International Journal of Applied Power Engineering (IJAPE)
International Journal of Applied Power Engineering (IJAPE) focuses on the applied works in the areas of power generation, transmission and distribution, sustainable energy, applications of power control in large power systems, etc. The main objective of IJAPE is to bring out the latest practices in research in the above mentioned areas for efficient and cost effective operations of power systems. The journal covers, but not limited to, the following scope: electric power generation, transmission and distribution, energy conversion, electrical machinery, sustainable energy, insulation, solar energy, high-power semiconductors, power quality, power economic, FACTS, renewable energy, electromagnetic compatibility, electrical engineering materials, high voltage insulation technologies, high voltage apparatuses, lightning, protection system, power system analysis, SCADA, and electrical measurements.
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<![CDATA[Optimal allocation of PV units using metaheuristic optimization considering PEVs charging demand ]]>
<![CDATA[Manjula, A.]]>;
<![CDATA[Yesuratnam, G.]]>
<![CDATA[ International Journal of Applied Power Engineering (IJAPE) Vol 14, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijape.v14.i2.pp282-290
<![CDATA[The distribution system is seeing a dramatic shift as a result of the increasing use of distributed generators (DGs) and plug-in electric vehicles (PEVs), or plug-in hybrid electric cars. The research endeavors to optimize the allocation of photovoltaic (PV) based DGs within radial distribution systems (RDS) while accommodating the load demand stemming from PEVs. A weighted-sum based multiobjective (WMO) technique is employed in this study to optimize three fundamental technical metrics of the distribution network: achieving the best possible voltage stability index (VSI) while reducing real power loss and total voltage variation to a minimum. Initially, the study investigates the impact of both conventional and PEVs load demand, considering PEVs load demand on distribution system performance under three charging scenarios: a situation involving peak charging, scenario involving off-peak charging, and scene of random charging. Subsequently, PV units are strategically planned, taking into account the PEVs demand within the distribution system utilizing an innovative weighted multiobjective electric eel foraging optimization (WMOEEFO) algorithm, its effectuality is validated with weighted multiobjective differential evolutionary (WMODE) and weighted multiobjective grey wolf optimization (WMOGWO) algorithms on standard test system IEEE 33-bus.]]>
<![CDATA[Assessment of the integration of electric vehicles into the Colombian market by 2050 using system dynamics ]]>
<![CDATA[Gálvez, Juan Camilo]]>;
<![CDATA[Dyner, Isaac]]>;
<![CDATA[Sanint, Enrique Ángel]]>;
<![CDATA[Aristizábal, Andrés Julián]]>
<![CDATA[ International Journal of Applied Power Engineering (IJAPE) Vol 14, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijape.v14.i2.pp421-431
<![CDATA[This article focuses on evaluating the prospects and potential that Colombia possesses for achieving a complete transition to electric vehicles (EV), with the goal of reaching a 100% penetration of such vehicles by the year 2050. To address this challenge, four potential scenarios are proposed, each based on different approaches and strategies. To achieve the objective described in the article, a simulation modeling approach was employed. Through this process, a definitive model was obtained that enables a visual representation of the progress of the different scenarios over the years. This graphical representation offers a clear insight into which scenarios align with the established parameters to achieve the target of nearly 100% electric vehicle adoption in Colombia by 2050. Additionally, there is a considerable reduction in CO2 emissions produced by the transportation sector in Colombia, with a 27% decrease compared to 2023. This is noteworthy given that the number of vehicles in 2050 is expected to be significantly higher than in the initial period, thus beginning a phase of declining pollution in the country.]]>
<![CDATA[Optimizing vehicle-to-grid scheduling and strategic placement for dynamic wireless charging of electric vehicles ]]>
<![CDATA[Mishra, Debani Prasad]]>;
<![CDATA[Sahay, Sanchita]]>;
