DocumentCode :
22233
Title :
Rolling Optimization of Wind Farm and Energy Storage System in Electricity Markets
Author :
Huajie Ding ; Zechun Hu ; Yonghua Song
Author_Institution :
Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
Volume :
30
Issue :
5
fYear :
2015
fDate :
Sept. 2015
Firstpage :
2676
Lastpage :
2684
Abstract :
Intraday energy markets have been established in some power markets mainly because of large-scale wind power integration. Inspired by the Spanish power market, this paper proposes a modified market design which contains day-ahead and intraday energy bidding sections to better accommodate stochastic wind energy. Then coordinated operation of the wind farm (WF) and energy storage system (ESS) is studied. Rolling stochastic optimization formulations for day-ahead, intraday biddings and real-time operations are put forward to obtain the optimal bidding strategy of WF-ESS union in each bidding section to maximize its overall profit. Case studies and sensitivity analyses are carried out on a union of WFs and a pumped storage plant (PSP). Simulation results show that the proposed rolling optimization method can effectively utilize the updated wind power forecast data and regulation capability of ESS, and thus increase profit for the union prominently.
Keywords :
energy storage; load forecasting; optimisation; power markets; wind power plants; ESS; PSP; electricity markets; energy storage system; intraday energy markets; modified market design; pumped storage plant; regulation capability; rolling optimization; rolling stochastic optimization formulations; sensitivity analyses; wind farm; wind power forecast data; Equations; Mathematical model; Optimization; Power markets; Real-time systems; Wind forecasting; Wind power generation; Energy storage system; intraday bidding; pumped storage plant; rolling optimization; wind farm;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2014.2364272
Filename :
6942257
Link To Document :
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