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- Energy transition process and community engagement on geographic islands: the case of Culatra Island (Ria Formosa, Portugal)Publication . Pacheco, André; Monteiro, Jânio; Santos, Joni; Sequeira, Claudia; Nunes, J.Islands have the potential to be precursors in the transition to clean energy, by adopting new technologies and applying innovative solutions that can serve as showcases at an international level. This paper is a contribution towards understating the importance of community engagement on energy transition processes. It covers multiple aspects of a green transition process, including technical, environmental, social, and economic issues. Starting by a participatory diagnosis process, the community of a small island located in Portugal (Culatra Island, Algarve), was challenged to lead the transition process and define different pillars of energy transition. The process brought together local authorities, academia, citizens and companies. Using practical examples, it is shown how the community is succeeding in tailoring new technological solutions for a green transition, according with the specific needs of the island, as expressed by the islanders themselves, including batteries, electric vehicles, retrofitting of homes, or heat pumps, which, when combined, could lay the foundations for the creation of a Renewable Energy Community and leverage socioeconomic benefits.
- On a new method to design solar photovoltaic systems in renewable energy communities: The case of Culatra Island (Ria Formosa, Portugal)Publication . Ewart, M.; Santos, J.; Pacheco, A.; Monteiro, Jânio; Sequeira, ClaudiaIslands must reach sustainable lifestyles by improving resources management and by getting accustomed to renewable energy sources. Culatra, a small Portuguese island, is actively increasing renewable energy penetration into local processes in order to be the first 100% sustainable Portuguese territory by 2030. Based on the electric consumption of Culatra, the objective of the present study is to project a photovoltaic unit composed of several sub-fields, each with a distinct orientation, in order to increase the self-consumption ratio while at the same time reducing the surplus of energy production, assessed by the self-sufficiency ratio criteria, resulting in a lower levelised cost of energy of the power system. To achieve this, MATLAB's implementation of a genetic algorithm was used to find the optimised set of orientations for a given load profile. The results indicate that it is possible to optimise the photovoltaic plant to reach a more continuous electricity generation through daytime, reducing the storage needs and increasing the value of photovoltaic systems. The method can be extended to other locations or demand curves, assisting on comparing different energy management strategies, and their respective advantages and disadvantages.