基于映射遗传算法的日前电价估计方法
DAY AHEAD ELECTRICITY PRICE ESTIMATION METHOD BASED ON MAPPING GENETIC ALGORITHM
朱雅魁 1张文 2苏欣 1赵莎莎 1安亚刚1
作者信息
- 1. 国网河北省电力有限公司营销服务中心 河北 石家庄 050000
- 2. 北京中电普华信息技术有限公司 北京 100085
- 折叠
摘要
将卷积神经网络(Convolutional Neural Networks,CNN)与进化算法相结合提出一种日前电价估计方法.基于基因定位结果,选择、变异和交叉生成竞争个体;根据基因二进制位与CNN参数/超参数之间的映射关系,设计最优的CNN结构.以某电力市场为例,验证所提方法有效性.实验结果表明,与其他预测方法相比,所提算法具有较高的预测精度和较低的误差率.
Abstract
A day ahead electricity price estimation method is proposed by combining the convolutional neural networks(CNN)with evolutionary algorithm.Based on the results of gene mapping,competitive individuals were selected,mutated and crossed.The optimal CNN structure was designed according to the mapping relationship between gene bits and CNN parameters and hyper parameters.A power market was taken as an example to verify the effectiveness of the proposed method.Experimental results show that the proposed algorithm has higher prediction accuracy and lower error rate than other prediction methods.
关键词
卷积神经网络/深度学习/电价预测/遗传算法/节点边际电价Key words
Convolution neural network/Deep learning/Electricity price forecasting/Genetic algorithm/Location marginal price引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据