Publicação
Clustering distributed Energy Storage units for the aggregation of optimized local solar energy
| Resumo: | Active communities are emerging thanks to the necessity of creating a cleaner and safer energy system. The growing concern regarding climate change urges a solution to remove fossil fuels from the production equation. The Distributed Generation (DG) technologies are presented as a substitute, but the main resources’ behavior is highly uncertain. Flexibility from the demand side is needed. In this way, the authors resort to mixed-integer linear programming optimization to schedule the active resources introduced by the Smart Grid concept: DG, Demand Response programs, and Energy Storage Systems. In this study, the last one is the focus where the impact of these technologies in an active community is analyzed and discussed. The authors performed a clustering method to identify patterns on Energy Storage System (ESS) profiles, finding the optimal number of clusters first. The results show the importance of ESS from both Aggregator and active consumer perspectives. |
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| Autores principais: | Silva, Cátia |
| Outros Autores: | Faria, Pedro; Fernandes, António; Vale, Zita |
| Assunto: | Clustering K-means Energy Storage Scheduling Prosumers |
| Ano: | 2022 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico do Porto |
| Idioma: | inglês |
| Origem: | Repositório Científico do Instituto Politécnico do Porto |
| Resumo: | Active communities are emerging thanks to the necessity of creating a cleaner and safer energy system. The growing concern regarding climate change urges a solution to remove fossil fuels from the production equation. The Distributed Generation (DG) technologies are presented as a substitute, but the main resources’ behavior is highly uncertain. Flexibility from the demand side is needed. In this way, the authors resort to mixed-integer linear programming optimization to schedule the active resources introduced by the Smart Grid concept: DG, Demand Response programs, and Energy Storage Systems. In this study, the last one is the focus where the impact of these technologies in an active community is analyzed and discussed. The authors performed a clustering method to identify patterns on Energy Storage System (ESS) profiles, finding the optimal number of clusters first. The results show the importance of ESS from both Aggregator and active consumer perspectives. |
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