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作 者:董飞飞[1] 刘涤尘[1] 吴军[1] 潘旭东[1] 王浩磊[1] 赵一婕[1] 宋春丽[1]
机构地区:[1]武汉大学电气工程学院,湖北省武汉市430072
出 处:《中国电机工程学报》2014年第16期2659-2667,共9页Proceedings of the CSEE
基 金:国家电网公司大电网重大专项资助项目课题(SGCC-MPLG029-2012);国家自然科学基金项目(51207114);中央高校基本科研业务费专项基金(2012207020207)~~
摘 要:构建核心骨干网架,对于有针对性地加强电网结构建设、提高电网抵御自然灾害能力、合理科学地进行差异化电网规划具有重要的指导作用。基于生存性指标体系,提出一种线路总长度最小、生存性综合指标最大的核心骨干网架构建方法,以网络连通性和电网安全运行为约束条件,采用引入余弦迁移模型、早熟判断机制以及变尺度混沌和柯西变异策略的改进生物地理学优化算法(improved biogeographybased optimization algorithm,IBBO)搜索最优骨干网架方案,并与传统的生物地理学优化算法(biogeography-based optimization algorithm,BBO)、粒子群算法(particle swarm optimization,PSO)、蚁群算法(binary ant colony algorithm,BACA)、遗传算法(genetic algorithm,GA)的搜索结果进行对比分析。仿真算例表明,所提方法准确有效,且具有收敛速度快和收敛精度高的优点。Constructing core backbone grid has instruction function for strengthening the construction of the grid structure, improving the ability of withstanding natural disasters, as well as realizing power grid's differentiation planning reasonably and scientifically. A method of constructing core backbone grid with the target of the smallest total line length and the largest integrated survivability index based on survivability index system was put forward with constraint conditions of network connectivity and power grid safe operation. The cosine migration model, the premature judgment mechanism, and the mutative scale of chaos and Cauchy mutation strategy were introduced into the improved biogeography-based optimization algorithm (BBO) to search for the optimal core backbone grid. Simulation results show that the proposed method is accurate and effective. Its convergence speed is faster and its convergence precision is higher than that of traditional BBO, particle swarm optimization (PSO), binary ant colony algorithm (BACA) and genetic algorithm (GA).
关 键 词:核心骨干网架 电网生存性 改进生物地理学优化算法 早熟判断机制 变异策略
分 类 号:TM71[电气工程—电力系统及自动化]
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