A Novel Predictive Fuzzy Logic-Based Energy Management System for Grid-Connected and Off-Grid Operation of Residential Smart Microgrids

Abstract

In this paper, a novel energy management system (EMS) with two operating horizons is proposed for a residential microgrid application. The microgrid utilizes the energies of a photovoltaic, a fuel cell (FC), and a battery bank to supply the local loads through a combination of electric and magnetic buses. The proposed microgrid operates in a large number of grid-connected and off-grid operation modes. The EMS includes a long-term data prediction unit based on a 2-D dynamic programing and a short-term fuzzy controller. The long-term prediction unit is designed to determine the appropriate variation range of the battery state of charge and FC state of hydrogen. The efficiency performance of the microgrid components, predicted energy generation and demand, energy cost, and the system constraints are taken into account. The resultant data then are sent to the short-term fuzzy controller which determines the operation mode of the microgrid based on the real-time condition of the microgrid elements. A prototype of the proposed microgrid including the EMS is developed, and experimental tests are conducted for three different energy management scenarios. The proposed management technique is validated through energy distribution and cost analysis.