广东电力2023，Vol.36Issue(11)：122-129,8.DOI:10.3969/j.issn.1007-290X.2023.11.013
基于改进人工鱼群算法的主动配电网日前两阶段优化调度
Two-stage Day-ahead Optimal Dispatching of Active Distribution Network Based on Improved Artificial Fish Swarm Algorithm
摘要
Abstract
With the increasing penetration of distributed generation(DG),traditional thermal power units are gradually being replaced by clean energy.In order to reduce the impact of new energy access on the economic operation and stable operation of the system,this paper proposes a two-stage model of active distribution network(ADN)day-ahead optimal dispatching.The first stage is the economic dispatching stage,in which the unit combination of DG,contract electricity purchase from large power grid and IL reduction is determined according to the time-of-use electricity price,fuel cost of DG source,and the cut-off price of the signed interruptible load(IL)for economic dispatching.The second stage is the reactive power optimization stage.On the basis of the economic dispatching results in the first stage,a reactive power optimization model that comprehensively considers the active power loss,voltage quality and voltage stability margin of the system is established by adjusting the output of DG and reactive power compensation devices.For the proposed optimization model,a cross feedback artificial fish swarm algorithm(CFAFSA)based on the idea of variable separation is proposed for solving.The algorithm realizes the decoupling of real variables and integer variables,reduces the dimensions of variables,and greatly improves the convergence speed and global optimization ability of the algorithm.The simulation of IEEE 33 bus active distribution system verifies the effectiveness of the model and the rapidity of the algorithm.关键词
分布式电源/主动配电网/经济调度/无功优化/人工鱼群算法Key words
distributed generation/active distribution network/economic dispatching/reactive power optimization/artificial fish swarm algorithm分类
信息技术与安全科学引用本文复制引用
刘洪波,高旭升,刘庸..基于改进人工鱼群算法的主动配电网日前两阶段优化调度[J].广东电力,2023,36(11):122-129,8.基金项目
国家电网有限公司总部管理科技项目(5100-202226021A-1-1-ZN) （5100-202226021A-1-1-ZN）
