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基于雾计算的住宅聚合商与家庭需求响应及配电网分层协调——第二部分:数据传输架构与案例研究
Fog-Based Hierarchical Coordination of Residential Aggregators and Household Demand Response With Power Distribution Grids—Part II: Data Transmission Architecture and Case Studies
| 作者 | Hamid Reza Massrur · Mahmud Fotuhi-Firuzabad · Payman Dehghanian · Frede Blaabjerg |
| 期刊 | IEEE Transactions on Power Systems |
| 出版日期 | 2024年4月 |
| 技术分类 | 储能系统技术 |
| 技术标签 | 储能系统 户用光伏 |
| 相关度评分 | ★★★★ 4.0 / 5.0 |
| 关键词 | 家庭需求响应 住宅聚合商 配电网运营商 雾计算架构 分布式协调框架 |
语言:
中文摘要
第一部分提出了家庭需求响应(HDR)、住宅聚合商(RAs)与配电系统运营商(DSO)之间的分层协调方案。本文作为配套研究,提出一种新颖的三层雾计算架构,构建高效的协调框架数据传输网络。该通信架构涵盖终端设备、边缘雾节点和云服务器层,支持大规模物联网型需求响应用户的可靠数据采集。文中建模分析了时延与带宽需求,并在改进的IEEE 33节点系统上开展数值仿真。结果表明,所提架构在满足网络运行约束下,提升了RAs的收益与灵活性,降低了具备HDR能力用户的用电成本,同时增加了居民产消者的经济效益。
English Abstract
Part I of this two-part paper series designed a solution for hierarchical coordination among Household Demand Response (HDR), Residential Aggregators (RAs) and DSO. This companion paper presents a novel three-layer fog-based architecture to establish an efficient data transmission network for the proposed coordination framework. The envisioned communication architecture includes the end-device, edge fog nodes, and cloud-server layers, providing a reliable solution for data collection of large-scale IoT-based Demand Responsive (DR) customers. The time delay and required bandwidth for the proposed data transmission architecture are modeled. To trace the effectiveness and economic impacts of the proposed fog-based hierarchical HDR-RAs-DSO distributed coordination framework, we perform extensive numerical studies on an enhanced IEEE 33-Bus test system. Several simulations are performed to investigate the time delay and required bandwidth of the proposed data transmission architecture in various scenarios, where it is found that the proposed coordination framework increases the RAs’ benefits and flexibility, while in compliance with the network operating constraints. Additionally, the proposed HDR-RAs-DSO coordination framework provides a less costly solution for customers with HDR capability and results in greater profits for residential prosumers.
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SunView 深度解读
该雾计算分层协调架构对阳光电源户用储能与智能运维体系具有重要应用价值。可直接应用于iSolarCloud云平台的边缘计算层设计,通过雾节点实现ST系列户用储能变流器与SG系列户用逆变器的本地化需求响应决策,降低云端通信时延。文中的三层架构(终端设备-边缘雾节点-云服务器)可优化大规模户用光储系统的聚合调度,提升虚拟电厂场景下的实时响应能力。时延与带宽建模方法为阳光电源设计分布式能源管理系统(EMS)提供通信网络规划依据,支撑产消者经济效益最大化与电网友好型并网控制策略的协同优化。