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International Journal of Applied Power Engineering (IJAPE)
Published by Institute of Advanced Engineering and Science
ISSN : 22528792     EISSN : 27222624     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
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.
Arjuna Subject : -
Articles 614 Documents
 58   59   60   61   62 
Rule-based energy management strategies for a hybrid microgrid using grey wolf optimizer Sarmid Shakir Abdulsattar; Chee Wei Tan; Shahrin Ayob; Yasir Shakir Abdulsattar; Ahmed Tijjani Dahiru; Chin Kim Gan; Kwan Yiew Lau
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i2.pp858-879

Abstract

This study utilizes grid-connected microgrids using photovoltaics (PVs) and wind turbines (WTs) in a residential system. For improved reliability, the system uses battery storage and diesel generators (Dgen). The proposed system uses supervisory controllers (as a rule-based energy management system) for energy management strategy implementations. The essence of using the grey wolf optimizer (GWO) is to strategize the rule-based energy management system in the proposed microgrid operations. The primary objectives are to achieve a low levelized cost of energy (LCOE) and determine the optimal number of microgrid components. The performance of the GWO is compared with three other optimization algorithms, namely, antlion optimizer (ALO), particle swarm optimizer (PSO), and cuckoo search algorithm (CSA), for benchmarking purposes. The findings indicate that the proposed GWO supersedes ALO, PSO, and CSO in energy cost reduction by 30.3% (0.0448 $/kWh), 65.6% (0.0971 $/kWh), and 120% (0.1774 $/kWh), respectively. The suggested algorithm selects the optimum number of the system’s components, which is 46 PV modules, 30 wind turbines, and 10 units of batteries. An improved GWO-based algorithm based on hybridization with gradient descent algorithms is envisaged to implement a customer-centered energy management that can ensure customer satisfaction and further reduce energy cost.
Comparative analysis of PM6:L8-BO organic and inverted organic solar cell Karthika Krishnakumar; Ashish Grover; Pardeep Kumar
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i2.pp770-780

Abstract

Advancements in solar technologies are driven by the pursuit of higher efficiency and reduced environmental impact. This study presents a comprehensive and comparative analysis of organic and inverted organic solar cells (OSC and IOSC), using the OghmaNano software for simulations and analysis. This work is specifically designed to compare conventional and inverted structures and understand how device engineering impacts performance metrics. When OSCs are characterized by a low work-function cathode on top, IOSCs feature a clear conductive oxide cathode at the bottom. The study focusses on extracting key electrical output, including short circuit current density (JSC), open-circuit voltage (VOC), fill factor (FF) and power conversion efficiency (PCE), through the calculated current-voltage characteristic (J-V). Various physical characteristics, such as thickness of different layers and materials deployed as electron transport layer (ETL) and hole transport layer (HTL), are systematically investigated. Diverse top and bottom electrodes, encompassing monothin and multithin layer configurations, are proposed. The study shows that IOSC achieves higher efficiency than OSC, reaching 21.60%, while using a multithin layer ZTZ (ZnO/TiOx/ZnO) as the bottom contact, demonstrating improved charge transport and overall efficiency.
Comparison of differential evolution optimization technique with other techniques in solving multi-objective optimal power flow Vineeta S. Chauhan; Jaydeep Chakravorty; Siddharthsingh K. Chauhan
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i2.pp663-673

Abstract

Optimal power flow (OPF) is a complex, non-linear optimization problem focused on determining the steady-state operating parameters of power systems for economic and secure operation. The challenge intensifies due to numerous system constraints that must be satisfied simultaneously. Although various evolutionary algorithms (EAs) have been applied to OPF in recent decades, these algorithms often use unconstrained search strategies. A common approach to handle constraint violations is the static penalty function, which penalizes infeasible solutions. However, selecting suitable penalty coefficients typically involves time-consuming trial and error, affecting overall performance. This study explores the integration of advanced constraint handling (CH) techniques within the differential evolution (DE) framework to enhance the performance of optimal power flow (OPF) solutions. In particular, it looks at three approaches: a hybrid ensemble of two CH techniques (ECHT), a self-adaptive penalty method (SP), and superiority of viable solutions (SF). The IEEE 30-bus and IEEE-57 bus benchmark systems are used to evaluate the efficacy of these techniques under a variety of OPF goals, including lowering emissions and generation costs, cutting power losses, and enhancing voltage stability. We took into consideration both weighted-sum multi-objective and single-objective formulations. The simulation outcomes indicate that the proposed CH-DE approaches deliver robust and competitive optimization results, demonstrating improved constraint handling capabilities when compared to contemporary methods in the literature.
Regenerative braking with battery management system in E-bike Divyashree, B. P.; Lakith, G.; Sukanya, H. N.; Gurav, Nagaling M.; Mallikarjuna, Neeli; Anil, Unnam
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i2.pp565-572

