Publication:
Optimized Intelligent Controller for Energy Storage based Microgrid towards Sustainable Energy Future

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dc.citedby0
dc.contributor.authorAbu S.M.en_US
dc.contributor.authorHannan M.A.en_US
dc.contributor.authorMansor M.en_US
dc.contributor.authorKer P.J.en_US
dc.contributor.authorYaw Long C.en_US
dc.contributor.authorid58116063000en_US
dc.contributor.authorid7103014445en_US
dc.contributor.authorid6701749037en_US
dc.contributor.authorid37461740800en_US
dc.contributor.authorid58902792500en_US
dc.date.accessioned2024-10-14T03:19:13Z
dc.date.available2024-10-14T03:19:13Z
dc.date.issued2023
dc.description.abstractThis 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.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1109/ETFG55873.2023.10407475
dc.identifier.scopus2-s2.0-85185816290
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85185816290&doi=10.1109%2fETFG55873.2023.10407475&partnerID=40&md5=48fbe720fd0c268642fe468be7a38eed
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/34351
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023
dc.subjectbattery
dc.subjectfuel cell
dc.subjecthybrid energy storage integrated grid
dc.subjecthydrogen
dc.subjectoptimization algorithm
dc.subjectsolar
dc.subjectsupercapacitor
dc.subjectsustainable
dc.subjectBattery storage
dc.subjectBenchmarking
dc.subjectElectric batteries
dc.subjectElectric loads
dc.subjectEnergy conservation
dc.subjectHybrid systems
dc.subjectHydrogen storage
dc.subjectMATLAB
dc.subjectParticle swarm optimization (PSO)
dc.subjectRenewable energy
dc.subjectSolar power generation
dc.subjectSupercapacitor
dc.subjectTwo term control systems
dc.subjectUninterruptible power systems
dc.subjectBattery
dc.subjectEnergy future
dc.subjectHybrid energy storage
dc.subjectHybrid energy storage integrated grid
dc.subjectHybrid energy system
dc.subjectMicrogrid
dc.subjectOptimization algorithms
dc.subjectSolar
dc.subjectSustainable
dc.subjectSustainable energy
dc.subjectFuel cells
dc.titleOptimized Intelligent Controller for Energy Storage based Microgrid towards Sustainable Energy Futureen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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