Estudo e desenvolvimento de abordagens multiobjetivo baseadas em programação linear e em metaheurísticas para otimização do custo com energia elétrica e do conforto do usuário

• Ano de defesa: 2018
• Autor(a) principal: Albuquerque, Pedro Urbano Braga de
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Teleinformática; Algoritmo genético; Energia elétrica - Otimização; Programação linear; Smart homes; Genetic algorithm; Energy efficiency; Integer linear programming; Pareto front
• Link de acesso: http://www.repositorio.ufc.br/handle/riufc/39409

Residential home automation is typically based on a Smart Home Controller (SHC) that controls the main loads and devices used in a home and helps reduce energy costs. This work presents a multi-objective approach to maximize energy savings and maximize comfort through a SHC with demand control in a variable rate system. The formalization of the problem was initially done through Integer Linear Programming (ILP), in which a weight aggregation function is presented for the two objectives under analysis, and finally a multiobjective meta-heuristic was implemented to treat the bi-objective, based Genetic Algorithm by means of the approximation of a Pareto frontier for automatic definition of the drive of the loads, thus offering the user options of choice, considering the criteria energy consumption and comfort. The differential of this proposal is the use of a new definition for objective function related to comfort, with the activation of loads with more than one daily operating cycle. The results of the algorithm used specify the best times to connect the loads (real household appliances) according to the constraint given by the contracted demand value and the user preferences. The efficacy of the proposed solution is demonstrated using the Weight Based Genetic Algorithm (WBGA) and Pareto Envelope-based Selection Algorithm II (PESA II) optimization techniques in a real smart home controller system in a mid-sized home. The results of the simulations demonstrated the generation of solutions that can reach an economy of more than 51% and comfort of over 96%, compared to the initial user preferences, giving the possibility of choosing the solution that best suits your needs.