Fuzzy energy management controller and scheduler for smart homes

Abstract

The integration of information and communication technologies in traditional grid brings about a smart grid. Energy management plays a vital role in maintaining the sustainability and reliability of a smart grid which in turn helps to prevent blackouts. Energy management at consumer's side is a complex task, it requires efficient scheduling of appliances with minimum delay to reduce peak-to-average ratio (PAR) and energy consumption cost. In this paper, the classification of appliances is introduced based on their energy consumption pattern. An energy management controller is developed for demand side management. We have used fuzzy logic and heuristic optimization techniques for cost, energy consumption and PAR reduction. Fuzzy logic is used to control the throttleable and interruptible appliances. On the other hand, the heuristic optimization algorithms, BAT inspired and flower pollination, are employed for scheduling of shiftable appliances. We have also proposed a hybrid optimization algorithm for the scheduling of home appliances, named as hybrid BAT pollination optimization algorithm. Simulation results show a significant reduction in energy consumption, cost and PAR.