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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS)
Prastawa, Andhika
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Control & Systems Engineering Electrical & Electronics Engineering

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A stacked LSTM model for day-ahead solar irradiance forecasting under tropical seasons in Java-Bali Nugroho, Muhammad Very; Prastawa, Andhika; Mardiansah, Fajril; Rezavidi, Arya; Fudholi, Ahmad; Palaloi, Sudirman
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i3.pp1878-1891

Abstract

Accurate short-term solar irradiance forecasting is essential for the efficient management and planning of power generation, especially for solar energy, which holds a major role in the Indonesian Government’s energy transition policy. A novel day-ahead solar irradiance forecasting is proposed using a stacked long short-term memory (LSTM) model to support the energy planning in the Java-Bali grid. The proposed model utilizes the first historical solar irradiance data of Java-Bali obtained from direct measurement to forecast the next day’s hourly irradiance. The results are compared with the methods of autoregressive integrated moving average (ARIMA) and recurrent neural network (RNN). This study revealed that the proposed model outperforms ARIMA and RNN, and regarded as a highly accurate forecast since root mean square error (RMSE), mean absolute percentage error (MAPE), and R2 are 25.56 W/m2, 7.27%, and 0.99, respectively. The stacked LSTM produces better forecasting in the dry season than in the wet season. The MAPE indicates that the LSTM's lowest accuracy for the dry season was 13.99%, which is categorized as a good forecast. The LSTM’s highest MAPE in the rainy season is 34.04%, which is categorized as a reasonable forecast. The proposed model shows its superiority and capability as a promising approach for short-term solar irradiance forecasting in Java-Bali.
Effect of the placement capacitor bank on electrical power quality in the ILST fan drive system Hermawan, Asep Dadan; Negara, I Made Yulistya; Nandar, Cuk Supriadi Ali; Prastawa, Andhika; Aryono, Nur Aryanto; Damara, Dio Randa; Dianti, Dwie Vannia; Nugraha, Heri
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i3.pp1435-1445

Abstract

Power quality is a critical aspect of the effective and dependable operation of electrical systems. In today's technologically advanced world, where industries rely significantly on electricity, understanding and maintaining power quality is critical. National Research and Innovation Agency (BRIN) has an important laboratory for aerodynamic testing technology service activities in Indonesia. This facility contains a closed wind tunnel, a DC drive system, and a DC electric motor. This innovative fan drive system employs a parallel DC drive system, with the master and slave motors connected to a master DC drive system and a slave DC drive system, respectively. The usage of a new system results in poor electrical power quality, with a power factor value of less than 0.85, resulting in higher electricity costs and increased current, which has an impact on other equipment, such as a rise in temperature. To improve the quality of electrical power according to standard operating procedures and lower electricity bills, the current work evaluated the new system using field tests and literature studies on the impact of installing capacitor banks in parallel DC motor systems to boost the power factor value. This evaluation aims to improve the quality of the ILST parallel electric power system by including a capacitor bank in each motor.
Co-Authors Ahmad Fudholi Aryono, Nur Aryanto Damara, Dio Randa Dianti, Dwie Vannia Heri Nugraha Hermawan, Asep Dadan I Made Yulistya Negara Mardiansah, Fajril Nandar, Cuk Supriadi Ali Nugroho, Muhammad Very Rezavidi, Arya sudirman palaloi