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Analytical approach to quantitative risk assessment for solar power projects

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  • Guindon, A.-A.
  • Wright, D.J.

Abstract

Quantifying the economic risk associated with a solar power project is essential in order to secure financing. Quantitative risk assessment is often conducted by rerunning a model to calculate economic viability measures, including Internal Rate of Return (IRR) and Levelized Cost of Electricity (LCOE), for ranges of values of uncertain input parameters that determine capital cost, operating cost, energy yield and revenue. This paper provides an analytical approach that avoids this repetitive recalculation. The analytical approach is based on differentiating the economic viability measures with respect to the input parameters of interest. Using 20% changes in parameter values, the analytical approach is shown to agree within 0.875% for a behind-the-meter project. For an off-grid utility scale project the analytical approach is exact for five cost and energy yield parameters and agrees within 0.01% for degradation rate and 0.14% for discount rate. Moreover, the analytical approach is extended to provide differential importance measures that indicate which parameters are contributing most/least to the riskiness of the project. Results indicate that the ranking of parameters is identical for IRR and LCOE despite these being very different measures of economic viability, thus further supporting the analytical method provided in this paper.

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  • Guindon, A.-A. & Wright, D.J., 2020. "Analytical approach to quantitative risk assessment for solar power projects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    • Handle: RePEc:eee:rensus:v:133:y:2020:i:c:s1364032120305517
    DOI: 10.1016/j.rser.2020.110262
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    References listed on IDEAS

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    3. Yana Duan & Yang Sun & Yu Zhang & Xiaoqi Fan & Qinghuan Dong & Sen Guo, 2021. "Risk Evaluation of Electric Power Grid Investment in China Employing a Hybrid Novel MCDM Method," Mathematics, MDPI, vol. 9(5), pages 1-22, February.

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