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| 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。 |
| 关键词: 电力市场 电价预测 相似搜索 数据挖掘 |
| DOI： |
| 分类号:TM73 F123.9 |
| 基金项目: |
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| Electricity price forecasting based on similarity search & weighted regression |
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LI Bang-yun1 YUAN Gui-chuan2 DING Xiao-qun1
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| Abstract: |
| 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. |
| Key words: electricity market,electricity price forecast,similarity search,data mining |
