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Valuing photovoltaic power plants by compound real options

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  • Mombello, Bruno
  • Olsina, Fernando
  • Pringles, Rolando

Abstract

Meeting electricity demand with renewable generation requires spending trillions of dollars in investments exposed to financial risk. Renewable projects have multiple strategic real options to manage investment risk, but they are usually priced separately in isolation. This paper proposes a framework for valuing multistage decisions in a grid-scale photovoltaic (PV) power plant under uncertainty. The project is modelled as a compound portfolio of American sequential and mutually exclusive options to defer, expand and relocate. The compound options are jointly priced by a hierarchically nested least-squares Monte Carlo algorithm. The framework incorporates uncertainties related to decreasing costs in solar technology and the emergence of more profitable renewable tariffs elsewhere. The results show that the value of the compound option portfolio significantly exceeds the value of the single deferral option commonly considered in practice. Ignoring expansion and relocation flexibilities may lead to underinvestment by mispricing the value of PV projects. Incorporating these options encourages early commitment of the PV investment. Moreover, summation of individual option prices may not be a good approximation of the true portfolio value, as interactions among options exist. These findings may improve allocation efficiency of renewable investments, accelerate energy transition and benefit investors, funding agencies and regulators.

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  • Mombello, Bruno & Olsina, Fernando & Pringles, Rolando, 2023. "Valuing photovoltaic power plants by compound real options," Renewable Energy, Elsevier, vol. 216(C).
    • Handle: RePEc:eee:renene:v:216:y:2023:i:c:s0960148123009357
    DOI: 10.1016/j.renene.2023.119021
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    References listed on IDEAS

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    2. Yang, Changhui & Fu, Yuting & He, Lijun & Jiang, Qi & Cui, Yangyu, 2024. "Real options analysis for regional investment decisions of household PV-ESS in China," Energy, Elsevier, vol. 293(C).

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