Cost Reduction of Integrated Renewable Energy Sources in Home Energy Management Systems (HEMS) using Particle Swarm Optimization

The purpose of this study is to optimize the 24-hour scheduling of various household appliances (schedulable appliances, entertainment appliances, and constrained appliances) to minimize the total cost of energy consumption. This approach is achieved by calculating and leveraging the lower cost of photovoltaic (PV) power supply during the day and minimizing reliance on grid power which is more expensive than PV power supply. Particle Swarm Optimization is used in this study which is inspired by the social behavior of swarm animals such as ants, bees and birds flocking. The optimization determines the optimal on/off schedule for each appliance, ensuring cost efficiency while considering the availability of renewable energy which is PV source in this case. It is different from conventional and traditional optimization methods such as gradient descent or linear programming and the comparison results are represented here.