DocumentCode :
1944544
Title :
A stochastic programming framework for optimal storage bidding in energy and reserve markets
Author :
Akhavan-Hejazi, Hossein ; Mohsenian-Rad, Hamed
Author_Institution :
Dept. of Electr. Eng., Univ. of California at Riverside, Riverside, CA, USA
fYear :
2013
fDate :
24-27 Feb. 2013
Firstpage :
1
Lastpage :
6
Abstract :
This paper focuses on a scenario where a group of independently-operated investor-owned storage units seek to offer both energy and reserve in the day-ahead as well as the hour-ahead markets. We are particularly interested in the case when a significant portion of the power generated in the grid is from wind and other intermittent renewable energy sources. In this regard, we formulate a stochastic programming framework to choose optimal energy and reserve bids for the storage units. Our design takes into account the fluctuating nature of the market prices due to the randomness in the renewable power generation availability. We show that the formulated stochastic program can be converted into a convex optimization problem and therefore it can be solved efficiently. Our simulation results show that our design can assure profitability of the private investment on storage units. In particular, our design results in much higher profit compared to a similar but deterministic design that simply uses the expected values of the price parameters.
Keywords :
convex programming; energy storage; investment; power generation economics; power generation reliability; power grids; power markets; pricing; profitability; stochastic programming; wind power plants; convex optimization problem; deterministic design; energy market; hour-ahead market; independently-operated investor-owned storage unit; intermittent renewable energy source; market price; optimal storage bidding; power generated grid; private investment; profitability; renewable power generation availability; reserve market; stochastic programming framework; wind power plant; Availability; Energy storage; Generators; Optimization; Stochastic processes; Wind farms; Wind power generation; Independent storage systems; energy and reserve markets; stochastic optimization; wind power integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Smart Grid Technologies (ISGT), 2013 IEEE PES
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4673-4894-2
Electronic_ISBN :
978-1-4673-4895-9
Type :
conf
DOI :
10.1109/ISGT.2013.6497826
Filename :
6497826
Link To Document :
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