电测与仪表2026，Vol.63Issue(4)：152-162,11.DOI:10.19753/j.issn1001-1390.2026.04.016
面向新型配电系统的光伏充电站负荷预测方法研究
Research on load forecasting method of photovoltaic charging station for novel distribution system
摘要
Abstract
In the novel power distribution system,photovoltaic(PV)charging stations have attracted much atten-tion as a typical distributed resource aggregation form.Since both distributed PV generation and charging loads are characterized by randomness and volatility,the load forecasting task of PV charging stations is particularly complex.In this paper,considering the dynamic impact of PV charging station access on the regional load profile,a PV char-ging station load forecasting method based on multi-layer limit learning machine and quantile regression theory is proposed.Firstly,the factors affecting the load of PV charging station are feature extracted and key feature quanti-ties are extracted.Secondly,combined with the quantile regression algorithm,a multi-layer kernel limit learning machine deep neural network model is constructed to realize the load interval prediction of PV charging station un-der different confidence levels,and the improved sparrow optimization algorithm is used for the parameter optimiza-tion and the optimal model is selected for the load prediction.Finally,the load data of a photovoltaic charging sta-tion in a northern region of China is selected for example analysis.The results demonstrate that the proposed PV charging station load prediction method oriented to the novel distribution system achieves satisfactory forecasting performance and enables more accurate acquisition of load forecasting information.关键词
新型配电系统/光伏充电站/分位数回归/多层极限学习机/区间预测Key words
novel distribution system/PV charging station/quantile regression/multi-layer extreme learning ma-chine/interval prediction分类
信息技术与安全科学引用本文复制引用
庞欢,何思源,郑子东,王雯靓,曹楠,王宇蛟..面向新型配电系统的光伏充电站负荷预测方法研究[J].电测与仪表,2026,63(4):152-162,11.基金项目
国家电网有限公司科技资助项目(2023YF-138) （2023YF-138）
