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Electricity demand uncertainty modeling using enhanced path-based scenario generation method

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dc.citedby4
dc.contributor.authorTahmasebi M.en_US
dc.contributor.authorPasupuleti J.en_US
dc.contributor.authorid55945605900en_US
dc.contributor.authorid11340187300en_US
dc.date.accessioned2023-05-29T06:37:57Z
dc.date.available2023-05-29T06:37:57Z
dc.date.issued2017
dc.descriptionCommerce; Deregulation; Electric power utilization; Errors; Gaussian noise (electronic); Power markets; Uncertainty analysis; Autoregressive moving average; Autoregressive moving average method; Day ahead market; Deregulated electricity market; Electricity demands; Mean absolute percentage error; Scenario generation; Uncertainty; Electric power generationen_US
dc.description.abstractOne of the most important realities and uncertainties in the deregulated electricity market is electricity demand. Electricity demand scenario generation in day-ahead markets using newly proposed Enhanced path-based scenario generation method based on autoregressive moving average is developed in this paper. A new enhanced path-based scenario generation method to generate scenarios of the random variable and uncertainties modeling to achieve lower mean absolute percentage error for scenario generation compared to path-based autoregressive moving average method is proposed. Comparison of expected values obtained from the proposed method and path-based ARMA method, as well as real values, shows lower mean absolute percentage error for proposed method. It is observed that the mean absolute percentage error is decreased 5% for electricity demand using newly proposed scenario generation method. Lower mean absolute percentage error indicates higher accuracy of this method for generation of scenarios. � 2017 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo8003747
dc.identifier.doi10.1109/IYCE.2017.8003747
dc.identifier.scopus2-s2.0-85030167442
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85030167442&doi=10.1109%2fIYCE.2017.8003747&partnerID=40&md5=f34999859e0c57253e820d98d1a641ca
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/23139
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2017 6th International Youth Conference on Energy, IYCE 2017
dc.titleElectricity demand uncertainty modeling using enhanced path-based scenario generation methoden_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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