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- Energy efficiency in buildings by using evolutionary algorithms: an approach to provide efficiency choices to the consumer, considering the rebound effectPublication . Santos, Ricardo; Matias, João; Abreu, AntónioEnergy efficiency can be achieved, by making optimal choices of household appliances, based on specific rules for consumption and use. However, it's not always possible to achieve good solutions, since in general, an efficient equipment, with an economic consumption savings during his life cycle, is usually an expensive one, with a high initial investment. Additionally, the interaction of these choices, associated with consumer behavior, could lead toward to efficient losses during the lifecycle of the equipment, and then to a situation of indirect rebound effect. In this work, it is presented an approach, applied to the residential buildings, by using evolutionary algorithms to support consumer decisions. The approach presented here, could promote energy efficiency by providing the consumer with several optimal and feasible solutions, and at the same time, with information about the impact of his choices made on future.
- Evolutionary algorithms on reducing energy consumption in buildings: An approach to provide smart and efficiency choices, considering the rebound effectPublication . Santos, Ricardo; Matias, João; Abreu, António; Reis, FranciscoThis paper presents a model to promote energy efficiency among household appliances, by supporting the consumer decisions through the maximization of his savings, associated to a set of electrical appliances from the market to be acquired. Not always an efficient equipment from the market, is more expensive than a less efficient one, which can lead the consumer to compromise the expected savings on future. Given the several models/brands available on market and its possible combinations, the problem can be defined as a combinatorial problem, whose complexity can compromise the efficiency of using deterministic algorithms. Genetic algorithms (GM) were therefore included in the model, whose results were compared later with Simplex to verify the quality of the obtained solutions, as well as their performance. In addition, it was performed a statistical analysis of the obtained results, as well as a sensitivity analysis of GAs parameters, to validate their robustness. we conclude that the proposed method can provide several efficient solutions to the problem, as well as sensitize the consumer to their choices made on future, by estimating their corresponding rebound effect.
- Getting eflcient choices in buildings by using Genetic Algorithms: assessment & validationPublication . Santos, Ricardo; Matias, João; Abreu, AntónioThe energy consumption in buildings, can be reduced through a rational choice of the household appliances to be acquired. This choice can be based, on a specific criteria, settled according to the consumer needs. However, such choice, still needs to be optimized, since in general, an efficient equipment has a high investment, although a low energy consumption. Genetic Algorithms (GAs) are used therefore, as an optimization technique, to get efficient and several solutions, based on those pre-selected from the market, and according to a set of criteria. However, there is a need to assess its robustness as well as its consistence in terms of convergence results. The quality of its solutions is also assessed, by comparing GAs results with those, obtained from Simplex method. The problem formulation, and its influence on GAs results, is also considered on this work, where it’s chosen the best one, among four proposed. In this paper it is presented a methodology that allows to promote energy efficiency in buildings, by achieving savings in terms of initial investment, energy consumption and CO2 emissions for the consumer. It is shown that GAs, can provide several and optimal solutions, through formulation and parameters suitable.