Multi-objective Fuzzy Chance Constrained Optimal Reactive Power Flow Based on Credibility Theory
Liu Wenxue1,Liang Jun1,Yun Zhihao1,Niu Rui2,Chu Zhuangzhuang1
1.Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan 250061 China 2.Nanjing Power Supply Company Nanjing 210019 China
Abstract Nowadays,large-scale intermittent powers are connected to the grid,and their uncertainty brings great impact to the reactive power optimization.Considering the uncertainty of intermittent powers and loads,trapezoidal fuzzy parameters are used to express the intermittent powers’ output and the load.Then a fuzzy chance constrained reactive power optimization model including multi-fuzzy parameters combined with credibility theory and fuzzy chance constrained programming is established,which is an improvement upon traditional deterministic optimal reactive power model.The fuzzy objective function and chance constraints’ credibility are solved through fuzzy power flow.The multi-objective optimization is converted to a single-objective optimization using target membership functions and interactive satisfaction.Then the bat algorithm is used to solve the model.Numerical results show that the proposed fuzzy chance constrained multi-objective reactive power optimization model and corresponding algorithm are suitable for voltage control and reactive power optimization in the case that the intermittent power output and load are expressed by fuzzy parameters.
Liu Wenxue,Liang Jun,Yun Zhihao等. Multi-objective Fuzzy Chance Constrained Optimal Reactive Power Flow Based on Credibility Theory[J]. Transactions of China Electrotechnical Society, 2015, 30(21): 82-89.
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2015, Vol. 30 
