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Advancing sustainable energy solutions
Publication . Mendonça, Maria Mendes; Santos, Vítor; NOVA Information Management School (NOVA IMS); Information Management Research Center (MagIC) - NOVA Information Management School; Elsevier
The effects of global warming are becoming increasingly evident in our daily lives, making it essential to develop sustainable, carbon-neutral solutions. The energy sector is a major contributor to global warming due to its reliance on coal, oil, and natural gas. Therefore, transitioning to renewable energy is crucial. However, renewable sources face intermittency issues, as their availability depends on weather conditions. To address this, a hybrid energy system that integrates multiple renewable sources can enhance reliability. This study optimized a hybrid renewable energy system for Portugal. It began with a systematic literature review on artificial intelligence and energy, identifying nine relevant studies that helped formulate the problem. A hybrid system incorporating solar panels and wind turbines was designed and optimized using a novel algorithm that combined Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO). By leveraging the strengths of both methods, the algorithm improved convergence toward the global optimum. To further enhance efficiency, the algorithm was parallelized to reduce execution time and computational demands. Three experiments were conducted to optimize the system. In the first experiment, the Average Best Fitness (ABF) started below 0.420, decreased to 0.390 by the third iteration, but later increased to approximately 0.400. To improve performance, hyperparameters were adjusted in a second experiment. However, results worsened, with ABF starting at 0.480 and only reaching 0.455 by iteration 14. The third experiment yielded the most promising results, with an initial ABF of 0.150, followed by a sharp drop at iteration 3 and a gradual decline with fluctuations. Future research should explore a broader range of hyperparameter combinations to refine optimization results. Additionally, incorporating economic and social objectives alongside technical and environmental criteria will provide a more comprehensive assessment of hybrid energy systems.
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Fundação para a Ciência e a Tecnologia
Programa de financiamento
Concurso de avaliação no âmbito do Programa Plurianual de Financiamento de Unidades de I&D (2017/2018) - Financiamento Base
Número da atribuição
UIDB/04466/2020