

260

Wind Powering America: Document Not Found  

Wind Powering America (EERE)

navigation to main content. U.S. Department of Energy Energy Efficiency and Renewable Energy navigation to main content. U.S. Department of Energy Energy Efficiency and Renewable Energy Wind Powering America Document Not Found This is a temporary URL for the U.S. Department of Energy's Wind Powering America website. Either this page does not reside on this temporary server or it does not actually exist. You may try to find it using the search engine. Your page may be located at this URL Illinois 50-Meter Wind Resource Map Indiana 50-Meter Wind Resource Map Missouri 50-Meter Wind Resource Map New Jersey 50-Meter Wind Resource Map Ohio 50-Meter Wind Resource Map New England Wind Projects Wind Energy for Schools - Project Locations Wind Energy Educational Programs and Training You may also find this page by manually navigating to it via Wind Powering

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

Forecasting the Impacts of Strong Wintertime Post-Cold Front Winds in the Northern Plains  

Science Conference Proceedings (OSTI)

Strong post-cold front wind events in the northern plains of the United States are a difficult problem for operational forecasters. The various atmospheric ingredients that lead to these events are examined from an operational point of view. ...

Anton F. Kapela; Preston W. Leftwich; Richard Van Ess

1995-06-01T23:59:59.000Z

262

Analyzing and Forecasting Rocky Mountain Lee Cyclogenesis Often Associated with Strong Winds  

Science Conference Proceedings (OSTI)

Since numerical forecast models often err in predicting the timing and location of lee cyclogenesis, a physically based method to diagnose such errors is sought. A case of Rocky Mountain lee cyclogenesis associated with strong winds is examined ...

David M. Schultz; Charles A. Doswell III

2000-04-01T23:59:59.000Z

263

Evaluation of the National Hurricane Center’s Tropical Cyclone Wind Speed Probability Forecast Product  

Science Conference Proceedings (OSTI)

A tropical cyclone (TC) wind speed probability forecast product developed at the Cooperative Institute for Research in the Atmosphere (CIRA) and adopted by the National Hurricane Center (NHC) is evaluated for U.S. land-threatening and landfalling ...

Michael E. Splitt; Jaclyn A. Shafer; Steven M. Lazarus; William P. Roeder

2010-04-01T23:59:59.000Z

264

Impact of Kalpana-1-Derived Water Vapor Winds on Indian Ocean Tropical Cyclone Forecasts  

Science Conference Proceedings (OSTI)

The water vapor winds from the operational geostationary Indian National Satellite (INSAT) Kalpana-1 have recently become operational at the Space Applications Centre (SAC). A series of experimental forecasts are attempted here to evaluate the ...

S. K. Deb; C. M. Kishtawal; P. K. Pal

2010-03-01T23:59:59.000Z

265

Using Wind Anomalies to Forecast East Coast Winter Storms  

Science Conference Proceedings (OSTI)

Forecasting major winter storms is a critical function for all weather services. Conventional model-derived fields from numerical weather prediction models most frequently utilized by operational forecasters, such as pressure level geopotential ...

Neil A. Stuart; Richard H. Grumm

2006-12-01T23:59:59.000Z

266

Emergency Response Transport Forecasting Using Historical Wind Field Pattern Matching  

Science Conference Proceedings (OSTI)

Historical pattern matching, or analog forecasting, is used to generate short-term mesoscale transport forecasts for emergency response at the Idaho National Engineering and Environmental Laboratory. A simple historical pattern-matching algorithm ...

Roger G. Carter; Robert E. Keislar

2000-03-01T23:59:59.000Z

267

Nettuno: Analysis of a Wind and Wave Forecast System in the Mediterranean Sea  

Science Conference Proceedings (OSTI)

Nettuno is a wind and wave forecast system in the Mediterranean Sea. It has been operational since 2009 producing twice a day high resolution forecasts for the next 72 hours. We have carried out a detailed analysis of the results, both in space ...

Luciana Bertotti; Luigi Cavaleri; Layla Loffredo; Lucio Torrisi

268

Datang Jilin Wind Power Stockholding Co Ltd Formerly Jilin Noble Wind Power  

Open Energy Info (EERE)

Stockholding Co Ltd Formerly Jilin Noble Wind Power Stockholding Co Ltd Formerly Jilin Noble Wind Power Stockholding Co Ltd Jump to: navigation, search Name Datang Jilin Wind Power Stockholding Co Ltd(Formerly Jilin Noble Wind Power Stockholding Co Ltd) Place Changchun, Jilin Province, China Sector Wind energy Product Wind farm developer. References Datang Jilin Wind Power Stockholding Co Ltd(Formerly Jilin Noble Wind Power Stockholding Co Ltd)[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Datang Jilin Wind Power Stockholding Co Ltd(Formerly Jilin Noble Wind Power Stockholding Co Ltd) is a company located in Changchun, Jilin Province, China . References ↑ "[ Datang Jilin Wind Power Stockholding Co Ltd(Formerly Jilin

269

A Comparison of Forecast Error Generators for Modeling Wind and Load Uncertainty  

SciTech Connect

This paper presents four algorithms to generate random forecast error time series, including a truncated-normal distribution model, a state-space based Markov model, a seasonal autoregressive moving average (ARMA) model, and a stochastic-optimization based model. The error time series are used to create real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast time series that statistically match historically observed forecasting data sets, used for variable generation integration studies. A comparison is made using historical DA load forecast and actual load values to generate new sets of DA forecasts with similar stoical forecast error characteristics. This paper discusses and compares the capabilities of each algorithm to preserve the characteristics of the historical forecast data sets.

Lu, Ning; Diao, Ruisheng; Hafen, Ryan P.; Samaan, Nader A.; Makarov, Yuri V.

2013-12-18T23:59:59.000Z

270

NREL: Wind Research - Mariah Power's Windspire Wind Turbine Testing and  

NLE Websites -- All DOE Office Websites (Extended Search)

Mariah Power's Windspire Wind Turbine Testing and Results Mariah Power's Windspire Wind Turbine Testing and Results A video of Mariah Power's Windspire wind turbine. Text Version As part of the National Renewable Energy Laboratory and U.S. Department of Energy (NREL/DOE) Independent Testing project, NREL tested Mariah Power's Windspire Giromill small wind turbine at the National Wind Technology Center (NWTC) through January 14, 2009 when NREL terminated its testing. Read a chronology of events and letter from Mariah Power to NREL. The Windspire is a 1.2-kilowatt (kW) vertical-axis small wind turbine. The turbine tower is 9.1 meters tall, and its rotor area is 1.2 by 6.1 meters. The turbine has a permanent-magnet generator with a single-phase output at 120 volts AC. Testing Summary Testing was terminated January 14, 2009. Published test reports include

271

2011 Grants for Offshore Wind Power | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Wind Manufacturing Facilities Wind Manufacturing Facilities Testing America's Wind Turbines Testing America's Wind Turbines U.S. Hydropower Potential from Existing Non-powered Dams...

272

Wind Power Plant SCADA and Controls  

SciTech Connect

Modern Wind Power Plants (WPPs) contain a variety of intelligent electronic devices (IEDs), Supervisory Control and Data Acquisition (SCADA) and communication systems. This paper discusses the issues related to a typical WPP's SCADA and Control. Presentation topics are: (1) Wind Turbine Controls; (2) Wind Plant SCADA, OEM SCADA Solutions, Third-Party SCADA Solutions; (3) Wind Plant Control; and (4) Security and Reliability Compliance.

Badrzadeh, Babak [IEEE PES Wind Plant Collector System Design Working Group; Castillo, Nestor [IEEE PES Wind Plant Collector System Design Working Group; Bradt, M. [IEEE PES Wind Plant Collector System Design Working Group; Janakiraman, R. [IEEE PES Wind Plant Collector System Design Working Group; Kennedy, R. [IEEE PES Wind Plant Collector System Design Working Group; Klein, S. [IEEE PES Wind Plant Collector System Design Working Group; Smith, Travis M [ORNL; Vargas, L. [IEEE PES Wind Plant Collector System Design Working Group

2011-01-01T23:59:59.000Z

273

Engineering innovation to reduce wind power COE  

SciTech Connect

There are enough wind resources in the US to provide 10 times the electric power we currently use, however wind power only accounts for 2% of our total electricity production. One of the main limitations to wind use is cost. Wind power currently costs 5-to-8 cents per kilowatt-hour, which is more than twice the cost of electricity generated by burning coal. Our Intelligent Wind Turbine LDRD Project is applying LANL's leading-edge engineering expertise in modeling and simulation, experimental validation, and advanced sensing technologies to challenges faced in the design and operation of modern wind turbines.

Ammerman, Curtt Nelson [Los Alamos National Laboratory

2011-01-10T23:59:59.000Z

274

Engineering innovation to reduce wind power COE  

DOE Green Energy (OSTI)

There are enough wind resources in the US to provide 10 times the electric power we currently use, however wind power only accounts for 2% of our total electricity production. One of the main limitations to wind use is cost. Wind power currently costs 5-to-8 cents per kilowatt-hour, which is more than twice the cost of electricity generated by burning coal. Our Intelligent Wind Turbine LDRD Project is applying LANL's leading-edge engineering expertise in modeling and simulation, experimental validation, and advanced sensing technologies to challenges faced in the design and operation of modern wind turbines.

Ammerman, Curtt Nelson [Los Alamos National Laboratory

2011-01-10T23:59:59.000Z

275

Arkansas 50m Wind Power Class  

NLE Websites -- All DOE Office Websites (Extended Search)

50m Wind Power Class 50m Wind Power Class Metadata also available as Metadata: Identification_Information Data_Quality_Information Spatial_Data_Organization_Information Spatial_Reference_Information Entity_and_Attribute_Information Distribution_Information Metadata_Reference_Information Identification_Information: Citation: Citation_Information: Originator: AWS TrueWind/NREL Publication_Date: April, 2007 Title: Arkansas 50m Wind Power Class Geospatial_Data_Presentation_Form: vector digital data Other_Citation_Details: The wind power resource estimates were produced by AWS TrueWind using their MesoMap system and historical weather data under contract to Wind Powering America/NREL. This map has been validated with available surface data by NREL and wind energy meteorological consultants.

276

Sixth Northwest Conservation & Electric Power Plan Draft Wholesale Power Price Forecasts  

E-Print Network (OSTI)

ANN-based Short-Term Load Forecasting in Electricity Markets Hong Chen Claudio A. Ca~nizares Ajit forecasting technique that considers electricity price as one of the main characteristics of the system load. B. Makram, "A Hybrid Wavelet- Kalman Filter Method for Load Forecasting," Electric Power Systems

277

Plan for the Wind Power Device to Make the Best of Earth Wind Energy  

Science Conference Proceedings (OSTI)

To make the best of wind energy resources on the earth surface, the plan for a new type of wind power device, named Multiple wind wheel Wind power Device, MWD in short, was put forward. MWD composes steel tower, trusses, generator, long axis, wind turbines ... Keywords: clean renewable sources, wind energy, wind power, wind turbine

Bingwen Zhang; Yingjin Zhang

2010-06-01T23:59:59.000Z

278

Wind Power Integration: Smoothing Short-Term Power Fluctuations  

Science Conference Proceedings (OSTI)

With the rapid growth of wind power generation, utility systems are beginning to feel the intermittent and variable nature of these wind resources in electricity transmission and distribution system operations. Both short-term power fluctuations resulting from gusty winds and longer term variations resulting from diurnal wind speed variations and shifting weather patterns can affect utility power delivery as well as grid operations. This report addresses the characteristics of short-term power fluctuatio...

2005-04-12T23:59:59.000Z

279

Jiuquan Xinmao Science and Technology Wind Power | Open Energy...  

Open Energy Info (EERE)

Jiuquan Xinmao Science and Technology Wind Power Jump to: navigation, search Name Jiuquan Xinmao Science and Technology Wind Power Place Gansu Province, China Sector Wind energy...

280

Zhangbei Guotou Wind Power Plant | Open Energy Information  

Open Energy Info (EERE)

Zhangbei Guotou Wind Power Plant Jump to: navigation, search Name Zhangbei Guotou Wind Power Plant Place Beijing Municipality, China Zip 100037 Sector Wind energy Product A company...

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

Liaoning Shenhua Xiehe Wind Power Investment Limited | Open Energy...  

Open Energy Info (EERE)

Shenhua Xiehe Wind Power Investment Limited Jump to: navigation, search Name Liaoning Shenhua Xiehe Wind Power Investment Limited Place Liaoning Province, China Sector Wind energy...

282

Ningxia Tianjing Shenzhou Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Tianjing Shenzhou Wind Power Co Ltd Jump to: navigation, search Name Ningxia Tianjing Shenzhou Wind Power Co Ltd Place Ningxia Autonomous Region, China Zip 750002 Sector Wind...

283

GWPS Global Wind Power Systems | Open Energy Information  

Open Energy Info (EERE)

GWPS Global Wind Power Systems Jump to: navigation, search Name GWPS (Global Wind Power Systems) Place Hamburg, Germany Zip 20095 Sector Wind energy Product Company specialised in...

284

Inner Mongolia Lianhe Wind Power Investment | Open Energy Information  

Open Energy Info (EERE)

Lianhe Wind Power Investment Jump to: navigation, search Name Inner Mongolia Lianhe Wind Power Investment Place Inner Mongolia Autonomous Region, China Sector Wind energy Product A...

