Optimized Intelligent Controller for Energy Storage based Microgrid towards Sustainable Energy Future
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 th...
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my.uniten.dspace-343512024-10-14T11:19:13Z Optimized Intelligent Controller for Energy Storage based Microgrid towards Sustainable Energy Future Abu S.M. Hannan M.A. Mansor M. Ker P.J. Yaw Long C. 58116063000 7103014445 6701749037 37461740800 58902792500 battery fuel cell hybrid energy storage integrated grid hydrogen optimization algorithm solar supercapacitor sustainable Battery storage Benchmarking Electric batteries Electric loads Energy conservation Hybrid systems Hydrogen storage MATLAB Particle swarm optimization (PSO) Renewable energy Solar power generation Supercapacitor Two term control systems Uninterruptible power systems Battery Energy future Hybrid energy storage Hybrid energy storage integrated grid Hybrid energy system Microgrid Optimization algorithms Solar Sustainable Sustainable energy Fuel cells 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. Final 2024-10-14T03:19:13Z 2024-10-14T03:19:13Z 2023 Conference Paper 10.1109/ETFG55873.2023.10407475 2-s2.0-85185816290 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185816290&doi=10.1109%2fETFG55873.2023.10407475&partnerID=40&md5=48fbe720fd0c268642fe468be7a38eed https://irepository.uniten.edu.my/handle/123456789/34351 Institute of Electrical and Electronics Engineers Inc. Scopus |
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battery fuel cell hybrid energy storage integrated grid hydrogen optimization algorithm solar supercapacitor sustainable Battery storage Benchmarking Electric batteries Electric loads Energy conservation Hybrid systems Hydrogen storage MATLAB Particle swarm optimization (PSO) Renewable energy Solar power generation Supercapacitor Two term control systems Uninterruptible power systems Battery Energy future Hybrid energy storage Hybrid energy storage integrated grid Hybrid energy system Microgrid Optimization algorithms Solar Sustainable Sustainable energy Fuel cells |
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battery fuel cell hybrid energy storage integrated grid hydrogen optimization algorithm solar supercapacitor sustainable Battery storage Benchmarking Electric batteries Electric loads Energy conservation Hybrid systems Hydrogen storage MATLAB Particle swarm optimization (PSO) Renewable energy Solar power generation Supercapacitor Two term control systems Uninterruptible power systems Battery Energy future Hybrid energy storage Hybrid energy storage integrated grid Hybrid energy system Microgrid Optimization algorithms Solar Sustainable Sustainable energy Fuel cells Abu S.M. Hannan M.A. Mansor M. Ker P.J. Yaw Long C. Optimized Intelligent Controller for Energy Storage based Microgrid towards Sustainable Energy Future |
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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. |
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58116063000 |
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58116063000 Abu S.M. Hannan M.A. Mansor M. Ker P.J. Yaw Long C. |
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Conference Paper |
author |
Abu S.M. Hannan M.A. Mansor M. Ker P.J. Yaw Long C. |
author_sort |
Abu S.M. |
title |
Optimized Intelligent Controller for Energy Storage based Microgrid towards Sustainable Energy Future |
title_short |
Optimized Intelligent Controller for Energy Storage based Microgrid towards Sustainable Energy Future |
title_full |
Optimized Intelligent Controller for Energy Storage based Microgrid towards Sustainable Energy Future |
title_fullStr |
Optimized Intelligent Controller for Energy Storage based Microgrid towards Sustainable Energy Future |
title_full_unstemmed |
Optimized Intelligent Controller for Energy Storage based Microgrid towards Sustainable Energy Future |
title_sort |
optimized intelligent controller for energy storage based microgrid towards sustainable energy future |
publisher |
Institute of Electrical and Electronics Engineers Inc. |
publishDate |
2024 |
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1814061051771092992 |
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13.222552 |