Efficient energy management for smart homes with grey wolf optimizer

Abstract

In this paper, a new swarm intelligence based algorithm called Grey Wolf Optimizer (GWO), mimicking the social hierarchy and hunting behavior of grey wolves, is used to optimally schedule the operation of Energy Storage Unit (ESU) in smart homes. The aim is to reduce the cost of power consumption and balance the load on the power grid. This is achieved by drawing the power from the grid when the price is cheap and using the excess power to store is the battery (ESU) and drawing from the ESU when the price is expansive. The algorithm determines when the power should be drawn from the grid and when the power should be drawn from the stored unit for each hour of the day. The algorithm was tested on the data collected from the Chicago region by the department of energy, United States. The results were compared with Particle Swarm Optimization (PSO) on the same dataset. GWO provides up to 25.57% of cost saving compared to PSO. In addition, GWO does not impose any restrictions on the consumer to use appliance at any time providing total freedom and still saving money.