基于BP神经网络的配网线损研究

Research on Line Loss of Distribution Network Based on BP Neural Network

配网线损是电力系统运行中存在的一个重要问题,对于电力公司的经济效益和社会影响有着极大的影响。传统的线损计算方法存在很多局限性,难以准确预测线路的损耗情况。为了解决这一问题,提出了一种基于反向传播(Back Propagation,BP)神经网络的配网线损研究方法。通过收集配电变压器的输入电量、输出电量和线路损耗等数据建立BP神经网络模型,利用模型预测线路损耗,通过实验验证方法的有效性,最后总结方法,提出未来的研究方向。

Distribution network line loss is an important problem in the operation of power system,which has a great impact on the economic benefit and social impact of power companies.The traditional line loss calculation method has many limitations,it is difficult to accurately predict the loss of the line.In order to solve this problem,a research method of distribution network line loss based on BP neural network is proposed in this paper.The Back Propagation(BP)neural network model is established by collecting the data of input power,output power and line loss of distribution transformer.The model is used to predict the line loss.The effectiveness of the method is verified by experiments.Finally,the method is summarized and the future research direction is put forward.