集散遗传算法在厂级AGC负荷分配中的应用Application of Gathering-Scattering Genetic Algorithm to Load Distribution of AGC in Plant Level
方彦军;伍洲;王琛;
摘要(Abstract):
针对目前电网采用的自动发电控制(automatic generation control,AGC)方式的缺点,提出了采用发电厂级AGC方式来优化分配厂内各机组负荷,以实现发电成本最小。建立了以各台机组负荷为自变量、发电成本为因变量的多约束条件的厂级AGC负荷分配模型。应用提出的基于种群差异的集散遗传算法进行优化,速度快且精度高。它根据个体间的欧氏距离反映的差异度,通过离散操作提高种群的多样性,通过集合操作提高种群的收敛速度,避免了普通遗传算法早熟和收敛速度慢的缺点。仿真结果表明:基于集散遗传算法的厂级AGC节能效果好,运算时间短且能准确稳定地收敛到最优解。
关键词(KeyWords): 厂级AGC;集散遗传算法;负荷分配;优化调度
基金项目(Foundation): 国家自然科学基金资助项目(60772107)~~
作者(Author): 方彦军;伍洲;王琛;
Email:
DOI: 10.13335/j.1000-3673.pst.2010.07.024
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