Advancing towards a sustainable energy model, uncovering the untapped potential of rural areas
Vanessa Miramontes-Viña , Noelia Romero-Castro , M. Ángeles López-Cabarcos
AIMS Environmental Science ›› 2023, Vol. 10 ›› Issue (2) : 287 -312.
Rural areas are essential to moving towards the necessary sustainable energy transition and climate change mitigation through renewable energy (RE) technologies. However, RE planning and decision-making in rural locations have not been developed to date with a focus on the local level and accompanied by a careful and thorough assessment of the simultaneous availability of alternative RE sources in a specific territory. Quite differently, RE investments in rural locations have been primarily driven by the interests of large power utilities to exploit a particular RE source, with benefits escaping from the rural economies to end up in the income statements of those large corporations. There is a need to approach RE planning at the municipal scale considering the availability of alternative RE sources. This study suggests the development of a rural RE potential index that could help in the identification of appropriate locations for the implementation of hybrid renewable energy systems (HRESs). The construction of a composite indicator to measure rural RE potential is exemplified through a case study that deals with ten indicators in the context of Galician rural municipalities, involving different RE potentials and some technical or regulatory constraints. Equal weighting and Principal Component Analysis are considered alternative methods for the index construction. Municipalities are the relevant local decision level where energy policy should be focused in order to diversify both the RE mix and the investor base. The proposed index could be the basis for future analyses aimed at optimizing the design and implementation of HRESs in rural environments at a local-regional-national scale.
sustainable energy transition / sustainable rural development / rural renewable energy potential / composite indicator / Principal Component Analysis
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