Designing a Smart Home Energy Management System to Improve Cost/Comfort Factor

Home energy management systems optimize the energy buying/selling amount to reduce high costs by increasing individual energy consumption. Shifting the consumption time depending on the tariff is provided as cost, and the more effective and automatic operation of the devices is offered to the user as comfort. In the study, a hardware and software are developed that can estimate solar energy potential, energy consumption and automatically regulate the comfort/cost ratio of domestic energy using these data. Battery status, electricity buying/selling price, weather condition and consumption forecast data are evaluated by fuzzy logic algorithm and provide the ratio of comfort and cost effectiveness. The obtained comfort and cost effectiveness determine the optimum energy supply amount between the battery, grid and solar energy using the simulated annealing algorithm. As a result of the study, it has been determined that the energy cost for the user has decreased and the comfort has increased.