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International Journal of Power Electronics and Drive Systems (IJPEDS)
ISSN : -     EISSN : 20888694     DOI : -
Core Subject : Engineering,
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.
Arjuna Subject : -
Articles 61 Documents
Search results for , issue "Vol 13, No 2: June 2022" : 61 Documents clear
An assessment of the share contributions of distortion sources for various load parameters Aleksandr Skamyin; Yaroslav Shklyarskiy; Iuliia Dobush; Vasiliy Dobush; Tole Sutikno; Mohd Hatta Jopri
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i2.pp%p

Abstract

The method for assessing the contributions of distortion sources based on measuring consumer currents and calculating their projections onto the supply current vector is considered in the paper. Determination of contributions is carried out on the basis of the developed model of an industrial enterprise in the food industry in MATLAB Simulink software. This study presents various cases of simulation, including variable parameters of linear and non-linear consumer load, changes in parameters of external distortion sources and passive harmonic filters. It is shown that the considered method gives correct results in the absence of external distortions in the electrical grid. The considered criteria for the share contributions make it possible to estimate the most efficient place for installing a passive filter in the absence of external distortions. An indicator for evaluating external distortions has also been developed based on calculating the projection of the harmonic system current onto the harmonic current of the shunt filter at the considered frequency.
A novel metaheuristic approach for control of SEPIC converter in a standalone PV system Dheeban Sembulingam Sankaralingam; Muthu Selvan Balasubramanian Natarajan; Maheswari Muthusamy; Sarojini Bagavath Singh
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i2.pp%p

Abstract

Fossil fuels are being replaced by renewables. Most of the renewables are intermittent, to have reliable power the renewables have to be conditioned before injecting into the utility grid. The DC-DC converters are perfect power electronic devices for conditioning the renewables. The single ended primary inductor converter (SEPIC) performs the conditioning with a very high voltage transfer gain and minimum ripples. The maximum power extraction from the PV panels is required for providing good quality DC power. Intelligent controllers can make use of optimization techniques. The particle swarm optimization (PSO) technique can optimize the controller to extract the maximum power. The SEPIC converter duty variation is optimized and a comparative analysis with the Buck-Boost converter is done in a MATLAB/Simulink environment. The proposed SEPIC converter system performed well by improving the power tracking by 40% and the system has been analysed in a battery charging environment.
Implementation of Harris Hawks optimization for load frequency control of hydropower plant Devendra Potnuru; Lagudu Venkata Suresh Kumar; Bankuru Sonia; Yellapragada Venkata Pavan Kumar; Darsy John Pradeep; Challa Pradeep Reddy
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i2.pp%p

Abstract

Hydropower has been used for many years and is essential to meet the renewable energy ambition of the world at present. In a hydroelectric power plant, voltage and frequency control are required, but, the voltage control could be done on the load side. In the present paper, frequency control using Harris Hawks optimization (HHO) for improved performance has been presented. Simulations are performed on the dynamic model of the hydropower plant and results are compared with the conventional PID that is designed using the Ziegler-Nichols method. The efficacy of the proposed algorithm is also tested at dynamic conditions of the hydropower plant.
Constant current-fuzzy logic algorithm for lithium-ion battery charging Muhammad Nizam; Hari Maghfiroh; Azis Ubaidilah; Inayati Inayati; Feri Adriyanto
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i2.pp%p

Abstract

The lithium-ion (Li-ion) battery has a high demand because of its long cycle, reliability, high energy density, low toxic, low self-discharge rate, high power density, and high efficiency. However, lithium-ion batteries have sensitivity to over-charge, temperature, and charge discharge currents. The conventional battery charging system takes a very long time to charge which makes the battery temperature high. Therefore, a charger system that can maximize charging capacity, shorten charging time, and extend battery life is needed. In this study, a battery charging system was developed using the constant current–fuzzy (CC-fuzzy) control method. The aim is to get faster charging time and maintain battery life by limiting the battery charging temperature. The proposed charger system is dual mode which can be operated in both buck and boost mode. The experimental result shows that the proposed method is superior compared to the constant current constant voltage (CCCV) method in charging time. The CC-fuzzy method charging time is faster compared to the CCCV method by 25% and 12.5% in buck and boost modes, respectively. Whereas from the battery temperature, in buck mode, the proposed method has a lower temperature by 0.5 ⁰C and in the boost mode, each method has the same temperature.
Artificial neural network based DC-DC converter for grid connected transformerless PV system Janardhan Gurram; Nukala Surendra Babu; Gondlala Narsaiah Srinivas
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i2.pp%p

Abstract

The transformerless photo voltaic (PV) inverter system connected to grid has created a new trend in the energy market due to its reduced space requirement, low cost and increased efficiency when compared to its counterpart i.e with transformer. Transformerless inverter system suffers from common mode leakage currents due to parasitic capacitances between PV panels and ground. However, different new inverter topologies and state of the art modulation strategies are proposed in the literature to counter it. A dc-dc converter is of more significant to maintain the constant PV output voltage at string level and extract maximum power from PV. This paper presents Artificial neural network (ANN) algorithm-based dc-dc converter to track maximum power from PV module connected to grid without transformer. It also compares the performance of ANN based algorithm with conventional perturb and Observe maximum power point tracking (MPPT) technique. MATLAB/Simulink environment is used to pursue the simulation of ANN based algorithm and analyses its performance for variety of irradiance levels.
Modified proportional integral controller for single ended primary inductance converter Boris Nikolaevich Abramovich; Denis Anatolevich Ustinov; Wael Joseph Abdallah
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i2.pp%p

