DocumentCode :
3760568
Title :
A study on short-term trading and optimal operation strategy for virtual power plant
Author :
Chunfa Dong;Xin Ai;Shuai Guo;Kunyu Wang;Yiran Liu;Le Li
Author_Institution :
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing, China
fYear :
2015
Firstpage :
2672
Lastpage :
2677
Abstract :
A virtual power plant (VPP) model, which consists of a wind power plant, interruptible loads, a pumped storage plant and a gas turbine, is built considering the uncertainty of the power output of renewable energy sources (RES) as well as the participation of demand response (DR) resources. Multi-scenario method is used to deal with the uncertainty of day-ahead market price and power output of wind power plant. A short-term trading model, which is based on multi-stage stochastic programming with the objective of maximization of VPP bidding profits in day-ahead market combined with penalty in balancing market, is constructed considering the characteristic that the uncertainty of stochastic variables reduces when time approaches. It is shown that the model constructed could notably promote the certainty gain of VPP.
Keywords :
"Stochastic processes","Decision support systems","Uncertainty","Programming","Optimization","Wind power generation"
Publisher :
ieee
Conference_Titel :
Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2015 5th International Conference on
Type :
conf
DOI :
10.1109/DRPT.2015.7432700
Filename :
7432700
Link To Document :
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