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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) International Journal of Advances in Applied Sciences
Yusoff, Siti Hajar
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Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Environmental Science Materials Science & Nanotechnology Mathematics Physics

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Performance inspection of high gain chopper designed to extract optimum output of photovoltaic source Akter, Khadiza; Motakabber, S. M. A.; Alam, A. H. M. Zahirul; Yusoff, Siti Hajar; Ahmed, Sajib; Annur, Tania
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 14, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v14.i4.pp2204-2216

Abstract

In recent years, the demand for power consumption has increased rapidly to fulfill the energy needs of households and industries worldwide. Solar electricity has emerged as the most practical form of renewable energy in this context. Due to its distinctive qualities such as being clean, quiet, and sustainable. Here, the study and analysis of a non-isolated high-gain chopper for solar photovoltaic (PV) systems are presented, which includes a quadratic cell and voltage doubler circuit (VDC). To ensure the utmost power produced by the solar system, the perturb and observe (P&O)-based maximum power point tracking (MPPT) algorithm is utilized. A quadratic VDC and a DC-DC boost converter are used to raise the PV voltage to a higher level (3.6 times higher with an MPPT controller, and 8 times higher with a battery source). The proposed converter exhibits notable improvements in efficiency, achieving an impressive 94%, which outperforms other state-of-the-art topologies. Additionally, the converter showcases a significant boost in voltage conversion gain, thereby substantiating its efficacy and superiority over other advanced topologies. Furthermore, comparatively less voltage stress on the switch with reduced voltage and current fluctuation increased the conversion effectiveness of the proposed configuration. Performance verification of the proposed topology is obtained by employing PSIM and MATLAB/Simulink.
Battery management system employing passive control method Fahmi, Muhamad Aqil Muqri Muhamad; Yusoff, Siti Hajar; Gunawan, Teddy Surya; Zabidi, Suriza Ahmad; Abu Hanifah, Mohd Shahrin
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v16.i1.pp35-44

Abstract

A battery management system (BMS) is essential for maintaining peak efficiency and longevity of rechargeable batteries. Conventional battery management system techniques often struggle to monitor, protect, and particularly have difficulties in balancing batteries. The project proposed has introduced a battery management system that employs passive control techniques to address excess energy and overcome these challenges. In the proposed design, a shunt resistor dissipates surplus energy from lithium-ion battery cells into heat following the proposed BMS design. This passive control technique is economically efficient, uncomplicated, and does not require an external power source. A prototype of the proposed BMS design was tested and was able to accurately monitor the battery, dissipate excess energy, and protect the battery while maintaining the cell charge balance. These findings suggest that the proposed BMS has the potential to improve both the effectiveness and longevity of rechargeable batteries.
Hybrid load forecasting considering energy efficiency and renewable energy using neural network Aizam, Adriana Haziqah Mohd; Dahlan, Nofri Yenita; Asman, Saidatul Habsah; Yusoff, Siti Hajar
International Journal of Advances in Applied Sciences Vol 13, No 4: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i4.pp759-768

Abstract

In recent years, the relationship between a country's gross domestic product (GDP) and its electricity consumption has changed significantly due to increased energy efficiency (EE) and renewable energy (RE) adoption. This decoupling disrupts conventional load forecasting models, affecting utility companies. This study has developed an innovative solution using an artificial neural network (ANN) Hybrid method for load forecasting, resulting in a remarkably accurate model with 99.68% precision. Applying this model to Malaysia's electricity consumption from 2020 to 2040 reveals a significant 13% reduction when accounting for EE and RE trends. This method aids risk management, contingency planning, and decision-making by accurately reflecting changing energy usage dynamics influenced by EE and RE sources.
Co-Authors Abu Hanifah, Mohd Shahrin Ahmed, Sajib Aizam, Adriana Haziqah Mohd Akter, Khadiza Alam, A. H. M. Zahirul Annur, Tania Asman, Saidatul Habsah Dahlan, Nofri Yenita Fahmi, Muhamad Aqil Muqri Muhamad Motakabber, S. M. A. Teddy Surya Gunawan Zabidi, Suriza Ahmad