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Advancements in intelligent cloud computing for power optimization and battery management in hybrid renewable energy systems: A comprehensive review

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dc.citedby21
dc.contributor.authorAL-Jumaili A.H.A.en_US
dc.contributor.authorMuniyandi R.C.en_US
dc.contributor.authorHasan M.K.en_US
dc.contributor.authorSingh M.J.en_US
dc.contributor.authorPaw J.K.S.en_US
dc.contributor.authorAmir M.en_US
dc.contributor.authorid57212194331en_US
dc.contributor.authorid14030355800en_US
dc.contributor.authorid55057479600en_US
dc.contributor.authorid58765817900en_US
dc.contributor.authorid58168727000en_US
dc.contributor.authorid57210089902en_US
dc.date.accessioned2024-10-14T03:17:34Z
dc.date.available2024-10-14T03:17:34Z
dc.date.issued2023
dc.description.abstractA cloud computing-based power optimization system (CC-POS) is an important enabler for hybrid renewable-based power systems with higher output, optimal solutions to extend battery storage life, and remotely flexible power distribution control. Recent advancements in cloud computing have begun to deliver critical insights, resulting in adaptive-based control of storage systems with improved performance. This study aims to review the recently published literature on the topic of power management systems and battery charging control. The role of intelligent based cloud computing is to improve the battery life and manage the battery state of charge (SoC). To achieve this purpose, publishers� databases and search engines were used to obtain the studies reviewed in this paper. We identify and review the purpose, achievements, tools/algorithm, and recommendations for each survey work, and thus outline a number of key findings and future directions. Furthermore, the review includes a listing of novels and recently used algorithms. Additionally, a critical review of 174 research articles were analyzed as per Web of Science (WoS) and Scopus database. The key findings of this study are discussed in two key conceptual frameworks that contain a power optimization system and an optimal battery management system. The power transmission, distribution, and charge and discharge processes are controlled and stored on cloud computing using the power mix between hybrid renewable energy and other power sources. � 2023 The Author(s)en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1016/j.egyr.2023.09.029
dc.identifier.epage2227
dc.identifier.scopus2-s2.0-85171323575
dc.identifier.spage2206
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85171323575&doi=10.1016%2fj.egyr.2023.09.029&partnerID=40&md5=e0dbc7b80dc1dff0de0f89edbe660e34
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/33978
dc.identifier.volume10
dc.pagecount21
dc.publisherElsevier Ltden_US
dc.relation.ispartofAll Open Access
dc.relation.ispartofGold Open Access
dc.sourceScopus
dc.sourcetitleEnergy Reports
dc.subjectBattery life
dc.subjectBattery management
dc.subjectCloud computing
dc.subjectPower consumption
dc.subjectRenewable energy systems
dc.subjectState of charge
dc.subjectAdaptive control systems
dc.subjectBattery management systems
dc.subjectCharging (batteries)
dc.subjectCloud computing
dc.subjectComputing power
dc.subjectElectric power distribution
dc.subjectElectric power transmission
dc.subjectGreen computing
dc.subjectRenewable energy resources
dc.subjectSearch engines
dc.subjectSecondary batteries
dc.subjectBattery life
dc.subjectBattery Management
dc.subjectCloud-computing
dc.subjectEnergy systems
dc.subjectHybrid renewable energies
dc.subjectOptimization system
dc.subjectPower Optimization
dc.subjectRenewable energies
dc.subjectRenewable energy system
dc.subjectStates of charges
dc.subjectElectric power utilization
dc.titleAdvancements in intelligent cloud computing for power optimization and battery management in hybrid renewable energy systems: A comprehensive reviewen_US
dc.typeReviewen_US
dspace.entity.typePublication
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