南方电网技术2016，Vol.10Issue(10)：37-42,6.DOI:10.13648/j.cnki.issn1674-0629.2016.10.006
基于小波去噪和决策树的个性化大用户负荷预测
Wavelet De-noising and Decision Tree Based Load Forecasting of Large Consumers
摘要
Abstract
Having a better understanding of the customs of consumers'electricity consumption and the accurate load forecasting of in-dividual consumer are of great significance to demand response implement and high efficient power system operation. Firstly the load characteristics of large consumers are analyzed,and it is pointed out that the load profiles of large consumers have characteristics such as large in volume and wide in coverage,variant in load features,highly short-term correlative with historic load,notable in fluctua-tion,and without clear periodic characteristic. According to these characteristics,a wavelet de-nosing and decision tree based method for pattern extraction and load forecasting is proposed. The method mines data of consumer's historical load and extracts their utiliza-tion patterns,then personalizes loads forecasting of consumers based on different utilization patterns. Case studies on 50 typical large consumers in a province of China show that the proposed method is superior to other forecasting methods in accuracy.关键词
大用户/负荷预测/小波去噪/决策树/模式挖掘Key words
large consumers/load forecasting/wavelet de-noising/decision tree/pattern extraction分类
信息技术与安全科学引用本文复制引用
罗敏,程将南,王毅,林国营,朱文俊,阙华坤..基于小波去噪和决策树的个性化大用户负荷预测[J].南方电网技术,2016,10(10):37-42,6.基金项目
中国南方电网公司科技项目（GD-KJXM-20150902）。@@@@Supported by the Technical Projects of China South-ern Power Grid （）
