International Journal of Power Electronics and Drive Systems (IJPEDS)
International Journal of Power Electronics and Drive Systems (IJPEDS, ISSN: 2088-8694, a SCOPUS indexed Journal) is the official publication of the Institute of Advanced Engineering and Science (IAES). The scope of the journal includes all issues in the field of Power Electronics and drive systems. Included are techniques for advanced power semiconductor devices, control in power electronics, low and high power converters (inverters, converters, controlled and uncontrolled rectifiers), Control algorithms and techniques applied to power electronics, electromagnetic and thermal performance of electronic power converters and inverters, power quality and utility applications, renewable energy, electric machines, modelling, simulation, analysis, design and implementations of the application of power circuit components (power semiconductors, inductors, high frequency transformers, capacitors), EMI/EMC considerations, power devices and components, sensors, integration and packaging, induction motor drives, synchronous motor drives, permanent magnet motor drives, switched reluctance motor and synchronous reluctance motor drives, ASDs (adjustable speed drives), multi-phase machines and converters, applications in motor drives, electric vehicles, wind energy systems, solar, battery chargers, UPS and hybrid systems and other applications.
Articles
2,594 Documents
<![CDATA[Comparative reliability and performance analysis of PV inverters with bifacial and monofacial panels ]]>
<![CDATA[Ramavath, Muneeshwar]]>;
<![CDATA[Venkata, Rama Krishna Puvvula]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1970-1982
<![CDATA[In the realm of solar energy systems, the reliability and performance of photovoltaic (PV) inverters play a critical role in ensuring efficient energy conversion and long-term operation. This study delves into a comprehensive reliability-oriented performance assessment of PV inverters, with a particular focus on the comparative analysis between bifacial and monofacial panels. Reliability evaluation is carried out by considering a yearly mission profile with a one-minute sample at Hyderabad, India. A test case of a 3-kW PV system for grid-connected applications is considered. By integrating reliability metrics with performance indicators, we aim to provide a holistic evaluation of PV inverters operating under varying conditions inherent to both panel types. The research methodology involves detailed simulations and field data analysis to capture the nuances of inverter performance influenced by the unique characteristics of bifacial panels, such as their ability to capture light from both sides, compared to the traditional monofacial panels. In this paper, performance parameters such as junction temperature, MCS, and B10 lifetime (system level (SL) and component level (CL)) are evaluated. Key findings highlight the impact of these differences on inverter reliability. The Bi-PV panel exhibits a decreasing trend. In India, CL reliability (B10) is decreased from 34 years to 1.5 years, and SL reliability (B10) is decreased from 24 years to 1 year. In comparison with monofacial panels, the thermal stress on the PV inverter due to the bifacial panel is increased, and reliability is decreased.]]>
<![CDATA[Photovoltaic energy harvesting for the power supply of medical devices ]]>
<![CDATA[Owida, Hamza Abu]]>;
<![CDATA[Izneid, Basem Abu]]>;
<![CDATA[Turab, Nidal]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1962-1969
<![CDATA[The increasing demand for sustainable and reliable power sources in portable and implantable medical devices has led to growing interest in photovoltaic (PV) energy harvesting. Traditional power sources, such as batteries, are limited by finite energy capacity and frequent replacement or recharging needs, particularly in implantable devices where surgical intervention is required for battery replacement. Photovoltaic energy harvesting, which converts light into electrical energy, offers a promising alternative, especially in environments with consistent light exposure. This review provides an in-depth analysis of the advancements in PV technologies for powering medical devices. It covers various types of PV materials, design innovations, and the integration of energy storage systems. Additionally, the review highlights the application of PV systems in both external and implantable medical devices, while addressing critical challenges such as ensuring biocompatibility, optimizing performance in low-light conditions, and miniaturizing PV systems for implantation. The potential of PV energy harvesting to improve device longevity and reduce the need for invasive procedures is emphasized. This review concludes by outlining the current challenges and future directions needed to achieve widespread clinical adoption, aiming to contribute to the development of sustainable power solutions in healthcare.]]>
<![CDATA[Advancing power quality via distributed power flow control solutions ]]>
<![CDATA[Yousfi, Abdelkader]]>;
<![CDATA[Mehedi, Fayçal]]>;
<![CDATA[Otmane, Khelifa Khelifi]]>;
<![CDATA[Bot, Youcef]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1801-1811
<![CDATA[The growing demand for enhanced power quality and reliable transmission has driven advancements in power flow control technologies. The distributed power flow controller (DPFC) represents an advancement over the unified power flow controller (UPFC). In contrast to the UPFC, the DPFC removes the DC link connecting the shunt and series converters, and redistributes the series converters along the transmission line as single-phase static series compensators. This modification enhances grid performance while maintaining full power flow control capabilities. The DPFC offers several advantages over the UPFC, including higher reliability, improved controllability, and greater cost-effectiveness. The system comprises a shunt converter in conjunction with multiple series converters, each with its own control circuit, all managed by a central control unit. This article presents the implementation of a DPFC model in MATLAB/Simulink. The simulation outcomes indicate that the DPFC significantly contributes to improved voltage stability and enhanced power transfer capability, thereby reinforcing system performance and reliability.]]>
