电力系统自动化2017，Vol.41Issue(19)：59-65,7.DOI:10.7500/AEPS20161222001
基于主成分分析的用电模式稳定性分析
Stability Analysis of Consumption Mode Based on Principal Component Analysis
摘要
Abstract
Consumption mode stability analysis (CMSA) is the precondition of load forecasting,the essence of which is to judge the similarity of a customer's consumption features in different historical time periods.Extracting consumption features from data of a long time period reduces the feasibility and accuracy of CMSA,using the short-time data might also be of low accuracy because daily consumption data are influenced by random factors.A method is therefore proposed to extract the customers' consumption modes by principal component analysis and taking daily consumption coefficients and daily consumption volatility as original consumption features.The stability of consumption mode is further judged by the Euclidean distance between the factor loading vectors of the principal components in two historical periods.A numerical example is provided by a residential community.Results show that the monthly consumption forecast accuracy is apparently different from the consumers in stable and unstable consumption modes judged by the proposed method and there is significant positive correlation between the similarity distance and the forecast error.It's also concluded that proper data period is of utmost importance to the feasibility and accuracy of CMSA.It seems 16 weeks will be appropriate for the CMSA problem.关键词
用电模式稳定性/主成分分析/相似性判定/负荷预测Key words
stability of consumption mode/principal component analysis/similarity judgment/load forecasting引用本文复制引用
牟婷婷,陆微,王兰君,辛洁晴..基于主成分分析的用电模式稳定性分析[J].电力系统自动化,2017,41(19):59-65,7.基金项目
国家自然科学基金资助项目(51337005) （51337005）
国家电网公司科技项目(5209141500QW).This work is supported by National Natural Science Foundation of China (No.51337005) and State Grid Corporation of China (No.5209141500QW). （5209141500QW）
