A Heuristic-based Home Energy Management System for Demand Response

The so-called Internet of Things (IoT) and advanced communication technologies have already demonstrated a great potential to manage residential energy resources via demand-side management. This work presents a home energy management system in that focused on the energy reallocation problem where consumers shall shift their energy consumption patterns away from peak periods and/or high electricity prices. Our solution differentiates residential loads into two categories: (i) fixed power appliances and (ii) flexible ones. Therefrom, we formulate our problem as constraint optimization problem, aiming to reduce the electricity cost based on day-ahead prices and the peak-to-average ratio. To solve this problem, two well-known heuristics, the Genetic Algorithm (GA) and the Harmony Search Algorithm (HSA), are employed. These two approaches are compared to the case where no reallocation happens. Our numerical results show that both methods; GA and HSA can effectively reduce the electricity cost by 0.9%, 3.98 %, and PAR by 15%, 5.8%, respectively.