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Minimizing the Utilized Area of PV Systems by Generating the Optimal Inter-Row Spacing Factor

Author

Listed:
  • Ayman Al-Quraan

    (Electrical Power Engineering Department, Hijjawi Faculty for Engineering Technology, Yarmouk University, Irbid 21163, Jordan)

  • Mohammed Al-Mahmodi

    (Mechanical Engineering Department, Renewable Energy, The University of Jordan, Amman 11942, Jordan)

  • Khaled Alzaareer

    (Department of Electrical Engineering, Faculty of engineering, Philadelphia University, Amman 19392, Jordan)

  • Claude El-Bayeh

    (Canada Excellent Research Chair Team, Concordia University, Montreal, QC H3H 2L9, Canada)

  • Ursula Eicker

    (Canada Excellent Research Chair Team, Concordia University, Montreal, QC H3H 2L9, Canada)

Abstract

In mounted photovoltaic (PV) facilities, energy output losses due to inter-row shading are unavoidable. In order to limit the shadow cast by one module row on another, sufficient inter-row space must be planned. However, it is not uncommon to see PV plants with such close row spacing that energy losses occur owing to row-to-row shading effects. Low module prices and high ground costs lead to such configurations, so the maximum energy output per available surface area is prioritized over optimum energy production per peak power. For any applications where the plant power output needs to be calculated, an exact analysis of the influence of inter-row shading on power generation is required. In this paper, an effective methodology is proposed and discussed in detail, ultimately, to enable PV system designers to identify the optimal inter-row spacing between arrays by generating a multiplier factor. The spacing multiplier factor is mathematically formulated and is generated to be a general formula for any geographical location including flat and non-flat terrains. The developed model is implemented using two case studies with two different terrains, to provide a wider context. The first one is in the Kingdome of Saudi Arabia (KSA) provinces, giving a flat terrain case study; the inter-row spacing multiplier factor is estimated for the direct use of a systems designer. The second one is the water pump for agricultural watering using renewable energy sources, giving a non-flat terrain case study in Dhamar, Al-Hada, Yemen. In this case study, the optimal inter-row spacing factor is estimated for limited-area applications. Therefore, the effective area using the proposed formula is minimized so that the shading of PV arrays on each other is avoided, with a simple design using the spacing factor methodology.

Suggested Citation

  • Ayman Al-Quraan & Mohammed Al-Mahmodi & Khaled Alzaareer & Claude El-Bayeh & Ursula Eicker, 2022. "Minimizing the Utilized Area of PV Systems by Generating the Optimal Inter-Row Spacing Factor," Sustainability, MDPI, vol. 14(10), pages 1-15, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:6077-:d:817335
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    References listed on IDEAS

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    1. Casares de la Torre, F.J. & Varo, Marta & López-Luque, R. & Ramírez-Faz, J. & Fernández-Ahumada, L.M., 2022. "Design and analysis of a tracking / backtracking strategy for PV plants with horizontal trackers after their conversion to agrivoltaic plants," Renewable Energy, Elsevier, vol. 187(C), pages 537-550.
    2. Hong, Taehoon & Lee, Minhyun & Koo, Choongwan & Jeong, Kwangbok & Kim, Jimin, 2017. "Development of a method for estimating the rooftop solar photovoltaic (PV) potential by analyzing the available rooftop area using Hillshade analysis," Applied Energy, Elsevier, vol. 194(C), pages 320-332.
    3. Ayman Al-Quraan & Muhannad Al-Qaisi, 2021. "Modelling, Design and Control of a Standalone Hybrid PV-Wind Micro-Grid System," Energies, MDPI, vol. 14(16), pages 1-23, August.
    4. Ghaleb, Belal & Asif, Muhammad, 2022. "Assessment of solar PV potential in commercial buildings," Renewable Energy, Elsevier, vol. 187(C), pages 618-630.
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    2. Rodrigo, Pedro M. & Mouhib, Elmehdi & Fernandez, Eduardo F. & Almonacid, Florencia & Rosas-Caro, Julio C., 2024. "Comprehensive ground coverage analysis of large-scale fixed-tilt bifacial photovoltaic plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).

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