Managing Energy in Smart Homes Using Binary Particle Swarm Optimization

The greenhouse gas emission is increasing around the globe. In order to reduce its emission factor, the concept of microgrid is introduced, which integrates renewable energy sources. The microgrid has a point of common coupling which helps to exchange power with utility during different times of a day to meet load demand. Based on all the system constraints, an energy management strategy is proposed in this research work, which helps to minimize the power consumption peak and operating cost of microgrid. For this purpose the appliances of each smart home in the residential area and distributed generator of microgrid are scheduled using binary particle swarm optimization to economically meet the consumer demand considering the desired objectives. For this purpose, proposed strategy is employed for the economic energy management of homes and microgrid. Significance of the proposed strategy is proved through performing simulations.