基于动态权重模型组合的短期区域净负荷预测方法  

Short-term Regional Net Load Forecasting Method Based on Dynamic Weight Model Combination

作　　者：甘业平 白云龙 韩号 刘丽新 GAN Yeping;BAI Yunlong;HAN Hao;LIU Lixin(State Grid Anhui Electric Power Co.,Ltd.,Hefei 230022,Anhui Province,China;Beijing Tsingsoft Technology Co.,Ltd.,Changping District,Beijing 100085,China)

机构地区：[1]国网安徽省电力有限公司,安徽省合肥市230022 [2]北京清软创新科技股份有限公司,北京市昌平区100085

出　　处：《电力信息与通信技术》2025年第3期17-24,共8页Electric Power Information and Communication Technology

基　　金：国网安徽电力2023售电市场智能分析预测系统优化与完善-设计开发实施项目(6G120B230002)。

摘　　要：净负荷预测对以新能源为主体的新型电力系统的运行控制有重要意义。为综合多种预测模型优势,进一步提升预测精度,文章提出了基于动态权重模型组合的短期区域净负荷预测方法。从差异性和关联性2个维度评价模型预测结果的可信度,提出了基于信息熵的时序不确定性评价方法和基于灰色关联度的代表性评价方法。通过模型动态权重的加权组合,得到基线负荷、分布式光伏功率和净负荷预测结果。所提方法的预测精度提高了1.44%~1.82%。Net load forecasting is of great significance for the operation and control of a new type of power system dominated by new energy.This paper proposes a short-term regional net load forecasting method based on a combination of dynamic weight models.The reliability of multiple model predictions evaluated from the dimensions of difference and correlation,and a time series uncertainty evaluation method based on information entropy and a representative evaluation method based on grey correlation degree are proposed.Based on the dynamic weight model combination,the predicted results of baseline load,distributed photovoltaic power generation,and net load are obtained.The proposed method significantly improves the prediction accuracy,with an accuracy increase of 1.44%~1.82%.

关 键 词：净负荷预测 组合预测 动态权重模型 新型电力系统 

分 类 号：TM715[电气工程—电力系统及自动化] TP18[自动化与计算机技术—控制理论与控制工程]