基于用电负荷的缺失数据插补方法研究

基于用电负荷的缺失数据插补方法研究
摘要:电力市场改革在我国开展以后，准确的负荷预测对于电力市场需求分析具有重要意义，而采集、统计过程中的缺失数据直接影响着电力负荷预测等数据分析的精度，为此对基于用电负荷的缺失数据插补方法展开了研究。首先选取了典型工商业用户，生成用电负荷曲线，按照拟合曲线特征，对用户负荷曲线进行分类。然后随机生成了每个用户10%缺失率下的不完整数据集，并利用均值插补、回归插补和期望最大化(expectation maximization，EM)插补方法补全缺失数据。最后对比了插补后数据集与原始数据集的数据情况，通过计算均方误差(mean square error，MSE)值比较并分析了插补效果。仿真结果验证了插补方法对于不同类别用电负荷的适用性与可行性。

Abstract：After the reform of power market has been carried out in China, accurate load forecasting is of great significance for power market demand analysis. And the missing data in the process of collection and statistics directly affects the accuracy of data analysis such as power load forecasting. Therefore, the missing data interpolation method based on electricity load was studied in this paper. Firstly the typical industrial and commercial users were selected to generate the power load curves. According to the characteristics of the fitting curves, the user load curves were divided into two categories. Then each user's incomplete data sets at 10% missing rate were randomly generated. And the missing data was supplemented by means of mean interpolation, regression interpolation and EM interpolation. Finally, the data sets after interpolation were compared with the original data sets, and the effect of interpolation was analyzed and compared by calculating mean square error (MSE). The simulation results verified the applicability and feasibility of the interpolation methods for different types of electrical loads.

标题：基于用电负荷的缺失数据插补方法研究
title:Research on Missing Data Interpolation Method Based on Electricity Load

作者：路昂
authors:LU Ang

关键词：数据插补,负荷预测,均值插补,回归插补,期望最大化(EM)插补,电力市场改革,
keywords:data interpolation,load forecasting,mean interpolation,regression interpolation,expectation maximization(EM) interpolation,electricity market reform,

发表日期：2020-09-21

2025-1-21 20:10 上传 基于用电负荷的缺失数据插补方法研究.pdf

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