基于差分进化算法和交叉算子的电力企业应急物资多目标分层调度方法
Multi-objective Hierarchical Scheduling Method for Emergency Power Supply in Power Enterprises Based on Differential Evolution Algorithm and Crossover Operator
胡梓锡 1耿笑冬 1霍晓娣 2刘双1
作者信息
- 1. 国网石家庄供电公司,石家庄 050000
- 2. 国网栾城区供电公司,石家庄 050000
- 折叠
摘要
为实现电力系统应急故障的高效抢修,降低故障风险,提出基于差分进化算法和交叉算子的电力企业应急物资多目标分层调度方法.该方法结合电力企业全局调度需求,确定电力企业应急物资多目标上层调度目标函数和下层调度目标函数,同时设计对应的约束条件;采用差分进化算法求解双层调度目标函数,并且为保证解的多样性和算法收敛性,引入进化过程信息优化算法变异算子的变异概率,以此保证目标函数的求解效果.测试结果显示:反世代距离和散布性分别在 0.034 和 0.28 以下;结合应急物资供应点位置进行应急物资调配路径规划;应急物资调度的公平性、资源覆盖满意度均在 0.92 以上;调度后,电力系统的风险固结函数结果均在 0.14 以下.
Abstract
In order to achieve efficient emergency repair of power system faults and reduce fault risks,a multi-objective hierar-chical scheduling method for emergency supplies in power enterprises based on differential evolution algorithm and crossover operator is proposed.This method combined the global scheduling needs of power enterprises to determine the multi-objective upper-level and lower-level scheduling objective functions for emergency supplies in power enterprises,while designing corre-sponding constraint conditions.We used differential evolution algorithm to solve the dual layer scheduling objective function.To ensure the diversity of solutions and algorithm convergence,we introduced evolutionary process information optimization algo-rithm to optimize the mutation probability of the mutation operator,thereby ensuring the effectiveness of solving the objective function.The test results show that the reverse generation distance and dispersion were below 0.034 and 0.28,respectively.Plan emergency material allocation paths based on the location of emergency material supply points and the fairness of emergen-cy material dispatch and satisfaction with resource coverage were both above 0.92.After scheduling,the risk consolidation function results of the power system were all below 0.14.
关键词
差分进化算法/交叉算子/电力企业/应急物资/多目标/分层调度Key words
differential evolution algorithm/cross operator/electric power enterprises/emergency supplies/multi-objective/hierarchical scheduling引用本文复制引用
出版年
2024
NETL
NSTL
万方数据