Economic and regulatory uncertainty in renewable energy system design: a review
Renewable energy is increasingly mobilizing more investment around the globe. However, there has been little attention to evaluating economic and regulatory (E&R) uncertainties, despite their enormous impact on the project cashflows. Consequently, this review analyzes, classifies, and discusses...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/386202 |
| Acceso en línea: | https://hdl.handle.net/2117/386202 https://dx.doi.org/10.3390/en16020882 |
| Access Level: | acceso abierto |
| Palabra clave: | Energy policy Uncertainty Renewable energy Electricity price Real options Optimization Política energètica Àrees temàtiques de la UPC::Energies::Aspectes econòmics |
| Sumario: | Renewable energy is increasingly mobilizing more investment around the globe. However, there has been little attention to evaluating economic and regulatory (E&R) uncertainties, despite their enormous impact on the project cashflows. Consequently, this review analyzes, classifies, and discusses 130 articles dealing with the design of renewable energy projects under E&R uncertainties. After performing a survey and identifying the selected manuscripts, and the few previous reviews on the matter, the following innovative categorization is designed: sources of uncertainty, uncertainty characterization methods, problem formulations, solution methods, and regulatory frameworks. The classification reveals that electricity price is the most considered source of uncertainty, often alone, despite the existence of six other equally influential groups of E&R uncertainties. In addition, real options and optimization arise as the two main approaches researchers use to solve problems in energy system design. Subsequently, the following aspects of interest are discussed in depth: how modeling can be improved, which are the most influential variables, and potential lines of research. Conclusions show the necessity of modeling E&R uncertainties with currently underrepresented methods, suggest several policy recommendations, and encourage the integration of prevailing approaches. |
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