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Emission and cost trade-off in renewable-based smart EV parking lots using ε-constraint and fuzzy multi-criteria method

Author

Listed:
  • Li, Zhifeng
  • Ziyang, Long
  • Nojavan, Sayyad

Abstract

This study introduces a robust bi-objective optimization framework for the economic and environmental management of a renewable-based smart electric vehicle parking lot (SPL). The proposed model integrates renewable energy sources (photovoltaic and wind systems), hydrogen storage systems (HSS), and electric vehicles (EVs), coordinated via a real-time pricing (RTP) scheme within a load response program (LRP). A hybrid solution approach combining the ε-constraint method and a fuzzy decision-making algorithm is adopted to resolve the trade-off between minimizing operational costs and carbon emissions. Simulation results demonstrate that under the RTP scheme, the total emission and operational cost of the SPL are reduced by 4.80 % and 1.27 %, respectively, compared to the conventional Time-of-Use (TOU) pricing approach. Specifically, the operating cost dropped from $3350.21 to $3307.45, while total emissions decreased from 27,788.53 kg to 26,454.43 kg. Additionally, the system exhibits stable performance under ±20 % variations in solar irradiance and wind speed. These findings underscore the potential of dynamic pricing and integrated multi-carrier energy systems in enhancing the sustainability and efficiency of EV-based infrastructures.

Suggested Citation

  • Li, Zhifeng & Ziyang, Long & Nojavan, Sayyad, 2025. "Emission and cost trade-off in renewable-based smart EV parking lots using ε-constraint and fuzzy multi-criteria method," Renewable Energy, Elsevier, vol. 255(C).
    • Handle: RePEc:eee:renene:v:255:y:2025:i:c:s0960148125014685
    DOI: 10.1016/j.renene.2025.123804
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    References listed on IDEAS

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