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Optimization of a residential communityʼs curtailed PV power to meet distribution grid load profile requirements

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  • Dellaly, Mariem
  • Skander-Mustapha, Sondes
  • Slama-Belkhodja, Ilhem

Abstract

The integration of a large number of photovoltaic systems into the electricity grid presents significant technical challenges. To address the issue of excess power injection into the grid, various standards recommend curtailment of PV systems, which results in penalizing renewable energy. This paper proposes a solution to the problem without resorting to curtailment. The key innovation is to optimize the energy injected into the grid, achieving a delicate balance between benefits for prosumers and the grid operator, while also avoiding PV curtailment. The results obtained underscore substantial advantages for prosumers when contrasted with commercial solutions that resort to curtailing PV power, while ensuring the alignment of interests with network providers. The proposed energy management system is based on a multi-objective linear programming algorithm and aims to increase energy injection into the grid during peak regional demand while simultaneously considering the electricity price profile. The study utilizes digital twin technology to establish a dependable framework for validating proposed algorithms and comparing simulated results with experimental ones. By doing so, this process guarantees the accuracy of simulation results and allows for informed decision-making regarding the system under investigation.

Suggested Citation

  • Dellaly, Mariem & Skander-Mustapha, Sondes & Slama-Belkhodja, Ilhem, 2023. "Optimization of a residential communityʼs curtailed PV power to meet distribution grid load profile requirements," Renewable Energy, Elsevier, vol. 218(C).
    • Handle: RePEc:eee:renene:v:218:y:2023:i:c:s0960148123012570
    DOI: 10.1016/j.renene.2023.119342
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    References listed on IDEAS

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    1. Makhdoomi, Sina & Askarzadeh, Alireza, 2020. "Daily performance optimization of a grid-connected hybrid system composed of photovoltaic and pumped hydro storage (PV/PHS)," Renewable Energy, Elsevier, vol. 159(C), pages 272-285.
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    1. Karipoğlu, Fatih & Denizli, Osmancan, 2025. "Towards renewable energy islands in Türkiye: Potential and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 211(C).
    2. Chou, Jui-Sheng & Krang, Ja & Limantono, Dani Nugraha, 2026. "Regional solar generation prediction with metaheuristically optimized artificial intelligence for sustainable grid management," Renewable Energy, Elsevier, vol. 257(C).

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