摘要
小波分析是一种新兴的数学工具 ,它能任意地提取短期负荷序列的细节。通过使用小波分析 ,可以在任何水平上分析短期负荷序列 ,它对信息成分采取逐渐精细的时域与频域处理 ,尤其对突发与短时的信息分析具有明显的优势。本文将小波分析引入了短期负荷预测 ,针对电力系统本身具有的负荷以天 ,周 ,年为周期发生波动的特点 ,使用周期自回归模型有选择的对分解序列进行预测 ,并对直接使用周期自回归 ( PAR)模型的预测结果及先使用小波分析处理的预测结果进行了比较 。
Wavelets analysis is a new mathematical tool which can abstract the details of the short term loading series at will. The short term loading series in any scale. In this way, the results of the short term loading forecast could be more accurate than the forecast results without using Wavelets analysis. This paper introduces the Wavelets analysis into the short term load forecast, and compares the forecasting results directly using Periodical auto regression (PAR) model with the results using Wavelets analysis before forecasting with PAR model. At the same time, A c program is also compiled to do a short term loading forecast with Wavelets analysis.
出处
《电力系统及其自动化学报》
CSCD
2003年第2期40-44,65,共6页
Proceedings of the CSU-EPSA
关键词
电力系统
短期负荷预测
小波分析
周期自回归模型
电网
Power system, Wavelets analysis, short term load forecasting, Periodical auto regression (PAR) model
