摘要
在电力市场环境下,进行准确的电价预测对市场中的各参与者有极其重要的意义。提出一种基于数据挖掘中的相似搜索技术和加权回归技术的短期电价预测方法,该方法简单、方便,对临近日和相似搜索所得到的相似日的负荷-电价数据用加权回归进行电价预测。最后用美国加州电能交易所(CalPX)公布的真实数据得到的预测结果验证了该方法的有效性。
Accurate electricity price forecast is of great importance to the participants of power market.A short-term price forecast method is put forward,which is based on the data mining tech-niques of similarity search and weighted regression.It is very simple and convenient,in which the load-price data from the previous days and similar days are obtained by similarity search and the electricity price is then forecasted using weighted regression.A simulation on real electricity market data acquired from California PX proves its effectiveness.
出处
《电力自动化设备》
EI
CSCD
北大核心
2004年第1期42-45,共4页
Electric Power Automation Equipment
关键词
电力市场
电价预测
相似搜索
数据挖掘
electricity market
electricity price forecast
similarity search
data mining
