ARIMA Models in Electrical Load Forecasting and Their Robustness to Noise

Ewa Chodakowska, Joanicjusz Nazarko and Łukasz Nazarko
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Ewa Chodakowska: Faculty of Engineering Management, Bialystok University of Technology, Wiejska 45A, 15-351 Bialystok, Poland
Joanicjusz Nazarko: Faculty of Engineering Management, Bialystok University of Technology, Wiejska 45A, 15-351 Bialystok, Poland
Łukasz Nazarko: Faculty of Engineering Management, Bialystok University of Technology, Wiejska 45A, 15-351 Bialystok, Poland

Energies, 2021, vol. 14, issue 23, 1-22

Abstract: The paper addresses the problem of insufficient knowledge on the impact of noise on the auto-regressive integrated moving average (ARIMA) model identification. The work offers a simulation-based solution to the analysis of the tolerance to noise of ARIMA models in electrical load forecasting. In the study, an idealized ARIMA model obtained from real load data of the Polish power system was disturbed by noise of different levels. The model was then re-identified, its parameters were estimated, and new forecasts were calculated. The experiment allowed us to evaluate the robustness of ARIMA models to noise in their ability to predict electrical load time series. It could be concluded that the reaction of the ARIMA model to random disturbances of the modeled time series was relatively weak. The limiting noise level at which the forecasting ability of the model collapsed was determined. The results highlight the key role of the data preprocessing stage in data mining and learning. They contribute to more accurate decision making in an uncertain environment, help to shape energy policy, and have implications for the sustainability and reliability of power systems.

Keywords: ARIMA; electricity load; forecasting; model identification; tolerance to noise; robustness; simulation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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