Residential Energy Management System utilizing Fuzzy Based Decision-Making

With regard to energy consumption, the advent of smart grid technologies has advanced buildings from simple passive consumers into sophisticated active agents able to manage and exchange locally generated energy. Additionally, the increasing penetration of smart home technologies and smart devices into daily lives have increased the energy demand of modern residential buildings. Naturally, the need for advanced intelligent decision-making systems in energy management of buildings has become eminent. Currently, there is no widely used approach that manages a two-way electricity flow in smart buildings purely driven by the goal of reducing the electricity bill. To that end, this paper proposes a fuzzy controller which concurrently handles solar and wind generators, Battery Energy System (BES), Electric Vehicle (EV) load, dynamic electricity pricing, and tariffs. The controller aims at reducing the electricity bill by handling the charging/discharging power of BES and the power exchange with the grid (PEG). In this paper, for validation purposes the energy consumption management in a simulated home is carried out for a period of a month showcasing the performance of the proposed controller.