基于积温效应和优化支持向量机的短期电力负荷预测

Short-term electric power load forecasting based on accumulated temperature effect and optimized support vector machine

从积温效应的表现形式出发,提出一种考虑积温效应的优化支持向量机负荷预测方法。在充分研究积温效应2种表现形式的基础上,建立温度修正模型,同时为进一步提高预测精度,采用优化支持向量机预测负荷。最后借助江苏某地区的历史数据,采用最小二乘法求解积温效应参数、修正温度,并将修正之后的结果代入预测方法中,结果表明预测精度较高,具有一定的应用价值。

The load forecast using optimized support vector machine was proposed based on accumulated temperature effect. The correction model of temperature was established based on study of two forms of accumulated temperature effects. In order to improve prediction accuracy, optimized support vector machine was adopted to forecast load. Finally, with the data of a region in Ji- angsu as history data, least squares was adopted to obtain optimal parameters, and then the correction of temperature was used into the above method to forecast load. The results show high prediction accuracy and have good prospect.