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Backtracking Search Algorithm Based Fuzzy Charging-Discharging Controller for Battery Storage System in Microgrid Applications

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dc.citedby19
dc.contributor.authorFaisal M.en_US
dc.contributor.authorHannan M.A.en_US
dc.contributor.authorKer P.J.en_US
dc.contributor.authorUddin M.N.en_US
dc.contributor.authorid57215018777en_US
dc.contributor.authorid7103014445en_US
dc.contributor.authorid37461740800en_US
dc.contributor.authorid55663372800en_US
dc.date.accessioned2023-05-29T07:28:09Z
dc.date.available2023-05-29T07:28:09Z
dc.date.issued2019
dc.descriptionBattery management systems; Charging (batteries); Controllers; Fuzzy logic; Fuzzy sets; Learning algorithms; Loading; Membership functions; Optimization; Particle swarm optimization (PSO); Secondary batteries; Backtracking search algorithms; Battery energy storage; Battery energy storage systems; Fuzzy controllers; Fuzzy logic control system; Fuzzy membership function; Micro grid; State of charge; Battery storageen_US
dc.description.abstractThis paper presents an efficient fuzzy logic control system for charging and discharging of the battery energy storage system in microgrid applications. Energy storage system can store energy during the off-peak hour and supply energy during peak hours in order to maintain the energy balance between the storage and microgrid. However, the integration of battery storage system with microgrid requires a flexible control of charging-discharging technique due to the variable load conditions. Therefore, a comparative evaluation of the developed model is analyzed by considering controllers with fuzzy only and optimized fuzzy algorithms. In this paper, backtracking search algorithm based fuzzy optimization is introduced to evaluate the state of charge of the battery by optimizing the input and output fuzzy membership functions of rate of change of the state of charge and power balance. Backtracking search algorithm is chosen due to its high convergence speed, and it is good for searching and exploration process with exploiting capabilities. To validate the performance of the developed controller, the obtained results are compared to the results obtained with the particle swarm optimization based fuzzy and fuzzy only controllers, respectively. Results show that the backtracking search algorithm based fuzzy optimization outperforms the other control methods in terms of effectively manage the charging-discharging of the battery storage to ensure the desired outcome and reliable microgrid operation. � 2013 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo8890729
dc.identifier.doi10.1109/ACCESS.2019.2951132
dc.identifier.epage159368
dc.identifier.scopus2-s2.0-85078288796
dc.identifier.spage159357
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85078288796&doi=10.1109%2fACCESS.2019.2951132&partnerID=40&md5=2e5728912b4968ef35d144f70caf9a8a
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24871
dc.identifier.volume7
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofAll Open Access, Gold
dc.sourceScopus
dc.sourcetitleIEEE Access
dc.titleBacktracking Search Algorithm Based Fuzzy Charging-Discharging Controller for Battery Storage System in Microgrid Applicationsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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