285

Fluctuating wind power penetration as limited by frequency standard.  

E-Print Network (OSTI)

??Fluctuating wind power is due to wind turbulence and is the part which should be filtered out leaving behind the more predictable mean wind power… (more)

Luo, Changling, 1980-

2005-01-01T23:59:59.000Z

286

Inner Mongolia Damo Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Damo Wind Power Co Ltd Jump to: navigation, search Name Inner Mongolia Damo Wind Power Co Ltd Place Inner Mongolia Autonomous Region, China Sector Wind energy Product...

287

Changtu Liaoneng Xiexin Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Changtu Liaoneng Xiexin Wind Power Co Ltd Jump to: navigation, search Name Changtu Liaoneng Xiexin Wind Power Co Ltd Place Liaoning Province, China Sector Wind energy Product...

288

Tongliao Taihe Wind Power Limited | Open Energy Information  

Open Energy Info (EERE)

Tongliao Taihe Wind Power Limited Jump to: navigation, search Name Tongliao Taihe Wind Power Limited Place Tongliao City, Inner Mongolia Autonomous Region, China Sector Wind energy...

289

Xinjiang Tianfeng Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Xinjiang Tianfeng Wind Power Co Ltd Jump to: navigation, search Name Xinjiang Tianfeng Wind Power Co Ltd Place Urumuqi, Xinjiang Autonomous Region, China Zip 830002 Sector Wind...

290

Changdao Liankai Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Changdao Liankai Wind Power Co Ltd Jump to: navigation, search Name Changdao Liankai Wind Power Co Ltd Place Yantai City, Shandong Province, China Zip 265800 Sector Wind energy...

291

Guodian Hefeng Wind Power Development Company | Open Energy Informatio...  

Open Energy Info (EERE)

Hefeng Wind Power Development Company Jump to: navigation, search Name Guodian Hefeng Wind Power Development Company Place Huludao, Liaoning Province, China Sector Wind energy...

292

Yantai Tianfeng Wind Power Development Co Ltd | Open Energy Informatio...  

Open Energy Info (EERE)

Tianfeng Wind Power Development Co Ltd Jump to: navigation, search Name Yantai Tianfeng Wind Power Development Co Ltd Place Shandong Province, China Sector Wind energy Product...

293

Datang Zhangzhou Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Zhangzhou Wind Power Co Ltd Jump to: navigation, search Name Datang Zhangzhou Wind Power Co Ltd Place Zhangzhou, Fujian Province, China Sector Wind energy Product Project developer...

294

Tongliao Changxing Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Changxing Wind Power Co Ltd Jump to: navigation, search Name Tongliao Changxing Wind Power Co Ltd Place Tongliao City, Inner Mongolia Autonomous Region, China Sector Wind energy...

295

Role of wind power in electric utilities  

SciTech Connect

Current estimates suggest that the cost of wind-generated power is likely to be competitive with conventionally generated power in the near future in regions of the United States with favorable winds and high costs for conventionally generated electricity. These preliminary estimates indicate costs of $500 to 700 per installed kW for mass-produced wind turbines. This assessment regarding competitiveness includes effects of reduced reliability of wind power compared to conventional sources. Utilities employing wind power are likely to purchase more peaking capacity and less baseload capacity than they would have otherwise to provide the lowest-cost reserve power. This reserve power is needed mainly when wind outages coincide with peak loads. The monetary savings associated with this shift contribute substantially to the value of wind energy to a utility.

Davitian, H

1977-09-01T23:59:59.000Z

296

Improving High-Resolution Model Forecasts of Downslope Winds in the Las Vegas Valley  

Science Conference Proceedings (OSTI)

Numerical simulations for severe downslope winds as well as trapped lee waves in Nevada’s Las Vegas Valley were performed in this study. The goal of this study was to improve model forecasts of downslope-wind-event intensities. This was measured ...

Andre K. Pattantyus; Sen Chiao; Stanley Czyzyk

2011-06-01T23:59:59.000Z

297

Utilization of Automatic Weather Station Data for Forecasting High Wind Speeds at Pegasus Runway, Antarctica  

Science Conference Proceedings (OSTI)

Reduced visibility due to blowing snow can severely hinder aircraft operations in the Antarctic. Wind speeds in excess of approximately 7–13 m s?1 can result in blowing snow. The ability to forecast high wind speed events can improve the safety ...

R. E. Holmes; C. R. Stearns; G. A. Weidner; L. M. Keller

2000-04-01T23:59:59.000Z

298

Improving the reliability of wind power through spatially distributed wind generation.  

E-Print Network (OSTI)

??Wind power is a fast-growing, sustainable energy source. However, the problem of wind variability as it relates to wind power reliability is an obstacle to… (more)

Fisher, Samuel Martin

2012-01-01T23:59:59.000Z

299

Wind Power Plants and System Operation in the Hourly Time Domain: Preprint  

DOE Green Energy (OSTI)

Because wind is an intermittent power source, the variability may have significant impacts on system operation. Part of the difficulty of analyzing the load following impact of wind is the inadequacy of most modeling frameworks to accurately treat wind plants and the difficulty of untangling causal impacts of wind plants from other dynamic phenomena. This paper presents a simple analysis of an hourly load-following requirement that can be performed without extensive computer modeling. The approach is therefore useful as a first step to quantifying these impacts when extensive modeling and data sets are not available. The variability that wind plants add to the electricity supply must be analyzed in the context of overall system variability. The approach used in this paper does just that. The results show that wind plants do have an impact on load following, but when calculated as a percentage of the installed wind plant capacity, this impact is not large. Another issue is the extent to which wind forecast errors add to imbalance. The relative statistical independence of wind forecast errors and load forecast errors can be used to help quantify the extent to which wind forecast errors impact overall system imbalances.

Milligan, M.

2003-05-01T23:59:59.000Z

300

Wind for Schools: A Wind Powering America Project (Brochure)  

Wind Powering America (EERE)

for Schools: for Schools: A Wind Powering America Project Donna Berry - Utah State University/PIX13969 2 2 What is the Wind for Schools Project? Energy is largely taken for granted within our society, but that perception is changing as the economic and environmental impacts of our current energy supply structure are more widely understood. The U.S. Department of Energy's (DOE's) Wind Powering America program (at the National Renewable Energy Laboratory) sponsors the Wind for Schools Project to raise awareness in rural America about the benefits of wind energy while simultaneously developing a wind energy knowledge base in future leaders of our communities, states, and nation. A wind turbine located at a school provides students and teachers with a physical example of how communities can take

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Reliability Assessment of Power Systems with Wind Power Generation.  

E-Print Network (OSTI)

??Wind power generation, the most promising renewable energy, is increasingly attractive to power industry and the whole society and becomes more significant in the portfolio… (more)

Wang, Shu

2008-01-01T23:59:59.000Z

302

On the Wind Power Input to the Ocean General Circulation  

Science Conference Proceedings (OSTI)

The wind power input to the ocean general circulation is usually calculated from the time-averaged wind products. Here, this wind power input is reexamined using available observations, focusing on the role of the synoptically varying wind. Power ...

Xiaoming Zhai; Helen L. Johnson; David P. Marshall; Carl Wunsch

2012-08-01T23:59:59.000Z

303

Gansu Xin an Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Xin an Wind Power Co Ltd Jump to: navigation, search Name Gansu Xin'an Wind Power Co Ltd Place Gansu Province, China Sector Wind energy Product A wind power project developer....

304

Tianjin Jinneng Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Jinneng Wind Power Co Ltd Jump to: navigation, search Name Tianjin Jinneng Wind Power Co Ltd Place Tianjin Municipality, China Sector Wind energy Product Tianjin-based wind power...

305

Network wind power over the Pacific Northwest  

DOE Green Energy (OSTI)

Since 1975 the Bonneville Power Administration (BPA) has been sponsoring wind power research at Oregon State University. A feasibility study that initially concentrated on the wind power potential in the Columbia River Gorge has expanded to the BPA service area which covers Washington, Oregon, Idaho, western Montana and northern Nevada. Previous BPA reports have documented the progress of this research.

Hewson, E W; Baker, R W; Barber, D A; Peterson, B

1978-09-01T23:59:59.000Z

306

Hardscrabble Wind Power Project | Open Energy Information  

Open Energy Info (EERE)

Hardscrabble Wind Power Project Hardscrabble Wind Power Project Jump to: navigation, search Name Hardscrabble Wind Power Project Facility Hardscrabble Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Developer Atlantic Wind Location Fairfield and Norway north of Little Falls NY Coordinates 43.076452°, -74.859602° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":43.076452,"lon":-74.859602,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

307

Power and Frequency Control as it Relates to Wind-Powered Generation  

E-Print Network (OSTI)

of large amounts of wind power production might requirewill be satisfactory as wind power provides an increasing64   7.2   Wind Power in Relation to System

Lacommare, Kristina S H

2011-01-01T23:59:59.000Z

308

Understanding Wind Turbine Price Trends in the U.S. Over the Past Decade  

E-Print Network (OSTI)

Bruce Valpy. 2011. Offshore Wind: Forecasts of future costsCarbon Trust. 2008. Offshore wind power: big challenge, bigfinancial support for offshore wind. Report prepared for the

Bolinger, Mark

2013-01-01T23:59:59.000Z

309

DOE Hydrogen Analysis Repository: Wind Power Integration  

NLE Websites -- All DOE Office Websites (Extended Search)

Project Summary Full Title: Large-Scale Integration of Wind Power into Different Energy Systems Project ID: 124 Principal Investigator: Henrik Lund Purpose The analysis...

310

Distributed Wind Power Generation - National Renewable Energy ...  

Technology breakthrough in roof-top distributed wind power generation Multi-billion $ market opportunity in next 10 years – recent venture capital investments

311

Arkansas 50m Wind Power Class  

NLE Websites -- All DOE Office Websites (Extended Search)

50m Wind Power Class Metadata also available as Metadata: IdentificationInformation DataQualityInformation SpatialDataOrganizationInformation SpatialReferenceInformation...

312

Finansiering av vindkraft; Financing of wind power.  

E-Print Network (OSTI)

?? The wind power increase of Gotland as well as other parts of Sweden during the last ten year period has meant that this renewable… (more)

Lewander, Christian

2012-01-01T23:59:59.000Z

313

Does Increased Horizontal Resolution Improve Hurricane Wind Forecasts?  

Science Conference Proceedings (OSTI)

The representation of tropical cyclone track, intensity, and structure in a set of 69 parallel forecasts performed at each of two horizontal grid increments with the Advanced Research Hurricane (AHW) component of the Weather and Research and ...

Christopher Davis; Wei Wang; Jimy Dudhia; Ryan Torn

2010-12-01T23:59:59.000Z

314

Wind Powering America's Wind for Schools Project: Summary Report  

DOE Green Energy (OSTI)

This report provides an overview of the U.S. Department of Energy, Wind Powering America, Wind for Schools project. It outlines teacher-training activities and curriculum development; discusses the affiliate program that allows school districts and states to replicate the program; and contains reports that provide an update on activities and progress in the 11 states in which the Wind for Schools project operates.

Baring-Gould, I.; Newcomb, C.

2012-06-01T23:59:59.000Z

315

Wind for Schools Project Power System Brief, Wind Powering America Fact Sheet Series  

Wind Powering America (EERE)

Powering America Fact Sheet Series Powering America Fact Sheet Series Energy Efficiency & Renewable Energy Wind for Schools Project Power System Brief Wind for Schools Project Power System Brief Wind for Schools Project Power System Brief This fact sheet provides an overview of the system components of a Wind Powering America Wind for Schools project. Wind Powering America's (WPA's) Wind for Schools project uses a basic system configuration for each school project. The system incorporates a single SkyStream(tm) wind turbine, a 70-ft guyed tower, disconnect boxes at the base of the turbine and at the school, and an interconnection to the school's electrical system. A detailed description of each system component is provided in this document. The local power cooperative or utility should be an integral part of

316

Wind Power and the Clean Development Mechanism  

E-Print Network (OSTI)

20 40 60 80 100 120 Biomass energy Hydro Agriculture EE Industry Wind Landfill gas Fossil fuel switchWind Power and the Clean Development Mechanism Romeo Pacudan PhD Wind Energy Development, Philippines EC-ASEAN ENERGY FACILITY #12;CD4CDM project Objective · Help developing countries participate

317

Wind Farm Power System Model Development: Preprint  

DOE Green Energy (OSTI)

In some areas, wind power has reached a level where it begins to impact grid operation and the stability of local utilities. In this paper, the model development for a large wind farm will be presented. Wind farm dynamic behavior and contribution to stability during transmission system faults will be examined.

Muljadi, E.; Butterfield, C. P.

2004-07-01T23:59:59.000Z

318

The Impact of Wind Power Generation on Wholesale Electricity Price ...  

Science Conference Proceedings (OSTI)

price for power generation are examined to forecast LNG price for power genera- tion. Information on future power plant's construction and decommission plan ...

319

Wind for Schools Project Power System Brief  

DOE Green Energy (OSTI)

This fact sheet provides an overview of the system components of a Wind Powering America Wind for Schools project. Wind Powering America's (WPA's) Wind for Schools project uses a basic system configuration for each school project. The system incorporates a single SkyStream(TM) wind turbine, a 70-ft guyed tower, disconnect boxes at the base of the turbine and at the school, and an interconnection to the school's electrical system. A detailed description of each system component is provided in this document.

