The growing integration of renewable energy production and important loads such as electric vehicles bring a lot of challenges to today’s electric systems. Demand-side management strategies are often presented as one of the solutions to these problems. In this study, a fuzzy logic supervision system is proposed to minimize energy transmission costs in distribution grids by controlling electric vehicles charging and electric water heater activation. The supervision system takes into account the production of renewable energy within the grid, the load consumption and other parameters including the comfort of the user. A genetic algorithm is used to optimize the supervisor’s parameters. Finally, the system’s performance is confirmed through simulation bytesting it on real distribution grid data.