 In recent years, demand side management, DSM, techniques have been developed for residential, industrial and commercial sectors. These techniques are highly effective in flattening the load profiles of customers in grid area networks. To address the issue of managing residential loads in a smart grid, a heuristic algorithms-based energy management controller was designed. Five algorithms were evaluated, genetic algorithm, GA, binary particle swarm optimization, BPSO, bacterial foraging optimization algorithm, BFOA, wind-driven optimization, WDO, and hybrid genetic wind-driven, GWD. The algorithms were tested in two scenarios, scheduling the load of a single home and scheduling the load of multiple homes. Our proposed GWD algorithm performed best in terms of the selected performance metrics. This article was authored by Nadim Javade, Sakina Javade, Wadud Abdull, and others.