Evaluation Metrics to Assess the Most Suitable Energy Community End-Users to Participate in Demand Response

Autor: Barreto, Rúben, Goncalves, Calvin, Gomes, Luis, Faria, Pedro, Vale, Zita
Přispěvatelé: Repositório Científico do Instituto Politécnico do Porto
Rok vydání: 2022
Předmět:
Zdroj: Energies; Volume 15; Issue 7; Pages: 2380
ISSN: 1996-1073
DOI: 10.3390/en15072380
Popis: In the energy sector, prosumers are becoming relevant entities for energy management systems since they can share energy with their citizen energy community (CEC). Thus, this paper proposes a novel methodology based on demand response (DR) participation in a CEC context, where unsupervised learning algorithms such as convolutional neural networks and k-means are used. This novel methodology can analyze future events on the grid and balance the consumption and generation using end-user flexibility. The end-users’ invitations to the DR event were according to their ranking obtained through three metrics. These metrics were energy flexibility, participation ratio, and flexibility history of the end-users. During the DR event, a continuous balancing assessment is performed to allow the invitation of additional end-users. Real data from a CEC with 50 buildings were used, where the results demonstrated that the end-users’ participation in two DR events allows reduction of energy costs by EUR 1.31, balancing the CEC energy resources.
This article is a result of the project RETINA (NORTE-01-0145-FEDER-000062), supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). The authors acknowledge the support of the GECAD research center (UIDB/ 00760/2020) for providing to the project team the needed work facilities and equipment.
Databáze: OpenAIRE
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