Publication:
Harmonic Distortion Prediction Model of a Grid -Connected Photovoltaic Using Grey Wolf Optimizer - Least Square Support Vector Machine

dc.citedby1
dc.contributor.authorYasin Z.M.en_US
dc.contributor.authorAshida Salim N.en_US
dc.contributor.authorAb Aziz N.F.en_US
dc.contributor.authorid57211410254en_US
dc.contributor.authorid57217177911en_US
dc.contributor.authorid57221906825en_US
dc.date.accessioned2023-05-29T07:22:26Z
dc.date.available2023-05-29T07:22:26Z
dc.date.issued2019
dc.descriptionForecasting; Harmonic analysis; Harmonic distortion; Heuristic algorithms; Heuristic methods; Irradiation; Particle swarm optimization (PSO); Photovoltaic cells; Renewable energy resources; Solar radiation; Support vector machines; Distortion predictions; Environmental awareness; Grid-connected photovoltaic; Grid-connected photovoltaic system; Least square support vector machines; Photovoltaic systems; Prediction accuracy; Total harmonic distortion (THD); Least squares approximationsen_US
dc.description.abstractThis paper depicts a new technique for prediction of the total harmonic distortion (THD) in Grid-Connected Photovoltaic System. Global environmental awareness, increasing demand for energy and down price tendency has led to new opportunities for utilization of renewable energy resources such as photovoltaic (PV) system. The integration of PV system to the grid must comply with the relevant standards given by the utility company. However, the output of PV somehow causes a harmonic distortion as the installation of inverter. The output of PV mainly depends on solar irradiation. Therefore, solar irradiation is selected as one of the input to the prediction model. The hybridize method of heuristic-algorithm namely Grey Wolf Optimizer-Least Square Support Vector (GWO-LSSVM) is introduced in order to improve the prediction accuracy. GWO is inspired by the leadership hierarchy and hunting mechanism of grey wolf in nature. The top hierarchy of grey wolf that considered as the fittest solution is alpha, followed by beta, delta and omega. The optimization process implementing three main steps such as hunting, searching for prey, encircling prey and attacking prey. GWO is utilized to optimize the parameters in LS-SVM model. The results showed that GWO-LSSVM predict more accurate than PSO-LSSVM and LSVM. � 2019 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo9105398
dc.identifier.doi10.1109/ICPES47639.2019.9105398
dc.identifier.scopus2-s2.0-85086640542
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85086640542&doi=10.1109%2fICPES47639.2019.9105398&partnerID=40&md5=84e3c734928c6705e5393018243db407
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24248
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2019 9th International Conference on Power and Energy Systems, ICPES 2019
dc.titleHarmonic Distortion Prediction Model of a Grid -Connected Photovoltaic Using Grey Wolf Optimizer - Least Square Support Vector Machineen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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