prikaz prve stranice dokumenta Prognoziranje cijene električne energije na tržištu različitim metodama
  Download
PDF 1.39 MB
master's thesis
Prognoziranje cijene električne energije na tržištu različitim metodama
2021. urn:nbn:hr:200:255773
Nikolić, Andrea
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

Cite this document

Nikolić, A. (2021). Prognoziranje cijene električne energije na tržištu različitim metodama (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:200:255773

Nikolić, Andrea. "Prognoziranje cijene električne energije na tržištu različitim metodama." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2021. https://urn.nsk.hr/urn:nbn:hr:200:255773

Nikolić, Andrea. "Prognoziranje cijene električne energije na tržištu različitim metodama." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2021. https://urn.nsk.hr/urn:nbn:hr:200:255773

Nikolić, A. (2021). 'Prognoziranje cijene električne energije na tržištu različitim metodama', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 19 February 2025, https://urn.nsk.hr/urn:nbn:hr:200:255773

Nikolić A. Prognoziranje cijene električne energije na tržištu različitim metodama [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2021 [cited 2025 February 19] Available at: https://urn.nsk.hr/urn:nbn:hr:200:255773

A. Nikolić, "Prognoziranje cijene električne energije na tržištu različitim metodama", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:200:255773

Please login to the repository to save this object to your list.
Metadata
TitlePrognoziranje cijene električne energije na tržištu različitim metodama
Title (english)Electricity price forecast using diferent methods
AuthorAndrea Nikolić
MentorKrešimir Fekete (mentor)
Committee memberKrešimir Fekete (predsjednik povjerenstva)
Committee memberZvonimir Klaić (član povjerenstva)
Committee memberZorislav Kraus (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 country2021-10-03, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Power Engineering
Abstract
U ovom diplomskom radu bilo je potrebno pronaći različite izvore koji se bave metodama za prognozu cijene električne energije. Kao glavne metode za prognozu cijene električne energije u ovom radu su metoda umjetne neuronske mreže i metoda strojnog učenja. Svaka od metoda je detaljno analizirana i objašnjena, zatim je napravljena paralela između te dvije metode. Nakon toga je osmišljen model za simulaciju i definirane su njegove osnovne faze provedbe. Simulacijski dio je napravljen u programu „Orange“, te su analizirane dobivene predviđene cijene električne energije u obje metode, cijene su uspoređene međusobno i još sa stvarnim cijenama koje se nalaze na hrvatskoj burzi električne energije. Na temelju rezultata i teorijskog dijela izveden je zaključak o točnosti obje metode i o samoj problematici prognoze koja je na kraju uspješno odrađena.
Abstract (english)
In this thesis it was required to find different sources that deal with methods for predicting the price of electricity. The main methods for predicting the price of electricity in this paper are the artificial neural network method and the machine learning method. Each of the methods was studied and explained in detail, then a parallel was made between the two methods. After that, a simulation model was designed and its basic implementation phases were defined. The simulation part was created in the "Orange" program, and the obtained predicted electricity prices in both methods were analyzed, the prices were compared with each other and with the actual prices on the Croatian electricity exchange. Based on the results and the theoretical part, a conclusion was made about the accuracy of both methods and the very problem of forecasting, which was eventually successfully completed.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:255773
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 on2021-11-23 13:44:04