Active Network Reconfiguration Based on Improved Chimp Optimization Algorithm
In order to better solve the problem of active network reconfiguration,this paper proposes an active network reconfiguration method based on improved chimp optimization algorithm(ICOA).Taking the system network loss,voltage offset index and load balance degree as the optimization objectives,a multi-objective reconfiguration model of active network is established,and the multi-objective is transformed into a single objective by using the weighted processing method.The chimp optimization algorithm(COA)is improved by using the nonlinear variation of convergence coefficient and the pinhole imaging learning strategy,and the ICOA with better optimization effect is obtained.The objective function is optimized by ICOA,and the effectiveness of the proposed method is verified by an example analysis.The results show that the system network loss,voltage offset index and load balance degree after ICOA reconfiguration decrease by 6.89％,56.82％and 45.76％respectively,and the economy and stability of active distribution network operation are improved comprehensively.
active network reconfigurationimproved chimp optimization algorithmdistributed generationfitness function
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