Mode-Based Intelligent Control for On-Grid Hybrid Electrical System in Residential Building Prosumers
The rapid diffusion of smart home technologies imposes new energy challenges to residential prosumers. Considering the additional energy demands of these technologies and the difficulty of occupants to manage their energy consumption on a regular basis, the need for autonomous energy management systems arises. In the current literature, no widely accepted approach integrates all the power components of a modern prosumer that is applicable in various climate conditions. To that end, this study 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. 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. A new multimodal EMS is also presented in order to expand the prosumer's management capabilities. This EMS is equipped with multiple modes to satisfy different objectives throughout a year based on resident’s consumption preferences. Its performance is compared to the aforementioned single-mode fuzzy EMS. Due to the multiple objectives of the EMS, we utilized three different metrics including electricity bill and average state of charge (SOC). Analysis of the results exhibits a reduction in the yearly electricity bill and higher average SOC. The performance of the energy management systems has been tested using a residential prosumer simulation with data (weather, prices) taken from three regions with different climate characteristics over a period of three years.