摘要
传统电力系统能源能耗分配算法偏差大,分配均衡性较差,提出一种基于DCNN的电力系统能源能耗分配算法。该算法对电力系统能源能耗数据实施预处理,根据预处理结果,基于深度卷积神经网络构建电力系统能源能耗分配模型;采用遗传算法优化该分配模型汇总的阈值与连接权值,并连接阈值与权值,作为遗传算法的染色体,执行编码二进制操作,将实际电力系统能源能耗值作为适应度函数,实现基于DCNN的电力系统能源能耗分配算法。实验结果表明,所提算法分配均衡性较好,能够实现电力系统能源能耗的快速分配。
Traditional power system energy consumption allocation algorithm has a large deviation and poor balance.This paper proposes a power system energy consumption allocation algorithm based on DCNN.The algorithm would conduct pre-process to energy consumption data and according to the results,a power system energy consumption allocation model is constructed based on deep convolution neural network.The genetic algorithm is used to optimize the threshold and connection weight of the distribution model,and the threshold and connection weight are used as the chromosome of the genetic algorithm.The coding binary operation is performed,and the actual power system energy consumption value is used as the fitness function to realize the power system energy consumption distribution algorithm based on DCNN.The experiment results show that the proposed algorithm has a good distribution balance and can realize the fast distribution of power system energy consumption.
作者
高丽芳
连阳阳
李启蒙
GAO Li-fang;LIAN Yang-yang;LI Qi-meng(Information and Communication Operation Inspection Center,State Grid Hebei Information&Telecommunication Branch,Shijiazhuang 050000,China)
出处
《信息技术》
2022年第9期106-111,117,共7页
Information Technology
关键词
深度卷积神经网络
电力系统
能源能耗分配
傅里叶变换
遗传算法
Deep Convolution Neural Network
power system
energy consumption distribution
Fourier Transform
genetic algorithm
