首页|基于GA和BP神经网络的配电线损计算研究

基于GA和BP神经网络的配电线损计算研究

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为了更加精准地计算配电线损,提出了基于遗传算法(GA)和反向传播(BP)神经网络的配电线损计算模型.利用 日电能消耗量和月电能消耗量作为原始数据,运用归一化和主成分分析(PCA)方法分别对原始电能消耗数据进行降维处理.通过GA优化BP神经网络参数,并使用完成训练的BP神经网络实现配电线路损耗的计算.基于某地区217条配电线路的实验结果表明,所提出的混合方法(GA&BP)的精确度优于其他线损计算方法.
Research on Calculation of Distribution Line Loss Based on GA and BP Neural Network
In order to calculate the distribution line loss more accurately,a distribution line loss calculation model based on ge-netic algorithm(GA)and back propagation(BP)neural network is proposed.Using the daily power consumption and the monthly power consumption as the original data,the normalization and principal component analysis(PCA)methods are used to reduce the dimension of the daily power consumption and the monthly power consumption respectively.The parameters of BP neural network are optimized by GA,and the loss calculation of distribution line is realized by using the trained BP neural network.The experimental analysis of 217 distribution lines in a certain area shows that the accuracy of the proposed hybrid method(GA&BP)is better than other line loss calculation methods.

line lossfeature extractionBP neural networkgenetic algorithmprincipal component analysis

吕冰、韩桂芳

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国网冀北电力有限公司信息通信分公司,北京 100053

北京博望华科科技有限公司,北京 100053

线损 特征提取 BP神经网络 遗传算法 主成分分析

2024

微型电脑应用
上海市微型电脑应用学会

微型电脑应用

CSTPCD
影响因子:0.359
ISSN:1007-757X
年,卷(期):2024.40(1)
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