Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/29920
DC FieldValueLanguage
dc.contributor.authorKotevska, Anaen_US
dc.contributor.authorKiteva Rogleva, Nevenkaen_US
dc.date.accessioned2024-04-05T09:42:59Z-
dc.date.available2024-04-05T09:42:59Z-
dc.date.issued2020-12-14-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/29920-
dc.description.abstractLoad forecasts are important for energy suppliers. Accurate models for load forecasting are essential to the operation and planning of a utility company. This paper involves the development of short-term load forecasting models for the Republic of North Macedonia and a comparison of various models. These models use time series analysis such as the Autoregressive Integrated Moving Average model and the Seasonal Autoregressive Integrated Moving Average with Explanatory Variable model. The results were evaluated by the Mean Absolute Percentage Error of 0.5% for the forecasted day.en_US
dc.language.isoenen_US
dc.publisherJournal of Electrical Engineering and Information Technologiesen_US
dc.relation.ispartofJournal of Electrical Engineering and Information Technologiesen_US
dc.subjectAutoregressive Integrated Moving Average (ARIMA), Autocorrelation Function (ACF), Mean Absolute Percentage Error (MAPE), Partial Autocorrelation Function (PACF), Seasonal Autoregressive Integrated Moving Average with Explanatory Variable (SARIMAX).en_US
dc.titleSHORT-TERM LOAD FORECASTING USING TIME SERIES ANALYSIS: A CASE STUDY FOR THE REPUBLIC OF NORTH MACEDONIAen_US
dc.typeArticleen_US
dc.identifier.doi10.51466/jeeit2052135k-
dc.identifier.volume5-
dc.identifier.issue2-
dc.identifier.fpage135-
dc.identifier.lpage142-
item.grantfulltextopen-
item.fulltextWith Fulltext-
crisitem.author.deptFaculty of Agricultural Sciences and Food-
Appears in Collections:Faculty of Electrical Engineering and Information Technologies: Journal Articles
Files in This Item:
File SizeFormat 
Short Term Load Forecasting Using Time Series Analysis_JEEIT2020.docx631.11 kBMicrosoft Word XMLView/Open
Show simple item record

Page view(s)

31
checked on Jul 11, 2024

Download(s)

9
checked on Jul 11, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.