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Solar tree design framework for maximized power generation with minimized structural cost

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  • Dey, Sumon
  • Pesala, Bala

Abstract

Conventional solar trees, inspite of their high-power density, are relatively unviable due to the huge shading losses (>30%) and structural cost (>50% of the total cost) associated with them. The paper proposes a location specific design framework for maximized electrical output from solar tree using minimized structural material. Actual solar insolation data is utilized to orient solar panels in a solar tree to maximize annual energy extraction. Preliminary structural optimization coupled with multi-objective optimization leveraging genetic algorithms with objectives as minimization of shading losses and projected ground footprint area are employed to position the solar panels. Further, the dimensions of the branches and trunks in the solar tree structure are individually tuned to ascertain structural stability at high wind speed using finite element modelling based von Mises stress analysis. The designed 3 kW solar tree, having a normalized ground footprint of 1.67 and shading loss of only 0.17% demonstrates the design framework. Energy generation estimates are validated using ray-optic simulations. Simultaneous structural optimization carried out to withstand a wind speed of 150 kmph, has resulted in 20% reduction in structural mass requirement. The study increases the feasibility of deployment of solar tree and can be extended to other geographical locations.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:162:y:2020:i:c:p:1747-1762
    DOI: 10.1016/j.renene.2020.07.035
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    References listed on IDEAS

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    1. 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.
    2. Ravi, Sujith & Macknick, Jordan & Lobell, David & Field, Christopher & Ganesan, Karthik & Jain, Rishabh & Elchinger, Michael & Stoltenberg, Blaise, 2016. "Colocation opportunities for large solar infrastructures and agriculture in drylands," Applied Energy, Elsevier, vol. 165(C), pages 383-392.
    3. Lo Piano, Samuele & Mayumi, Kozo, 2017. "Toward an integrated assessment of the performance of photovoltaic power stations for electricity generation," Applied Energy, Elsevier, vol. 186(P2), pages 167-174.
    4. Le Roux, W.G., 2016. "Optimum tilt and azimuth angles for fixed solar collectors in South Africa using measured data," Renewable Energy, Elsevier, vol. 96(PA), pages 603-612.
    5. Lin, Chih-Kuang & Dai, Chen-Yu & Wu, Jiunn-Chi, 2013. "Analysis of structural deformation and deformation-induced solar radiation misalignment in a tracking photovoltaic system," Renewable Energy, Elsevier, vol. 59(C), pages 65-74.
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    1. Grassi, Larissa Bonadiman & Marins, Daniela Pawelski Amaro & Paim, Juliana Fonseca & Palaoro, Lohane Barcelos & Segatto, Marcelo Eduardo Vieira & Paiva, Marcia Helena Moreira, 2024. "Fibonacci solar tree: Mathematical modeling of the solar incidence as a function of its constructive variables," Renewable Energy, Elsevier, vol. 229(C).
    2. 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.

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