Modeliranje časovne vrste neto pozicije električne energije za Nemčijo

Demšar, Eva (author), Kastelec, Damijana (mentor)

V nalogi je analizirana časovna vrsta urne razlike med izvozom in uvozom električne energije za Nemčijo. Razliko med izvozom in uvozom električne energije z drugo besedo imenujemo neto pozicija električne energije in je eden izmed pomembnejših pojmov mednarodnega trgovanja z električno energijo. Neto pozicija sledi proizvodnji in porabi električne energije, ki se spreminjata po urah, dnevih in sezonah. Predmet raziskovanja je kratkoročna napoved neto pozicije. Analizirani podatki se navezujejo na urne vrednosti obdobja med 1. 6. 2013 in 31. 5. 2014. Narava časovne vrste urne neto pozicije narekuje uporabo sezonskega integriranega avtoregresijskega modela in modela drsečih sredin (SARIMA). V nalogi so uporabljeni različni časovni intervali urnih mesečnih podatkov, ki jih obravnavamo v namen modeliranja. Uporabljena je tudi serija simulacij za namen ovrednotenja modelov ter navzkrižno preverjanje za primerjavo točnosti napovedi po izbranih SARIMA modelih.

• Language: Slovenian
• Keywords: analiza časovnih vrst, neto pozicija električne energije, napovedovanje časovnih vrst, sezonski ARIMA
• Work type: Master's thesis/paper
• Organization: FE - Faculty of Electrical Engineering
• Year: 2016
• PID: 20.500.12556/RUL-87015
• Publication date in RUL: 14.11.2016

DEMŠAR, Eva, 2016, Modeliranje časovne vrste neto pozicije električne energije za Nemčijo [online]. Master’s thesis. [Accessed 30 April 2025]. Retrieved from: https://repozitorij.uni-lj.si/IzpisGradiva.php?lang=eng&id=87015

Secondary language

• Language: English
• Title: Time series modelling of net position of electrical energy for German

Abstract

The hourly time series of differences between export and import of electrical energy for Germany have been studied. Difference between export and import is called net position, and it is one of the most important terms in the world trade of electrical energy. Net position follows the production and consumption of electrical energy, which vary according to hours, days and seasons. The objective of our research is short term forecast of net position. The analyzed data consists of the hourly values of the net position for the period between 1.6.2013 and 31.5.2014. The time series of hourly net position was modelled as a seasonal autoregressive integrated moving average process (SARIMA). Various one-month time intervals of the data were considered as training sets. The time series simulation was used for evaluation of the models and cross validation for accuracy of the forecasts of different models was analyzed and compared.

• Keywords: forecasting, net position, time series anaysis, seasonal ARIMA