张沈习;程浩忠;李珂;

• 1:电力传输与功率变换控制教育部重点实验室(上海交通大学)

摘要(Abstract)：

考虑到负荷和风力发电机组(wind turbine generator,WTG)之间存在定的负相关性,文章首先采用拉丁超立方采样(Latin hypercube sampling,LHS)技术和Cholesky分解法排序产生相关性样本,然后以规划期内总成本小为目标,建立了多阶段WTG选址定容机会约束规划模型,并采用模糊自适应遗传算法(fuzzy adaptive genetic algorithm,FAGA)进行求解。在FAGA中,设计了种新的模糊逻辑控制器,使得算法在迭代过程中能够动态调整控制参数,增加算法对解空间的搜索能力,从而克服了基本遗传算法容易陷入局部优、收敛速度慢等缺点。33节点配电网算例的仿真分析表明,在进行WTG选址定容规划时不能忽略负荷和WTG之间的相关性。同时,算例仿真结果也验证了FAGA在求解规划模型时的高效性。

关键词(KeyWords)： 配电网;风力发电机组;多阶段;选址定容;相关性;模糊自适应遗传算法

Abstract:

Keywords:

基金项目(Foundation): 国家重点基础研究发展计划资助项目(973项目)(2009CB219703);; 国家自然科学基金资助项目(51261130473)~~

作者(Author): 张沈习;程浩忠;李珂;

Email:

DOI: 10.13335/j.1000-3673.pst.2014.01.009

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