Abstract

Energy neither be created nor be destroyed, but it can be transformed into other forms as per the law of conservation of energy. This information is epitomized by the regenerative braking system (RBS), which transforms kinetic energy into mechanical energy, thus recuperating waste energy into mechanical energy and making it beneficial. The regenerative braking have significant impact in electric vehicle technology due to the contemporary energy challenges and dwindling resources. Regenerative braking involves apprehending the lost kinetic energy during braking and converting it into a storable or instantly usable form. The recuperated kinetic energy can be reintegrated into vehicle’s power system or stored for further use, often in a battery, especially lithium-ion batteries which are managed by a battery management system (BMS) to ensure optimal performance and longevity. The utilization of various sensors by BMS to monitor parameters such as temperature, current, and voltage, entitling it to assess the battery’s health and determine its state of charge and discharge. Additionally, the BMS protects the battery against cavernous discharge and over-voltage, which can result from rapid discharging and charging currents, thereby optimizing the utilization of battery energy. In this article, the design of an electrical regenerative braking system with a battery management system in an electric bicycle (E-bike) applications are presented. The results show that the system works well in both battery-operated and regenerative modes. When in regenerative mode, the voltage and current stay within the specified range and are suitable for charging batteries. On the other hand, during regular operation, the increase in energy consumption is matched with the battery mode mileage.
Self tuning of output scaling factor for type-2 interval fuzzy controllers Mouna Ghanai; Kheireddine Chafaa; Ali Medjghou; Nadia Bounouara
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i2.pp480-491

Abstract

In this study presents a self-tuning type-2 fuzzy logic controller framework, which operates on the principle of continuously adjusting the controller structure by modifying the controller gain (scaling factor) as a function of the error and its rate of change, in order to achieve optimal control performance. The proposed structure is both simple and robust, with real-time gain adaptation facilitated by two type-2 fuzzy systems; the first one containing the rules of control task for speed regulation, and the second one containing the rules for the adaptation of the scaling factor. Both systems have the same inputs error and its variation. This work specifically focuses on tuning the output scaling factor, which is considered equivalent to the controller gain. The effectiveness of the proposed approach is evaluated through its application to the control of an induction machine, a system known for its complexity and strong nonlinearity. Simulation results demonstrate that the fuzzy controller significantly enhances performance, even under challenging operating conditions such as low-speed regimes.
Analysis of CCS implementation in Indonesia’s coal fired power plants, economic optimization, and potential impact on Java-Bali grid for future decarbonization Anggit Raksajati; Sanggono Adisasmito; Veri Hendrayawan
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i2.pp927-941

Abstract

This study aims to evaluate impact of retrofitting carbon capture and storage (CCS) technology on coal fired power plants (CFPP) in Indonesia. Using a representative 3×330 MW CFPP, the integration of CCS increases the levelized cost of electricity (LCoE) to 124 USD/MWh. Key cost components include CO₂ capture (21.7%), energy penalty from steam extraction (18.5%), and CO₂ transport and injection (16.7%). Sensitivity analysis indicates that CCS becomes financially viable under a high carbon cap (0.9 tCO₂/MWh) and a carbon tax of 76 USD/tCO₂. Meanwhile, International carbon markets offer a potential revenue at 75 USD/tCO₂ can fully offset CCS costs. Additionally, CAPEX grants can reduce LCoE to 12.4%, serving to mitigate upfront investment for CCS deployment. Within the Java-Bali grid, CFPP account for 58.8% of the generation mix with 41% aged 10-20 years using predominantly subcritical technology while 28% are over 20 years old and follow natural retirement being replaced by renewable energy. CCS retrofitting is more economically and technically viable for mid aged plants with newer technologies and lower emission intensities, supporting grid stability with limited renewable base load availability. This strategy also serves as a transitional pathway toward long term renewable integration until the LCoE of PV+BESS falls below 50 USD/MWh.
Energy-aware dynamic adjustment integrated kookaburra optimization based efficient routing in WSN Shobanbabu R. Jaganathan; R. Sathya; R. Karthikeyan
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i2.pp724-734

