Wind storage power joint allocation based on the robust optimization method
DING Jia han, WANG Guan zhong, ZHANG Meng fan, ZENG Shu yun, HUANG Min xiang
(College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

Abstract: Aiming at the problem of wind power fluctuation and storage allocation in power grid planning, the components of the wind power generation efficiency and the cost of wind system were analyzed, and the optimization objective with the global economic in planning years considered was constructed from the point of view of power grid construction, operation and maintenance. The robust optimization method was used to quantify the minimum capacity of energy storage configuration and to establish the bi level programming model. The model is a mixed integer programming problem with random variables. The optimization problem was solved by genetic algorithm and robust linear programming theory. The effectiveness of the proposed model and solving method was tested in a Garver6 node system. The results indicate that wind storage joint allocation method bases on robust optimization theory can scientifically guide the selection of location and capacity of wind power and energy storage. The economic benefit of the scheme is stronger, and the scheme can combat wind power fluctuations effectively.

Key words: uncertainty; wind energy; energy storage; robust linear optimization; genetic algorithm