基于改进遗传算法的220 kV变电站限流调度策略研究

Study of Current-Limiting Scheduling Strategyfor 220 kV Substation Based on Improved Genetic Algorithm

220 kV变电站运行方式较复杂,且变电站限流调度具有多目标约束,运用传统的遗传算法难以找到最优的限流调度策略。提出了基于改进遗传算法的220 kV变电站限流调度策略。分析220 kV变电站的四种限流调度措施对导纳矩阵的影响。结合分析结果,建立限流调度策略效果模型和经济成本模型,并将两者相结合搭建220 kV变电站限流调度多目标优化策略。采用混沌映射、非支配排序和自适应函数的改进遗传算法进行多目标优化策略求解,所获取的最优解即为最优限流调度策略。结合最优策略,实现220 kV变电站限流调度。仿真试验结果表明,所提策略的限流调度效果更理想、电能损耗量更少。该策略对于变电站限流调度具有参考价值。

220 kV substation operation mode is more complex, and substation current-limiting scheduling has multi-objective constraints, it is difficult to find the optimal current-limiting scheduling strategy by using the traditional genetic algorithm.The 220 kV substation current-limiting scheduling strategy based on improved genetic algorithm is proposed.The effects of four types of current-limiting scheduling measures on the conductivity matrix of 220 kV substations are analyzed.The effect model and the economic cost model of current-limiting scheduling strategy are established by combining the results of the analysis to build a multi-objective optimization strategy of current-limiting scheduling for 220 kV substations by combining the both.The improved genetic algorithm with chaotic mapping, non-dominated sorting and adaptive function is used to solve the multi-objective optimization strategy, and the optimal solution obtained is the optimal current-limiting scheduling strategy.Combined with the optimal strategy, the current-limiting scheduling of 220 kV substation is realized.The simulation test results show that the proposed strategy has better current-limiting scheduling effect and less power loss.This strategy has reference value for current-limiting scheduling of substations.