Not Available

2007-08-01T23:59:59.000Z

320

NREL: Wind Research - Small Wind Site Assessment: Wind Powering...  

NLE Websites -- All DOE Office Websites (Extended Search)

environmental impacts have increased the demand for small wind energy systems for homeowners, schools, businesses, and local governments. Over the past decade, the knowledge,...

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

New England Wind Forum: Motivations for Buying Wind Power  

Wind Powering America (EERE)

Motivations for Buying Wind Power Motivations for Buying Wind Power Voluntary Voluntary purchases are often referred to as "Green Power." Voluntary purchases are made by individuals, businesses, governments, and groups of each (known as aggregations) to express personal preferences or meet personal or institutional commitments. One recent example of a government purchase is a request for proposals, issued in February 2005, to supply the Rhode Island State House with renewable energy for a five-year period. Hedging Hedging is a growing motivation to reduce exposure to volatile and rising energy costs. New England's publicly-owned utilities, as well as Vermont's utilities, can stabilize their fuel cost-driven supply portfolios with wind generation. In competitive markets that dominate the New England landscape, larger electricity customers are beginning to look to longer-term purchases of wind power as a means to protect their energy budgets against the volatile fossil-fuel-driven costs. Examples include:

322

NREL: Wind Research - Wind Power Development's Economic Impact...  

NLE Websites -- All DOE Office Websites (Extended Search)

Wind Power Development's Economic Impact on Rural Communities June 12, 2013 Audio with Jason Brown, Kansas City Federal Reserve Bank Economist (MP3 2.5 MB). Download Windows Media...

323

Neppel Wind Power Project | Open Energy Information  

Open Energy Info (EERE)

Neppel Wind Power Project Neppel Wind Power Project Jump to: navigation, search Name Neppel Wind Power Project Facility Neppel Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Developer Alliant Energy Energy Purchaser Alliant/IES Utilities Location Armstrong IA Coordinates 43.402001°, -94.578989° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":43.402001,"lon":-94.578989,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

324

Fenner Wind Power Project | Open Energy Information  

Open Energy Info (EERE)

Fenner Wind Power Project Fenner Wind Power Project Jump to: navigation, search Name Fenner Wind Power Project Facility Fenner Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner Enel North America Developer Atlantic Renewable Energy Energy Purchaser Market Location Fenner NY Coordinates 43.000482°, -75.762498° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":43.000482,"lon":-75.762498,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

325

Somerset Wind Power Project | Open Energy Information  

Open Energy Info (EERE)

Wind Power Project Wind Power Project Jump to: navigation, search Name Somerset Wind Power Project Facility Somerset Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner NextEra Energy Resources Developer Atlantic Renewable Energy Energy Purchaser Exelon Location Somerset County PA Coordinates 39.979794°, -79.009216° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":39.979794,"lon":-79.009216,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

326

POWER4 Amstel Wind Energy | Open Energy Information  

Open Energy Info (EERE)

POWER4 Amstel Wind Energy Jump to: navigation, search Name POWER4 Amstel Wind Energy Place Bangalore, Karnataka, India Zip 560034 Sector Wind energy Product Bangalore-based wind...

327

M N Wind Power Ltd | Open Energy Information  

Open Energy Info (EERE)

Wind Power Ltd Jump to: navigation, search Name M&N Wind Power Ltd Place Penzance, United Kingdom Zip TR20 8HX Sector Wind energy Product Wind farm developers in conjunction with...

328

Maoming Zhong ao Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Maoming Zhong ao Wind Power Co Ltd Jump to: navigation, search Name Maoming Zhong'ao Wind Power Co Ltd Place Guangdong Province, China Sector Wind energy Product Maoming-based wind...

329

FCG Putian Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

FCG Putian Wind Power Co Ltd Jump to: navigation, search Name FCG (Putian) Wind Power Co Ltd Place Fuzhou, Fujian Province, China Zip 320001 Sector Wind energy Product Wind project...

330

Dongbai Mountain Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Dongbai Mountain Wind Power Co Ltd Jump to: navigation, search Name Dongbai Mountain Wind Power Co Ltd Place Zhejiang Province, China Sector Wind energy Product Dongyang-based wind...

331

Chahar Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Chahar Wind Power Co Ltd Jump to: navigation, search Name Chahar Wind Power Co Ltd Place China Sector Wind energy Product Inner Mongolia, Shangyi-based wind project developer...

332

BeWind Power Ltd | Open Energy Information  

Open Energy Info (EERE)

BeWind Power Ltd Jump to: navigation, search Name BeWind Power Ltd Place India Sector Wind energy Product Wind turbine manufacturer, jointly owned by Indowind and EU Energy...

333

Sinomatech Wind Power Blade aka Sinoma Science Technology Wind Turbine  

Open Energy Info (EERE)

Sinomatech Wind Power Blade aka Sinoma Science Technology Wind Turbine Sinomatech Wind Power Blade aka Sinoma Science Technology Wind Turbine Blade Co Ltd Jump to: navigation, search Name Sinomatech Wind Power Blade (aka Sinoma Science & Technology Wind Turbine Blade Co Ltd) Place Nanjing, Jiangsu Province, China Zip 210012 Sector Wind energy Product Jiangsu-based wind turbine blade manufactuer. Coordinates 32.0485°, 118.778969° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":32.0485,"lon":118.778969,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

334

Wind Power Partners '94 Wind Farm | Open Energy Information  

Open Energy Info (EERE)

4 Wind Farm 4 Wind Farm Jump to: navigation, search Name Wind Power Partners '94 Wind Farm Facility Wind Power Partners '94 Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner NextEra Energy Resources Developer Kenetech Wind Power Energy Purchaser Lower Colorado River Authority Location Culberson County TX Coordinates 31.3508°, -104.443° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":31.3508,"lon":-104.443,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

335

Power Transformer Application for Wind Plant Substations  

Science Conference Proceedings (OSTI)

Wind power plants use power transformers to step plant output from the medium voltage of the collector system to the HV or EHV transmission system voltage. This paper discusses the application of these transformers with regard to the selection of winding configuration, MVA rating, impedance, loss evaluation, on-load tapchanger requirements, and redundancy.

Behnke, M. R. [IEEE PES Wind Plant Collector System Design Working Group; Bloethe, W.G. [IEEE PES Wind Plant Collector System Design Working Group; Bradt, M. [IEEE PES Wind Plant Collector System Design Working Group; Brooks, C. [IEEE PES Wind Plant Collector System Design Working Group; Camm, E H [IEEE PES Wind Plant Collector System Design Working Group; Dilling, W. [IEEE PES Wind Plant Collector System Design Working Group; Goltz, B. [IEEE PES Wind Plant Collector System Design Working Group; Li, J. [IEEE PES Wind Plant Collector System Design Working Group; Niemira, J. [IEEE PES Wind Plant Collector System Design Working Group; Nuckles, K. [IEEE PES Wind Plant Collector System Design Working Group; Patino, J. [IEEE PES Wind Plant Collector System Design Working Group; Reza, M [IEEE PES Wind Plant Collector System Design Working Group; Richardson, B. [IEEE PES Wind Plant Collector System Design Working Group; Samaan, N. [IEEE PES Wind Plant Collector System Design Working Group; Schoene, Jens [IEEE PES Wind Plant Collector System Design Working Group; Smith, Travis M [ORNL; Snyder, Isabelle B [ORNL; Starke, Michael R [ORNL; Walling, R. [IEEE PES Wind Plant Collector System Design Working Group; Zahalka, G. [IEEE PES Wind Plant Collector System Design Working Group

2010-01-01T23:59:59.000Z

336

Gansu China Power Jiuquan Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Power Jiuquan Wind Power Co Ltd Jump to: navigation, search Name Gansu China Power Jiuquan Wind Power Co Ltd Place Gansu Province, China Sector Wind energy Product China-based wind...

337

Global ocean wind power sensitivity to surface layer stability  

E-Print Network (OSTI)

2005), Evaluation of global wind power, J. Geophys. Res. ,Pryor (2003), Can satellite sampling of offshore wind speedsrealistically represent wind speed distributions? , J. Appl.

Capps, Scott B; Zender, Charles S

2009-01-01T23:59:59.000Z

338

RELIABILITY OF WIND POWER FROM DISPERSED SITES: A PRELIMINARY ASSESSMENT  

E-Print Network (OSTI)

Coincidence of Demand and Wind Resource Diurnal PowerOutput Variations for Three Wind Regimes List of TablesCAPACITY CREDIT FOR WIND ARRAYS: THE PROBLEM . . . . . . .

Kahn, E.

2011-01-01T23:59:59.000Z

339

Jilin Tianhe Wind Power Equipment Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Baicheng, Jilin Province, China Sector Wind energy Product Baicheng-based wind turbine tower producer. References Jilin Tianhe Wind Power Equipment Co Ltd1 LinkedIn Connections...

340

Indian Wind Power Association IWPA | Open Energy Information  

Open Energy Info (EERE)

Association IWPA Jump to: navigation, search Name Indian Wind Power Association (IWPA) Place Chennai, Tamil Nadu, India Zip 600 020 Sector Wind energy Product Chennai-based wind...

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

Jilin Longyuan Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Co Ltd Jump to: navigation, search Name Jilin Longyuan Wind Power Co Ltd Place Changchun, Jilin Province, China Zip 130061 Sector Wind energy Product Joint venture wind development...

342

Wind speed forecasting at different time scales: a non parametric approach  

E-Print Network (OSTI)

The prediction of wind speed is one of the most important aspects when dealing with renewable energy. In this paper we show a new nonparametric model, based on semi-Markov chains, to predict wind speed. Particularly we use an indexed semi-Markov model, that reproduces accurately the statistical behavior of wind speed, to forecast wind speed one step ahead for different time scales and for very long time horizon maintaining the goodness of prediction. In order to check the main features of the model we show, as indicator of goodness, the root mean square error between real data and predicted ones and we compare our forecasting results with those of a persistence model.

D'Amico, Guglielmo; Prattico, Flavio

2013-01-01T23:59:59.000Z

343

Trends of Wind and Wind Power Over the Coterminous United States.  

E-Print Network (OSTI)

??The trends of wind and wind power at a typical wind turbine hub height (80 m) are analyzed using the North American Regional Reanalysis (NARR)… (more)

Holt, Eric M

2011-01-01T23:59:59.000Z

344

Application of Radar Wind Observations for Low-Level NWP Wind Forecast Validation  

Science Conference Proceedings (OSTI)

The Finnish Meteorological Institute has produced a new numerical weather prediction model–based wind atlas of Finland. The wind atlas provides information on local wind conditions in terms of annual and monthly wind speed and direction averages. ...

Kirsti Salonen; Sami Niemelä; Carl Fortelius

2011-06-01T23:59:59.000Z

345

Forecast of Icing Events at a Wind Farm in Sweden  

Science Conference Proceedings (OSTI)

This paper introduces a method to identify icing events using a physical icing model, driven by atmospheric data from the WRF model, and applies it to a wind park in Sweden. Observed wind park icing events were identified by deviation from an ...

Neil Davis; Andrea N. Hahmann; Niels-Erik Clausen; Mark Žagar

346

California Regional Wind Energy Forecasting System Development, Volume 2:  

Science Conference Proceedings (OSTI)

The rated capacity of wind generation in California is expected to grow rapidly in the future beyond the approximately 2100 MW in place at the end of 2005. The main drivers are the state's 20 percent renewable portfolio standard requirement in 2010 and the low cost of wind energy relative to other renewable energy sources.

2006-11-15T23:59:59.000Z

347

Base Resource Forecasts - Power Marketing - Sierra Nevada Region...  

NLE Websites -- All DOE Office Websites (Extended Search)

Marketing > Base Resource Forecasts Base Resource Forecasts Note: Annual, rolling (monthly for 12 months), base resource forecasts are posted when they become available. Annual...

348

wind powering america | OpenEI Community  

Open Energy Info (EERE)

41 41 Varnish cache server Home Groups Community Central Green Button Applications Developer Utility Rate FRED: FRee Energy Database More Public Groups Private Groups Features Groups Blog posts Content Stream Documents Discussions Polls Q & A Events Notices My stuff Energy blogs 429 Throttled (bot load) Error 429 Throttled (bot load) Throttled (bot load) Guru Meditation: XID: 2142235241 Varnish cache server wind powering america Home Graham7781's picture Submitted by Graham7781(2002) Super contributor 30 January, 2013 - 10:55 Wind Powering America Guidebook officially launched on OpenEI guidebook OpenEI wind powering america WPA Wind Powering America's Small Wind Guidebook is now featured in OpenEI, the U.S. Department of Energy's wiki platform for energy information. This guide and the state-specific versions are some of the most successful

349

Impact of Wind Power Plants on Voltage and Transient Stability of Power Systems  

SciTech Connect

A standard three-machine, nine-bus wind power system is studied and augmented by a radially connected wind power plant that contains 22 wind turbine generators.

Muljadi, E.; Nguyen, Tony B.; Pai, M. A.

