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Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Distributed Energy Resources Scheduling and Aggregation in the Context of Demand Response Programs
This article belongs to the Special Issue Distributed Energy Resources Management 2018 ; Distributed energy resources can contribute to an improved operation of power systems, improving economic and technical efficiency. However, aggregation of resources is needed to make these resources profitable. The present paper proposes a methodology for distributed resources management by a Virtual Power Player (VPP), addressing the resources scheduling, aggregation and remuneration based on the aggregation made. The aggregation is made using K-means algorithm. The innovative aspect motivating the present paper relies on the remuneration definition considering multiple scenarios of operation, by performing a multi-observation clustering. Resources aggregation and remuneration profiles are obtained for 2592 operation scenarios, considering 548 distributed generators, 20,310 consumers, and 10 suppliers ; This work has received funding from the following projects: SIMOCE Project (ANI | P2020); and from FEDER Funds through the COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013. This work was also supported by the European Union's Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie Grant Agreement 641794–DREAM-GO Project. ; info:eu-repo/semantics/publishedVersion
Distributed Energy Resources Scheduling and Aggregation in the Context of Demand Response Programs
This article belongs to the Special Issue Distributed Energy Resources Management 2018 ; Distributed energy resources can contribute to an improved operation of power systems, improving economic and technical efficiency. However, aggregation of resources is needed to make these resources profitable. The present paper proposes a methodology for distributed resources management by a Virtual Power Player (VPP), addressing the resources scheduling, aggregation and remuneration based on the aggregation made. The aggregation is made using K-means algorithm. The innovative aspect motivating the present paper relies on the remuneration definition considering multiple scenarios of operation, by performing a multi-observation clustering. Resources aggregation and remuneration profiles are obtained for 2592 operation scenarios, considering 548 distributed generators, 20,310 consumers, and 10 suppliers ; This work has received funding from the following projects: SIMOCE Project (ANI | P2020); and from FEDER Funds through the COMPETE program and from National Funds through FCT under the project UID/EEA/00760/2013. This work was also supported by the European Union's Horizon 2020 Research and Innovation Programme under the Marie Sklodowska-Curie Grant Agreement 641794–DREAM-GO Project. ; info:eu-repo/semantics/publishedVersion
Distributed Energy Resources Scheduling and Aggregation in the Context of Demand Response Programs
Faria, Pedro (Autor:in) / Spínola, João (Autor:in) / Vale, Zita (Autor:in)
01.01.2018
doi:10.3390/en11081987
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
DDC:
690
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