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dc.contributor.author
Rios, Daniel  
dc.contributor.author
Blanco Bogado, Gerardo Alejandro  
dc.contributor.author
Olsina, Fernando Gabriel  
dc.date.available
2021-02-04T17:27:06Z  
dc.date.issued
2019-05  
dc.identifier.citation
Rios, Daniel; Blanco Bogado, Gerardo Alejandro; Olsina, Fernando Gabriel; Integrating Real Options Analysis with long-term electricity market models; Elsevier; Energy Economics; 80; 5-2019; 188-205  
dc.identifier.issn
0140-9883  
dc.identifier.uri
http://hdl.handle.net/11336/124814  
dc.description.abstract
In liberalized electricity markets, the investment postponement option is deemed decisive for understanding the addition of new generating capacity. Basically, it refers to the possibility for investors to postpone projects for a period while waiting for the arrival of new and better information about the market evolution. When such development involves major uncertainties, the generation business becomes riskier, and the investors' “wait-and-see” behavior might limit the timely addition of new power plants. In that sense, the literature provides solid empirical evidence about the occurrence of construction cycles in the deregulated electricity industry. However, the strategic flexibility inherent to the option to defer new power plants has not yet been rigorously incorporated to investment signals in existing market models. Therefore, this paper proposes a novel methodology to assess the long-term development of liberalized power markets based on a more realistic approach for valuing generation investments. The work is based on a stochastic dynamic market model, built upon System Dynamics simulation approach. The decision-making framework considers that the addition of new capacity is driven by the economic value of the strategic flexibility associated with deferring investments under uncertainties. Thus, the value of the postponement option is quantified in monetary terms through Real Options Analysis. Simulations confirm the cyclical behavior of the energy-only market in the long run, as suggested by the empirical evidence found in the literature. In addition, sensitivity analysis regarding some relevant exogenous variables depicts an even more fluctuating evolution of the capacity due to the combination of strong demand growth rates with large volatilities. Finally, the model validity is assessed through a formal procedure according to the scope of System Dynamics modeling approach.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Elsevier  
dc.rights
info:eu-repo/semantics/restrictedAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
POWER GENERATION  
dc.subject
POWER MARKET  
dc.subject
REAL OPTIONS  
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STOCHASTIC SIMULATION  
dc.subject
STRATEGIC FLEXIBILITY  
dc.subject
SYSTEM DYNAMICS  
dc.subject.classification
Ingeniería Eléctrica y Electrónica  
dc.subject.classification
Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información  
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS  
dc.title
Integrating Real Options Analysis with long-term electricity market models  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2020-12-11T14:56:54Z  
dc.journal.volume
80  
dc.journal.pagination
188-205  
dc.journal.pais
Países Bajos  
dc.description.fil
Fil: Rios, Daniel. Universidad Nacional de Asunción; Paraguay  
dc.description.fil
Fil: Blanco Bogado, Gerardo Alejandro. Universidad Nacional de Asunción; Paraguay  
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.journal.title
Energy Economics  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.eneco.2018.12.023  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0140988319300027