2008-09-30T23:59:59.000Z

350

Wind Power Price Trends in the United States  

E-Print Network (OSTI)

Review] Wind Power Price Trends in the United States Markof these drivers – i.e. , trends in U.S. wind power prices –Capacity Wind Power Price Trends in the U.S. Berkeley Lab

Bolinger, Mark

2010-01-01T23:59:59.000Z

351

Wind Power Price Trends in the United States  

E-Print Network (OSTI)

price of power from new U.S. wind projects higher in 2009.should eventually help wind power regain the downward pricein Modern Energy Review] Wind Power Price Trends in the

Bolinger, Mark

2010-01-01T23:59:59.000Z

352

The Political Economy of Wind Power in China  

E-Print Network (OSTI)

in this paper, not offshore wind power—a very small yetthe press declaring offshore wind power to be cheaper thanfully occupied and offshore wind power resources grabbed in

Swanson, Ryan Landon

2011-01-01T23:59:59.000Z

353

Wind Power Price Trends in the United States  

E-Print Network (OSTI)

should eventually help wind power regain the downward priceModern Energy Review] Wind Power Price Trends in the Unitedled the world in adding new wind power capacity in 2008, and

Bolinger, Mark

2010-01-01T23:59:59.000Z

354

Datang Jilin Wind Power Stockholding Co Ltd Formerly Jilin Noble...  

Open Energy Info (EERE)

Stockholding Co Ltd Formerly Jilin Noble Wind Power Stockholding Co Ltd Jump to: navigation, search Name Datang Jilin Wind Power Stockholding Co Ltd(Formerly Jilin Noble Wind Power...

355

A Comparative Analysis of Community Wind Power Development Models  

E-Print Network (OSTI)

Whip Up Hopes for Wind Power Again. ” The Wall StreetProduction Tax Credit for Wind Power. LBNL-51465. Berkeley,This combination is making wind power an important new cash

Bolinger, Mark; Wiser, Ryan; Wind, Tom; Juhl, Dan; Grace, Robert; West, Peter

2005-01-01T23:59:59.000Z

356

Wind Power: How Much, How Soon, and At What Cost?  

E-Print Network (OSTI)

Evaluation of Global Wind Power." Journal of Geophysical2008. "The Economics of Wind Power with Energy Storage."Economics of Large-Scale Wind Power in a Carbon Constrained

Wiser, Ryan H

2010-01-01T23:59:59.000Z

357

The Political Economy of Wind Power in China  

E-Print Network (OSTI)

adds 18.9 GW of new wind power capacity in 2010. ? GlobalEnd Challenged Subsidies in Wind Power Case. ? Internationalemergence in the global wind power industry. ? Ph. D.

Swanson, Ryan Landon

2011-01-01T23:59:59.000Z

358

RELIABILITY OF WIND POWER FROM DISPERSED SITES: A PRELIMINARY ASSESSMENT  

E-Print Network (OSTI)

ON METHODOLOGY: FROM WIND POWER FREQUENCY TO LOSS-OF-LOADJ.P. , "Some Aspects of Wind Power Statistics, " J. of Appl.S£CTION Reliability of Wind Power From Dispersed Sites: A Pr

Kahn, E.

2011-01-01T23:59:59.000Z

359

Dynamic Models for Wind Turbines and Wind Power Plants  

DOE Green Energy (OSTI)

The primary objective of this report was to develop universal manufacturer-independent wind turbine and wind power plant models that can be shared, used, and improved without any restrictions by project developers, manufacturers, and engineers. Manufacturer-specific models of wind turbines are favored for use in wind power interconnection studies. While they are detailed and accurate, their usages are limited to the terms of the non-disclosure agreement, thus stifling model sharing. The primary objective of the work proposed is to develop universal manufacturer-independent wind power plant models that can be shared, used, and improved without any restrictions by project developers, manufacturers, and engineers. Each of these models includes representations of general turbine aerodynamics, the mechanical drive-train, and the electrical characteristics of the generator and converter, as well as the control systems typically used. To determine how realistic model performance is, the performance of one of the models (doubly-fed induction generator model) has been validated using real-world wind power plant data. This work also documents selected applications of these models.

Singh, M.; Santoso, S.

2011-10-01T23:59:59.000Z

360

Verification of Mesoscale NWP Forecasts of Abrupt Cold Frontal Wind Changes  

Science Conference Proceedings (OSTI)

During a wildfire, a sharp wind change can lead to an abrupt increase in fire activity and change the rate of spread, endangering firefighters working on what had been the flank of the fire. In southeastern Australia, routine forecast of cold-...

Yimin Ma; Xinmei Huang; Graham A. Mills; Kevin Parkyn

2010-02-01T23:59:59.000Z

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

The effect of high penetration of wind power on primary frequency control of power systems.  

E-Print Network (OSTI)

??In this work, a power system with wind power units and hydro power units are considered. The hydro power unit and variable speed wind turbine… (more)

Motamed, Bardia

2013-01-01T23:59:59.000Z

362

The Effects of Marine Winds from Scatterometer Data on Weather Analysis and Forecasting  

Science Conference Proceedings (OSTI)

Satellite scatterometer observations of the ocean surface wind speed and direction improve the depiction of storms at sea. Over the ocean, scatterometer surface winds are deduced from multiple measurements of reflected radar power made from ...

R. Atlas; R. N. Hoffman; S. M. Leidner; J. Sienkiewicz; T-W. Yu; S. C. Bloom; E. Brin; J. Ardizzone; J. Terry; D. Bungato; J. C. Jusem

2001-09-01T23:59:59.000Z

363

Do Wind Forecasts Make Good Generation Schedules? Preprint  

SciTech Connect

Energy market scheduling conventions can needlessly increase the wind balancing area's regulation requirements. This economic inefficiency can be eliminated once it is recognized. The paper provides a detailed discussion of these issues.

Dragoon, K.; Kirby, B.; Milligan, M.

2008-06-01T23:59:59.000Z

364

Do Wind Forecasts Make Good Generation Schedules? Preprint  

DOE Green Energy (OSTI)

Energy market scheduling conventions can needlessly increase the wind balancing area's regulation requirements. This economic inefficiency can be eliminated once it is recognized. The paper provides a detailed discussion of these issues.

Dragoon, K.; Kirby, B.; Milligan, M.

2008-06-01T23:59:59.000Z

365

FORECAST OF ENSEMBLE POWER PRODUCTION BY GRID-CONNECTED PV SYSTEMS Elke Lorenz*, Detlev Heinemann*, Hashini Wickramarathne*, Hans Georg Beyer +  

E-Print Network (OSTI)

FORECAST OF ENSEMBLE POWER PRODUCTION BY GRID-CONNECTED PV SYSTEMS Elke Lorenz*, Detlev Heinemann will highly benefit from forecast information on the expected power production. This forecast information and evaluate an approach to forecast regional PV power production. The forecast quality was investigated

Heinemann, Detlev

366

Wind Power in China | Open Energy Information  

Open Energy Info (EERE)

in China in China Jump to: navigation, search This article is a stub. You can help OpenEI by expanding it. Contents 1 Summary 2 Estimate Potential 3 Current Projects 4 China Manufacturers 4.1 Wind Companies in Wind Power in China 5 China's Wind Goals 6 References Summary Installed wind capacity: approximately 30 GW by end of 2010 (est), added 13.8 GW in 2009 Installed wind capacity doubled each year, Min Deqing China_2050_Wind_Technology_Roadmap Estimate Potential Offshore wind energy generation potential in China estimate to be 11,000 terawatt-hours (TWh) similar to that of the North Sea in western Europe.[1][2] Current Projects 7 large projects or "megabases" (2010) [3] Inner Mongolia approximately 4.3 GW capacity in 2010 (66 projects; 40 more planned)[4] 1.25 GW offshore project in Guangdong

367

Harbin Wind Power Equipment Company | Open Energy Information  

Open Energy Info (EERE)

Login | Sign Up Search Page Edit with form History Facebook icon Twitter icon Harbin Wind Power Equipment Company Jump to: navigation, search Name Harbin Wind Power Equipment...

368

Lianyungang Zhongneng United Wind Power Co Ltd | Open Energy...  

Open Energy Info (EERE)

Page Edit with form History Facebook icon Twitter icon Lianyungang Zhongneng United Wind Power Co Ltd Jump to: navigation, search Name Lianyungang Zhongneng United Wind Power...

369

Huaneng Shouguang Wind Power Company Limited | Open Energy Information  

Open Energy Info (EERE)

Up Search Page Edit with form History Facebook icon Twitter icon Huaneng Shouguang Wind Power Company Limited Jump to: navigation, search Name Huaneng Shouguang Wind Power...

370

Jilin Wind Power Stockholding Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Login | Sign Up Search Page Edit with form History Facebook icon Twitter icon Jilin Wind Power Stockholding Co Ltd Jump to: navigation, search Name Jilin Wind Power...

371

Inner Mongolia Sansheng Wind Power | Open Energy Information  

Open Energy Info (EERE)

Search Page Edit with form History Facebook icon Twitter icon Inner Mongolia Sansheng Wind Power Jump to: navigation, search Name Inner Mongolia Sansheng Wind Power Place Inner...

372

US DOE Wind Powering America | Open Energy Information  

Open Energy Info (EERE)

Logo: Wind Powering America Name Wind Powering America AgencyCompany Organization U.S. Department of Energy Partner National Renewable Energy Laboratory Sector Energy Focus...

373

Changes related to "Ningxia Yinyi Wind Power Generation Co Ltd...  

Open Energy Info (EERE)

this page on Facebook icon Twitter icon Changes related to "Ningxia Yinyi Wind Power Generation Co Ltd" Ningxia Yinyi Wind Power Generation Co Ltd Jump to:...

374

Ningxia Yinyi Wind Power Generation Co Ltd | Open Energy Information  

Open Energy Info (EERE)

with form History Share this page on Facebook icon Twitter icon Ningxia Yinyi Wind Power Generation Co Ltd Jump to: navigation, search Name Ningxia Yinyi Wind Power...

375

Application Filing Requirements for Wind-Powered Electric Generation...  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Wind-Powered Electric Generation Facilities (Ohio) Application Filing Requirements for Wind-Powered Electric Generation Facilities (Ohio) Eligibility Commercial Developer Utility...

376

Analysis of Wind Power Ramping Behavior in ERCOT  

DOE Green Energy (OSTI)

This report analyzes the wind power ramping behavior using 10-minute and hourly average wind power data from ERCOT and presents statistical properties of the large ramp events.

Wan, Y. H.

2011-03-01T23:59:59.000Z

377

Pages that link to "Qingdao Hengfeng Wind Power Generator Co...  

Open Energy Info (EERE)

Share this page on Facebook icon Twitter icon Pages that link to "Qingdao Hengfeng Wind Power Generator Co Ltd" Qingdao Hengfeng Wind Power Generator Co Ltd Jump to:...

378

Changes related to "Qingdao Hengfeng Wind Power Generator Co...  

Open Energy Info (EERE)

Share this page on Facebook icon Twitter icon Changes related to "Qingdao Hengfeng Wind Power Generator Co Ltd" Qingdao Hengfeng Wind Power Generator Co Ltd Jump to:...

379

Fujian Pingtan Changjiangao Wind Power Co Ltd | Open Energy Informatio...  

Open Energy Info (EERE)

Fujian Pingtan Changjiangao Wind Power Co Ltd Jump to: navigation, search Name Fujian Pingtan Changjiangao Wind Power Co Ltd Place Pingtan, Fujian Province, China Zip 350400 Sector...

380

Controlling hour-long power of wind farms.  

E-Print Network (OSTI)

??In attempting to control the power output of a wind farm, it is first necessary to smooth the power fluctuations due to wind turbulence. This… (more)

Li, Pei, 1981-

2007-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Dongshan Aozaishan Wind Power Development Co Ltd | Open Energy...  

Open Energy Info (EERE)

Dongshan Aozaishan Wind Power Development Co Ltd Jump to: navigation, search Name Dongshan Aozaishan Wind Power Development Co Ltd Place Zhangzhou, Fujian Province, China Sector...

382

The Economic Impact of Wind Power on Ercot Regulation Market.  

