电力勘测设计Issue(7)：35-41,7.DOI:10.13500/j.dlkcsj.issn1671-9913.2025.07.005
基于DAAGA-BP神经网络的中长期电力负荷预测分析
Analysis of Medium-and Long Term Power Load Prediction Based on DAAGA-BP Neural Network
邱金鹏1
作者信息
- 1. 中国电力工程顾问集团西南电力设计院有限公司,四川 成都 610021
- 折叠
摘要
Abstract
Predicting power load is a traditional problem in the power grid.Effective peak load forecasting can economically and reasonably arrange the start and stop of generator units,maintain the safety and stability of the power system,under the premise of ensuring the normal production and life of society,reduce the cost of electricity generation,and effectively improve social and economic benefits.The characteristics of power load forecasting have been studied in detail,We proposed a DAAGA-BP neural network prediction model and conducted in-depth comparative analysis of multiple prediction algorithms.Through simulation calculations,comparing the fitted data with the actual load values,the predicted value curve is closer to the actual value curve.It has been proven that the model has adaptability and is generally feasible and effective when applied to power grid load forecasting analysis.关键词
负荷预测/神经网络模型/遗传算法Key words
load forecasting/neural network model/genetic algorithm分类
信息技术与安全科学引用本文复制引用
邱金鹏..基于DAAGA-BP神经网络的中长期电力负荷预测分析[J].电力勘测设计,2025,(7):35-41,7.
