Optimized Intelligent Controller for Energy Storage based Microgrid towards Sustainable Energy Future - Abu S.M. (Institute of Electrical and Electronics Engineers Inc., 2024)
This study focuses on a sustainable microgrid-based hybrid energy system (HES), primarily focusing on analyzing the performance of the fuel cell and its impact on the overall HES into optimizing system performance. This system relies on a single renewable energy source, a photovoltaic (PV) system that is integrated with the energy storage system (ESS) including hydrogen-based fuel cell, battery, and supercapacitor for effective power management. The optimization of HES performance is achieved through fine-tuning of the proportional-integral (PI) controller using the particle swarm optimization (PSO) algorithm. The load profile utilized in the microgrid (MG) is characterized by a constant power output, ensuring a stable and uninterrupted supply of electricity from 6am to 6pm in a 24-hour time period. This approach is comparable to meeting the specific demands of industrial and critical facilities, such as manufacturing plants and hospitals, where continuous power is important. The selection of a constant load profile is benchmark with the alignment of Denham Hydrogen Demonstration Plant, Western Australia, enhancing the MG's overall reliability and validation into real-world application. Through simulation and analysis using MATLAB Simulink, the results demonstrate the remarkable impact of PSO on enhancing the fuel cell system's efficiency with air consumption, and fuel consumption reduction by utilization of 90% of the H2 to electrical energy. Significantly, the optimized total source power output enables seamless energy storage and intelligent load matching, leading to a stable and reliable grid power supply. This research study findings highlights the essential role of PSO in elevating sustainability and maximizing resource utilization within microgrid-based hybrid energy systems, establishing a pathway towards a greener and more sustainable energy future. 2023 IEEE.