Prediction of Hydropower Plant Electricity Production Dependence on Weather Conditions Using the SARIMAX Model

Dennis Hasnan Zulfialda; Catur Arie  Nugroho; Hakim Luthfi  Malasan

doi:10.37899/journallamultiapp.v6i1.1841

Dennis Hasnan Zulfialda Program Studi S2, Sains Komputasi, Fakultas Matematika dan Ilmu Pengetahuan Alam, Institut Teknologi Bandung PT PLN (Persero) Jakarta, Indonesia
Catur Arie Nugroho Program Studi S2, Sains Komputasi, Fakultas Matematika dan Ilmu Pengetahuan Alam, Institut Teknologi Bandung PT PLN (Persero) Jakarta, Indonesia
Hakim Luthfi Malasan KK Astronomi dan Program Studi Sains Komputasi, Fakultas Matematika dan Ilmu Pengetahuan Alam, Institut Teknologi Bandung Bandung, Indonesia

DOI: https://doi.org/10.37899/journallamultiapp.v6i1.1841

Keywords: Hydropower, SARIMAX, El Niño, Electricity production, Weather

Abstract

Electricity production from Hydroelectric Power Plants (PLTA) that depends on the water capacity in the dam. The water capacity depends on uncertain weather conditions such as drought caused by the El Niño Storm, which has an impact on the lack of water supply that enters the hydropower turbine which is then converted into electrical energy. Accurate predictions are needed to be able to mitigate existing weather fluctuations. In this study, the SARIMAX model on electricity production data integrated with weather data for 4 years from January 2020 to December 2023. The SARIMAX model with optimal parameters (p=0, d=1, q=1, P=1, D=0, Q=1, s=12) provides quite satisfactory prediction results for hydropower power production. SARIMAX obtained MSE values of 0.00101, MAE 0.0274, and RMSE 0.0318. The study also highlights the significance of accurate prediction of hydropower production, emphasizing the importance of external factors such as weather in particular El Niño. Understanding and predicting weather patterns is critical to the power generation system of hydropower in making decisions and optimizing the operation of the electricity system efficiently.

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