短期负荷综合预测模型新算法

A Novel Comprehensive Prediction Algorithm for Short-Term Load Forecasting

本文结合马尔科夫校正算法对灰色理论模型加以改进,提出了一种改进灰色-马尔科夫的预测模型。将该模型运用到短期负荷预测中,并与指数平滑模型、人工神经网络模型的预测结果进行比较,结果表明运用改进后的灰色—马尔科夫预测模型可以大大提高预测精度。笔者在这三种预测方法的基础上,应用时变权系数法建立综合预测模型,对待预测日进行短期负荷预测。

This paper presents a grey-Markov prediction model that based on an improved grey theory model.The improved model takes Markov correction algorithm into consideration.The proposed grey-Markov prediction model shows a significant enhancement in terms of the prediction accuracy compared to the common exponential smoothing model and artificial neural network model schemes.In addition,for the purpose of predicting the short-term load,a comprehensive prediction model,which employing the time-varying weight coefficient algorithm,is established mainly according to the three prediction schemes.