<![CDATA[Kumar, Ayush]]>;
<![CDATA[Salkuti, Surender Reddy]]>
<![CDATA[ International Journal of Applied Power Engineering (IJAPE) Vol 14, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijape.v14.i2.pp328-337
<![CDATA[Dynamic wireless charging of electric vehicles (EVs) has become popular in intelligent transportation systems (ITS). However, both economic and smart city perspectives should be taken into account in the integration of wireless charging infrastructure for electric vehicles. Current research mainly focuses on power transfer (PT) or autonomous vehicle-to-grid (V2G) transfer. This paper presents a multilayered approach that combines optimal PT planning based on urban traffic and energy efficiency data with dynamic V2G planning. Simulation results show that the efficiency of PT placement and V2G scheduling increases and provides good results for smart city enterprises. This multilayered approach not only optimizes the efficiency of power transfer placement and V2G scheduling but also positions itself as a pivotal driver for the sustainable evolution of urban mobility. As dynamic wireless charging continues to shape the future of intelligent transportation systems, this research stands at the intersection of technological innovation, economic prudence, and urban planning, offering a blueprint for the seamless integration of EVs into the fabric of smart cities.]]>
<![CDATA[Generator analysis and comparison of working fluids in the organic Rankine cycle for biomass power plants using Aspen Plus software ]]>
<![CDATA[Siregar, Yulianta]]>;
<![CDATA[Sihotang, Wahyu Franciscus]]>;
<![CDATA[Mohamed, Nur Nabila]]>
<![CDATA[ International Journal of Applied Power Engineering (IJAPE) Vol 14, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijape.v14.i2.pp467-478
<![CDATA[The organic Rankine cycle utilizes low-temperature heat (flue heat) in power plants to produce electrical power. Several factors, including the working fluid's temperature and pressure, influence the efficiency of an organic Rankine cycle. This research method includes calculations using the gasification method in calculating electrical energy in PLTBM and calculating the experimental results of a series of organic Rankine cycles by taking into account the temperature and pressure of the working fluid using Aspen Plus Software, which is analyzed using statistical methods. The results of research using the gasification method in PLTBM fuel produced power of 27,279.38 MW/year for coconut shells, 6,489.66 MW/year for rice husks, and 532.62 MW/year for corn cobs. For the organic Rankine cycle series, rice husk waste produces the largest power of 8,336.67 kW, for coconut shells of 569,723.95 kW. For corn cobs of 358,639.63 with an efficiency value of organic working fluid in R-22 of 25.37% and the R-32 organic working fluid of 11.92% at a temperature of 125 °C in coconut shell waste, it can be concluded that the temperature of the working fluid has more influence on the efficiency of the organic Rankine cycle than the pressure of the working fluid.]]>
<![CDATA[Solar-powered bidirectional charging of electric vehicle ]]>
<![CDATA[Karthik, Nachagari]]>;
<![CDATA[Kallakunta, Ravi Kumar]]>;
<![CDATA[Cheerla, Sreevardhan]]>;
<![CDATA[Mohan, Kaja Krishna]]>;
<![CDATA[Inthiyaz, Syed]]>;
<![CDATA[Prakash, Nelaturi Nanda]]>;
<![CDATA[Rajanna, Bodapati Venkata]]>;
<![CDATA[Ahammad, Sk. Hasane]]>
<![CDATA[ International Journal of Applied Power Engineering (IJAPE) Vol 14, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijape.v14.i2.pp382-391
<![CDATA[Solar-powered bidirectional charging of an electric vehicle has three different modes of operation. The first mode of operation is “solar-powered electric vehicle charging” in which the vehicle is charged with solar energy. The second mode of operation is “grid-powered electric vehicle charging” which charges the vehicle in the absence of solar energy. The third mode of operation is “vehicle supplying to the grid” and in this mode, the vehicle energy is transferred back to the grid when there is demand to charge the other electric vehicles connected to the same grid. The system uses maximum power point tracking (MPPT) to improve power extraction from solar panels under standard test cell conditions, allowing for effective charging of electric cars. It also uses a proportional-integral (PI) controller to continually monitor the battery's state of charge (SOC). This controller modulates the duty cycle of pulse width modulation (PWM), which regulates the charging current. The charging system includes a buck-boost converter, which functions as a buck converter while supplying grid voltage to the vehicle, and a boost converter in supplying excess voltage of the vehicle to the grid. For three different modes of operation, the battery parameters such as voltage, current, and charging state are presented. The grid voltage and current are observed for the last two modes of operation.]]>
