Optimizing Home Energy Systems with Electric Vehicles for Sustainable Living

Enhancing the sustainability of the energy sector has emerged as a critical priority in combating climate change. To tackle this challenge while ensuring comfort and affordable energy for the population, this paper develops two energy management strategies for electric vehicles (EVs): one designed for EVs equipped with unidirectional chargers and another with bidirectional chargers. These strategies are integrated with load scheduling in a Smart Home (SH) with photovoltaic generation, and the problem is modeled in a multi-objective approach using Non-dominated Sorting Genetic Algorithm III as an optimization technique to achieve a trade-off between energy cost and user comfort. To analyze and compare the performance of these strategies under different operating patterns, a study case was conducted over a 1-year period (365 days) in a SH using a time-of-use tariff scheme and considering the costs associated with EV battery degradation. The results show an average daily reduction of 7.29% in energy costs, 7.65% in peak power demand, and 93.33% in peak energy consumption for solutions that maintain the same level of user comfort. These results underscore the technical and economic feasibility of using bi-directional chargers.