A Virtual Power Plant Architecture for the Demand-Side Management of Smart Prosumers

被引:88
作者
Pasetti, Marco [1 ]
Rinaldi, Stefano [1 ]
Manerba, Daniele [2 ,3 ]
机构
[1] Univ Brescia, Dept Informat Engn, Via Branze 38, I-25123 Brescia, Italy
[2] Politecn Torino, Dept Control & Comp Engn, Corso Duca Abruzzi 24, I-10129 Turin, Italy
[3] Politecn Torino, ICT City Logist & Enterprise Lab, Corso Duca Abruzzi 24, I-10129 Turin, Italy
来源
APPLIED SCIENCES-BASEL | 2018年 / 8卷 / 03期
关键词
virtual power plant; demand-side management; energy management system; demand response; smart grid; urban energy system; distributed energy resources; multi-agent system; LINEAR-PROGRAMMING MODEL; ENERGY; NETWORK; INTEGRATION; STRATEGY; SYSTEMS; DESIGN;
D O I
10.3390/app8030432
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
In this paper, we present a conceptual study on a Virtual Power Plant (VPP) architecture for the optimal management of Distributed Energy Resources (DERs) owned by prosumers participating in Demand-Side Management (DSM) programs. Compared to classical VPP architectures, which aim to aggregate several DERs dispersed throughout the electrical grid, in the proposed VPP architecture the supervised physical domain is limited to single users, i.e., to single Points of Delivery (PODs) of the distribution network. The VPP architecture is based on a service-oriented approach, where multiple agents cooperate to implement the optimal management of the prosumer's assets, by also considering different forms of Demand Response (DR) requests. The considered DR schemes range from Price-Based DRs to Event-Based DRs, covering both the normal operating functions and the emergency control requests applied in modern distribution networks. With respect to centralized approaches, in this study the control perspective is moved from the system level to the single prosumer's level, who is allowed to independently provide flexible power profiles through the aggregation of multiple DERs. A generalized optimization model, formulated as a Mixed-Integer Linear Programming (MILP) problem, is also introduced. Such a model is able to compute the optimal scheduling of a prosumer's assets by considering both DR requests and end-users' requirements in terms of comfort levels while minimizing the costs.
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页数:20
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