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Title: The value of improved wind power forecasting: Grid flexibility quantification, ramp capability analysis, and impacts of electricity market operation timescales

Abstract

The value of improving wind power forecasting accuracy at different electricity market operation timescales was analyzed by simulating the IEEE 118-bus test system as modified to emulate the generation mixes of the Midcontinent, California, and New England independent system operator balancing authority areas. The wind power forecasting improvement methodology and error analysis for the data set were elaborated. Production cost simulation was conducted on the three emulated systems with a total of 480 scenarios, considering the impacts of different generation technologies, wind penetration levels, and wind power forecasting improvement timescales. The static operational flexibility of the three systems was compared through the diversity of generation mix, the percentage of must-run baseload generators, as well as the available ramp rate and the minimum generation levels. The dynamic operational flexibility was evaluated by the real-time upward and downward ramp capacity. Simulation results show that the generation resource mix plays a crucial role in evaluating the value of improved wind power forecasting at different timescales. In addition, the changes in annual operational electricity generation costs were mostly influenced by the dominant resource in the system. Lastly, the impacts of pumped-storage resources, generation ramp rates, and system minimum generation level requirements on the valuemore » of improved wind power forecasting were also analyzed.« less

Authors:
 [1];  [1];  [1];  [1];  [1]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1336896
Alternate Identifier(s):
OSTI ID: 1414629
Report Number(s):
NREL/JA-5D00-67360
Journal ID: ISSN 0306-2619
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Accepted Manuscript
Journal Name:
Applied Energy
Additional Journal Information:
Journal Volume: 184; Journal Issue: C; Journal ID: ISSN 0306-2619
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; 24 POWER TRANSMISSION AND DISTRIBUTION; wind power integration; wind power forecasting; grid flexibility; ramp capability; operation timescales; storage

Citation Formats

Wang, Qin, Wu, Hongyu, Florita, Anthony R., Brancucci Martinez-Anido, Carlo, and Hodge, Bri-Mathias. The value of improved wind power forecasting: Grid flexibility quantification, ramp capability analysis, and impacts of electricity market operation timescales. United States: N. p., 2016. Web. doi:10.1016/j.apenergy.2016.11.016.
Wang, Qin, Wu, Hongyu, Florita, Anthony R., Brancucci Martinez-Anido, Carlo, & Hodge, Bri-Mathias. The value of improved wind power forecasting: Grid flexibility quantification, ramp capability analysis, and impacts of electricity market operation timescales. United States. https://doi.org/10.1016/j.apenergy.2016.11.016
Wang, Qin, Wu, Hongyu, Florita, Anthony R., Brancucci Martinez-Anido, Carlo, and Hodge, Bri-Mathias. Fri . "The value of improved wind power forecasting: Grid flexibility quantification, ramp capability analysis, and impacts of electricity market operation timescales". United States. https://doi.org/10.1016/j.apenergy.2016.11.016. https://www.osti.gov/servlets/purl/1336896.
@article{osti_1336896,
title = {The value of improved wind power forecasting: Grid flexibility quantification, ramp capability analysis, and impacts of electricity market operation timescales},
author = {Wang, Qin and Wu, Hongyu and Florita, Anthony R. and Brancucci Martinez-Anido, Carlo and Hodge, Bri-Mathias},
abstractNote = {The value of improving wind power forecasting accuracy at different electricity market operation timescales was analyzed by simulating the IEEE 118-bus test system as modified to emulate the generation mixes of the Midcontinent, California, and New England independent system operator balancing authority areas. The wind power forecasting improvement methodology and error analysis for the data set were elaborated. Production cost simulation was conducted on the three emulated systems with a total of 480 scenarios, considering the impacts of different generation technologies, wind penetration levels, and wind power forecasting improvement timescales. The static operational flexibility of the three systems was compared through the diversity of generation mix, the percentage of must-run baseload generators, as well as the available ramp rate and the minimum generation levels. The dynamic operational flexibility was evaluated by the real-time upward and downward ramp capacity. Simulation results show that the generation resource mix plays a crucial role in evaluating the value of improved wind power forecasting at different timescales. In addition, the changes in annual operational electricity generation costs were mostly influenced by the dominant resource in the system. Lastly, the impacts of pumped-storage resources, generation ramp rates, and system minimum generation level requirements on the value of improved wind power forecasting were also analyzed.},
doi = {10.1016/j.apenergy.2016.11.016},
journal = {Applied Energy},
number = C,
volume = 184,
place = {United States},
year = {Fri Nov 11 00:00:00 EST 2016},
month = {Fri Nov 11 00:00:00 EST 2016}
}

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Works referenced in this record:

Costs and benefits of renewables portfolio standards in the United States
journal, December 2015


Cost Analysis and Pricing Policy of Wind Power in China
journal, September 2011


Wind Power Forecasts Using Gaussian Processes and Numerical Weather Prediction
journal, March 2014


Short-term wind power forecasting using ridgelet neural network
journal, December 2011

  • Amjady, Nima; Keynia, Farshid; Zareipour, Hamidreza
  • Electric Power Systems Research, Vol. 81, Issue 12
  • DOI: 10.1016/j.epsr.2011.08.007

