应用聚类分析与非参数核密度估计的空间负荷分布规律

Spatial Load Distribution Based on Clustering Analysis and Non-Parametric Kernel Density Estimation

空间负荷预测是配电网规划的前提和基础。针对现有研究偏重对预测方法的理论创新和精度提升,缺乏对各地各类空间负荷分布规律研究的不足,提出一种基于聚类分析与非参数核密度估计的空间负荷分布规律研究方法。以浙江电网为例,对调研采集的空间负荷按城市发展类型、用地类型进行二级划分后,利用基于非参数核密度估计方法提取各类样本负荷密度的典型分布特征,结合实际对浙江11个城市的工业、商业、居住等多类空间负荷的分布规律进行分析研究,为配电网规划提供可靠支撑。

Spatial load forecasting is precondition and foundation for distribution network planning. Existing researches focus on theoretical innovation and accuracy improvement of forecasting method, neglecting load distribution research. Based on clustering analysis and non-parametric kernel density estimation, a method of spatial load distribution is proposed. Taking Zhejiang power grid as example, spatial load research samples are classified according to a two-level partition of urban development types and land use types. Then typical load density distribution characteristics are extracted in all kinds of samples using the proposed method. Finally, industrial, commercial, residential and other spatial load distribution patterns are analyzed, providing reliable support for distribution network planning.