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系统并网技术 充电桩 微电网 电压调节 并网逆变器 ★ 4.0

面向主动配电网电压支撑的移动充电解决方案多时间尺度运行优化:一种两阶段协同方法

Multi-Timescale Operational Optimization for Mobile Charging Solutions Considering Voltage Regulation Support for ADN: A Two-Stage Coordination Approach

作者 Zhijun Zhang · Tianjing Wang · Zhao Yang Dong · Christine Yip · Fengji Luo · Shuying Lai · Yuechuan Tao
期刊 IEEE Transactions on Sustainable Energy
出版日期 2025年6月
卷/期 第 17 卷 第 1 期
技术分类 系统并网技术
技术标签 充电桩 微电网 电压调节 并网逆变器
相关度评分 ★★★★ 4.0 / 5.0
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中文摘要

本文提出两阶段协同优化方法,协调移动充电机器人(MCR)与主动配电网(ADN)。第一阶段以帧为单位最大化MCR集群收益;第二阶段利用空闲MCR无功功率提供ADN电压支撑,降低网损。采用Lyapunov优化解耦有功/无功调度,兼顾经济性与电压安全。

English Abstract

To alleviate the pressure of traditional fixed charging methods, mobile charging solutions have emerged in recent years. This article presents a two-stage coordination approach for mobile charging robots (MCRs) and active distribution networks (ADN). In the first stage, we maximize the total revenue for the MCRs from providing charging services for electric vehicles (EVs) and interacting with the ADN within a frame-based time scale, where the duration of each frame is determined by the charging decisions of MCRs. Furthermore, we consider the long-term objectives of meeting the battery energy deficit constraint for each MCR, thereby improving their battery life. Lyapunov optimization is utilized to transform frame-based scheduling into an optimization problem within a specified time slot, simplifying the process of solving the optimization problem. To avoid affecting charging efficiency when MCRs interact with the power grid, we use the reactive power of free MCRs to provide voltage regulation support for the ADN, improving power quality and minimizing total network loss simultaneously. Decoupling active and reactive power in two stages ensures both the profitability of the MCRs cluster and the voltage security of the ADN, resulting in a win-win situation. The simulation results, based on the 18-bus and 51-bus distribution networks, confirm the effectiveness and superiority of the proposed approach.
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SunView 深度解读

该研究与阳光电源ST系列储能变流器(PCS)及iSolarCloud平台高度契合:MCR集群可类比为分布式柔性资源,其无功电压支撑能力可复用ST PCS的VSG/下垂控制与无功调节功能;iSolarCloud可扩展支持MCR集群调度与ADN协同优化。建议将相关算法集成至PowerTitan智能EMS中,提升光储充一体化电站对配网的主动支撑能力,并拓展至电动汽车聚合商服务场景。