Forecasting of daily load curve on monthly peak day using load research data and harmonics model

Somboon Nuchprayoon

Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/57089

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DC Field	Value	Language
dc.contributor.author	Somboon Nuchprayoon	en_US
dc.date.accessioned	2018-09-05T03:34:55Z	-
dc.date.available	2018-09-05T03:34:55Z	-
dc.date.issued	2017-04-05	en_US
dc.identifier.other	2-s2.0-85018978994	en_US
dc.identifier.other	10.1109/ICCSCE.2016.7893595	en_US
dc.identifier.uri	https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85018978994&origin=inward	en_US
dc.identifier.uri	http://cmuir.cmu.ac.th/jspui/handle/6653943832/57089	-
dc.description.abstract	© 2016 IEEE. This work applies a harmonics model to forecast a daily load curve on a monthly peak day. The harmonics model is applied to capture periodic pattern of daily load and to avoid relying on weather-sensitive parameters. The harmonics model is a function of a base load, an hourly load, and a Fourier series. The dataset was obtained from load research data over the year 2008-2012 from the Provincial Electricity Authority of Thailand. It was found that the fifth harmonic model is proper to forecast the load curves on the monthly peak day. The forecasts of different tariff schedules are performed to compare the load patterns of residential, commercial, and industrial customers.	en_US
dc.subject	Computer Science	en_US
dc.subject	Engineering	en_US
dc.subject	Mathematics	en_US
dc.title	Forecasting of daily load curve on monthly peak day using load research data and harmonics model	en_US
dc.type	Conference Proceeding	en_US
article.title.sourcetitle	Proceedings - 6th IEEE International Conference on Control System, Computing and Engineering, ICCSCE 2016	en_US
article.stream.affiliations	Chiang Mai University	en_US
Appears in Collections:	CMUL: Journal Articles

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