SEHAS: A Novel Metaheuristic Algorithm for Home Appliances Scheduling in Smart Grid

Abstract

The home appliance scheduling (HAS) problem is a critical issue in the home energy management system (HEMS). The aim of the HAS is to control the appliances at home more efficiently and economically. However, there is still plenty room for improvement because the home appliances scheduling problem is a challenging issue due to its complexity. Many researchers have proposed schemes to solve this problem, but most of the results are either unsatisfied or taking too much computation effort but with limited performance improvement. In this paper, we propose a novel metaheuristic algorithm called search economics for home appliances scheduling (SEHAS) to address this issue more efficiently. SEHAS approach is based on search economies (SE). We first formulate the the HAS problem as a knapsack problem, and then we define our objectives as minimization of the electricity cost. We then present the proposed SEHAS in details to show how it can solve the scheduling problem efficiently. To better evaluate our proposed scheme, we conduct simulations to compare results with two classical metaheuristic algorithm, including genetic algorithm (GA) and ant colony optimization (ACO) algorithms. The experimental results show that when compared to the scenario without any scheduling algorithm that GA and ACO can reduce the electricity cost 17.60% and 18.05% respectively, and the proposed metaheuristic algorithm SEHAS can save the cost up to 19.29%. In addition, GA, ACO and SEHAS can reduce peak-to-average ratio (PAR) 13.53%, 24.01% and 24.01% respectively.