E-Print Network (OSTI)

??U.S. wind power generation has grown rapidly in the last decade due to government policies designed to reduce pollution. Although wind power does not contribute… (more)

Zheng, Bin

2013-01-01T23:59:59.000Z

383

Marquiss Wind Power | Open Energy Information  

Open Energy Info (EERE)

Marquiss Wind Power Marquiss Wind Power Jump to: navigation, search Name Marquiss Wind Power Place Folsom, California Zip 95630 Sector Wind energy Product US-based manufacturer of patented ducted micro-scale wind turbines for use on commercial and industrial rooftops. Coordinates 39.474081°, -80.529699° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":39.474081,"lon":-80.529699,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

384

Madison Wind Power Project | Open Energy Information  

Open Energy Info (EERE)

Madison Wind Power Project Madison Wind Power Project Facility Madison Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner Horizon Developer Atlantic Renewable/PG&E Generating Energy Purchaser Market Location Madison County NY Coordinates 42.91455°, -75.569851° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":42.91455,"lon":-75.569851,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

385

Northwestern Wind Power | Open Energy Information  

Open Energy Info (EERE)

Northwestern Wind Power Northwestern Wind Power Jump to: navigation, search Name Northwestern Wind Power Place Wasco, Oregon Zip OR 97065 Sector Wind energy Product US-based wind project developer. Coordinates 45.591395°, -120.69777° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":45.591395,"lon":-120.69777,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

386

Desert Wind Power | Open Energy Information  

Open Energy Info (EERE)

Desert Wind Power Desert Wind Power Facility Desert Wind Power Sector Wind energy Facility Type Commercial Scale Wind Facility Status Proposed Developer Iberdrola Renewables Location Pasquotank and Perquimans Counties NC Coordinates 36.435688°, -76.232786° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":36.435688,"lon":-76.232786,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

387

Shiloh Wind Power Project | Open Energy Information  

Open Energy Info (EERE)

Shiloh Wind Power Project Shiloh Wind Power Project Facility Shiloh Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner PPM Energy Inc Developer PPM Energy Inc Energy Purchaser PG&E -Modesto Irrigation District & City of Palo Alto Utilities Location Solano County CA Coordinates 38.154041°, -121.876066° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":38.154041,"lon":-121.876066,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

388

Evergreen Wind Power LLC | Open Energy Information  

Open Energy Info (EERE)

Wind Power LLC Wind Power LLC Jump to: navigation, search Name Evergreen Wind Power LLC Place Bangor, Maine Zip 4401 Sector Wind energy Product Formed to develop wind projects in Maine. Coordinates 43.892445°, -90.990484° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":43.892445,"lon":-90.990484,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

389

Moraine Wind Power Project | Open Energy Information  

Open Energy Info (EERE)

Moraine Wind Power Project Moraine Wind Power Project Facility Moraine Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner PPM Energy Inc Developer PPM Energy Inc Energy Purchaser Xcel Energy Location Pipestone and Murray Counties MN Coordinates 43.993574°, -96.047301° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":43.993574,"lon":-96.047301,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

390

Optimal site selection and sizing of distributed utility-scale wind power plants  

DOE Green Energy (OSTI)

As electric market product unbundling occurs, sellers in the wholesale market for electricity will find it to their advantage to be able to specify the quantity of electricity available and the time of availability. Since wind power plants are driven by the stochastic nature of the wind itself, this can present difficulties. To the extent that an accurate wind forecast is available, contract deviations, and therefore penalties, can be significantly reduced. Even though one might have the ability to accurately forecast the availability of wind power, it might not be available during enough of the peak period to provide sufficient value. However, if the wind power plant is developed over geographically disperse locations, the timing and availability of wind power from these multiple sources could provide a better match with the utility`s peak load than a single site. There are several wind plants in various stages of planning or development in the US. Although some of these are small-scale demonstration projects, significant wind capacity has been developed in Minnesota, with additional developments planned in Wyoming and Iowa. As these and other projects are planned and developed, there is a need to perform analysis of the value of geographically diverse sites on the efficiency of the overall wind plant. In this paper, the authors use hourly wind-speed data from six geographically diverse sites to provide some insight into the potential benefits of disperse wind plant development. They provide hourly wind power from each of these sites to an electric reliability simulation model. This model uses generating plant characteristics of the generators within the state of Minnesota to calculate various reliability indices. Since they lack data on wholesale power transactions, they do not include them in the analysis, and they reduce the hourly load data accordingly. The authors present and compare results of their methods and suggest some areas of future research.

Milligan, M.R. [National Renewable Energy Lab., Golden, CO (United States)] [National Renewable Energy Lab., Golden, CO (United States); Artig, R. [Minnesota Dept. of Public Service, St. Paul, MN (United States)] [Minnesota Dept. of Public Service, St. Paul, MN (United States)

1998-04-01T23:59:59.000Z

391

Short-Term Power Fluctuations of Large Wind Power Plants: Preprint  

DOE Green Energy (OSTI)

With electric utilities and other power providers showing increased interest in wind power and with growing penetration of wind capacity into the market, questions about how wind power fluctuations affect power system operations and about wind power's ancillary services requirements are receiving lots of attention. The project's purpose is to acquire actual, long-term wind power output data for analyzing wind power fluctuations, frequency distribution of the changes, the effects of spatial diversity, and wind power ancillary services.

Wan, Y.; Bucaneg, D.

2002-01-01T23:59:59.000Z

392

Stakeholder Engagement and Outreach: What Is Wind Power?  

Wind Powering America (EERE)

What Is Wind Power? What Is Wind Power? A three-bladed wind turbine with the internal components visible. Six turbines in a row are electrically connected to the power grid. Wind Power Animation This aerial view of a wind turbine plant shows how a group of wind turbines can make electricity for the utility grid. The electricity is sent through transmission and distribution lines to homes, businesses, schools, and so on. View the wind turbine animation to see how a wind turbine works or take a look inside. Wind power or wind energy describes the process by which the wind is used to generate mechanical power or electricity. Wind turbines convert the kinetic energy in the wind into mechanical power. This mechanical power can be used for specific tasks (such as grinding grain or pumping water), or

393

Study of a Wind Farm Power System: Preprint  

Science Conference Proceedings (OSTI)

A wind power system differs from a conventional power system. In a conventional power plant, the operator can control the plant's output. The output of a wind farm cannot be controlled because the output fluctuates with the wind. In this paper, we investigate the power-system interaction resulting from power variations at wind farms using steady-state analysis.

Muljadi, E.; Wan, Y.; Butterfield, C. P.; Parsons, B.

2002-01-01T23:59:59.000Z

394

Forecasting photovoltaic array power production subject to mismatch losses  

Science Conference Proceedings (OSTI)

The development of photovoltaic (PV) energy throughout the world this last decade has brought to light the presence of module mismatch losses in most PV applications. Such power losses, mainly occasioned by partial shading of arrays and differences in PV modules, can be reduced by changing module interconnections of a solar array. This paper presents a novel method to forecast existing PV array production in diverse environmental conditions. In this approach, field measurement data is used to identify module parameters once and for all. The proposed method simulates PV arrays with adaptable module interconnection schemes in order to reduce mismatch losses. The model has been validated by experimental results taken on a 2.2 kW{sub p} plant, with three different interconnection schemes, which show reliable power production forecast precision in both partially shaded and normal operating conditions. Field measurements show interest in using alternative plant configurations in PV systems for decreasing module mismatch losses. (author)

Picault, D.; Raison, B.; Bacha, S. [Grenoble Electrical Engineering Laboratory (G2Elab), 961, rue Houille Blanche BP 46, 38402 St Martin d'Heres (France); de la Casa, J.; Aguilera, J. [Grupo de Investigacion IDEA, Departamento de Electronica, Escuela Politecnica Superior, Universidad de Jaen, Campus Las Lagunillas, 23071 Jaen (Spain)

2010-07-15T23:59:59.000Z

395

Wind power for farms, homes, and small industry  

DOE Green Energy (OSTI)

Information is presented concerning basic wind turbine energy conversion; wind behavior and site selection; power and energy requirements; the components of a wind energy conversion system; selecting a wind energy conversion system and system economics; and legal aspects.

Park, J.; Schwind, D.

1978-09-01T23:59:59.000Z

396

Environmental Energy Technologies Division Energy Analysis Department Community Wind Power  

E-Print Network (OSTI)

Environmental Energy Technologies Division · Energy Analysis Department Community Wind Power projects * standard US commercial wind development #12;Environmental Energy Technologies Division · Energy % Community- Owned Community- Owned Wind Capacity (MW) Total Wind Capacity (MW) #12;Environmental Energy

397

Wind Powering America: Document Not Found  

Wind Powering America (EERE)

navigation to main content. U.S. Department of Energy Energy Efficiency and Renewable Energy Wind Powering America Document Not Found This is a temporary URL for the U.S....

398

Large-Scale Offshore Wind Power  

NLE Websites -- All DOE Office Websites (Extended Search)

Large-Scale Offshore Wind Power in the United States EXECUTIVE SUMMARY September 2010 NOTICE This report was prepared as an account of work sponsored by an agency of the United...

399

Hawaii 50 m Wind Power Class  

NLE Websites -- All DOE Office Websites (Extended Search)

using their MesoMap system and historical weather data under contract to Wind Powering AmericaNREL. This map has been validated with available surface data by NREL and...

400

Wind Power Amercia Final Report  

SciTech Connect

The objective of this grant was to further the development of Montana�¢����s vast wind resources for small, medium and large scale benefits to Montana and the nation. This was accomplished through collaborative work with wind industry representatives, state and local governments, the agricultural community and interested citizens. Through these efforts DEQ was able to identify development barriers, educate and inform citizens as well as participate in regional and national dialogue that will spur the development of wind resources.

Brian Spangler, Kathi Montgomery and Paul Cartwright

2012-01-30T23:59:59.000Z

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

Wildlife Risks of Wind and Solar Power  

Science Conference Proceedings (OSTI)

This report examines the potential wildlife impacts resulting from wind and solar power development. The report defines the potential wildlife impacts, the business reasoning for assessing these impacts, details regarding site selection to minimize impacts, strategies to assess impacts, and management strategies to mitigate or minimize impacts. The report will assist utility generation planners and electric power company environmental staff in identifying and evaluating the wildlife impacts of wind and s...

2011-12-13T23:59:59.000Z

402

Avian Interactions with Wind Power Structures  

Science Conference Proceedings (OSTI)

In October of 2002, in Jackson Hole, Wyoming, EPRI held a conference on avian interactions with wind power structures. Previous EPRI conferences on this same topic have focused on various aspects of the topic; the focus areas in 2002 were 1) assessing the state of knowledge with respect to avian interactions with wind powered generation facilities, and 2) providing a context for future research and development efforts. This report is an abbreviated version of the complete proceedings, which will be poste...

2003-03-31T23:59:59.000Z

403

Wind Power | OpenEI  

Open Energy Info (EERE)

information related to world wind energy. It is part of a supporting dataset for the book World On the Edge: How to Prevent Environmental and Economic Collapse by Lester R....

404

Wind powering America: South Dakota  

DOE Green Energy (OSTI)

This fact sheet contains a description of South Dakota's wind energy resources, and the state's financial incentives that support the installation of renewable energy systems. The fact sheet includes a list of contacts for those interested in obtaining more information.

NREL

2000-04-11T23:59:59.000Z

405

Power quality analysis of wind generator connected to the weak grid during low wind speed  

Science Conference Proceedings (OSTI)

Power quality analysis based on measurements performed on wind generator during low wind speed is presented in the paper. Wind generator is connected via 10 kV cable to the distribution network, where grid is weak with low value of short-circuit power. ... Keywords: distribution network, harmonics, power quality, wind speed, wind turbine

Aleksandar Nikolic; Branka Kostic; Maja Markovic; Sasa Minic; Srdjan Milosavljevic

2011-07-01T23:59:59.000Z

406

Wind Power Quality Test for Comparison of Power Quality Standards  

SciTech Connect

Power quality testing is important to wind power applications for several reasons. The nature of wind turbine generation is different from conventional power plants. Although windfarms are growing in capacity and diversifying in nature in the U.S. and throughout the globe, there is no standard that addresses the power quality of wind turbines or wind farms. The International Electrotechnical Committee (IEC) has convened Working Group 10 (WG10) to address testing and assessment of power quality characteristics of wind turbines. A IEEE task force has been appointed to reconsider flicker measurement procedures in the U.S. Lastly, power quality tests are now required as part of the certification process for wind turbines. NREL began this work both in response to industry request and in support of the IEC working group. (Mr. Gregory is a member of the IEC working group) This paper presents the NREL Certification Testing Team's effort in developing procedures and equipment for power quality testing for wind turbine certification. Summaries of several power quality standards that are applicable to this process are also presented in this paper.

Jacobson, R.; Gregory, B. (National Wind Technology Center)

1999-09-09T23:59:59.000Z

407

Wind Power Quality Test for Comparison of Power Quality Standards  

DOE Green Energy (OSTI)

Power quality testing is important to wind power applications for several reasons. The nature of wind turbine generation is different from conventional power plants. Although windfarms are growing in capacity and diversifying in nature in the U.S. and throughout the globe, there is no standard that addresses the power quality of wind turbines or wind farms. The International Electrotechnical Committee (IEC) has convened Working Group 10 (WG10) to address testing and assessment of power quality characteristics of wind turbines. A IEEE task force has been appointed to reconsider flicker measurement procedures in the U.S. Lastly, power quality tests are now required as part of the certification process for wind turbines. NREL began this work both in response to industry request and in support of the IEC working group. (Mr. Gregory is a member of the IEC working group) This paper presents the NREL Certification Testing Team's effort in developing procedures and equipment for power quality testing for wind turbine certification. Summaries of several power quality standards that are applicable to this process are also presented in this paper.

Jacobson, R.; Gregory, B. (National Wind Technology Center)

1999-09-09T23:59:59.000Z

408

Wind Powering America FY06 Activities Summary  

DOE Green Energy (OSTI)

The Wind Powering America FY06 Activities Summary reflects the accomplishments of our state wind working groups, our programs at the National Renewable Energy Laboratory, and our partner organizations. The national WPA team remains a leading force for moving wind energy forward in the United States. WPA continues to work with its national, regional, and state partners to communicate the opportunities and benefits of wind energy to a diverse set of stakeholders. WPA now has 29 state wind working groups (welcoming New Jersey, Indiana, Illinois, and Missouri in 2006) that form strategic alliances to communicate wind's benefits to the state stakeholders. More than 120 members of national and state public and private sector organizations from 34 states attended the 5th Annual WPA All-States Summit in Pittsburgh in June.

