Sulaiman, Shahril Irwan
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Performance of grid-connected photovoltaic systems in Northern and Southern Hemispheres under equatorial climate Abdul Rahim, Yang Ilya Akila; Zainuddin, Hedzlin; Setiawan, Eko Adhi; Madsuha, Alfian Ferdiansyah; Hussin, Mohamad Zhafran; Sulaiman, Shahril Irwan; Ibrahim, Siti Nor Nadhirah
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 2: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i2.pp858-873

Abstract

This work studied the actual and simulated technical performance between two grid-connected photovoltaic (GCPV) systems representing opposite latitudes. The system with a capacity of 5.4 kWp installed in Kelantan, Malaysia represents the northern equator, and the 183.6 kWp system installed in Cikarang, Indonesia, denotes the southern equator. The performance was simulated using PVsyst software, which included the energy output (E_outt), reference yield (Y_r), final yield 〖(Y〗_f), performance ratio (PR), and capacity factor (CF). The mean bias error (MBE) between the actual and simulated technical performance were as follows; for system A, the yearly MBE for the E_out, Y_r, Y_f, PR, and CF were -0.4%, 17.1%, -1.4%, -15.8%, and 1.4%, respectively, and for system B, the E_out, Y_r, 〖 Y〗_f, PR, and CF values were 9.80%, 18.3%, 10.0%, -7.2%, and 10.0% respectively. The results have proven that PVsyst has successfully simulated the yearly E_out, 〖 Y〗_f and CF for both systems including PR, for system B, with MBE less than 10%. However, it is noteworthy to highlight that PVsyst significantly overestimated the Y_r of both systems up to 18.3% and conversely underestimated the PR for system A by 15.8%, which highly likely caused by the Meteonorm imported weather data.
Optimizing battery energy storage sizing in microgrids using manta ray foraging optimization algorithm Yatim, Yazhar; Tajuddin, Mohammad Faridun Naim; Sulaiman, Shahril Irwan; Azmi, Azralmukmin; Ayob, Shahrin Md; Sutikno, Tole
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i4.pp2535-2544

Abstract

The integration of renewable energy sources (RES) into microgrids (MGs) is becoming increasingly important as the world strives to transition towards more sustainable and eco-friendly energy systems. Unfortunately, integrating RES such as solar and wind power into MGs poses challenges due to their intermittent nature. The batteries need to be integrated into the MG system to overcome these challenges and ensure a stable and reliable power supply. However, the size of the battery presents another challenge as it affects the total operation cost of the MG system. Manta ray foraging optimization (MRFO) is used as an optimization technique to minimize the total operation cost of the MG system while ensuring optimum battery capacity. This algorithm is compared with the particle swarm optimization (PSO), differential evolution (DE), and the sine cosine algorithm (SCA). As a result, the proposed technique achieved a better solution than the existing algorithms.
Performance comparison of artificial intelligence techniques in short term current forecasting for photovoltaic system Othman, Muhammad Murtadha; Fazil, Mohammad Fazrul Ashraf Mohd; Harun, Mohd Hafez Hilmi; Musirin, Ismail; Sulaiman, Shahril Irwan
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 10, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (292.241 KB) | DOI: 10.11591/ijpeds.v10.i4.pp2148-2156

Abstract

This paper presents artificial intelligence approach of artificial neural network (ANN) and random forest (RF) that used to perform short-term photovoltaic (PV) output current forecasting (STPCF) for the next 24-hours. The input data for ANN and RF is consists of multiple time lags of hourly solar irradiance, temperature, hour, power and current to determine the movement pattern of data that have been denoised by using wavelet decomposition. The Levenberg-Marquardt optimization technique is used as a back-propagation algorithm for ANN and the bagging based bootstrapping technique is used in the RF to improve the results of forecasting. The information of PV output current is obtained from Green Energy Research (GERC) University Technology Mara Shah Alam, Malaysia and is used as the case study in estimation of PV output current for the next 24-hours. The results have shown that both proposed techniques are able to perform forecasting of future hourly PV output current with less error.
Mitigation of power quality problems using series active filter in a microgrid system Farooqi, Awais; Othman, Muhammad Murtadha; Abidin, Ahmad Farid; Sulaiman, Shahril Irwan; Radzi, Mohd Amran Mohd
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 10, No 4: December 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1115.912 KB) | DOI: 10.11591/ijpeds.v10.i4.pp2245-2253

Abstract

Dynamic voltage restorer (DVR) is a series active filter device that is used to protect sensitive loads from power quality issues such as voltage sag, swell, harmonics or disturbances. This implies that the DVR is capable to mitigate power quality disturbances at load terminal. Harmonic is a major power quality problem polluting distribution network causing the end-user equipment to fail operating due to the occurrence of disturbances in voltage, current or frequency. This paper discusses on the DVR used as the proposed technique to mitigate the voltage sag and swell in a distribution network connected with energy storage system and mini-hydro turbine system.