摘要
为了解决主动配电网优化运行问题,给出了一种基于改进布谷鸟(Improved Cuckoo Search,ICS)算法的主动配电网(Active Distribution Network,ADN)优化调度方法。以ADN运行总成本最小为目标函数,综合考虑ADN系统运行约束,建立了ADN优化调度模型。利用动态调整发现概率和反向学习扰动策略对布谷鸟(Cuckoo Search,CS)算法进行改进,得到了搜索性能更强且求解精度更高的ICS算法。采用ICS算法对ADN优化调度模型进行求解,并与CS算法、粒子群(Particle Swarm Optimization,PSO)算法和遗传算法(Genetic Algorithm,GA)的收敛性能进行比较,结果表明,ICS算法的收敛迭代次数、收敛时间及ADN运行总成本分别为32次、7.2秒和100659.24元,均优于CS算法、PSO算法和GA算法等几种对比算法,验证了所提ADN优化调度方法的正确性和实用性。
An active distribution network(ADN)optimization scheduling method based on the improved cuckoo search(ICS)algorithm is proposed to optimize the operation of the active distribution network.Taking the minimum total operating cost of ADN as the objective function and considering the operational constraints of the ADN system,an active distribution network optimization scheduling model is established.By utilizing dynamic adjustment of discovery probability and reverse learning perturbation strategy,the cuckoo search(CS)algorithm was improved,resulting in an ICS algorithm with stronger search performance and higher solution accuracy.The ICS algorithm was used to solve the ADN optimization scheduling model,and the convergence performance of the ICS algorithm was compared with CS algorithm,particle swarm optimization(PSO),and genetic algorithm(GA).The results showed that the convergence iterations,convergence time,and total ADN running cost of the ICS algorithm were 32 times,7.2 seconds,and 100659.24 yuan respectively,which were superior to the comparative algorithms.This verified the correctness and practicality of the proposed ADN optimization scheduling method.
作者
范成武
刘胜
FAN Chengwu;LIU Sheng(Huangshi Power Supply Company of State Grid Hubei Electric Power Co.,Ltd.,Huangshi 435000,China)
出处
《安徽电气工程职业技术学院学报》
2024年第1期51-58,共8页
Journal of Anhui Electrical Engineering Professional Technique College
关键词
主动配电网
优化调度
改进布谷鸟算法
运行总成本
active distribution network
optimize scheduling
improved cuckoo bird algorithm
total operating cost
