A fuzzy logic energy management system of on-grid electrical system for residential prosumers

Abstract

The fast emergent of smart grid technologies in the last few decades has significantly altered the energy profiles of residential buildings by allowing them to resume an active role in generating energy in addition to consuming the energy delivered by the utility. This dual role has transformed residential buildings into prosumers (i.e., joint producer-consumers), imposing elevated energy management challenges as a result of the increased complexity in decision making. Considering the physical and time constraints of human residents, there is a need for automated intelligent energy management systems (EMSs) that achieve efficient decisions concerning power consumption needs and expenses. In the current literature, no widely accepted approach integrates all the power components of a modern prosumer aiming at reducing the electricity bill that is applicable in various climate conditions. To that end, this paper proposes a climate-independent fuzzy logic EMS that integrates solar and wind generators, battery energy system (BES), electric vehicle (EV) load, dynamic electricity pricing, and tariffs and has the goal of reducing the prosumer's electricity bill. To test the performance of the fuzzy management system, a residential prosumer simulation has been implemented with data (weather, prices) taken from three regions with different climate characteristics over a period of three years. Its performance is benchmarked against two different management systems – a simple rule-based system and a linear optimization approach – with results showing that the proposed method attained the lowest consumption cost.