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MCDM Optimization-Based Development of a Plus-Energy Microgrid Architecture for University Buildings and Smart Parking

Author

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  • Mahmoud Ouria

    (Institute of Systems and Robotics, Department of Electrical and Computer Engineering, University of Coimbra, 3030-290 Coimbra, Portugal)

  • Alexandre F. M. Correia

    (Institute of Systems and Robotics, Department of Electrical and Computer Engineering, University of Coimbra, 3030-290 Coimbra, Portugal)

  • Pedro Moura

    (Institute of Systems and Robotics, Department of Electrical and Computer Engineering, University of Coimbra, 3030-290 Coimbra, Portugal)

  • Paulo Coimbra

    (Institute of Systems and Robotics, Department of Electrical and Computer Engineering, University of Coimbra, 3030-290 Coimbra, Portugal)

  • Aníbal T. de Almeida

    (Institute of Systems and Robotics, Department of Electrical and Computer Engineering, University of Coimbra, 3030-290 Coimbra, Portugal)

Abstract

This paper presents a multi-criteria decision-making (MCDM) approach for optimizing a microgrid system to achieve Plus-Energy Building (PEB) performance at the University of Coimbra’s Electrical Engineering Department. Using Python 3.12.8, Rhino 7, and PVsyst 8.0.1, simulations considered architectural and visual constraints, with economic feasibility assessed through a TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) analysis. The system is projected to generate approximately 1 GWh annually, with a 98% probability of exceeding 1076 MWh based on Gaussian estimation. Consumption is estimated at 460 MWh, while a 3.8 MWh battery ensures up to 72 h of autonomy. Rooftop panels and green parking arrays, fixed at 13.5° and 59°, minimize visual impact while contributing a surplus of +160% energy injection (or a net surplus of +60% energy after self-consumption). Assuming a battery cost of EUR 200/kWh, each hour of energy storage for the building requires 61 kWh of extra capacity with a cost of 12,200 (EUR/hr.storage). Recognizing environmental variability, these figures represent cross-validated probabilistic estimates derived from both PVsyst and Monte Carlo simulation using Python, reinforcing confidence in system feasibility. A holistic photovoltaic optimization strategy balances technical, economic, and architectural factors, demonstrating the potential of PEBs as a sustainable energy solution for academic institutions.

Suggested Citation

  • Mahmoud Ouria & Alexandre F. M. Correia & Pedro Moura & Paulo Coimbra & Aníbal T. de Almeida, 2025. "MCDM Optimization-Based Development of a Plus-Energy Microgrid Architecture for University Buildings and Smart Parking," Energies, MDPI, vol. 18(14), pages 1-37, July.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:14:p:3641-:d:1698276
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    References listed on IDEAS

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    1. José F. C. Castro & Ronaldo A. Roncolatto & Antonio R. Donadon & Vittoria E. M. S. Andrade & Pedro Rosas & Rafael G. Bento & José G. Matos & Fernando A. Assis & Francisco C. R. Coelho & Rodolfo Quadro, 2023. "Microgrid Applications and Technical Challenges—The Brazilian Status of Connection Standards and Operational Procedures," Energies, MDPI, vol. 16(6), pages 1-25, March.
    2. Husein, Munir & Chung, Il-Yop, 2018. "Optimal design and financial feasibility of a university campus microgrid considering renewable energy incentives," Applied Energy, Elsevier, vol. 225(C), pages 273-289.
    3. Sreedharan, P. & Farbes, J. & Cutter, E. & Woo, C.K. & Wang, J., 2016. "Microgrid and renewable generation integration: University of California, San Diego," Applied Energy, Elsevier, vol. 169(C), pages 709-720.
    4. Edrees Yahya Alhawsawi & Khaled Salhein & Mohamed A. Zohdy, 2024. "A Comprehensive Review of Existing and Pending University Campus Microgrids," Energies, MDPI, vol. 17(10), pages 1-29, May.
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