Publication:
Investigating the Power of LSTM-Based Models in Solar Energy Forecasting

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dc.citedby21
dc.contributor.authorJailani N.L.M.en_US
dc.contributor.authorDhanasegaran J.K.en_US
dc.contributor.authorAlkawsi G.en_US
dc.contributor.authorAlkahtani A.A.en_US
dc.contributor.authorPhing C.C.en_US
dc.contributor.authorBaashar Y.en_US
dc.contributor.authorCapretz L.F.en_US
dc.contributor.authorAl-Shetwi A.Q.en_US
dc.contributor.authorTiong S.K.en_US
dc.contributor.authorid58297401800en_US
dc.contributor.authorid58296523900en_US
dc.contributor.authorid57191982354en_US
dc.contributor.authorid55646765500en_US
dc.contributor.authorid57884999200en_US
dc.contributor.authorid56768090200en_US
dc.contributor.authorid6602660867en_US
dc.contributor.authorid57004922700en_US
dc.contributor.authorid15128307800en_US
dc.date.accessioned2024-10-14T03:18:33Z
dc.date.available2024-10-14T03:18:33Z
dc.date.issued2023
dc.description.abstractSolar is a significant renewable energy source. Solar energy can provide for the world�s energy needs while minimizing global warming from traditional sources. Forecasting the output of renewable energy has a considerable impact on decisions about the operation and management of power systems. It is crucial to accurately forecast the output of renewable energy sources in order to assure grid dependability and sustainability and to reduce the risk and expense of energy markets and systems. Recent advancements in long short-term memory (LSTM) have attracted researchers to the model, and its promising potential is reflected in the method�s richness and the growing number of papers about it. To facilitate further research and development in this area, this paper investigates LSTM models for forecasting solar energy by using time-series data. The paper is divided into two parts: (1) independent LSTM models and (2) hybrid models that incorporate LSTM as another type of technique. The Root mean square error (RMSE) and other error metrics are used as the representative evaluation metrics for comparing the accuracy of the selected methods. According to empirical studies, the two types of models (independent LSTM and hybrid) have distinct advantages and disadvantages depending on the scenario. For instance, LSTM outperforms the other standalone models, but hybrid models generally outperform standalone models despite their longer data training time requirement. The most notable discovery is the better suitability of LSTM as a predictive model to forecast the amount of solar radiation and photovoltaic power compared with other conventional machine learning methods. � 2023 by the authors.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo1382
dc.identifier.doi10.3390/pr11051382
dc.identifier.issue5
dc.identifier.scopus2-s2.0-85160800465
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85160800465&doi=10.3390%2fpr11051382&partnerID=40&md5=648aa3e5dd02a1c040406f5bc234d207
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/34234
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.subjectdeep learning
dc.subjecthybrid model
dc.subjectlong short-term memory
dc.subjectphotovoltaic power forecasting
dc.subjectrenewable energy
dc.subjectsolar irradiance forecasting
dc.subjectBrain
dc.subjectGlobal warming
dc.subjectLearning systems
dc.subjectLong short-term memory
dc.subjectMean square error
dc.subjectNatural resources
dc.subjectSolar energy
dc.subjectSolar power generation
dc.subjectSolar radiation
dc.subjectDeep learning
dc.subjectHybrid model
dc.subjectPhotovoltaic power
dc.subjectPhotovoltaic power forecasting
dc.subjectPower
dc.subjectPower forecasting
dc.subjectRenewable energies
dc.subjectRenewable energy source
dc.subjectSolar irradiance forecasting
dc.subjectSolar irradiances
dc.subjectForecasting
dc.titleInvestigating the Power of LSTM-Based Models in Solar Energy Forecastingen_US
dc.typeReviewen_US
dspace.entity.typePublication
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