Optimal Scheduling of Household Appliances in Off-Grid Hybrid Energy System using PSO Algorithm for Energy Saving

Abstract

 In a stand-alone renewables energy system (SRES), maintaining the balance of power between supply and demand with minimum cost in homes connected to these systems present one of the most important challenges to consider. In SRES, a large capacity of batteries is usually used to store the energy and reuse it when the absence or insufficient power supply to maintain energy balance. However, the batteries are costly, as well as a large amount of power lost during the charging and discharging process, represent big issues that should be avoided. One of the most important tools to redress these issues is the scheduling strategy for household appliances. In this paper, Particle Swarm Optimization Algorithm (PSO) is proposed to schedule the household appliances in the off-grid hybrid energy system (PV, Wind turbine, batteries, and diesel generator) with the objective of saving energy and reduce the energy consumption cost (i.e. energy of diesel) by maximizing the using the power of renewable energy sources and minimizing using the power of batteries. The scheduling algorithm is based on the data forecast of one day ahead of renewable energy and the daily load power consumption profile, a case study of meteorological data in the south of Spain are selected and tested for the simulation. Two scenarios of scheduling strategy are presented and compared with the scenario without scheduling of appliances. The simulation results show that the optimization of cost reached to 50% with 0.472 kWh of energy saved in scheduling with user preferences and can be reached up to 64% with 0.811 kWh of energy saved in case of optimal scheduling which considered the optimal for saving energy.