<![CDATA[State-augmented adaptive sliding-mode observer for estimation of state of charge and measurement fault in lithium-ion batteries ]]>
<![CDATA[Vinh, Thuy Nguyen]]>;
<![CDATA[Van, Chi Nguyen]]>;
<![CDATA[Van, Vy Nguyen]]>
<![CDATA[ International Journal of Applied Power Engineering (IJAPE) Vol 14, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijape.v14.i2.pp291-299
<![CDATA[Estimating the state of charge (SoC) in lithium-ion batteries (LiB) encounters challenges due to model uncertainties and sensor measurement errors. To solve this issue, this study introduces an estimator based on an innovative adaptive augmented sliding mode approach. This approach incorporates measurement faults as additional state variables to minimize the impacts of uncertainties effectively. Furthermore, based on the sliding mode framework, the design of this estimator addresses resistance to model uncertainties. However, sliding estimators commonly face the chattering issue. To counteract this, the paper suggests employing adaptive dynamics to determine the estimator's gain. This adaptive approach allows the gain calculation to minimize estimation errors across all time steps, effectively reducing chattering and enhancing estimation accuracy. The performance of the proposed method is validated through simulations using two practical data sets. Results demonstrate superior accuracy compared to conventional sliding methods, with improvements in SoC and terminal voltage estimation.]]>
<![CDATA[Prediction of wind power with various air speed using neuro-fuzzy logic in MATLAB ]]>
<![CDATA[Tushar, Naimur Rahman]]>;
<![CDATA[Shuvo, Md. Tanvir Ahmed]]>;
<![CDATA[Das, Dilip Kumar]]>;
<![CDATA[Chowdhury, Suman]]>
<![CDATA[ International Journal of Applied Power Engineering (IJAPE) Vol 14, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijape.v14.i2.pp432-440
<![CDATA[The energy crisis in Bangladesh has persisted for many years, predominantly reliant on fossil fuels for power generation, which is both economically and environmentally costly. It is imperative to transition away from fossil fuels towards more cost-effective and eco-friendly energy sources. Wind energy presents a viable solution to alleviate this crisis, especially considering Bangladesh's extensive coastline, offering great potential for harnessing significant amounts of electricity. Extensive research has been conducted on the feasibility of deploying wind turbines across various coastal zones to generate power and facilitate irrigation seasons. This research delves into the operational principles and performance parameters of wind turbines. A modified fan is utilized to assess power generation under varying air speeds, with data analysis conducted using neuro-fuzzy logic. The findings reveal a minimal percentage error of 0.09, underscoring the reliability of the proposed fuzzy model in predicting wind power output based on wind speed. This underscores the potential for leveraging wind energy as a sustainable and reliable alternative to fossil fuels in addressing Bangladesh's energy challenges.]]>
<![CDATA[Comparison of MPP methods for photovoltaic system ]]>
<![CDATA[Mishra, Debani Prasad]]>;
<![CDATA[Senapati, Rudranarayan]]>;
<![CDATA[Biswal, Prabin]]>;
<![CDATA[Satapathy, Swayamjyoti]]>;
<![CDATA[Sahu, Smruti Susmita]]>;
<![CDATA[Salkuti, Surender Reddy]]>
<![CDATA[ International Journal of Applied Power Engineering (IJAPE) Vol 14, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijape.v14.i2.pp338-346
