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

Abstract

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.

Keywords

• 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