Optimized scheduling of Distribution Network with Distributed Generation Based on Coronavirus Herd Immunity Optimizer Algorithm

doi:10.16182/j.issn1004731x.joss.22-0882

Abstract

Abstract:

Following the large-scale entry of distributed new energy into the network, the uncertainty factor of the distribution network increases significantly, and the difficulty of reactive power optimization scheduling increases accordingly. Traditional optimization solutions have many limitations and shortcomings, and a dynamic reactive power optimization scheme for active distribution networks based on a multi-scenario approach is proposed. The mathematical modeling is carried out separately for the uncertainty of new energy and load, and the multi-scenario method is used to transform the uncertainty problem into a deterministic problem. A mathematical model is constructed on the distribution network side to pursue the integrated optimal value of the expected cost of network loss and reactive power compensation equipment regulation, and the coronavirus herd immunity optimizer is used to solve it. The results show that the optimization scheme obtained from the algorithm can effectively save the distribution network operation cost and reduce the network loss.

Key words: distribution network, coronavirus herd immunity optimizer, reactive power optimization, power system simulation

CLC Number:

TP391.9

Wu Xiaomeng, Yuan Rongze, Li Yingliang, Zhu Qi. Optimized scheduling of Distribution Network with Distributed Generation Based on Coronavirus Herd Immunity Optimizer Algorithm[J]. Journal of System Simulation, 2023, 35(12): 2692-2702.

Figures/Tables 9

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