Not Available

2007-02-01T23:59:59.000Z

409

Making european-style community wind power development work in the United States  

E-Print Network (OSTI)

Support for Community Wind Power Development. LBNL-54715.at 2003 Oklahoma Wind Power and Bioenergy Conference, JuneWind. 2001. Distributed Wind Power Assessment. Prepared for

Bolinger, Mark A.

2004-01-01T23:59:59.000Z

410

New England Wind Forum: A Wind Powering America Project - Newsletter #6 - September 2010, (NEWF), Wind and Water Power Program (WWPP)  

Wind Powering America (EERE)

6 - September 2010 6 - September 2010 WIND AND WATER POWER PROGRAM PIX 16204 New England and Northeast Look to the Horizon...and Beyond, for Offshore Wind In early December, Boston hosted the American Wind Energy Association's second annual Offshore Wind Project Workshop. U.S. and European offshore wind stakeholders convened to discuss the emerging U.S. offshore wind industry and provided evidence of a significant increase in activity along the Atlantic Coast from the Carolinas to Maine. The wind power industry and policymakers are looking to offshore for long-term growth, driven by aggressive policy goals, economic develop- ment opportunities, a finite set of attractive land-based wind sites, and immense wind energy potential at a modest distance from major population centers.

411

On the Wind Power Input to the Ocean General Circulation  

E-Print Network (OSTI)

The wind power input to the ocean general circulation is usually calculated from the time-averaged wind products. Here, this wind power input is reexamined using available observations, focusing on the role of the synoptically ...

Zhai, Xiaoming

412

Wind Farm Aggregation Impact on Power Quality: Preprint  

SciTech Connect

This paper explores the effects of wind farm power fluctuations on the power network. A dynamic simulation of a wind farm is performed and the spatial distribution of the wind turbines is considered.

Bialasiewicz, J. T.; Muljadi, E.

2006-11-01T23:59:59.000Z

413

Guohua Dongtai Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Wind Power Co Ltd Jump to: navigation, search Name Guohua (Dongtai) Wind Power Co Ltd Place Dongtai, Jiangsu Province, China Zip 224200 Sector Wind energy Product Dongtai-based...

414

Jilin Licheng Xiehe Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Licheng Xiehe Wind Power Co Ltd Jump to: navigation, search Name Jilin Licheng Xiehe Wind Power Co Ltd Place Jilin Province, China Sector Wind energy Product Baicheng-based JV...

415

Xilinguole Guotai Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Xilinguole Guotai Wind Power Co Ltd Jump to: navigation, search Name Xilinguole Guotai Wind Power Co Ltd Place China Sector Wind energy Product Hong Kong-based project developer...

416

Wholesale Electricity Price Forecast This appendix describes the wholesale electricity price forecast of the Fifth Northwest Power  

E-Print Network (OSTI)

representing the ed cycle power plants high thermal efficiency, low environmental impact, short construction-cycle gas turbines 100 MW wind power plants - prime resource areas 100 MW wind power plants - secondary, curtailment, or by imports from xmp® simulates power plant dispatch in each of 16 load- resource zones

417

Wind for Schools Project Power System Brief, Wind Powering America Fact Sheet Series  

SciTech Connect

Wind Powering America's (WPA's) Wind for Schools project uses a basic system configuration for each school project. The system incorporates a single SkyStream wind turbine, a 70-ft guyed tower, disconnect boxes at the base of the turbine and at the school, and an interconnection to the school's electrical system. This document provides a detailed description of each system component.

Baring-Gould, I.

2009-05-01T23:59:59.000Z

418

Wind: wind power density GIS data at 50m above ground and 1km...  

Open Energy Info (EERE)

Wind: wind power density GIS data at 50m above ground and 1km resolution for Central America from NREL

(Abstract):  Raster GIS data, 50 m wind power density...

419

Wind: wind power density maps at 50m above ground and 1km resolution...  

Open Energy Info (EERE)

Wind: wind power density maps at 50m above ground and 1km resolution for Ghana from NREL

(Abstract):  Raster GIS data, 50 m wind power density for Ghana.

...

420

Wind: wind power density maps at 50 m above ground and 1km resolution...  

Open Energy Info (EERE)

Wind: wind power density maps at 50 m above ground and 1km resolution for Cuba from NREL

(Abstract):  Raster GIS data, 50 m wind power density for Cuba.

...

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Wind: wind power density GIS data at 50m above ground and 1km...  

Open Energy Info (EERE)

Wind: wind power density GIS data at 50m above ground and 1km resolution for Cuba from NREL

(Abstract):  Raster GIS data, exported as BIL file, 50 m wind power...

422

Wind: wind power density maps at 50m above ground and 1km resolution...  

Open Energy Info (EERE)

Wind: wind power density maps at 50m above ground and 1km resolution for Central America from NREL

(Abstract):  50 m wind power density (Wm2) maps of Central...

423

Green Power Wind Farm | Open Energy Information  

Open Energy Info (EERE)

Green Power Wind Farm Green Power Wind Farm Facility Green Power Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner NextEra Energy Resources Developer GE Energy Energy Purchaser Southern California Edison Co Location San Gorgonio CA Coordinates 33.9095°, -116.734° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":33.9095,"lon":-116.734,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

424

On the Evaluation of Wind Power from Short Wind Records  

Science Conference Proceedings (OSTI)

A method to estimate the meteorological mean wind power of a given site and year based upon data of only three months is presented. It is based on the minimization of the rms errors between observations and a representation by means of empirical ...

Vicente R. Barros; Eduardo A. Estevan

1983-06-01T23:59:59.000Z

425

Power and Frequency Control as it Relates to Wind-Powered Generation  

SciTech Connect

This report is a part of an investigation of the ability of the U.S. power system to accommodate large scale additions of wind generation. The objectives of this report are to describe principles by which large multi-area power systems are controlled and to anticipate how the introduction of large amounts of wind power production might require control protocols to be changed. The operation of a power system is described in terms of primary and secondary control actions. Primary control is fast, autonomous, and provides the first-line corrective action in disturbances; secondary control takes place on a follow-up time scale and manages the deployment of resources to ensure reliable and economic operation. This report anticipates that the present fundamental primary and secondary control protocols will be satisfactory as wind power provides an increasing fraction of the total production, provided that appropriate attention is paid to the timing of primary control response, to short term wind forecasting, and to management of reserves for control action.

Lacommare, Kristina S H

2010-12-20T23:59:59.000Z

426

Wind Powering America Podcasts (Postcards), Wind Powering America (WPA), Energy Efficiency & Renewable Energy (EERE)  

Wind Powering America (EERE)

Photo from iStock/ 6495435 Photo from iStock/ 6495435 Wind Powering America Podcasts Wind Powering America and the National Association of Farm Broadcasters produce a series of radio interviews featuring experts discussing wind energy topics. The interviews are aimed at a rural stakeholder audience and are available as podcasts. On the Wind Powering America website, you can access past interviews on topics such as: * Keys to Local Wind Energy Development Success * What to Know about Installing a Wind Energy System on Your Farm * Wind Energy Development Can Revitalize Rural America. Printed with a renewable-source ink on paper containing at least 50% wastepaper, including 10% post consumer waste. DOE/GO-102012-3585 · April 2012 windpoweringamerica.gov/podcasts_agricultural.asp

427

STANDARDS FOR MEASUREMENTS AND TESTING OF WIND TURBINE POWER QUALITY Poul Srensen, Ris National Laboratory, P.O.Box 49, DK-4000 Roskilde, Denmark.  

E-Print Network (OSTI)

unconsidered outages of single turbines reflect a higher forecast error than expected from NWP. Wind power. The wind farm was in the commissioning phase in early 2001, when gradually more and more turbines became due to turbine wakes in the wind park and vi) accounting the availability of turbines with respect

Heinemann, Detlev

428

Fuxin Union Wind Power Co Ltd formerly known as Liaoning Zhangwu Xiehe Wind  

Open Energy Info (EERE)

Ltd formerly known as Liaoning Zhangwu Xiehe Wind Ltd formerly known as Liaoning Zhangwu Xiehe Wind Power Co Ltd Jump to: navigation, search Name Fuxin Union Wind Power Co Ltd (formerly known as Liaoning Zhangwu Xiehe Wind Power Co Ltd) Place Liaoning Province, China Sector Wind energy Product JV between CWP Development (a wholly-owned subsidiary of Wind Power) and Shenzhen KWC set up to develop, construct and operate wind power facilities. References Fuxin Union Wind Power Co Ltd (formerly known as Liaoning Zhangwu Xiehe Wind Power Co Ltd)[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Fuxin Union Wind Power Co Ltd (formerly known as Liaoning Zhangwu Xiehe Wind Power Co Ltd) is a company located in Liaoning Province, China .

429

MSU-Wind Applications Center: Wind Resource Worksheet Theoretical Power Calculation  

E-Print Network (OSTI)

MSU-Wind Applications Center: Wind Resource Worksheet Theoretical Power Calculation Equations: A= swept area = air density v= velocity R= universal gas constant Steps: 1. Measure wind speed from fan. = ___________/(________*________)= _________kg/m3 5. Theoretical Power a. Low Setting Theoretical Wind Power i. Power= ½*______*______*______*.59

Dyer, Bill

430

Analysis of wind power ancillary services characteristics with German 250-MW wind data  

DOE Green Energy (OSTI)

With the increasing availability of wind power worldwide, power fluctuations have become a concern for some utilities. Under electric industry restructuring in the US, the impact of these fluctuations will be evaluated by examining provisions and costs of ancillary services for wind power. This paper analyzes wind power in the context of ancillary services, using data from a German 250 Megawatt Wind project.

Ernst, B.

1999-12-09T23:59:59.000Z

431

QuikSCAT Impacts on Coastal Forecasts and Warnings: Operational Utility of Satellite Ocean Surface Vector Wind Data  

Science Conference Proceedings (OSTI)

This study reports on the operational utility of ocean surface vector wind (SVW) data from Quick Scatterometer (QuikSCAT) observations in the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) Weather Forecast ...

Ralph F. Milliff; Peter A. Stamus

2008-10-01T23:59:59.000Z

432

The Impact of Radar Data on Short-Term Forecasts of Surface Temperature, Dewpoint Depression, and Wind Speed  

Science Conference Proceedings (OSTI)

A statistical system that uses surface observations and radar data to provide 1-, 3-, and 6-h forecasts of temperature, dewpoint depression, and wind speed is developed. Application of the system to independent data demonstrates that the radar ...

Emily K. Grover-Kopec; J. Michael Fritsch

2003-12-01T23:59:59.000Z

433

Wind powering America: South Dakota  

SciTech Connect

This fact sheet contains a description of South Dakota's wind energy resources, and the state's financial incentives that support the installation of renewable energy systems. The fact sheet includes a list of contacts for those interested in obtaining more information.

NREL

2000-04-11T23:59:59.000Z

434

Fenton Wind Power Project | Open Energy Information  

Open Energy Info (EERE)

Fenton Wind Power Project Fenton Wind Power Project Jump to: navigation, search Name Fenton Wind Power Project Facility Fenton Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner EnXco Developer EnXco Energy Purchaser Xcel Energy Location Murray and Nobles Counties near Chandler MN Coordinates 43.909806°, -95.965884° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":43.909806,"lon":-95.965884,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

435

Kumeyaay Wind Power Project | Open Energy Information  

Open Energy Info (EERE)

Kumeyaay Wind Power Project Kumeyaay Wind Power Project Jump to: navigation, search Name Kumeyaay Wind Power Project Facility Kumeyaay Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner Babcock & Brown Developer Superior Renewable Energy Energy Purchaser San Diego Gas & Electric Location East of San Diego CA Coordinates 32.710183°, -116.333224° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":32.710183,"lon":-116.333224,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

436

Uses and Applications of Climate Forecasts for Power Utilities  

Science Conference Proceedings (OSTI)

The uses and potential applications of climate forecasts for electric and gas utilities were assessed 1) to discern needs for improving climate forecasts and guiding future research, and 2) to assist utilities in making wise use of forecasts. In-...

Stanley A. Changnon; Joyce M. Changnon; David Changnon

1995-05-01T23:59:59.000Z

437

Autonomous wind power systems are economically competitive  

Science Conference Proceedings (OSTI)

Autonomous wind power systems, i.e. electric conversion systems utilizing the wind as the only energy source, are especially useful for isolated applications (telecommunications, measuring stations, pumps, ...) and for remote individual domestic applications (direct feed of electrical energy into household mains, space and water heating, ...) or in the farm (greenhouse heating, milk cooling, ...). The power rating of autonomous systems can range from a few 100 W to about 50 kW. Usually a storage is incorporated in the form of electric batteries or standard night storage heaters, improving considerably the ability of the system to sustain the average power and ameliorate the reliability.

Van Leuven, J.

1983-12-01T23:59:59.000Z

438

Stakeholder Engagement and Outreach: How Do I Get Wind Power?  

