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Fuzzy chance-constrained multi-objective optimization of configuration and operation of building-photovoltaics-assisted distributed energy system under source-load uncertainties

Author

Listed:
  • Yang, Qian
  • Tian, Ming
  • Li, Li
  • Deng, Hongying

Abstract

Building-integrated photovoltaics can be seamlessly integrated with distributed energy systems. However, the inherent variability in solar irradiation and the fluctuating cooling, heating, and power demands of buildings pose substantial challenges for system design and operational management. This study constructs a photovoltaics-assisted distributed energy system and proposes a bi-layer fuzzy chance-constrained optimization model is proposed to optimize the system configuration and energy dispatch strategies. Both source-load uncertainties of solar irradiation and loads of electric vehicle charge, building electricity, heat, and cold are characterized in the scenario generation method and chance-constraint with confidence level. The multiple optimization objectives of economy, energy, emission, and system independence on the electricity grid are considered. The fuzzy chance-constrained model is reformatted to a deterministic optimization with a certain confidence level and it is solved in the ε-constraint method. A building community case study validates the proposed model. The simulation results demonstrate that the economic, energy, and emission benefits decline by 0.37 %, 0.27 %, and 0.39 %, respectively, when the confidence level increases from 0.5 to 0.9. However, the system independence increases by 5.71 %. The system configurations and energy dispatch strategies are closely related to source-load uncertainty. By introducing chance constraints at a certain confidence level, the optimization model balances system reliability and cost-effectiveness.

Suggested Citation

  • Yang, Qian & Tian, Ming & Li, Li & Deng, Hongying, 2026. "Fuzzy chance-constrained multi-objective optimization of configuration and operation of building-photovoltaics-assisted distributed energy system under source-load uncertainties," Renewable Energy, Elsevier, vol. 256(PF).
    • Handle: RePEc:eee:renene:v:256:y:2026:i:pf:s0960148125020695
    DOI: 10.1016/j.renene.2025.124405
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