Wind Energy: Forecasting Challenges for Its Operational Management
journal, November 2013


An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed
journal, January 2016


Exploiting sparsity of interconnections in spatio-temporal wind speed forecasting using Wavelet Transform
journal, March 2016


Performance analysis of four modified approaches for wind speed forecasting
journal, November 2012


Short-term wind speed forecasting with Markov-switching model
journal, October 2014


Automatic tuning of Kalman filters by maximum likelihood methods for wind energy forecasting
journal, August 2013


Wind power forecasting based on principle component phase space reconstruction
journal, September 2015


A Short-Term Wind Power Forecasting Approach With Adjustment of Numerical Weather Prediction Input by Data Mining
journal, October 2015

  • Xu, Qianyao; He, Dawei; Zhang, Ning
  • IEEE Transactions on Sustainable Energy, Vol. 6, Issue 4
  • DOI: 10.1109/TSTE.2015.2429586

Probabilistic wind power forecasting based on logarithmic transformation and boundary kernel
journal, May 2015


Probabilistic Forecasting of Wind Power Generation Using Extreme Learning Machine
journal, May 2014


Demand Dispatch and Probabilistic Wind Power Forecasting in Unit Commitment and Economic Dispatch: A Case Study of Illinois
journal, January 2013

  • Botterud, Audun; Zhou, Zhi; Wang, Jianhui
  • IEEE Transactions on Sustainable Energy, Vol. 4, Issue 1
  • DOI: 10.1109/TSTE.2012.2215631

A review on the recent history of wind power ramp forecasting
journal, December 2015

  • Gallego-Castillo, Cristobal; Cuerva-Tejero, Alvaro; Lopez-Garcia, Oscar
  • Renewable and Sustainable Energy Reviews, Vol. 52
  • DOI: 10.1016/j.rser.2015.07.154

Wind Power Forecasting in U.S. Electricity Markets
journal, April 2010

  • Botterud, Audun; Wang, Jianhui; Miranda, Vladimiro
  • The Electricity Journal, Vol. 23, Issue 3
  • DOI: 10.1016/j.tej.2010.03.006

Wind power forecasting uncertainty and unit commitment
journal, November 2011


The value of day-ahead solar power forecasting improvement
journal, May 2016


Quantifying the value of improved wind energy forecasts in a pool-based electricity market
journal, August 2015


Quantifying the Economic and Grid Reliability Impacts of Improved Wind Power Forecasting
journal, October 2016

  • Wang, Qin; Martinez-Anido, Carlo Brancucci; Wu, Hongyu
  • IEEE Transactions on Sustainable Energy, Vol. 7, Issue 4
  • DOI: 10.1109/TSTE.2016.2560628

The Wind Integration National Dataset (WIND) Toolkit
journal, August 2015


A suite of metrics for assessing the performance of solar power forecasting
journal, January 2015


Risk-Based Locational Marginal Pricing and Congestion Management
journal, September 2014

  • Wang, Qin; Zhang, Guangyuan; McCalley, James D.
  • IEEE Transactions on Power Systems, Vol. 29, Issue 5
  • DOI: 10.1109/TPWRS.2014.2305303

A Novel Market Simulation Methodology on Hydro Storage
journal, March 2014


Review of energy system flexibility measures to enable high levels of variable renewable electricity
journal, May 2015

  • Lund, Peter D.; Lindgren, Juuso; Mikkola, Jani
  • Renewable and Sustainable Energy Reviews, Vol. 45
  • DOI: 10.1016/j.rser.2015.01.057

Integrating large scale wind power into the electricity grid in the Northeast of Brazil
journal, April 2016


Analyzing operational flexibility of electric power systems
journal, November 2015


Grid flexibility and storage required to achieve very high penetration of variable renewable electricity
journal, March 2011


Works referencing / citing this record:

Simulating wind power forecast error distributions for spatially aggregated wind power plants
journal, September 2019

  • Miettinen, Jari; Holttinen, Hannele; Hodge, Bri‐Mathias
  • Wind Energy, Vol. 23, Issue 1
  • DOI: 10.1002/we.2410

A universal power-law model for wind speed uncertainty
journal, November 2017


Optimal energy storage sizing and offering strategy for the presence of wind power plant with energy storage in the electricity market
journal, May 2018

  • Aghajani, Afshin; Kazemzadeh, Rasool; Ebrahimi, Afshin
  • International Transactions on Electrical Energy Systems, Vol. 28, Issue 11
  • DOI: 10.1002/etep.2621

Multi-Objective Optimal Capacity Planning for 100% Renewable Energy-Based Microgrid Incorporating Cost of Demand-Side Flexibility Management
journal, September 2019

  • Kiptoo, Mark Kipngetich; Adewuyi, Oludamilare Bode; Lotfy, Mohammed Elsayed
  • Applied Sciences, Vol. 9, Issue 18
  • DOI: 10.3390/app9183855

Integrating high levels of variable renewable energy into electric power systems
journal, November 2017