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PV park site selection for utility-scale solar guides combining GIS and power flow analysis: A case study on a Swedish municipality

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  • Lindberg, O.
  • Birging, A.
  • Widén, J.
  • Lingfors, D.

Abstract

Utility-scale solar photovoltaic (PV) parks have dominated the international market for the past few years. However, in some countries, like Sweden, utility-scale PV is on the verge to economic viability. Using existing infrastructure in a resource-efficient manner could be a crucial strategy for a successful implementation at scale. In this study, a new methodology for a utility-scale solar guide is developed by studying the hosting capacity in the local grid and identifying land appropriate for PV parks. The method is applied on a rural municipality in Sweden (512 km2) with a local distribution grid (5,000 customers). The impact on the grid, if connecting a PV park to a substation, was analyzed through power flow simulations and the geographical assessment was done using multi-criteria analysis with a Boolean approach. Three different sizes of PV parks, 1, 3, and 5 MWp, were analyzed. Results showed that 3.7% of the studied area is qualified for locating 1 MWp PV parks. However, if introducing a maximum distance threshold to the nearest substation that can host the PV generation from the park, the potential is further reduced (e.g., to 1% for a 750 m threshold). Furthermore, parts of the grid can host PV parks of 3 and 5 MWp, but only near urban areas, where qualified land is lacking. The results highlight that the proposed methodology can function as a tool in the dialog between utility companies, municipalities, PV companies, land-owners and other stakeholders in order to find resource- and system-efficient locations for PV parks.

Suggested Citation

  • Lindberg, O. & Birging, A. & Widén, J. & Lingfors, D., 2021. "PV park site selection for utility-scale solar guides combining GIS and power flow analysis: A case study on a Swedish municipality," Applied Energy, Elsevier, vol. 282(PA).
  • Handle: RePEc:eee:appene:v:282:y:2021:i:pa:s0306261920315129
    DOI: 10.1016/j.apenergy.2020.116086
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    3. Barbón, A. & Bayón-Cueli, C. & Bayón, L. & Carreira-Fontao, V., 2022. "A methodology for an optimal design of ground-mounted photovoltaic power plants," Applied Energy, Elsevier, vol. 314(C).
    4. Liu, Zhengguang & Guo, Zhiling & Song, Chenchen & Du, Ying & Chen, Qi & Chen, Yuntian & Zhang, Haoran, 2023. "Business model comparison of slum-based PV to realize low-cost and flexible power generation in city-level," Applied Energy, Elsevier, vol. 344(C).
    5. Romero-Ramos, J.A. & Gil, J.D. & Cardemil, J.M. & Escobar, R.A. & Arias, I. & Pérez-García, M., 2023. "A GIS-AHP approach for determining the potential of solar energy to meet the thermal demand in southeastern Spain productive enclaves," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).
    6. Asadi, Meysam & Ramezanzade, Mohsen & Pourhossein, Kazem, 2023. "A global evaluation model applied to wind power plant site selection," Applied Energy, Elsevier, vol. 336(C).
    7. Pillot, Benjamin & Al-Kurdi, Nadeem & Gervet, Carmen & Linguet, Laurent, 2021. "Optimizing operational costs and PV production at utility scale: An optical fiber network analogy for solar park clustering," Applied Energy, Elsevier, vol. 298(C).
    8. Hasan Eroğlu, 2022. "Development of a novel solar energy need index for identifying priority investment regions: a case study and current status in Turkey," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(6), pages 8840-8855, June.
    9. Lindberg, O. & Lingfors, D. & Arnqvist, J., 2022. "Analyzing the mechanisms behind temporal correlation between power sources using frequency separated time scales: A Swedish case study on PV and wind," Energy, Elsevier, vol. 259(C).
    10. Kocabaldır, Canan & Yücel, Mehmet Ali, 2023. "GIS-based multicriteria decision analysis for spatial planning of solar photovoltaic power plants in Çanakkale province, Turkey," Renewable Energy, Elsevier, vol. 212(C), pages 455-467.
    11. Nikolaos Nagkoulis & Eva Loukogeorgaki & Michela Ghislanzoni, 2022. "Genetic Algorithms-Based Optimum PV Site Selection Minimizing Visual Disturbance," Sustainability, MDPI, vol. 14(19), pages 1-19, October.

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