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基于粒子群优化的最优负荷恢复算法 被引量:30

Optimal Load Restoration Based on Particle Swarm Optimization
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摘要 建立了考虑冷负荷特性的最优负荷恢复模型,考虑了系统的频率、电压和发电机有功出力等动态约束条件,以确保在恢复尽可能多负荷的同时,使系统维持合理的运行频率和网络电压水平等。利用PSS/E软件提供的二次开发语言IPLAN,引入粒子群优化算法对所建的最优负荷恢复模型进行求解,并采用罚函数法对动态约束条件进行处理,可以快速求得在满足系统安全稳定约束条件下可恢复的最大负荷量及负荷位置。算例分析验证了该方法的有效性。 The optimal load restoration model concerning cold load pickup is formulated as an optimization problem subjected to the system operation constraints including frequency, voltage and generation output, so that the maximum load may be picked up when maintaining reasonable frequency and voltage profiles. With IPLAN programming language provided by PSS/E, particle swarm optimization algorithm is applied to solve the proposed optimization problem. In addition, penalty function is introduced to handle system operation constraints. The proposed method is able to determine the load positions and amounts that can be picked up without disturbing system security and stability. Simulation is performed on a test system and the results demonstrate the effectiveness of the proposed method.
作者 程改红 徐政
出处 《电力系统自动化》 EI CSCD 北大核心 2007年第16期62-65,74,共5页 Automation of Electric Power Systems
关键词 故障恢复 冷负荷恢复 最优负荷恢复 粒子群优化 罚函数 fault restoration cold load pickup optimal load restoration particle swarm optimization penalty function
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参考文献13

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