Title :
Robust bidding strategy for wind power plants and energy storage in electricity markets
Author :
Thatte, A.A. ; Viassolo, D.E. ; Le Xie
Author_Institution :
Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX, USA
Abstract :
This paper explores a robust optimization-based bidding strategy for operating a wind farm in combination with energy storage devices in electricity markets. Through coordination with moderate capacity of energy storage, variable wind resources can be utilized in multi-time-scale electricity market operations, as opposed to being utilized only as real-time non-dispatchable energy producers. Given the inherent uncertainties in electricity market prices and available wind generator output, a robust optimization-based approach is formulated to determine the bidding strategy. Case studies on day-ahead and hour-ahead markets show that robust-optimization based bidding strategy provides computationally practical and economically efficient approach to operating wind farms and co-located storage when uncertainties are severe.
Keywords :
optimisation; power generation economics; power markets; wind power plants; day-ahead markets; electricity markets; energy storage devices; hour-ahead markets; multi-ime-scale electricity market operations; real-time nondispatchable energy producers; robust bidding strategy; robust optimization-based bidding strategy; wind farm; wind generator; wind power plants; Electricity; Energy storage; Optimization; Robustness; Uncertainty; Wind farms; Wind forecasting; Electricity market; energy storage; robust optimization; virtual power plants; wind power;
Conference_Titel :
Power and Energy Society General Meeting, 2012 IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-2727-5
Electronic_ISBN :
1944-9925
DOI :
10.1109/PESGM.2012.6344870