Mutation operator integrated ant colony optimization based domestic appliance scheduling for lucrative demand side management

Abstract The unceasing growth of energy consumption demands has staggeringly broaden the gap between energy demand and supply during peak hours resulting a significant rise in the monetary value of grid electricity. Appliance scheduling with heuristic algorithms considered as a potential solution approach. Nevertheless, the plausibility of Ant Colony Optimization based scheduling has become controversial due to the tendency for premature convergence. Hence, herein we propose a mutation operator integrated ant colony optimization scheduling scheme with pre-defined consumption thresholds to minimize electricity cost and waiting time, while alleviating the disputed drawback of ant colony optimization. The proposed scheduling scheme was compared with existing ant colony optimization based energy management controller and obtained 5.44% reduction from total cost. Hence, comparative analysis confirms superiority of proposed work in terms of reducing cost, peak load, waiting time, and Peak-to-Average Ratio, affirming its potential to mainstream as a lucrative solution for demand side management problems.