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面向电动汽车协调的两阶段输电系统运营商-配电系统运营商服务提供框架
Two-Stage TSO-DSO Services Provision Framework for Electric Vehicle Coordination
| 作者 | Yi Wang · Dawei Qiu · Fei Teng · Goran Strbac |
| 期刊 | IEEE Transactions on Power Systems |
| 出版日期 | 2024年12月 |
| 技术分类 | 电动汽车驱动 |
| 技术标签 | 储能系统 强化学习 |
| 相关度评分 | ★★★★★ 5.0 / 5.0 |
| 关键词 | 电动汽车 频率响应服务 电压支持 两阶段框架 强化学习算法 |
语言:
中文摘要
高比例可再生能源接入导致电力系统惯性下降,对频率响应服务的需求日益增加。电动汽车(EV)凭借车网互动(V2G)能力可为输电系统运营商(TSO)提供经济高效的频率调节服务,但其在参与频率支撑时可能引发电压安全问题,影响配电系统运营商(DSO)运行。为此,本文提出一种两阶段多电动汽车服务提供框架:第一阶段参与日前TSO-DSO频率备用调度;第二阶段在配电网中实时执行备用交付并支持电压调节。针对大规模EV与复杂环境,第二阶段采用去中心化调控范式,并设计通信高效的强化学习算法以降低多智能体训练的通信开销,同时保持策略性能。基于6节点输电网、33节点及69节点配电网的案例验证了该方法在频率与电压协同支持方面的有效性与可扩展性。
English Abstract
High renewable penetration has been witnessed in power systems, resulting in reduced system inertia and increasing requirements for frequency response services. Electric vehicles (EVs), owing to their vehicle-to-grid (V2G) capabilities, can provide cost-effective frequency services for transmission system operators (TSOs). However, EVs that are inherently connected to distribution networks may pose voltage security issues for distribution system operators (DSOs) when supporting TSO frequency. To coordinate both TSO frequency and DSO voltage, this paper proposes a two-stage service provision framework for multi-EVs. At stage one, EVs participate in day-ahead TSO-DSO interactions for frequency reserve schedules; at stage two, EVs make real-time dispatching behaviors in distribution networks for reserve delivery while supporting DSO voltage. Considering the potentially large EV number and environment complexity, a decentralized operation paradigm is introduced for real-time EV dispatches at stage two, while a communication-efficient reinforcement learning (RL) algorithm is proposed to reduce the communication overhead during large-scale multi-agent RL training without compromising policy performance. Case studies are carried out on a 6-bus transmission and 33-bus distribution network as well as a 69-bus distribution network to evaluate the effectiveness and scalability of the proposed method in enabling EVs for frequency service and voltage support.
S
SunView 深度解读
该两阶段TSO-DSO协调框架对阳光电源充电桩与储能业务具有重要应用价值。文章提出的去中心化强化学习算法可直接应用于阳光电源充电桩产品,实现V2G双向充放电时的频率-电压协同控制,避免频率支撑服务引发配网电压越限。该框架与PowerTitan储能系统的多层级调度架构高度契合:日前阶段可优化储能参与辅助服务市场的容量配置,实时阶段通过通信高效的多智能体算法降低ST系列储能变流器的通信带宽需求。特别是去中心化控制范式可增强阳光电源分布式储能集群的可扩展性,为构建输配协同的新型电力系统解决方案提供技术路径,提升iSolarCloud平台的智能调度能力。