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Rolling horizon optimization based real-time energy management of a residential neighborhood considering PV and ESS usage fairness

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  • Erdinç, Fatma Gülşen

Abstract

The incorporation of decentralized energy solutions, including solar photovoltaic (PV) installations and energy storage systems (ESSs), into residential communities has received substantial interest in recent times. This is driven by the objective of enhancing the self-reliance of residential zones while decreasing their reliance on centralized power grids. Effective management of these systems can yield advantages such as load equalization, cost reduction, and diminished emissions. The process of optimizing energy management in residential communities entails addressing multiple factors, including uncertainty, equity, and efficiency.

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  • Erdinç, Fatma Gülşen, 2023. "Rolling horizon optimization based real-time energy management of a residential neighborhood considering PV and ESS usage fairness," Applied Energy, Elsevier, vol. 344(C).
    • Handle: RePEc:eee:appene:v:344:y:2023:i:c:s0306261923006396
    DOI: 10.1016/j.apenergy.2023.121275
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    References listed on IDEAS

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    1. Pascual, Julio & Arcos-Aviles, Diego & Ursúa, Alfredo & Sanchis, Pablo & Marroyo, Luis, 2021. "Energy management for an electro-thermal renewable–based residential microgrid with energy balance forecasting and demand side management," Applied Energy, Elsevier, vol. 295(C).
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    6. Çiçek, Alper & Şengör, İbrahim & Erenoğlu, Ayşe Kübra & Erdinç, Ozan, 2020. "Decision making mechanism for a smart neighborhood fed by multi-energy systems considering demand response," Energy, Elsevier, vol. 208(C).
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    Cited by:

    1. Feng, Ran & Wang, Kai & Xu, Xu & Yu, Zi-Tao & Lin, Qingyang, 2024. "Triple-layer optimization of distributed photovoltaic energy storage capacity for manufacturing enterprises considering carbon emissions and load management," Applied Energy, Elsevier, vol. 364(C).
    2. Marrasso, E. & Martone, C. & Pallotta, G. & Roselli, C. & Sasso, M., 2024. "Assessment of energy systems configurations in mixed-use Positive Energy Districts through novel indicators for energy and environmental analysis," Applied Energy, Elsevier, vol. 368(C).
    3. Li, Yutong & Hou, Jian & Yan, Gangfeng, 2024. "Exploration-enhanced multi-agent reinforcement learning for distributed PV-ESS scheduling with incomplete data," Applied Energy, Elsevier, vol. 359(C).

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