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dc.contributor.author
Pringles, Rolando Marcelo
dc.contributor.author
Olsina, Fernando Gabriel
dc.contributor.author
Penizzotto Bacha, Franco Victor
dc.date.available
2021-10-14T16:33:10Z
dc.date.issued
2020-05
dc.identifier.citation
Pringles, Rolando Marcelo; Olsina, Fernando Gabriel; Penizzotto Bacha, Franco Victor; Valuation of defer and relocation options in photovoltaic generation investments by a stochastic simulation-based method; Pergamon-Elsevier Science Ltd; Renewable Energy; 151; 5-2020; 846-864
dc.identifier.issn
0960-1481
dc.identifier.uri
http://hdl.handle.net/11336/143628
dc.description.abstract
Risk management is crucial when committing investments in electricity markets. Investment projects for the generation of electricity are capital-intensive, in large part irreversible and future performance is subject to high uncertainty. Fortunately, most power generation projects have strategic flexibility for handling uncertainty and for mitigating risks under unfavorable scenarios. Modern corporate finance recognizes Real Option analysis (ROA) as the correct way to value investment projects with these characteristics. Due to both, environmental concerns and escalation of fuel prices, electricity generation from renewable sources has grown dramatically worldwide over the last decade. Renewable investment projects share many of the features mentioned. As such, option valuation methods should be applied to estimate the monetary value of flexibility in renewable energy investments. This work presents an appropriate methodology for assessing the economic value of a photovoltaic power plant under uncertainties. ROA is applied to determine the value of delaying the investment decision while waiting for better market information that would reduce acquisition costs due to progress in solar technology. The flexibility of relocating the solar facility in the future upon the appearance of a more attractive site in terms of cost, network accessibility or regulatory policies is also valued. The problem of option valuation is solved through stochastic simulation combined with recursive approximate dynamic programming techniques. The methodology developed might be used by investors for more efficient decision-making and by regulatory agencies for designing adequate support policies that encourage investment in renewable energy generation.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Pergamon-Elsevier Science Ltd
dc.rights
info:eu-repo/semantics/openAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
Flexibility
dc.subject
Uncertainty
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Irreversibility
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Real options
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Solar energy
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Monte Carlo
dc.subject.classification
Ingeniería Eléctrica y Electrónica
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Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS
dc.title
Valuation of defer and relocation options in photovoltaic generation investments by a stochastic simulation-based method
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2021-09-08T18:56:46Z
dc.journal.volume
151
dc.journal.pagination
846-864
dc.journal.pais
Estados Unidos
dc.description.fil
Fil: Pringles, Rolando Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentina
dc.description.fil
Fil: Olsina, Fernando Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentina
dc.description.fil
Fil: Penizzotto Bacha, Franco Victor. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Energía Eléctrica. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Energía Eléctrica; Argentina
dc.journal.title
Renewable Energy
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S0960148119317756
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.renene.2019.11.082
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