<![CDATA[Machine learning techniques for solar energy generation prediction in photovoltaic systems ]]>
<![CDATA[Sumithra, J.]]>;
<![CDATA[Vinitha, J. C.]]>;
<![CDATA[Suganya, M. J.]]>;
<![CDATA[Anuradha, M.]]>;
<![CDATA[Sivakumar, P.]]>;
<![CDATA[Balaji, R.]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp2055-2062
<![CDATA[For photovoltaic (PV) systems to be as effective and dependable as they possibly can be, it is vital to make an accurate prediction of the amount of power that will be generated by the sun. Using machine learning, it is now much simpler to forecast the amount of solar energy that will be generated. These approaches are more accurate and are able to adapt to the ever changing conditions of the nature of the environment. We take a look at the most recent machine learning algorithms for predicting solar energy and examine their methodology, as well as their strengths and drawbacks, in this paper. Using performance metrics like root mean squared error (RMSE), mean absolute error (MAE), and mean squared error (MSE) makes it possible to evaluate important algorithms like support vector machines, decision trees, and linear regression. The results show that machine learning could help make predictions more accurate, lower the amount of uncertainty in operations, and help people make decisions in real time for PV systems. The study also points out important areas where research is lacking and suggests ways to move forward with the use of machine learning in systems that produce renewable energy.]]>
<![CDATA[DC bus control strategy and implications for voltage source converter system ]]>
<![CDATA[Fadel, Haider]]>;
<![CDATA[Ali, Ahmed Abdulredha]]>;
<![CDATA[Hameed, Mustafa Jameel]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1505-1515
<![CDATA[Significantly, the use of power electronic devices in residential and industrial settings has grown significantly in the last several years. Recent advancements in power semiconductors and microelectronics may be the main reason of their growing use in power systems for filtering, conditioning, and compensating. Additionally, the proliferation of semiconductor switches appropriate for high-power applications, and the enhancement of microelectronics enable mixed signal processing and control mechanisms. Furthermore, the concentration on renewable energy sources within the electric utility industry has emphasized the incorporation of power electronic converters into power systems. The operation and control of the regulated DC-voltage power port are examined in this work, a key part in different applications, such as STATCOM, dual mode HVDC converter systems, and aerodynamic wind energy converters with adaptive-speed optimization, emphasizing its significance in upholding a stable voltage level throughout the DC bus. The research also highlights the importance of power electronic converters within contemporary power systems, emphasizing their crucial role in facilitating effective and reliable power distribution. The obtained simulation results confirmed the efficacy of feed forward compensation in stabilizing the voltage responses of the DC bus.]]>
<![CDATA[Oxygen/sulphur self-doped tunnel-like porous carbon from yellow bamboo for advanced supercapacitor applications ]]>
<![CDATA[Taer, Erman]]>;
<![CDATA[Yanti, Novi]]>;
<![CDATA[Putri, Rahma Lia]]>;
<![CDATA[Apriwandi, Apriwandi]]>;
<![CDATA[Martin, Awaludin]]>;
<![CDATA[Julnaidi, Julnaidi]]>;
<![CDATA[Chitraningrum, Nidya]]>;
<![CDATA[Fudholi, Ahmad]]>;
<![CDATA[Taslim, Rika]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp2030-2042
<![CDATA[The 3D hierarchical pore structure with tunnel-like pores is essential to the performance of porous activated carbon (AC) materials used in symmetric supercapacitors. This study aimed to effect of adding (0.3, 0.5, and 0.7) M KOH reagent and heat treatment on the formation of 3D porous, tunnel-like AC derived from yellow bamboo (YB) through N2-CO2 pyrolysis at 850 °C. The AC produced had a high concentration of nanopores, becoming a valuable storage medium with favorable physical-electrochemical properties. The results showed that 0.5-YBAC had the best physical and electrochemical properties, with a carbon purity, 89.16%, micro crystallinity of 7.374 Å, and excellent amorphous porosity. Furthermore, 3D hierarchical pore structure, enriched naturally occurring heteroatoms, dopant of oxygen (10.14%) and sulfur (0.10%). A maximum surface area of 421.99 m² g⁻¹, along with a dominant combination of micro-mesopores. The electrochemical performance test of the 0.5-YBAC electrode showed a Csp of 214 F g⁻¹, with Esp 24.7 Wh kg⁻¹ and Psp 19.2 W kg⁻¹. In conclusion, this study showed the potential of YB stems to enhance the development of supercapacitors, offering superior porosity characteristics for efficient energy storage applications.]]>
<![CDATA[Dual-aware EV charging scheduling with traffic integration ]]>
<![CDATA[Yadav, Maneesh]]>;
<![CDATA[Jena, Satyaranjan]]>;
<![CDATA[Panigrahi, Chinmoy Kumar]]>;
<![CDATA[Pati, Ranjan Keshari]]>;
<![CDATA[Sahu, Jayanta Kumar]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1446-1456