Wind Powering America (EERE)

Education Education Printable Version Bookmark and Share Learn About Wind About Wind Power Locating Wind Power Getting Wind Power Installed Wind Capacity Wind for Schools Project Collegiate Wind Competition School Project Locations Education & Training Programs Curricula & Teaching Materials Resources How do I get Wind Power? Learn how you can own, partner with, host, and support wind power. Construct A Wind Project On Your Own Land There are wind turbines designed for everyone from residential homeowners to utilities, and from private to corporate use. Small wind turbines can be bought with cash, and commercial-scale projects can be financed. To learn more about small projects, such as those for a home or ranch or business that are less than or equal to 100 kilowatts (kW), see the small wind

439

Wind powering America: Clean energy for the 21st century  

Science Conference Proceedings (OSTI)

This Wind Powering America brochure provides the perspectives on the benefits of wind power from 10 U.S. citizens from different sectors of society, including ranching, utility commissioner, parent, Native American, farmer/county commissioner, business owner, and independent turbine operator. It also provides basic facts about wind power, contacts for information about wind power, and a brief description of the Wind Powering America Initiative, its goals and its benefits.

O'Dell, K.

2000-03-27T23:59:59.000Z

440

Wind Powering America: Clean Energy for the 21st Century  

Science Conference Proceedings (OSTI)

Wind Powering America Clean Energy for the 21st Century provides basic information about the benefits of wind power, contacts for information about wind power, and a brief description of the Wind Powering America Program, it goals, and its benefits. In addition, the brochure contains perspectives on the benefits of wind power from 10 U.S. citizens from different sectors of society including, farming, ranching, government, education, and the energy industry.

Not Available

2002-10-01T23:59:59.000Z

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Analysis of wind power for battery charging  

DOE Green Energy (OSTI)

One type of wind-powered battery charging will be explored in this paper. It consists of a wind turbine driving a permanent magnet alternator and operates at variable speed. The alternator is connected to a battery bank via a rectifier. The characteristic of the system depends on the wind turbine, the alternator, and the system configuration. If the electrical load does not match the wind turbine, the performance of the system will be degraded. By matching the electrical load to the wind turbine, the system can be improved significantly. This paper analyzes the properties of the system components. The effects of parameter variation and the system configuration on the system performance are investigated. Two basic methods of shaping the torque-speed characteristic of the generator are presented. The uncompensated as well as the compensated systems will be discussed. Control strategies to improve the system performance will be explored. Finally, a summary of the paper will be presented in the last section.

Muljadi, E.; Drouilhet, S.; Holz, R. [National Renewable Energy Lab., Golden, CO (United States); Gevorgian, V. [University of Armenia, Yerevan (Armenia). State Engineering

1995-11-01T23:59:59.000Z

442

Analysis of wind power for battery charging  

Science Conference Proceedings (OSTI)

One type of wind-powered battery charging is explored which consists of a wind turbine driving a permanent magnet alternator and which operates at variable speed. The alternator is connected to a battery bank via a rectifier. The characteristics of the system depend on the wind turbine, the alternator, and the system configuration. If the electrical load does not match the wind turbine, the performance of the system will be degraded. By matching the electrical load to the wind turbine, the system can be improved significantly. This paper analyzes the properties of the system components. The effects of parameter variation and the system configuration on the system performance are investigated. Two basic methods of shaping the torque-speed characteristic of the generator are presented. The uncompensated as well as the compensated systems are discussed. Control strategies to improve the system performance are explored.

Muljadi, E.; Drouilhet, S.; Holz, R.; Gevorgian, V.

1995-01-01T23:59:59.000Z

443

Testing Active Power Control from Wind Power at the National Wind Technology Center (NWTC) (Presentation)  

DOE Green Energy (OSTI)

In order to keep the electricity grid stable and the lights on, the power system relies on certain responses from its generating fleet. This presentation evaluates the potential for wind turbines and wind power plants to provide these services and assist the grid during critical times.

Ela, E.

2011-05-01T23:59:59.000Z

444

Wind Derivatives: Modeling and Pricing  

Science Conference Proceedings (OSTI)

Wind is considered to be a free, renewable and environmentally friendly source of energy. However, wind farms are exposed to excessive weather risk since the power production depends on the wind speed, the wind direction and the wind duration. This risk ... Keywords: Forecasting, Pricing, Wavelet networks, Weather derivatives, Wind derivatives

A. Alexandridis; A. Zapranis

2013-03-01T23:59:59.000Z

445

Improving Regional Air Quality with Wind Power  

Wind Powering America (EERE)

Improving Regional Air Quality with Improving Regional Air Quality with Wind Power National Renewable Energy Laboratory Improving Regional Air Quality with Wind Power National Renewable Energy Laboratory * Clean Air Act (CAA) framework * Air quality challenges * CAA policies as market drivers * Met. Wash. Council of Governments (MWCOG) case study * Environmental Protection Agency (EPA) guidance on State Implementation Plan (SIP) credit for EERE * Model SIP documentation for wind purchases * Related marketing innovations Overview Overview * CAA requires regional air quality plans (SIPs) * "Window of opportunity" - Revised SIPs required by 2006/2007 to meet new 8-hour ozone and PM standards - August 2004 EPA guidance and NREL model SIP documentation for wind purchases Clean Air Act Framework Clean Air Act Framework

446

Cielo Wind Power | Open Energy Information  

Open Energy Info (EERE)

Cielo Wind Power Cielo Wind Power Address 823 Congress Avenue Place Austin, Texas Zip 78701 Sector Wind energy Product Wind energy developer Website http://www.cielowind.com/ Coordinates 30.270585°, -97.741444° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":30.270585,"lon":-97.741444,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

447

AG Wind Power Ltd | Open Energy Information  

Open Energy Info (EERE)

Wind Power Ltd Wind Power Ltd Place Sheffield, United Kingdom Zip S3 8EN Sector Wind energy Product UK-based company focused on wind turbine erection and maintenance. Coordinates 53.38311°, -1.464544° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":53.38311,"lon":-1.464544,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

448

Wind and Power | Open Energy Information  

Open Energy Info (EERE)

Wind and Power Wind and Power Place Warszawa, Poland Zip 04-320 Sector Solar, Wind energy Product The firm offers small-scale PV panels, inverters, accumulators, solar collectors and wind turbines, and has distributors in Germany, Hungary and Rumania. Coordinates 52.23537°, 21.009485° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":52.23537,"lon":21.009485,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

449

Wind Power Energia | Open Energy Information  

Open Energy Info (EERE)

Wind Power Energia Wind Power Energia Place Fortaleza, Ceara, Brazil Zip 60160-230 Sector Wind energy Product Brazil-based small scale wind turbine manufacturer. Coordinates -3.718404°, -38.542924° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":-3.718404,"lon":-38.542924,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

450

Clear Wind Renewable Power | Open Energy Information  

Open Energy Info (EERE)

Clear Wind Renewable Power Clear Wind Renewable Power Place Minneapolis, Minnesota Zip 55416 Sector Wind energy Product Clear Wind focuses its efforts on projects ranging in size from 5 to 50MW in the midwest US. Coordinates 44.979035°, -93.264929° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":44.979035,"lon":-93.264929,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

451

Extreme learning machine based wind speed estimation and sensorless control for wind turbine power generation system  

Science Conference Proceedings (OSTI)

This paper proposes a precise real-time wind speed estimation method and sensorless control for variable-speed variable-pitch wind turbine power generation system (WTPGS). The wind speed estimation is realized by a nonlinear input-output mapping extreme ... Keywords: Extreme learning machine, Sensorless control, Wind speed estimation, Wind turbine power generation system

Si Wu; Youyi Wang; Shijie Cheng

2013-02-01T23:59:59.000Z

452

This introduction to wind power technology is meant to help communities in considering or planning wind  

E-Print Network (OSTI)

detail. Wind Power: Performance & Economics Wind Power on the Community Scale Renewable Energy Research money from wind Energy Production Estimates The amount of energy (MWh) that a wind turbine makes each and type of turbine. This table gives a rough estimate of the amount of energy that a commercial-scale wind

Massachusetts at Amherst, University of

453

Jilin CWP Milestone Wind Power Investment Limited | Open Energy Information  

Open Energy Info (EERE)

CWP Milestone Wind Power Investment Limited CWP Milestone Wind Power Investment Limited Jump to: navigation, search Name Jilin CWP-Milestone Wind Power Investment Limited Place Baicheng, Jilin Province, China Sector Wind energy Product JV between Top Well (a wholly-owned subsidiary of Wind Power) and Shenzhen KWC set up to develop, construct and operate wind power facilities in China. References Jilin CWP-Milestone Wind Power Investment Limited[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Jilin CWP-Milestone Wind Power Investment Limited is a company located in Baicheng, Jilin Province, China . References ↑ "Jilin CWP-Milestone Wind Power Investment Limited" Retrieved from "http://en.openei.org/w/index.php?title=Jilin_CWP_Milestone_Wind_Power_Investment_Limited&oldid=347495"

454

The amount of power in the wind is very dependent on the speed of the wind. Because the power in the wind  

E-Print Network (OSTI)

The amount of power in the wind is very dependent on the speed of the wind. Because the power in the wind is proportional to the cube of the wind speed, small differences in the wind speed make a big. This gives rise to the primary reason for wind re- source assessment. In order to more accurately predict

Massachusetts at Amherst, University of

455

California Regional Wind Energy Forecasting System Development, Volume 4: California Wind Generation Research Dataset (CARD)  

Science Conference Proceedings (OSTI)

The rated capacity of wind generation in California is expected to grow rapidly in the future beyond the approximately 2100 megawatts in place at the end of 2005. The main drivers are the state's 20 percent renewable portfolio standard requirement in 2010 and the low cost of wind energy relative to other renewable energy sources. As wind is an intermittent generation resource and weather changes can cause large and rapid changes in output, system operators will need accurate and robust wind energy forec...

2006-11-13T23:59:59.000Z

456

Control system for wind-powered generators  

DOE Green Energy (OSTI)

In a system of wind-powered generators, a reliable yet inexpensive control system is desirable. Such a system would be completely automatic so it could be left unattended for long periods. It would respond to electrical representations of data such as bearing temperature, vibration, wind velocity, turbine velocity, torque, or any other pertinent data. It would respond by starting or stopping the turbine, controlling the loading, or sounding an alarm. A microprocessor-based controller capable of these functions is described.

Kroth, G.J.

1977-05-01T23:59:59.000Z

457

Wind Powering America FY07 Activities Summary  

DOE Green Energy (OSTI)

The Wind Powering America FY07 Activities Summary reflects the accomplishments of our state wind working groups, our programs at the National Renewable Energy Laboratory, and our partner organizations. The national WPA team remains a leading force for moving wind energy forward in the United States. WPA continues to work with its national, regional, and state partners to communicate the opportunities and benefits of wind energy to a diverse set of stakeholders. WPA now has 30 state wind working groups (welcoming Georgia and Wisconsin in 2007) that form strategic alliances to communicate wind's benefits to the state stakeholders. More than 140 members of national and state public and private sector organizations from 39 U.S. states and Canada attended the 6th Annual WPA All-States Summit in Los Angeles in June. WPA's emphasis remains on the rural agricultural sector, which stands to reap the significant economic development benefits of wind energy development. Additionally, WPA continues its program of outreach, education, and technical assistance to Native American communities, public power entities, and regulatory and legislative bodies.

Not Available

2008-02-01T23:59:59.000Z

458

PowerJet Wind Turbine Project  

SciTech Connect

PROJECT OBJECTIVE The PowerJet wind turbine overcomes problems characteristic of the small wind turbines that are on the market today by providing reliable output at a wide range of wind speeds, durability, silent operation at all wind speeds, and bird-safe operation. Prime Energy�s objective for this project was to design and integrate a generator with an electrical controller and mechanical controls to maximize the generation of electricity by its wind turbine. The scope of this project was to design, construct and test a mechanical back plate to control rotational speed in high winds, and an electronic controller to maximize power output and to assist the base plate in controlling rotational speed in high winds. The test model will continue to operate beyond the time frame of the project, with the ultimate goal of manufacturing and marketing the PowerJet worldwide. Increased Understanding of Electronic & Mechanical Controls Integrated With Electricity Generator The PowerJet back plate begins to open as wind speed exceeds 13.5 mps. The pressure inside the turbine and the turbine rotational speed are held constant. Once the back plate has fully opened at approximately 29 mps, the controller begins pulsing back to the generator to limit the rotational speed of the turbine. At a wind speed in excess of 29 mps, the controller shorts the generator and brings the turbine to a complete stop. As the wind speed subsides, the controller releases the turbine and it resumes producing electricity. Data collection and instrumentation problems prevented identification of the exact speeds at which these events occur. However, the turbine, controller and generator survived winds in excess of 36 mps, confirming that the two over-speed controls accomplished their purpose. Technical Effectiveness & Economic Feasibility Maximum Electrical Output The output of electricity is maximized by the integration of an electronic controller and mechanical over-speed controls designed and tested during the course of this project. The output exceeds that of the PowerJet�s 3-bladed counterparts (see Appendix). Durability All components of the PowerJet turbine assembly�including the electronic and mechanical controls designed, manufactured and field tested during the course of this project�proved to be durable through severe weather conditions, with constant operation and no interruption in energy production. Low Cost Materials for the turbine, generator, tower, charge controllers and ancillary parts are available at reasonable prices. Fabrication of these parts is also readily available worldwide. The cost of assembling and installing the turbine is reduced because it has fewer parts and requires less labor to manufacture and assemble, making it competitively priced compared with turbines of similar output manufactured in the U.S. and Europe. The electronic controller is the unique part to be included in the turbine package. The controllers can be manufactured in reasonably-sized production runs to keep the cost below $250 each. The data logger and 24 sensors are for research only and will be unnecessary for the commercial product. Benefit To Public The PowerJet wind-electric system is designed for distributed wind generation in 3 and 4 class winds. This wind turbine meets DOE�s requirements for a quiet, durable, bird-safe turbine that eventually can be deployed as a grid-connected generator in urban and suburban settings. Results As described more fully below and illustrated in the Appendices, the goals and objectives outlined in 2060 SOPO were fully met. Electronic and mechanical controls were successfully designed, manufactured and integrated with the generator. The turbine, tower, controllers and generators operated without incident throughout the test period, surviving severe winter and summer weather conditions such as extreme temperatures, ice and sustained high winds. The electronic controls were contained in weather-proof electrical boxes and the elec

