基于GA-PSO-BP神经网络的电网后评价项目电量预测模型

GA-PSO-BP Neural Network-based Predictive Model for Electricity in Post-grid-project Evaluation

介绍了电网项目后评价工作效益评价的主要内容及关键技术要点。提出了一种GA-PSO-BP神经网络算法,根据全省不同地区不同电压等级项目运行数据搭建基于GA-PSO-BP神经网络的电网后评价项目电量预测模型。以某500 kV电网输变电工程项目为例开展的电量预测实验表明,所提出的方法较传统方法偏差量小、精度高,具有一定工程实际价值。

This paper outlines main issues and key points of post-grid-project evaluation,and proposes a GA-PSO-BP neural network algorithm.It establishes a predictive model for electricity in post-grid-project evaluation based on the proposed algorithm according to operation data of grid projects with different voltage levels in different regions of the province.The proposed method has been proved by a case experiment on an actual 500 kV transmission project to have a smaller deviation and a higher accuracy compared to conventional methods,and hence a certain applicative value.