电力系统保护与控制Issue(22)：128-133,6.
基于改进k-均值聚类的负荷概率模型
Probabilistic load model based on improved k-means clustering algorithm
摘要
Abstract
To avoid the difficulty of choosing initial cluster centers and clustering number for the k-means algorithm, an improved k-means clustering algorithm is proposed to build multistep load model from the hourly load data. The extended probabilistic load model considering bus load uncertainty and correlation is built. RBTS and IEEE RTS79 reliability test system is used to validate the proposed load model. Case studies show that the result based on proposed load model has high accuracy and it saves the calculation time when adopting the state sampling method;the uncertainty and correlation of bus loads have great effect on the adequacy indices of generating system. The proposed load model is helpful for the generation and composite system’s reliability assessment.关键词
k-均值聚类/层次聚类/负荷模型/不确定性/相关性Key words
k-means algorithm/hierarchical clustering/load model/uncertainty/correlation分类
信息技术与安全科学引用本文复制引用
陈凡,刘海涛,黄正,张雪娇..基于改进k-均值聚类的负荷概率模型[J].电力系统保护与控制,2013,(22):128-133,6.基金项目
南京工程学院科研基金项目（QKJA2011003）；江苏省教育厅自然科学基金项目（11KJB470008）；南京工程学院大学生科技创新基金项目 （）
