基于趋势指标与长短时记忆网络的电力市场日前电价预测

Day-ahead Electricity Price Forecasting of Power Market Based on Trend Index and Long Short Term Memory

摘要: 为提高电力市场日前电价的预测精度，提出一种基于趋势指标与长短时记忆网络（LSTM）的日前电价预测模型。首先，计算日前电价的随机指标（KDJ）与异同移动平均线指标（MACD），挖掘电价的内在规律信息；然后，将计算出的趋势指标与电价信息输入LSTM，对电力市场日前电价进行预测；最后，利用电力市场日前电价数据进行验证。算例分析表明该模型相比反向传播神经网络（BPNN）、LSTM和门控循环单元网络（GRU）等模型预测精度更高。

Abstract: In order to improve the forecasting accuracy of day ahead price in power market,a day ahead price forecasting model based on trend index and long-term and short-term memory neural network is proposed. Firstly,the KDJ index and MACD index of the day ahead electricity price are calculated,the inherent law information of electricity price is mined;Secondly,the calculated trend index and electricity price information are input into LSTM to forecast the day ahead electricity price in the electricity market;Finally,the experiment is carried out by using the electricity market day ahead price data. The example analysis shows that the prediction accuracy of the proposed model is higher than that of BPNN,LSTM and GRU.