<![CDATA[Solar electricity is usually a ubiquitous photovoltaic (PV) power source that converts sunlight into electricity. This makes solar energy a key factor in meeting the growing global demand. However, solar energy production from photovoltaic cells can be limited by many factors, so the power source needs to be optimized to reach the maximum level. One of the crucial technologies to enhance the power production of photovoltaic structures is maximum power point tracking (MPPT) measurement. This technology increases energy production by providing many advantages such as security, freedom, maximum energy efficiency, and environmental protection. MPPT continuously monitors the maximum power point of the photovoltaic structure to ensure the system operates at peak efficiency. This technology is indispensable in today’s solar systems, enabling the use of solar energy and reducing dependence on fossil fuels. By optimizing solar energy production, MPPT technology plays a crucial role in supporting the future of energy. It helps reduce climate change and promotes environmentally friendly practices through the use of renewable energy. MPPT technology also increases solar reliability, reduces maintenance costs, and improves overall performance. This makes MPPT an essential part of the modern solar system, ensuring they are efficient and effective.]]>
<![CDATA[Integral backstepping control design for enhanced stability and dynamic performance of VSC-HVDC systems ]]>
<![CDATA[Lakhdairi, Chaimaa]]>;
<![CDATA[Benaboud, Aziza]]>;
<![CDATA[Bahri, Hicham]]>;
<![CDATA[Talea, Mohamed]]>
<![CDATA[ International Journal of Applied Power Engineering (IJAPE) Vol 14, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijape.v14.i2.pp255-263
<![CDATA[The increasing demand for efficient and reliable high-voltage direct current (HVDC) transmission systems has underscored the necessity for advanced control strategies to augment system performance. This article presents the design and implementation of an integral backstepping control approach customized for voltage source converter (VSC)-based HVDC systems. The proposed methodology primarily concentrates on tackling the inherent nonlinearities, uncertainties, and disturbances that typically impede the stability and efficiency of VSC-HVDC systems. By incorporating integral action into the backstepping control framework, two key objectives are accomplished: i) precise regulation of the direct voltage at the rectifier station and accurate control of the active power at the inverter station, and ii) effective power factor correction (PFC) at both stations within the HVDC system. These objectives contribute to robust tracking performance, enhanced dynamic stability, and improved overall system efficiency. The theoretical design has been verified through extensive numerical simulations conducted in the MATLAB/Simulink environment, showcasing the efficacy of the proposed control strategy in ensuring stability and performance under varying conditions.]]>
<![CDATA[Solar and battery input super boost DC–DC converter for solar powered electric vehicle ]]>
<![CDATA[Yadagiri, Aerpula]]>;
<![CDATA[Talagadadeevi, Srinivasa Rao]]>;
<![CDATA[Rao, Seetamraju Venkata Bala Subrahmanyeswara]]>;
<![CDATA[Rao, Bitra Janardhana]]>;
<![CDATA[Inthiyaz, Syed]]>;
<![CDATA[Prakash, Nelaturi Nanda]]>;
<![CDATA[Rajanna, Bodapati Venkata]]>;
<![CDATA[Kumar, Cheeli Ashok]]>
<![CDATA[ International Journal of Applied Power Engineering (IJAPE) Vol 14, No 2: June 2025 ]]>
Publisher : <![CDATA[Institute of Advanced Engineering and Science ]]>
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DOI: 10.11591/ijape.v14.i2.pp479-487
<![CDATA[The electric vehicle (EV) is increasingly emerging as an attractive solution to reduce reliance on fossil fuels in India. In commercial EVs, solar photovoltaic (PV) technology is employed both to charge the battery and power the vehicle. However, the conventional bidirectional DC-DC converter layout results in underutilization of solar PV power when the battery's state of charge (SOC) reaches maximum capacity. This work offers a unique dual input super boost (DISB) DC-DC converter designed specifically for solar-powered electric vehicles (EVs) to address the aforementioned challenge. The recently suggested converter operates in six different modes to effectively capture solar photovoltaic (PV) power. Notable benefits of this design include a wide range of speed control and fewer conduction devices in each mode, which eventually result in increased overall efficiency. An extensive analysis of the suggested DISB DC-DC converter is carried out by the study, encompassing detailed examination of operating waveforms and dynamic evaluations. Furthermore, the converter's performance and operation under the six different modes are verified through simulation.]]>
