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Optimal solar tree design for increased flexibility in seasonal energy extraction

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  • Dey, Sumon
  • Lakshmanan, Madan Kumar
  • Pesala, Bala

Abstract

The paper proposes location/application specific tuning of the solar power generation curve by appropriately orienting solar panels in a solar tree. The initial part of the study involving optimization of single panel orientation, emphasizes the need to adopt data driven approach. Study carried out for 15 locations covering a large latitude range shows that optimal orientation cannot be determined based on the latitude angle alone and azimuth angle also needs to be considered, especially for locations having asymmetric solar insolation pattern during a day. Based on these insights, feasibility of tuning annual solar power generation curve is shown by designing a 1 kW solar tree for four locations. Genetic algorithm based optimization is used for positioning of the solar panels so that shadow losses are minimized. Validation with ray optic simulations for solar trees designed for two locations have shown less than 2% shading losses. The optimized solar trees for San Francisco and Paris show increase in power generation of 2.04% and 7.38% respectively compared to latitude tilt. The simulations are further validated using a scaled down prototype solar tree showing excellent match. The methodology presented here can be easily extended to the design of optimized solar tree for any location and capacity.

Suggested Citation

  • Dey, Sumon & Lakshmanan, Madan Kumar & Pesala, Bala, 2018. "Optimal solar tree design for increased flexibility in seasonal energy extraction," Renewable Energy, Elsevier, vol. 125(C), pages 1038-1048.
  • Handle: RePEc:eee:renene:v:125:y:2018:i:c:p:1038-1048
    DOI: 10.1016/j.renene.2018.02.017
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    References listed on IDEAS

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    Cited by:

    1. Al Garni, Hassan Z. & Awasthi, Anjali & Wright, David, 2019. "Optimal orientation angles for maximizing energy yield for solar PV in Saudi Arabia," Renewable Energy, Elsevier, vol. 133(C), pages 538-550.
    2. Essa Alhamer & Addison Grigsby & Rydge Mulford, 2022. "The Influence of Seasonal Cloud Cover, Ambient Temperature and Seasonal Variations in Daylight Hours on the Optimal PV Panel Tilt Angle in the United States," Energies, MDPI, vol. 15(20), pages 1-14, October.
    3. Mahmood Alharbi & Ramzi Alahmadi & Ahmed Alahmadi, 2023. "Meteorological-Data-Based Modeling for PV Performance Optimization," Sustainability, MDPI, vol. 15(11), pages 1-16, May.
    4. Dey, Sumon & Pesala, Bala, 2020. "Solar tree design framework for maximized power generation with minimized structural cost," Renewable Energy, Elsevier, vol. 162(C), pages 1747-1762.
    5. Kwak, Younghoon & Mun, Sun-Hye & Park, Chang-Dae & Lee, Sang-Moon & Huh, Jung-Ho, 2022. "Statistical analysis of power generation of semi-transparent photovoltaic (STPV) for diversity in building envelope design: A mock-up test by azimuth and tilt angles," Renewable Energy, Elsevier, vol. 188(C), pages 651-669.
    6. Arias-Rosales, Andrés & LeDuc, Philip R., 2023. "Urban solar harvesting: The importance of diffuse shadows in complex environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
    7. Vyas, Maharshi & Chowdhury, Sumit & Verma, Abhishek & Jain, V.K., 2022. "Solar Photovoltaic Tree: Urban PV power plants to increase power to land occupancy ratio," Renewable Energy, Elsevier, vol. 190(C), pages 283-293.
    8. Arias-Rosales, Andrés & LeDuc, Philip R., 2022. "Shadow modeling in urban environments for solar harvesting devices with freely defined positions and orientations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 164(C).

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