Abstract

In this paper a novel kookaburra optimization algorithm based dynamic adjustment strategy (KOA-DAS) method has been proposed in this paper for the energy efficient (EE) clustering and routing in wireless sensor network (WSN). The satin bowerbird optimization (SBO) is utilized for optimum cluster head (CH) selection. The proposed KOA-DAS model is utilized for an efficient routing through considering the fitness functions like distance from CH to base station (BS), remaining energy and intra-communication cost. The suggested framework has been assessed using a MATLAB simulator. The efficacy of the suggested KOA-DAS framework has been determined using evaluation metrics including execution time, average residual energy, network lifetime (NL), latency, packet delivery ratio (PDR), computation cost, energy consumption (EC), and alive nodes. The suggested KOA-DAS framework achieves the lowest energy efficiency by 23.44%, 19.31%, and 14.44% than the ASFO, EELCR, and K-LionER approaches. The proposed model effectively selects the CH and routing through dynamically adjusting parameters, which results in minimum EC and extending NL.
A novel single-stage high-voltage gain DC-DC boost converter for on-board PEV charging system Motepalli Siva Rama Ganesh; S. Sasikumar; B. Suresh Babu
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i2.pp610-619

Abstract

Currently, the utilization of plug-in electric vehicles is quickly increasing in the vehicle industry owing to reduced costs of transportation, no need for fossil fuels, simple servicing, no fuel expense, and lower environmental effect compared to internal-combustion motor vehicles. In actuality, these motor vehicles function based on available battery energy that are charged by a utility-grid-supplied charging station. In this charging facility, a power converter defined on-board charger is generally used to charge the batteries, which improves the utility grid specifications by reducing the presence of harmonics and power factor regulation. An active two-stage load conditioning approach is commonly employed, however it doubles the conversion stages, requires larger switching components, complicated circuitry, large switching losses, and decreased efficiency, among other issues. To address these issues, a unique single-stage on-board EV charger has been used to regulate utility-grid specifications and seamless management of battery state-of-charge using a load-side DC-DC conditioning method. The major goal of this study is to propose a unique DC-DC boost converter that provides substantial voltage gain, consistent input current, minimal current ripples, and highest efficiency among numerous converters. The effectiveness of the proposed unique single-stage on-board EV charger has been evaluated through MATLAB/Simulink application, and the simulation findings have been presented.
Comparative performance analysis of MPPT algorithms for wind power generation: P&O, INC, and TSR methods Muhammad Aulia Desky; Yulianta Siregar; Maksum Pinem
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i2.pp894-904

Abstract

Wind energy has great potential, especially in areas with high wind speeds such as Southeast Aceh. However, wind speed fluctuations reduce turbine efficiency, necessitating maximum power point tracking (MPPT) for optimization. This study compared three MPPT methods perturb and observe (P&O), incremental conductance (INC), and tip speed ratio (TSR) to identify the most effective technique. Using MATLAB Simulink, simulations were conducted with wind speed data from Southeast Aceh and a DC-DC boost converter. Results showed the P&O method performed best, producing 847.83 W at 10 m/s, compared to 702.40 W for INC and 324.35 W for TSR. P&O also achieved the highest current output, reaching 16.45 A, while INC and TSR produced 13.66 A and 6.34 A, respectively. At lower wind speeds, P&O continued to outperform the other methods. This study concludes that the P&O method is the most effective method to improve the efficiency of wind turbines in Southeast Aceh, while INC shows moderate performance and TSR is the least effective method due to fluctuating wind speeds in a short time, so that TSR cannot maintain its maximum value. Therefore, P&O is recommended as the optimal MPPT technique for wind power plants in this region.
Investigation of the photoluminescence properties of quantum dots using theoretical simulation Le Doan Duy; Le Xuan Thuy
International Journal of Applied Power Engineering (IJAPE) Vol 15, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijape.v15.i2.pp942-947

Abstract

This study investigates the optical behavior of CdSe quantum dots, a class of semiconductor nanomaterials widely studied for light-emitting, photovoltaic, and bioimaging applications owing to their size-dependent electronic structure. The objective is to clarify the relationship between quantum dot size, size distribution, and emission characteristics through experimental and simulated optical spectra. UV-Vis absorption, photoluminescence, and simulated PL spectra were analyzed for CdSe quantum dots excited at 325 nm. The experimental PL spectrum exhibits a single and narrow emission band assigned to the 1Se → 1Sh transition, which is blue-shifted compared with bulk CdSe, confirming strong quantum confinement in 2-3 nm particles with a very narrow size distribution of less than 1%. A large Stokes shift of 0.93 eV is observed, attributed to confinement effects and surface-related states. Simulated photoluminescence (PL) spectra for 3-6 nm quantum dots show progressive red-shifting and spectral broadening with increasing particle size, while smaller quantum dots display stronger PL intensity due to enhanced confinement and more efficient radiative recombination. Parameter analysis further reveals that size deviation and linewidth broaden emission and reduce intensity without changing the peak wavelength. These findings provide useful guidance for optimizing CdSe quantum dots for QLEDs, bioimaging, and broadband optoelectronic devices.

Page 60 of 62 | Total Record : 614

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