Abstract

The article highlights and optimizes a controller for the single ended primary inductance converter (SEPIC) direct current-direct current (DC-DC) converter. The SEPIC converter adjusts a range of dc input voltages and delivers a constant and stable output voltage. Three different models of the SEPIC converter are presented in order to derive its transfer function. Being a 4th order, an approximation method for the reduction of this transfer function to 2nd and 1st order is implemented. Two methods for controlling the converter are presented, the first one is based on guessing techniques and the second explains the design steps of the controller based on the internal model control (IMC). Furthermore, an improvement on the IMC controller is proposed and results were shown and discussed. IMC is based on integrating the “process model” in the control operation of the actual system. By using an approximation of the original transfer function of the system, it is expected that the IMC control will be able to achieve the desired results. Control schemes of the SEPIC will be presented and results will be shown. The response of the controller was tested with mathematical models for batteries and supercapacitors in MATLAB, as non-ideal DC-sources, and results were presented.
Technical-economical assessment of solar PV systems on small-scale fishing vessels I Made Aditya Nugraha; Febi Luthfiani; Grangsang Sotyaramadhani; Aris Widagdo; I Gusti Made Ngurah Desnanjaya
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i2.pp%p

Abstract

The source of lighting in ships can be sourced from electrical energy generated by using generators or now can utilize new renewable energy, such as solar energy using PV. Based on the existing potential, Indonesia has good solar energy potential. The measurement results show that the potential for solar energy reaches 6.37 kWh/m2/day. This potential can certainly be utilized in the marine and fisheries world. The utilization of PV as a source of electrical energy on fishing boats is expected to help support government policies in terms of the blue economy and overcome the limited number of fossil energy sources. In this study, the installation of PV with a size of 100 WP was installed on fishing boats. The need for electrical energy for PV energy output shows that it can meet 50.52% of electrical energy needs. This result is supported by the Wilcoxon test that electrical energy needs can be met by PV with a p < 0.005. The results of the economic analysis also show that the use of solar energy as a source of electrical energy provides an IRR of 9%, with a payback period of 8.87 years.
Roof top PV for charging the EV using hybrid GWO-CSA Dhamodharan Selvaraj; Dhanalakshmi Rangasamy
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i2.pp%p

Abstract

In this paper, a novel idea of charging the vehicle on the go while using the solar panels on the roof of the vehicle is introduced. The use of electric vehicles has increased among people as the vehicles are affordable. Electric vehicle charging is one of the major problems faced by most manufacturers today. The PV panels take the energy from sunlight, and it can charge the vehicle battery. When the vehicle is moving on the road, the power extraction for charging may not be proper due to the partial shaded condition. To extract sufficient power for charging, a hybrid optimization algorithm has been introduced. In this paper, an electric vehicle model that uses the hybrid optimization algorithm of grey wolf optimization and cuckoo search algorithm (GWO-CSA) is developed and compared with the conventional particle swarm optimization (PSO) algorithm. The extraction of maximum power and the performance of the vehicle are analysed using MATLAB/Simulink, and the simulation results are discussed. To test the effectiveness of the algorithm, it is compared with the other three algorithms.
Motion control of linear induction motor using self-recurrent wavelet neural network trained by model predictive controller Fatimah Fadhil Jaber; Diyah Kammel Shary; Haider Alrudainy
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i2.pp%p

Abstract

Due to end effects phenomena that cause a decrease of air-gap flux and thrust force, obtaining a precise velocity for a linear induction motor (LIM) has become a significant challenge. This study suggests implementing a novel controller based on a self-recurrent wavelet neural network (SRWNN) and model predictive controller (MPC) to regulate the velocity and thrust force of LIM. The MPC was used to train the SRWNN in this study. The ultimate goal of employing such a control approach in neural network training is to reduce the degree of uncertainty caused by changes in motor parameters and load disturbance. The indirect field-oriented control (IFOC) approach was used to investigate velocity and flux control under varied loading circumstances. Furthermore, to supply the required LIM stator voltage, a SVPWM dependent voltage source inverter was used in this work. To ensure reliable performance, the suggested system combines the benefits of neural networks with the MPC method, resulting in a versatile controller with a basic construction that is easy to accomplish. The MATLAB package is utilized to simulates and outputs LIM responses. The results confirm that the proposed method, which efficiently controls the velocity and thrust force of the LIM, can cope with changes in load force disruption and motor parameters.
Analysis of open circuit voltage and state of charge of high power lithium ion battery Jairam Chandra Dutt Mushini; Kuldeep Rana; Mruttanjaya Sanganna Aspalli
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i2.pp%p

Abstract

Electric vehicles (EVs) are the emerging technologies in the transport sector around the world. EV runs using an electric motor with electricity which is stored in Li-ion batteries (LIBs). Because of its superior qualities LIBs become the market leader for the usage in EVs. With the increased penetration of LIBs in EVs, it is important to monitor the charging and discharging process of the batteries. Accurate estimation of state of charge (SoC) and open circuit voltage (OCV) is essential for the better control of EV. In the present study LIB of 40 Ah nickel manganese cobalt (NMC) cell chemistry has been used for estimation of state of charge at different C-rates as 0.3, 0.5, 1 and 2 C rates. The relationship between the SoC and OCV is nonlinear however relationship between SoC and Ah is linear. Slight rise has been observed in cell terminal temperature at lower C rating at higher C-rating it is found that temperature rise is more (around 10 ℃). Hence, it is important to consider the C-rate of the battery from SoC-OCV curve of the battery. Also, higher C-rate may lead to incorrect estimation of the SoC, reduction in battery life and may lead to potential safety risks.