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Coordinated energy management for a cluster of buildings through deep reinforcement learning

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Listed:
  • Pinto, Giuseppe
  • Piscitelli, Marco Savino
  • Vázquez-Canteli, José Ramón
  • Nagy, Zoltán
  • Capozzoli, Alfonso

Abstract

Advanced control strategies can enable energy flexibility in buildings by enhancing on-site renewable energy exploitation and storage operation, significantly reducing both energy costs and emissions. However, when the energy management is faced shifting from a single building to a cluster of buildings, uncoordinated strategies may have negative effects on the grid reliability, causing undesirable new peaks.

Suggested Citation

  • Pinto, Giuseppe & Piscitelli, Marco Savino & Vázquez-Canteli, José Ramón & Nagy, Zoltán & Capozzoli, Alfonso, 2021. "Coordinated energy management for a cluster of buildings through deep reinforcement learning," Energy, Elsevier, vol. 229(C).
    • Handle: RePEc:eee:energy:v:229:y:2021:i:c:s0360544221009737
    DOI: 10.1016/j.energy.2021.120725
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    References listed on IDEAS

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