skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Ramp forecasting performance from improved short-term wind power forecasting over multiple spatial and temporal scales

Abstract

The large variability and uncertainty in wind power generation present a concern to power system operators, especially given the increasing amounts of wind power being integrated into the electric power system. Large ramps, one of the biggest concerns, can significantly influence system economics and reliability. The Wind Forecast Improvement Project (WFIP) was to improve the accuracy of forecasts and to evaluate the economic benefits of these improvements to grid operators. This paper evaluates the ramp forecasting accuracy gained by improving the performance of short-term wind power forecasting. This study focuses on the WFIP southern study region, which encompasses most of the Electric Reliability Council of Texas (ERCOT) territory, to compare the experimental WFIP forecasts to the existing short-term wind power forecasts (used at ERCOT) at multiple spatial and temporal scales. The study employs four significant wind power ramping definitions according to the power change magnitude, direction, and duration. The optimized swinging door algorithm is adopted to extract ramp events from actual and forecasted wind power time series. The results show that the experimental WFIP forecasts improve the accuracy of the wind power ramp forecasting. This improvement can result in substantial costs savings and power system reliability enhancements.

Authors:
; ; ; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
OSTI Identifier:
1344441
Report Number(s):
NREL/JA-5D00-68007
Journal ID: ISSN 0360-5442
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article
Resource Relation:
Journal Name: Energy (Oxford); Journal Volume: 122; Journal Issue: C
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; 24 POWER TRANSMISSION AND DISTRIBUTION; wind forecasting; grid integration; ramp forecasting; ERCOT; optimized swinging door algorithm

Citation Formats

Zhang, Jie, Cui, Mingjian, Hodge, Bri-Mathias, Florita, Anthony, and Freedman, Jeffrey. Ramp forecasting performance from improved short-term wind power forecasting over multiple spatial and temporal scales. United States: N. p., 2017. Web. doi:10.1016/j.energy.2017.01.104.
Zhang, Jie, Cui, Mingjian, Hodge, Bri-Mathias, Florita, Anthony, & Freedman, Jeffrey. Ramp forecasting performance from improved short-term wind power forecasting over multiple spatial and temporal scales. United States. doi:10.1016/j.energy.2017.01.104.
Zhang, Jie, Cui, Mingjian, Hodge, Bri-Mathias, Florita, Anthony, and Freedman, Jeffrey. Wed . "Ramp forecasting performance from improved short-term wind power forecasting over multiple spatial and temporal scales". United States. doi:10.1016/j.energy.2017.01.104.
@article{osti_1344441,
title = {Ramp forecasting performance from improved short-term wind power forecasting over multiple spatial and temporal scales},
author = {Zhang, Jie and Cui, Mingjian and Hodge, Bri-Mathias and Florita, Anthony and Freedman, Jeffrey},
abstractNote = {The large variability and uncertainty in wind power generation present a concern to power system operators, especially given the increasing amounts of wind power being integrated into the electric power system. Large ramps, one of the biggest concerns, can significantly influence system economics and reliability. The Wind Forecast Improvement Project (WFIP) was to improve the accuracy of forecasts and to evaluate the economic benefits of these improvements to grid operators. This paper evaluates the ramp forecasting accuracy gained by improving the performance of short-term wind power forecasting. This study focuses on the WFIP southern study region, which encompasses most of the Electric Reliability Council of Texas (ERCOT) territory, to compare the experimental WFIP forecasts to the existing short-term wind power forecasts (used at ERCOT) at multiple spatial and temporal scales. The study employs four significant wind power ramping definitions according to the power change magnitude, direction, and duration. The optimized swinging door algorithm is adopted to extract ramp events from actual and forecasted wind power time series. The results show that the experimental WFIP forecasts improve the accuracy of the wind power ramp forecasting. This improvement can result in substantial costs savings and power system reliability enhancements.},
doi = {10.1016/j.energy.2017.01.104},
journal = {Energy (Oxford)},
number = C,
volume = 122,
place = {United States},
year = {Wed Mar 01 00:00:00 EST 2017},
month = {Wed Mar 01 00:00:00 EST 2017}
}