Publication:
Evaluating the Efficacy of Intelligent Methods for Maximum Power Point Tracking in Wind Energy Harvesting Systems

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dc.citedby8
dc.contributor.authorUmar D.A.en_US
dc.contributor.authorAlkawsi G.en_US
dc.contributor.authorJailani N.L.M.en_US
dc.contributor.authorAlomari M.A.en_US
dc.contributor.authorBaashar Y.en_US
dc.contributor.authorAlkahtani A.A.en_US
dc.contributor.authorCapretz L.F.en_US
dc.contributor.authorTiong S.K.en_US
dc.contributor.authorid57218304981en_US
dc.contributor.authorid57191982354en_US
dc.contributor.authorid58297401800en_US
dc.contributor.authorid55627877302en_US
dc.contributor.authorid56768090200en_US
dc.contributor.authorid55646765500en_US
dc.contributor.authorid6602660867en_US
dc.contributor.authorid15128307800en_US
dc.date.accessioned2024-10-14T03:18:20Z
dc.date.available2024-10-14T03:18:20Z
dc.date.issued2023
dc.description.abstractAs wind energy is widely available, an increasing number of individuals, especially in off-grid rural areas, are adopting it as a dependable and sustainable energy source. The energy of the wind is harvested through a device known as a wind energy harvesting system (WEHS). These systems convert the kinetic energy of wind into electrical energy using wind turbines (WT) and electrical generators. However, the output power of a wind turbine is affected by various factors, such as wind speed, wind direction, and generator design. In order to optimize the performance of a WEHS, it is important to track the maximum power point (MPP) of the system. Various methods of tracking the MPP of the WEHS have been proposed by several research articles, which include traditional techniques such as direct power control (DPC) and indirect power control (IPC). These traditional methods in the standalone form are characterized by some drawbacks which render the method ineffective. The hybrid techniques comprising two different maximum power point tracking (MPPT) algorithms were further proposed to eliminate the shortages. Furtherly, Artificial Intelligence (AI)-based MPPT algorithms were proposed for the WEHS as either standalone or integrated with the traditional MPPT methods. Therefore, this research focused on the review of the AI-based MPPT and their performances as applied to WEHS. Traditional MPPT methods that are studied in the previous articles were discussed briefly. In addition, AI-based MPPT and different hybrid methods were also discussed in detail. Our study highlights the effectiveness of AI-based MPPT techniques in WEHS using an artificial neural network (ANN), fuzzy logic controller (FLC), and particle swarm optimization (PSO). These techniques were applied either as standalone methods or in various hybrid combinations, resulting in a significant increase in the system�s power extraction performance. Our findings suggest that utilizing AI-based MPPT techniques can improve the efficiency and overall performance of WEHS, providing a promising solution for enhancing renewable energy systems. � 2023 by the authors.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo1420
dc.identifier.doi10.3390/pr11051420
dc.identifier.issue5
dc.identifier.scopus2-s2.0-85160767978
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85160767978&doi=10.3390%2fpr11051420&partnerID=40&md5=a8a77e3a47689ac0ef8461b68a0f7996
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/34185
dc.identifier.volume11
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)en_US
dc.relation.ispartofAll Open Access
dc.relation.ispartofGold Open Access
dc.sourceScopus
dc.sourcetitleProcesses
dc.subjectartificial intelligence
dc.subjectMPPT
dc.subjectwind energy harvesting system
dc.subjectEnergy harvesting
dc.subjectFuzzy inference
dc.subjectFuzzy neural networks
dc.subjectKinetic energy
dc.subjectKinetics
dc.subjectMaximum power point trackers
dc.subjectParticle swarm optimization (PSO)
dc.subjectWind power
dc.subjectWind turbines
dc.subjectEnergy harvesting systems
dc.subjectIntelligent method
dc.subjectMaximum power point
dc.subjectMaximum Power Point Tracking
dc.subjectMaximum Power Point Tracking algorithms
dc.subjectMaximum power point tracking techniques
dc.subjectPerformance
dc.subjectTracking method
dc.subjectWind energy harvesting
dc.subjectWind energy harvesting system
dc.subjectWind
dc.titleEvaluating the Efficacy of Intelligent Methods for Maximum Power Point Tracking in Wind Energy Harvesting Systemsen_US
dc.typeReviewen_US
dspace.entity.typePublication
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