Robust optimization of distributed generation in a microgrid based on grey target decision-making and multi-objective cuckoo search algorithm

被引:0
|
作者
Yang, Huanhong [1 ]
Wang, Jie [1 ]
Tai, Nengling [2 ]
Ding, Yutao [1 ]
机构
[1] School of Electrical Engineering, Shanghai University of Electric Power, Shanghai,200090, China
[2] Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai,200240, China
基金
中国国家自然科学基金;
关键词
Budget control - Decision making - Learning algorithms - Optimal systems - Pareto principle;
D O I
10.7667/PSPC180036
中图分类号
学科分类号
摘要
There are uncertainties in load demands and renewable energy outputs of wind turbine and photovoltaic. These factors bring great challenges to the stable operation of microgrids. In view of the characteristic, firstly, the uncertainty set of the constraints is constructed and the operating cost and the environmental cost are considered. Thus, the multi-objective robust scheduling model of the microgrid is built. Also, robust uncertainty budget is introduced to adjust the conservatism of the uncertainty set. Secondly, an improved and nonlinear multi-objective cuckoo search algorithm based on Pareto domination is used to solve the Pareto optimal solution set. Based on multi-objective grey target decision-making, the satisfactory solution is selected from the optimal solution set. Finally, the scheduling model for a small microgrid is established and solved. The simulation results are compared to verify the reliability and validity of the proposed method. © 2019, Power System Protection and Control Press. All right reserved.
引用
收藏
页码:20 / 27
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