ENERGY MANAGEMENT IN BUILDINGS

With the emergence of smart grid (SG), the consumers have the opportunity to integrate renewable energy sources (RESs) and take part in demand side management. In this paper, we introduce generic home energy management control system (HEMCS) to efficiently schedule the household load and integrate RESs. The HEMCS is based on the genetic algorithm, binary particle swarm optimization, winddriven optimization (WDO), and our proposed genetic WDO algorithm to schedule appliances of single and multiple homes. For energy cost calculation, real-time pricing (RTP) and inclined block rate schemes are combined, because in case of only RTP, there is a possibility of building peaks during off-peak hours that may damage the entire power system.Moreover, to control the demand under the grid station capacity, the feasible region is defined and a problem is formulated using multiple knapsack. Energy efficient integration of RESs in SG is a challenging task due to time varying and their intermittent nature. The simulation results show that the proposed scheme avoids voltage rise problem in areas with high penetration of renewable energy. Moreover, the proposed scheme also reduces the electricity cost up to 48% and peak to average ratio of aggregated load up to 37.69%. INDEX TERMS Renewable energy sources, demand side management, load scheduling, meta-heuristic techniques, trading/cooperation.