Multi-factorial methodology for Wind Power Plant repowering optimization: A Spanish case study
Due to the climate change, there have been changes in the rhythm of nature over the last decades. In addition, there has been an increasing social consciousness regarding decarbonization and emissions, promoting governments new policies and economic support measures for renewable integration. In thi...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universidad a Distancia de Madrid (UDIMA) |
| Repositorio: | udiMundus. Repositorio Institucional de la Universidad a Distancia de Madrid |
| OAI Identifier: | oai:udimundus.udima.es:20.500.12226/1889 |
| Acceso en línea: | http://hdl.handle.net/20.500.12226/1889 |
| Access Level: | acceso abierto |
| Palabra clave: | Wind Power Plants (WPP) Repowering Multi-Criteria Decision Making (MCDM) Optimal planning |
| Sumario: | Due to the climate change, there have been changes in the rhythm of nature over the last decades. In addition, there has been an increasing social consciousness regarding decarbonization and emissions, promoting governments new policies and economic support measures for renewable integration. In this scenario, the participation of the onshore and offshore wind sectors play a crucial role, expecting that more than 6000 GW will be globally installed in 2050. In parallel, the useful life of other wind power plants is coming to their end. Therefore, some countries will face in the coming years the decision of repowering, decommissioning, installing new turbines, or a combination of them. In general, the areas with the greatest wind potential are already occupied by relatively old wind turbines. Subsequently, a complex group of factors influences on the most appropriate solution decision-making, involving climatic, technological, environmental, social or economic aspects. This paper proposes an optimized methodology based on multi-criteria decision-making to estimate the most appropriate solution for extending the useful-life of wind power plants. An initial group of 26 factors were identified, corresponding to seven categories: technical, geographic, socio-environmental, location, economic, political and climate. The methodology is divided into three stages: (i) data, (ii) alternatives, and (iii) optimization. It was assessed with a Spanish onshore wind power plant connected to the grid. From the initial data and factors, 11 alternatives were designed based on a selection of 10 most relevant factors. The results provide an optimal solution, combining both repowering and installation of new wind turbines. From the results, this methodology would allow reducing the LCOE of the new wind plants installed in the European Union by more than 50%. |
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