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master's thesis
Prognoza cijene električne energije
Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2018. urn:nbn:hr:200:003882
Klešić, Ines
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Power Engineering
Chair of Power Systems and Substations

Institutional repository: Faculty of Electrical Engineering, Computer Science and Information Technology Osijek

Cite this document

Klešić, I. (2018). Prognoza cijene električne energije (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:003882

Klešić, Ines. "Prognoza cijene električne energije." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2018. https://urn.nsk.hr/urn:nbn:hr:200:003882

Klešić, Ines. "Prognoza cijene električne energije." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2018. https://urn.nsk.hr/urn:nbn:hr:200:003882

Klešić, I. (2018). 'Prognoza cijene električne energije', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 14 May 2024, https://urn.nsk.hr/urn:nbn:hr:200:003882

Klešić I. Prognoza cijene električne energije [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2018 [cited 2024 May 14] Available at: https://urn.nsk.hr/urn:nbn:hr:200:003882

I. Klešić, "Prognoza cijene električne energije", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:200:003882

Metadata
TitlePrognoza cijene električne energije
Title (english)Electricity price forecasting
AuthorInes Klešić
MentorSrete Nikolovski (mentor)
MentorKrešimir Fekete (mentor)
Committee memberSrete Nikolovski (predsjednik povjerenstva)
Committee memberGoran Knežević (član povjerenstva)
Committee memberKrešimir Fekete (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Power Engineering)
(Chair of Power Systems and Substations)
Osijek
Defense date and country2018-03-14, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Power Engineering
Abstract
Diplomski rad podijeljen je na teorijski i praktični dio. Ovisno o vrsti primjene, predviđanje opterećenja i cijena dijeli se u tri glavne kategorije: kratkoročno, srednjoročno i dugoročno. Faktori koji utječu na obrasce opterećenja i cijene su opisani. ANN metoda se koristi jer pruža jednostavan i učinkovit način za prognozu u praktičnoj primjeni te također predstavlja i nelinearne funkcije. Načini učenja i metode treniranja su pojašnjeni. Praktični dio najprije opisuje podatke za trening i testiranje koji su korišteni za predloženi model za kratkoročnu prognozu opterećenja i cijene. Opterećenje, cijena i temperatura su prikazani. Rezultati su razmotreni na temelju srednje apsolutne postotne pogreške.
Abstract (english)
The final thesis has theoretical and the pratical part. Based on its specific application, load and price forecasting can be categorized into short-term, mid-term and longterm. Factors affecting load and price patterns are described. ANN method is used because it provides a simple and powerful tool for forecasting in practical systems and it also represents non-linear functions. Learning strategies and training methods are explained. Practical section first described training and test data used to test the proposed ANN model for short-term load and price forecasting. Load, price and temperature data are presented. Then results are discussed based on the mean absolute percentage error.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:003882
Study programmeTitle: Graduate University Study Programme in Electrical Engineering; specializations in: Communications and Informatics, Power Engineering
Course: Power Engineering
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka elektrotehnike (magistar/magistra inženjer/inženjerka elektrotehnike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2018-04-11 15:07:04