<![CDATA[Electric vehicle adoption is a trend in many countries, and the demand for charging station infrastructure is at a rapid pace. The placement of charging stations is the key research topic of many researchers, but charging scheduling is also a problem that is going to rise in the near future. The proper charger utilization, maintaining coordination between charging stations, and satisfying users' demands are some of the key challenges. The traffic pattern is uncertain, coordination of distances between charging stations and users is done by Euclidean distance. The traffic-aware fair charging scheduling (TAFCS) strategy is proposed, which will have a balance on charger utilization and user prioritization, and keep the fairness by equal distribution of electric vehicles among all the charging stations having a centralized charging system monitored by an aggregator. The distribution of the traffic pattern of electric vehicles is performed by Monte Carlo simulation. The proposed system is tested on the IEEE 33 bus standard system using the predefined voltage limits of each bus and limiting power loss to lessen its burden. The discharging process of 50 electric vehicles (V2G) is performed by optimal placement by obtaining the weakest buses, which makes it an intelligent distribution system. This proposed charging framework is validated on MATLAB R2020a.]]>
<![CDATA[Analysis of cascaded H-Bridge multilevel inverters using SPWM with multi-sinusoidal reference ]]>
<![CDATA[Alias, Azrita]]>;
<![CDATA[Halim, Wahidah Abdul]]>;
<![CDATA[Azri, Maaspaliza]]>;
<![CDATA[Lazi, Jurifa Mat]]>;
<![CDATA[Aihsan, Muhammad Zaid]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1740-1751
<![CDATA[Multilevel inverters have become the preferred choice for medium voltage and high-power applications due to their superior waveform quality, reduced stress on switching components, and overall enhanced performance. Among these, the cascaded H-bridge inverter stands out for its simpler control and modulation techniques, as well as its greater efficiency compared to other multilevel inverter topologies. This paper presents the design and performance evaluation of a cascaded H-bridge multilevel inverter (CHMI) for five, seven, nine, eleven, thirteen, and fifteen levels, utilizing sinusoidal pulse width modulation (SPWM) in MATLAB Simulink. The proposed technique, the multi-sinusoidal reference, is implemented by comparing multiple sinusoidal wave signals with a carrier triangular signal, with the resulting comparison pulses used to control the inverter's switching. The output results indicate that as the number of levels in multilevel inverters increases, the total harmonic distortion (THD) decreases, and the output voltage improves.]]>
<![CDATA[An approach of battery adaptation in wireless sensor network with resource aware in extreme environmental area ]]>
<![CDATA[Parenreng, Jumadi Mabe]]>;
<![CDATA[Shiraj, Muhammad Reza]]>;
<![CDATA[Zain, Satria Gunawan]]>;
<![CDATA[Wahid, Abdul]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp1812-1821
<![CDATA[A wireless sensor network (WSN) is a distributed wireless system that employs sensor nodes to perform various tasks, including sensing, monitoring, data transmission, and delivering information to users via internet communication. Resource availability in WSNs is a critical factor influencing data delivery performance. One of the main challenges is the rapid depletion of resources, particularly batteries, which play a pivotal role in the system’s operational sustainability. This study evaluates the impact of battery adaptation through four testing scenarios. The results show that implementing battery adaptation significantly extends system lifespan compared to scenarios without adaptation. In the scenario without both a classification algorithm and adaptation, the system lasts approximately 270 minutes. When battery adaptation is applied without a classification algorithm, the lifespan increases to 330 minutes and 30 seconds. In contrast, the scenario using a classification algorithm without adaptation yields a lifespan of about 185 minutes, while combining the classification algorithm with adaptation extends it to approximately 252 minutes. The findings demonstrate that battery adaptation enhances the longevity and resource efficiency of WSN systems. However, the use of a classification algorithm tends to reduce operational time compared to scenarios that do not employ such algorithms.]]>
<![CDATA[Design and optimization of hybrid microgrid renewable energy system for electricity sustainability in remote area ]]>
<![CDATA[Ogbuanya, Theresa Chinyere]]>;
<![CDATA[Adebayo, Taiwo Felix]]>
<![CDATA[ International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 16, No 3: September 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijpeds.v16.i3.pp2063-2071
<![CDATA[Off-grid hybrid electrical systems have become a viable option for sustainable energy solutions, meeting the energy supply needs of rural communities. These systems use a broad approach to tackle sustainability, dependability, and environmental protection problems. The suggested hybrid system combines battery storage, biogas generators, and solar photovoltaic (PV) to provide a reliable and strong energy source for Ivoko Village in Enugu State using particle swarm optimization (PSO) and HOMER Pro Software. The paper compares three different configurations of sustainable power systems (HRES) to determine the best architecture that is suitable for rural areas. The result shows that case-1 (biogas/PV/bat) is the best option, with net present cost (NPC) and cost of energy (COE) values of $1,225,914 and 0.2865$/kWh, respectively. The results show that the PSO-based hybrid power system is more cost-effective than the HOMER-based optimizer. The NPC and lower COE for meeting peak demands emphasize the increasing role of biogas system generators as a cost-effective local power source. This highlights the PSO's potential in maximizing hybrid renewable power systems for rural areas, offering a financially viable and sustainable energy solution.]]>
