Dispatching Method for Large-scale Electric Vehicles Connecting to Distribution Network Considering Multiple Uncertainties

被引：0

作者：

Li J. ^{[1
]}

Feng H. ^{[2
]}

Chen X. ^{[3
]}

Zhang H. ^{[2
]}

Zhan Z. ^{[4
]}

Xu Y. ^{[1
]}

机构：

[1] Tsinghua Shenzhen International Graduate School, Shenzhen

[2] Lishui Power Supply Company of State Grid Zhejiang Electric Power Co., Ltd., Lishui

[3] State Grid Zhejiang Electric Power Co., Ltd., Hangzhou

[4] Electric Power Research Institute of State Grid Zhejiang Electric Power Co., Ltd., Hangzhou

来源：

Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2024年 / 48卷 / 07期

关键词：

distribution network; distributionally robust optimal model; electric vehicle (EV); joint chance constraint; optimal Bonferroni approximation method; risk management; uncertainty;

D O I：

10.7500/AEPS20230830009

中图分类号：

学科分类号：

摘要：

The escalating scale of electric vehicles (EVs) and renewable energy introduces uncertainties, posing severe challenges to the safe operation of distribution networks. In order to comprehensively consider multiple uncertainties and balance the operation cost with the system reliability, firstly, an EV-distribution network charging and discharging dispatching model based on the distributionally robust joint chance constrainted model is proposed. This model effectively manages the overall system reliability by jointly constraining nodal voltages, branch power, and reserve demand. Then, to solve the model, the joint chance constraint problem is transformed into a mixed integer quadratic programming model based on the optimized Bonferroni approximation method. Notably, the risk level is also treated as a decision variable. Subsequently, the effectiveness and scalability of the proposed model are verified across various power systems. The results demonstrate that the proposed model overcomes the problems of classical stochastic and robust optimization, effectively balancing cost and reliability with high computational efficiency and good scalability. The model achieves approximately a 6.5% cost reduction compared to the Bonferroni approximation method. © 2024 Automation of Electric Power Systems Press. All rights reserved.

引用

页码：138 / 146

页数：8

共 25 条

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