电力系统保护与控制2024，Vol.52Issue(8)：77-87,11.DOI:10.19783/j.cnki.pspc.231203
基于数据潮流模型的高比例光伏配电网三相不平衡优化
Three-phase unbalanced optimization of a distribution network with a high proportion of distributed photovoltaic energy based on a data-driven power flow model
摘要
Abstract
With the increasing penetration of distributed photovoltaic energy,the inherent three-phase unbalanced problem of a distribution network is becoming more serious.This brings adverse effects on power quality and economic operation of the system.In addition,a high proportion of photovoltaic leads to a more complex physical structure and operation mode of the distribution network,resulting in it being difficult to apply the current three-phase unbalanced optimization method that relies on precise topology and line parameters.Therefore,this paper proposes a three-phase unbalanced optimization method of a distribution network with a high proportion of photovoltaic based on a data-driven power flow model.First,a dual-stage attention-based recurrent neural network is used to establish the data-driven power flow model,and the functional relationship between the variables in the three-phase power flow constraint is fitted.At the same time,a graph feature embedding method is proposed to embed the partially known topology information into the model to improve the fitting accuracy.Secondly,the three-phase unbalanced optimization model is reconstructed based on a trained data-driven power flow model.Finally,the conditional gradient descent method is used to analyze the model,and a modified IEEE 33-node distribution network is taken as an example to verify the effectiveness of the proposed method.关键词
配电网三相不平衡/分布式光伏/潮流模型/数据驱动/深度神经网络Key words
three-phase unbalance of distribution network/distributed photovoltaic/power flow model/data-driven/deep neural network引用本文复制引用
高雪寒,高源,赵健,刘箭,刘兴业..基于数据潮流模型的高比例光伏配电网三相不平衡优化[J].电力系统保护与控制,2024,52(8):77-87,11.基金项目
This work is supported by the National Natural Science Foundation of China(No.51907114). 国家自然科学基金项目资助(51907114) （No.51907114）
上海市教育委员会"晨光计划"项目资助(19CG61) （19CG61）
