基于CNN-TPA-GRU的电价预测模型研究与应用
Research and Application of Electricity Price Prediction Model Based on CNN-TPA-GRU
刘科 1王玲霞 1苗伊 1王梓霁 2尚虹霖2
作者信息
- 1. 内蒙古龙源新能源发展有限公司,内蒙古 呼和浩特 010000
- 2. 华北电力大学(保定),河北 保定 071003
- 折叠
摘要
文章介绍一种解决电力市场价格波动的电价预测方法.该方法利用卷积神经网络提取输入序列的局部特征,并降维处理.同时,应用时序模式注意力机制,考虑不同时间步之间的依赖关系,为每个时间步分配权重,优化门控循环单元的输入特征.该模型在TGE数据集上进行了验证,并与其他算法进行了比较,结果在各项评价指标上均达到最优,证实了其适应性和在电力现货市场中的可行性.
Abstract
This paper introduces a method of electricity price prediction to solve the fluctuation of electricity market price.In this method,Convolution Neural Networks are used to extract local features of input sequences and reduce dimensionality.At the same time,the Temporal Pattern Attention mechanism is applied to consider the dependencies between different time steps,assign weights to each time step,and optimize input characteristics of the Gate Recurrent Unit.The model is verified on TGE dataset,and compares with other algorithms,and reaches the optimal in each evaluation index,which confirmed its adaptability and feasibility in the power spot market.
关键词
时序模式注意力/循环神经网络/电价预测/卷积神经网络/GRUKey words
temporal pattern attention/Recurrent Neural Network/electricity price prediction/Convolutional Neural Network/GRU引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
维普
万方数据