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Prediction of solar irradiance using grey Wolf optimizer least square support vector machine

Prediction of solar irradiance is important for minimizing energy costs and providing high power quality in a photovoltaic (PV) system. This paper proposes a new technique for prediction of hourly-ahead solar irradiance namely Grey Wolf Optimizer Least Square Support Vector Machine (GWO-LSSVM). Leas...

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Main Authors: Yasin, Z.M., Salim, N.A., Aziz, N.F.A., Mohamad, H., Wahab, N.A.
Format: Article
Language:English
Published: 2020
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spelling my.uniten.dspace-132762020-07-03T08:02:07Z Prediction of solar irradiance using grey Wolf optimizer least square support vector machine Yasin, Z.M. Salim, N.A. Aziz, N.F.A. Mohamad, H. Wahab, N.A. Prediction of solar irradiance is important for minimizing energy costs and providing high power quality in a photovoltaic (PV) system. This paper proposes a new technique for prediction of hourly-ahead solar irradiance namely Grey Wolf Optimizer Least Square Support Vector Machine (GWO-LSSVM). Least Squares Support Vector Machine (LSSVM) has strong ability to learn a complex nonlinear problems. In GWO-LSSVM, the parameters of LSSVM are optimized using Grey Wolf Optimizer (GWO). GWO algorithm is derived based on the hierarchy of leadership and the grey wolf hunting mechanism in nature. The main step of the grey wolf hunting mechanism are hunting, searching, encircling, and attacking the prey. The model has four input vectors: time, relative humidity, wind speed and ambient temperature. Mean Absolute Performance Error (MAPE) is used to measure the prediction performance. Comparative study also carried out using LSSVM and Particle Swarm Optimizer-Least Square Support Vector Machine (PSO-LSSVM). The results showed that GWO-LSSVM predicts more accurate than other techniques. Copyright © 2020 Institute of Advanced Engineering and Science. All rights reserved. 2020-02-03T03:31:29Z 2020-02-03T03:31:29Z 2019 Article 10.11591/ijeecs.v17.i1.pp10-17 en
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
language English
description Prediction of solar irradiance is important for minimizing energy costs and providing high power quality in a photovoltaic (PV) system. This paper proposes a new technique for prediction of hourly-ahead solar irradiance namely Grey Wolf Optimizer Least Square Support Vector Machine (GWO-LSSVM). Least Squares Support Vector Machine (LSSVM) has strong ability to learn a complex nonlinear problems. In GWO-LSSVM, the parameters of LSSVM are optimized using Grey Wolf Optimizer (GWO). GWO algorithm is derived based on the hierarchy of leadership and the grey wolf hunting mechanism in nature. The main step of the grey wolf hunting mechanism are hunting, searching, encircling, and attacking the prey. The model has four input vectors: time, relative humidity, wind speed and ambient temperature. Mean Absolute Performance Error (MAPE) is used to measure the prediction performance. Comparative study also carried out using LSSVM and Particle Swarm Optimizer-Least Square Support Vector Machine (PSO-LSSVM). The results showed that GWO-LSSVM predicts more accurate than other techniques. Copyright © 2020 Institute of Advanced Engineering and Science. All rights reserved.
format Article
author Yasin, Z.M.
Salim, N.A.
Aziz, N.F.A.
Mohamad, H.
Wahab, N.A.
spellingShingle Yasin, Z.M.
Salim, N.A.
Aziz, N.F.A.
Mohamad, H.
Wahab, N.A.
Prediction of solar irradiance using grey Wolf optimizer least square support vector machine
author_facet Yasin, Z.M.
Salim, N.A.
Aziz, N.F.A.
Mohamad, H.
Wahab, N.A.
author_sort Yasin, Z.M.
title Prediction of solar irradiance using grey Wolf optimizer least square support vector machine
title_short Prediction of solar irradiance using grey Wolf optimizer least square support vector machine
title_full Prediction of solar irradiance using grey Wolf optimizer least square support vector machine
title_fullStr Prediction of solar irradiance using grey Wolf optimizer least square support vector machine
title_full_unstemmed Prediction of solar irradiance using grey Wolf optimizer least square support vector machine
title_sort prediction of solar irradiance using grey wolf optimizer least square support vector machine
publishDate 2020
_version_ 1672614219763154944
score 13.222552

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