| 改进自适应模糊C均值算法在负荷特性分类的应用 |
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| 引用本文： | 曾博,张建华,丁蓝,董军. 改进自适应模糊C均值算法在负荷特性分类的应用[J]. 电力系统自动化, 2011, 35(12): 42-46 |
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| 作者姓名： | 曾博 张建华 丁蓝 董军 |
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| 作者单位： | 1. 新能源电力系统国家重点实验室,华北电力大学,北京市102206
2. 华北电力大学经济与管理学院,北京市,102206 |
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| 摘 要： | 模糊C均值(FCM)算法是一种用于电力负荷特性分类的有效方法.针对传统FCM算法易陷入局部最优且对初始条件敏感的问题,文中提出了基于微分进化(DE)自适应优化的改进措施.相对于FCM算法的梯度最速下降寻优策略,改进算法利用DE多点随机并行搜索,对控制参数及非最优个体进行自适应调整,具有全局搜索能力强、鲁棒性高的特点.实际算例仿真表明,所述算法降低了负荷特性分类对初始值的依赖度,在不同聚类数目的条件下仍具有良好的性能,适用于实际电网滚动规划等对负荷特性分类精度要求更高的领域.
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| 关 键 词： | 负荷特性分类 微分进化算法 模糊C均值算法 自适应 电网规划运行 |
| 收稿时间： | 2010-08-26 |
| 修稿时间： | 2011-06-03 |
An Improved Adaptive Fuzzy C-means Algorithm for Load Characteristics Classification |
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| ZENG Bo,ZHANG Jianhu,DING Lan,DONG Jun. An Improved Adaptive Fuzzy C-means Algorithm for Load Characteristics Classification[J]. Automation of Electric Power Systems, 2011, 35(12): 42-46 |
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| Authors: | ZENG Bo ZHANG Jianhu DING Lan DONG Jun |
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| Affiliation: | ZENG Bo1,ZHANG Jianhua1,DING Lan1,DONG Jun2 (1.State Key Laboratory for Alternate Electrical Power System with Renewable Energy Sources,North China Electric Power University,Beijing 102206,China,2.School of Economics and Management,China) |
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| Abstract: | Fuzzy C-means(FCM) algorithm is effective for the power load characteristics classification.Since FCM algorithm is prone to fall into a local optimum zone and sensitive to the initial values,an improved algorithm is proposed based on differential evolution(DE) adaptive optimization.The improved algorithm uses random parallel search of DE to replace steepest descent gradient of FCM,and integrates an adaptive adjusting strategy for control parameters and non-optimal individuals to achieve strong global search... |
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| Keywords: | load characteristics classification differential evolution algorithm fuzzy C -means algorithm adaptiveness power grid planning and operation |
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