Bartlett, Raymond J

2008-11-30T23:59:59.000Z

459

Electricity for road transport, flexible power systems and wind power  

Open Energy Info (EERE)

road transport, flexible power systems and wind power road transport, flexible power systems and wind power (Smart Grid Project) Jump to: navigation, search Project Name Electricity for road transport, flexible power systems and wind power Country Denmark Coordinates 56.26392°, 9.501785° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":56.26392,"lon":9.501785,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

460

Wind to Power Systems | Open Energy Information  

Open Energy Info (EERE)

Wind to Power Systems Wind to Power Systems Place Madrid, Spain Zip 28108 Sector Wind energy Product Wind to Power Systems designs, supplies and installs a device designed for use in wind turbines to provide fault ride-through capability, enabling wind turbines to maintain grid connection during periods of transmission line faults and voltage dips. Coordinates 40.4203°, -3.705774° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":40.4203,"lon":-3.705774,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

Miracle Wind Power Components Manufacture Co Ltd | Open Energy...  

Open Energy Info (EERE)

Login | Sign Up Search Page Edit with form History Facebook icon Twitter icon Miracle Wind Power Components Manufacture Co Ltd Jump to: navigation, search Name Miracle Wind...

462

CECIC Wind Power Investment Co Ltd | Open Energy Information  

Open Energy Info (EERE)

China Zip 100037 Sector Wind energy Product A subsidiary of China Energy Conservation Investment (CECIC), mainly engages in wind power project developing, investment and...

463

Wind Powering America FY08 Activities Summary (Book)  

SciTech Connect

The Wind Powering America FY08 Activities Summary reflects the accomplishments of state Wind Working Groups, WPA programs at the National Renewable Energy Laboratory, and partner organizations.

Not Available

2009-02-01T23:59:59.000Z

464

Energy Storage System in Wind Power System on Islands.  

E-Print Network (OSTI)

?? The wind energy has several merits but there exit some barriers in the development of wind power plant, and this is as a result… (more)

Jiang, Yuning

2013-01-01T23:59:59.000Z

465

Equilibrium pricing in electricity markets with wind power.  

E-Print Network (OSTI)

?? Estimates from the World Wind Energy Association assert that world total wind power installed capacity climbed from 18 Gigawatt (GW) to 152 GW from… (more)

Rubin, Ofir David

2010-01-01T23:59:59.000Z

466

Equilibrium pricing in electricity markets with wind power.  

E-Print Network (OSTI)

??Estimates from the World Wind Energy Association assert that world total wind power installed capacity climbed from 18 Gigawatt (GW) to 152 GW from 2000… (more)

Rubin, Ofir David

2010-01-01T23:59:59.000Z

467

Wind-hydrogen energy systems for remote area power supply.  

E-Print Network (OSTI)

??Wind-hydrogen systems for remote area power supply are an early niche application of sustainable hydrogen energy. Optimal direct coupling between a wind turbine and an… (more)

Janon, A

2009-01-01T23:59:59.000Z

468

Wind Powering America: FY09 Activities Summary (Book)  

DOE Green Energy (OSTI)

The Wind Powering America FY09 Activities Summary reflects the accomplishments of state Wind Working Groups, WPA programs at the National Renewable Energy Laboratory, and partner organizations.

Not Available

2010-03-01T23:59:59.000Z

469

Inner Mongolia Wind Power Corporation | Open Energy Information  

Open Energy Info (EERE)

Corporation Jump to: navigation, search Name Inner Mongolia Wind Power Corporation Place Inner Mongolia Autonomous Region, China Sector Wind energy Product A company engages in...

470

Shanghai Wind Power Co Ltd | Open Energy Information  

Open Energy Info (EERE)

Ltd Jump to: navigation, search Name Shanghai Wind Power Co Ltd Place Shanghai Municipality, China Zip 200437 Sector Wind energy Product Engaged in the design and manufacturing of...

471

Modeling and analysis of wind farm impacts on power systems.  

E-Print Network (OSTI)

??The wind energy industry has undergone a dramatic transformation during the last decade. The total operating wind power capacity in the world has increased greatly.… (more)

Zhou, Fengquan, 1969-

2005-01-01T23:59:59.000Z

472

Global Wind Power Ltd GWP | Open Energy Information  

Open Energy Info (EERE)

GWP Jump to: navigation, search Name Global Wind Power Ltd. (GWP) Place Mumbai, Maharashtra, India Zip 400 059 Sector Wind energy Product Mumbai-based firm involved in...

473

Wind Power: How Much, How Soon, and At What Cost?  

E-Print Network (OSTI)

Wind Power Capacity Incremental Capacity (2007, MW) United States China Spain Germany Indiaand India (Table 3). With major development now occurring on several continents, wind

Wiser, Ryan H

2010-01-01T23:59:59.000Z

474

Wind Power Technology Status and Performance and Cost Estimates - 2009  

Science Conference Proceedings (OSTI)

This report provides an update on the status and cost of wind power technology based on the Wind Power Technology Status and Performance and Cost Estimates – 2008 (EPRI report 1015806). It addresses the status of wind turbine and related technology for both onshore and offshore applications and the performance and cost of onshore wind power plants.

2009-11-20T23:59:59.000Z

475

Jilin Taihe Wind Power Limited | Open Energy Information  

Open Energy Info (EERE)

Taihe Wind Power Limited Taihe Wind Power Limited Jump to: navigation, search Name Jilin Taihe Wind Power Limited Place Zhenlai, Jilin Province, China Sector Wind energy Product Top Well and Tianjin DH entered into a contract to establish a joint venture in Zhenlai, in Chinaâ€(tm)s Jilin province to develop a 50MW wind farm in the area under the name Jilin Taihe Wind Power Limited. References Jilin Taihe Wind Power Limited[1] LinkedIn Connections CrunchBase Profile No CrunchBase profile. Create one now! This article is a stub. You can help OpenEI by expanding it. Jilin Taihe Wind Power Limited is a company located in Zhenlai, Jilin Province, China . References ↑ "Jilin Taihe Wind Power Limited" Retrieved from "http://en.openei.org/w/index.php?title=Jilin_Taihe_Wind_Power_Limited&oldid=347531

476

Long-Term Considerations on Wind Power's Environmental Impact  

E-Print Network (OSTI)

· Control and regulation · Scientific computing · Components · Grid and power transmission · Blade materials-of-the-art wind power system Mapping current trends of wind power technologies and concepts Expert panel

477

Category:Wind power in China | Open Energy Information  

Open Energy Info (EERE)

power in China Jump to: navigation, search Category: Wind Power in China Pages in category "Wind power in China" The following 2 pages are in this category, out of 2 total. C China...

478

Excise Tax Exemption for Solar- or Wind-Powered Systems  

Energy.gov (U.S. Department of Energy (DOE))

Massachusetts law exempts any "solar or wind powered climatic control unit and any solar or wind powered water heating unit or any other type unit or system powered thereby," that qualifies for the...

479

Laizhou Luneng Wind Power | Open Energy Information  

Open Energy Info (EERE)

Laizhou Luneng Wind Power Laizhou Luneng Wind Power Jump to: navigation, search Name Laizhou Luneng Wind Power Place Laizhou, Shandong Province, China Sector Wind energy Product A wind project developer. Established in a 2007 joint venture between Shandong Luneng Group and Yantai Dongyuan Power for a total investment of CNY 90m (USD 1.1m). Coordinates 37.168011°, 119.942223° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":37.168011,"lon":119.942223,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

480

Students Learn about Wind Power First-Hand through Wind for Schools Program  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Learn about Wind Power First-Hand through Wind for Schools Learn about Wind Power First-Hand through Wind for Schools Program Students Learn about Wind Power First-Hand through Wind for Schools Program February 18, 2011 - 3:48pm Addthis JMU student Greg Miller shows Northumberland students how the blades of a wind turbine work | courtesy of Virginia Center for Wind Energy JMU student Greg Miller shows Northumberland students how the blades of a wind turbine work | courtesy of Virginia Center for Wind Energy April Saylor April Saylor Former Digital Outreach Strategist, Office of Public Affairs What will the project do? Wind for Schools raises awareness in rural America about the benefits of wind energy while simultaneously developing a wind energy knowledge base in communities across the nation. For years, Jenny Christman tried to find a way to get a wind turbine to

Note: This page contains sample records for the topic "wind power forecasting" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

The Answer Is Blowing in the Wind: Analysis of Powering Internet Data Centers with Wind Energy  

E-Print Network (OSTI)

The Answer Is Blowing in the Wind: Analysis of Powering Internet Data Centers with Wind Energy Yan. As a result, many IDC operators have started using renewable energy, e.g., wind power, to power their data centers. Unfortunately, the utilization of wind energy has stayed at a low ratio due to the intermittent

482

Yinhe Avantis Wind Power Co Ltd formerly known as Avantis Yinhe Wind Power  

Open Energy Info (EERE)

Yinhe Avantis Wind Power Co Ltd formerly known as Avantis Yinhe Wind Power Yinhe Avantis Wind Power Co Ltd formerly known as Avantis Yinhe Wind Power Co Ltd Jump to: navigation, search Name Yinhe Avantis Wind Power Co Ltd (formerly known as Avantis Yinhe Wind Power Co Ltd ) Place Beihai, Guangxi Autonomous Region, China Zip 536000 Sector Wind energy Product Large scale wind turbine manufacturer developing 2.5MW turbines. Coordinates 21.484501°, 109.105309° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":21.484501,"lon":109.105309,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

483

The Political Economy of Wind Power in China  

E-Print Network (OSTI)

biores/108435/. ?China‘s power generation capacity leapshtm. ?Analysis of UK Wind Power Generation: November 2008 tofor Renewable Energy Power Generation Prices and Expenses? [

Swanson, Ryan Landon

2011-01-01T23:59:59.000Z

484

Solar Power Forecasting at UC San Diego Jan Kleissl, Dept of Mechanical & Aerospace Engineering, UCSD  

E-Print Network (OSTI)

Solar Power Forecasting at UC San Diego Jan Kleissl, Dept of Mechanical & Aerospace Engineering and discharging of fast storage devices with relatively low power (e.g. batteries or supercapacitors) could the economics of solar power. However, accurate short term forecasting of cloudiness is required for efficient

Fainman, Yeshaiahu

485

An Integrated Approach for Optimal Coordination of Wind Power and Hydro Pumping Storage  

E-Print Network (OSTI)

The increasing wind power penetration in power systems represents a techno-economic challenge for power producers and system operators. Due to the variability and uncertainty of wind power, system operators require new solutions in order to increase the controllability of wind farm output. On the other hand, producers that include wind farms in their portfolio need to find new ways to boost their profits in electricity markets. This can be done by optimizing the combination of wind farms and storage so as to make larger profits when selling power (trading) and reduce penalties from imbalances in the operation. The present work describes a new integrated approach for analyzing wind-storage solutions that make use of probabilistic forecasts and optimization techniques to aid decision-making on operating such systems. The approach includes a set of three complementary functions suitable for use in current systems. A reallife system is studied, comprising two wind farms and a large hydro station with pumping capacity. Economic profits and better operational features can be obtained from the proposed cooperation between the wind farms and storage. The revenues are function of the type of hydro storage used and the market characteristics and several options are compared in this study. The results show that the use of a storage device can lead to a significant increase in revenue, up to 11 % (2010 data, Iberian market). Also, the

Edgardo D. Castronuovo; Julio Usaola; Ricardo Bessa; Manuel Matos; I. C. Costa; L. Bremermann; Jesus Lugaro; George Kariniotakis; Sophia Antipolis France

2013-01-01T23:59:59.000Z

486

The Political Economy of Wind Power in China  

E-Print Network (OSTI)

framework,? Energy Policy 32 (2004): ?PR China,? Global WindWind Power in China: Policy and development challenges,? Energy PolicyPolicies for Renewable Energy-the example of China‘s wind

Swanson, Ryan Landon

2011-01-01T23:59:59.000Z

487

Wind Power Technology Status and Performance and Cost Estimates - 2008  

Science Conference Proceedings (OSTI)

This report addresses the status of wind turbine and related technology for both onshore and offshore applications, and the performance and cost of onshore wind power plants. It also presents a sample analysis of wind project financial performance.

2008-12-15T23:59:59.000Z