Anomalous Electricity Load Events: An Evaluation Based on Mahakam Data

Syalam Ali Wira Dinata, Azka, Primadina Hasanah, Suhartono, Moh Danil Hendry Gamal

Abstract

This paper investigates a case study on the short-term forecasting of data from Mahakam with emphasis on special days, such as public holidays. Anomalous load conditions occur on different days, such as public holidays. These conditions are difficult to model because of their infrequent occurrence and significant deviation from standard load. A time series of load demand electricity recorded at hourly intervals contains more than one seasonal pattern. There is a great attraction to using a modeling time series method that is able to capture triple seasonalities. The triple seasonal ARIMA model has been adapted for this purpose and is competitive for modeling load. Herein, we demonstrate the triple seasonal ARIMA is an alternative strategy for providing accurate forecasts of electricity load from Kalimantan for planning, operational maintenance, and market-related activities.

 

 

Keywords: electricity, anomalous load, triple seasonal ARIMA, AIC, SBC.

 


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References


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