Optimal self-scheduling of home appliances and electrical vehicles with Home Energy Management System [comunicação oral]

Abstract

This work investigates the self-scheduling of home appliances and provides a timeline for optimal charging of Electric Vehicles (EVs) at home. The model utilizes a computer-based self-scheduling algorithm to minimize the cost of electricity while the preferences of the end-users have been considered in the model. Different electricity tariffs have been simulated in this study to assess the electricity costs of residential end-users in Portugal. The cost reduction strategy is expected to change consumer behavior while consumer preferences are maintained. In addition, the other home appliances will be organized in such a way as to respect the preferences of the end-users in terms of plugging time and utilization of the controllable home appliances. The model is elaborated as a Home Energy Management System (HEMS), represented as a standard Mixed-Integer Linear Programming (MILP) optimization problem. The developed model is tested and verified for cost reduction strategy at the residential level while the possibility of EV charging at home is considered. A typical load profile is selected to test the HEMS capability. The cost reduction potentials for the given smart home for different electricity tariffs have been elaborated.