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Sensitivity analysis in the technical potential assessment of onshore wind and ground solar photovoltaic power resources at regional scale

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  • Bossavy, Arthur
  • Girard, Robin
  • Kariniotakis, Georges

Abstract

Potential assessment has served various objectives in the development of renewable energies. However, the prospective nature of this type of assessment sometimes makes it difficult to evaluate and compare estimation results based on different data and modeling. To facilitate this comparison, uncertainty estimates need to be systematically provided. Since potential assessment sometimes relies on numerous parameters, this may first require determining the most important inputs to focus on. In this paper, we propose a sensitivity analysis methodology based on Sobol indices so as to identify the main inputs from a nonlinear assessment model. We illustrate the proposed methodology through analyzing sensitivity in an onshore wind and ground solar photovoltaic (PV) potential assessment covering two French regions. As a result, we show that, when estimating the potential of these renewable energy sources, parameters defining surface availability are more prevalent than those related to technology.

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  • Bossavy, Arthur & Girard, Robin & Kariniotakis, Georges, 2016. "Sensitivity analysis in the technical potential assessment of onshore wind and ground solar photovoltaic power resources at regional scale," Applied Energy, Elsevier, vol. 182(C), pages 145-153.
  • Handle: RePEc:eee:appene:v:182:y:2016:i:c:p:145-153
    DOI: 10.1016/j.apenergy.2016.08.075
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    Cited by:

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    2. McKenna, Russell & Pfenninger, Stefan & Heinrichs, Heidi & Schmidt, Johannes & Staffell, Iain & Bauer, Christian & Gruber, Katharina & Hahmann, Andrea N. & Jansen, Malte & Klingler, Michael & Landwehr, 2022. "High-resolution large-scale onshore wind energy assessments: A review of potential definitions, methodologies and future research needs," Renewable Energy, Elsevier, vol. 182(C), pages 659-684.
    3. Heggarty, Thomas & Bourmaud, Jean-Yves & Girard, Robin & Kariniotakis, Georges, 2019. "Multi-temporal assessment of power system flexibility requirement," Applied Energy, Elsevier, vol. 238(C), pages 1327-1336.
    4. Makhloufi, Saida & Khennas, Smail & Bouchaib, Sami & Arab, Amar Hadj, 2022. "Multi-objective cuckoo search algorithm for optimized pathways for 75 % renewable electricity mix by 2050 in Algeria," Renewable Energy, Elsevier, vol. 185(C), pages 1410-1424.
    5. Jung, Christopher & Schindler, Dirk, 2022. "On the influence of wind speed model resolution on the global technical wind energy potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    6. Zhang, Hengxu & Cao, Yongji & Zhang, Yi & Terzija, Vladimir, 2018. "Quantitative synergy assessment of regional wind-solar energy resources based on MERRA reanalysis data," Applied Energy, Elsevier, vol. 216(C), pages 172-182.
    7. Krishna Muniyoor, 2020. "Cost-benefit analysis of adopting the solar photovoltaic water pumping system: A case of Rajasthan," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2020(2), pages 35-49.
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    9. Ikäheimo, Jussi & Lindroos, Tomi J. & Kiviluoma, Juha, 2023. "Impact of climate and geological storage potential on feasibility of hydrogen fuels," Applied Energy, Elsevier, vol. 342(C).

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