Research on the optimisation strategy of short-circuit current limitation based on quantum genetic algorithm

The Journal of Engineering

Mingxing Guo¹  Weidong Qiao¹  Fei Fei¹  Jianlin Yang¹  Yuan Ji¹  Mengyao Zhang¹ 

[1] State Grid Shanghai Electric Power Company Economic Research Institute;

关键词: genetic algorithms;    power grids;    current limiters;    short-circuit currents;    short-circuit current limitation;    short-circuit current limiting measure configuration optimisation;    urban power grid expansion;    power grid scale reduction;    economic costs;    current-limiting performance;    quantum genetic algorithm-based solving method;    multiobjective model;   

DOI  :  10.1049/joe.2018.8785

来源: DOAJ

【 摘 要 】

With the expansion of urban power grid, short-circuit current issue becomes more important. This study proposes an effective approach to optimise short-circuit current limiting measure configuration. Before applying short-circuit current limiting measures, the Ward equivalence is utilised to reduce power grid's scale so as to reduce the computational work in short-circuit current limiting measure configuration optimisation. In order to balance the current-limiting performance and the economic costs of short-circuit current limiting measures, a multi-objective model for optimising short-circuit current limiting measure configuration is proposed. A quantum genetic algorithm-based solving method for the optimisation model is proposed. Finally, the proposed approach is verified by the simulations on an actual power grid.

【 授权许可】

Unknown