prikaz prve stranice dokumenta Prognoziranje opterećenja u distributivnoj mreži 35 kV Elektroslavonije Osijek
  Download
PDF 2.09 MB
master's thesis
Prognoziranje opterećenja u distributivnoj mreži 35 kV Elektroslavonije Osijek
2023. urn:nbn:hr:200:210199
Matić, Marija
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

Matić, M. (2023). Prognoziranje opterećenja u distributivnoj mreži 35 kV Elektroslavonije Osijek (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:200:210199

Matić, Marija. "Prognoziranje opterećenja u distributivnoj mreži 35 kV Elektroslavonije Osijek." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2023. https://urn.nsk.hr/urn:nbn:hr:200:210199

Matić, Marija. "Prognoziranje opterećenja u distributivnoj mreži 35 kV Elektroslavonije Osijek." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2023. https://urn.nsk.hr/urn:nbn:hr:200:210199

Matić, M. (2023). 'Prognoziranje opterećenja u distributivnoj mreži 35 kV Elektroslavonije Osijek', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 11 May 2024, https://urn.nsk.hr/urn:nbn:hr:200:210199

Matić M. Prognoziranje opterećenja u distributivnoj mreži 35 kV Elektroslavonije Osijek [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2023 [cited 2024 May 11] Available at: https://urn.nsk.hr/urn:nbn:hr:200:210199

M. Matić, "Prognoziranje opterećenja u distributivnoj mreži 35 kV Elektroslavonije Osijek", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:200:210199

Please login to the repository to save this object to your list.
Metadata
TitlePrognoziranje opterećenja u distributivnoj mreži 35 kV Elektroslavonije Osijek
Title (english)Load forecasting in the 35 kV distribution network of Elektroslavonija Osijek
AuthorMarija Matić
MentorKrešimir Fekete (mentor)
MentorSlaven Kaluđer (sumentor)
Committee memberKrešimir Fekete (predsjednik povjerenstva)
Committee memberZvonimir Klaić (član povjerenstva)
Committee memberRužica Kljajić (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 country2023-09-27, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Power Engineering
Abstract
U ovom diplomskom radu opisano je kako se predviđanje opterećenja može podijeliti prema vremenu, te kako određeni aspekti mogu utjecati na predviđanje opterećenja. Opisani su različiti modeli za predviđanje opterećenja električne energije. Zatim je odrađena simulacija u programu „Orange“ korištenjem metode neuronske mreže na 35 kV mreži Baranje. Predviđanje opterećenja izvršeno je na četiri transformatorske stanice (TS Bilje, TS Branjin Vrh, TS Draž i TS Kneževi Vinogradi) koristeći podatke sa 10 kV strane trafo polja. Vremenski interval za koji je rađeno predviđanje iznosi jedan kvartal. Potvrđeno je da odabir atributa, broj intervala i broj promatranih godina utječe na validnost rezultata, te same vjerojatnosti opterećenja. U sklopu diplomskog rada izvršeno je nekoliko simulacija gore navedenom metodom, a dobiveni rezultati za pojedine slučaje dosežu vjerojatnost i do 70%.
Abstract (english)
This thesis describes how load forecasting can be divided according to time, and how certain aspects can affect load forecasting. Different models for forecasting electricity load are described. Then a simulation was performed in the "Orange" program using the neural network method on the 35 kV network of Baranja. Load forecasting was performed at four transformer stations (TS Bilje, TS Branjin Vrh, TS Draž and TS Kneževi Vinogradi) using data from the 10 kV side of the transformer field. The time interval for which the forecast was made is one quarter. It has been confirmed that the selection of attributes, the number of intervals and the number of observed years affects the validity of the results, as well as the load probabilities themselves. As part of the thesis, several simulations were performed using the above-mentioned method, and the obtained results for certain cases reach a probability of up to 70%.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:210199
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 on2023-10-11 09:18:57