International Journal of Applied Power Engineering (IJAPE)
International Journal of Applied Power Engineering (IJAPE), p-ISSN 2252-8792, e-ISSN 2722-2624 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 and electrical energy sources. The journal covers, but is not limited to, the following scope: electric power generation, transmission and distribution, utilization of electric power, 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, electrical measurements, and the electrical apparatus connected to such systems. The journal is published by the Intelektual Pustaka Media Utama (IPMU) in collaboration with Institute of Advanced Engineering and Science (IAES). Beginning with issue 1 of volume 10 (2021), the IJAPE will be published as a three-monthly journal (4 issues/year). We are happy to announce that the International Journal of Applied Power Engineering has been accepted for inclusion in Scopus, the world's largest abstract and citation database of peer-reviewed literature, and got Q2 in the journal ranking by ScimagoJR.
Institute of Advanced Engineering and Science
Performance enhancement using sensor and sensorless control techniques for a modified bridgeless Ćuk converter-based BLDC motor in EV applications
This work proposes a solar photovoltaic (PV)-powered, modified bridgeless Ćuk converter tailored for electric vehicle applications. It overcomes limitations such as high ripple, reduced power density, significant switching losses, and complex circuit structures in traditional designs. The system integrates a boost converter with a bridgeless Ćuk topology to ensure a reliable and efficient direct current (DC) power output. Performance evaluation includes sensor-based and sensorless speed control techniques-pulse width modulation (PWM), proportional integral derivative (PID), back electromotive force (EMF), and spider controllers-under both no-load and full-load scenarios. Key parameters such as rise time, overshoot, settling time, and steady-state error are analyzed. MATLAB/Simulink simulations indicate that the spider controller delivers superior dynamic behavior and stability. A 48 W, 1500 rpm hardware prototype confirms the simulation outcomes, demonstrating the practical viability and effectiveness of the proposed converter.
Copyright (c) 2025 W. Margaret Amutha, S. Premalatha, M. Karthikeyan http://creativecommons.org/licenses/by-sa/4.0
Multi-objective energy management and environmental index optimization of a microgrid using swarm intelligence algorithm
Due to the need for better reliability, high energy quality, lower losses and cost, and clean environment, the application of renewable energy sources such as wind energy and solar energy in recent years has become more widespread mainly. In this work, one of the most general of all swarm intelligence algorithms, called particle swarm optimization (PSO) is applied to solve the optimal energy management (OEM) and environmental index optimization (EIO) problems of micro-grid (MG) operating by renewable and sustainable generation systems (RSGS). The PSO approach was examined and tested on standard MG composed of different types of RSGS, such as wind turbines (WT), photovoltaic systems (PV), fuel cells (FC), micro turbine (MT), and diesel electric generator (DEG) with energy storage systems (ESS). The results are promising and show the effectiveness and robustness of proposed approach to solve the OEM and the EIO. The results obtained were compared with some well-known references. The results show that the optimization process reduced the energy generation costs from 257283 ($/h), 263929 ($/h), and 263526 ($/h), respectively. While the environmental index further improved to 0.1548 (ton/h).
Copyright (c) 2025 Ahmed Bahri, Nabil Mezhoud, Bilel Ayachi, Farouk Boukhenoufa, Lakhdar Bouras http://creativecommons.org/licenses/by-sa/4.0
Design and implementation of solar-grid based charging station for electric vehicle with fault detection method using R-Pi and IoT processor
In this research describes the electrical vehicle (EV) charging station using PV panel with fault detection methods. The PV modules will failure for some time, because of some external factors and internal factors. In direct fault condition the monitor and analyze the external factors such as the life span, high intensity and breakage of the PV panels using Raspberry Pi (R-Pi) processor with internet of things (IoT) system. In power demand/day on the PV panel will be evaluated and analyzed through R-Pi processor and IoT. The efficiency and the range values of the PV panels will be monitored and analyzed through IoT. Proposed work explains, how the fault detection techniques have been improved and adopted in using R-Pi processor through IoT platform. The proposed dataset pre-processing system is incorporated with IoT module. The grid fault clearing time will be compared with the actual values through R-Pi processor. The PV panel faults are detected using thermal image processing, that image parameter values analysis through IoT based internal monitoring system.
Copyright (c) 2025 M. Vaigundamoorthi, S. Karthick, V. S. Chandrika, D. Chithra, K. V. Balaramakrishna, K. Lakshmi Khandan, Lakshmana Phaneendra Maguluri, S. Chandrasekar, M. Janarthanan http://creativecommons.org/licenses/by-sa/4.0
Design of a half-bridge inverter with digital SPWM control for pure sine wave output
To foster the widespread adoption of solar power, especially that produced by photovoltaic (PV) systems, we must move beyond the mere utilization of renewable energy sources. Prioritizing cost-effective approaches through innovative grid integration is essential. This strategic transformation significantly contributes to the global expansion of electrical energy production. One pioneering approach involves the implementation of inverters operating at high frequencies to efficiently filter and eliminate undesirable current harmonics, thus enhancing system performance. This innovative technique relies on the generation of rapid complementary digital pulse width modulation (PWM) signals, complete with built-in dead time, to manage a half-bridge inverter with a single phase. The paper recommends employing the IR2110 driver, an often-used component for MOSFET switch management, to execute this strategy. The entire system is controlled by high-frequency PWM signals, meticulously programmed for precision, generated by a microcontroller driver board. With its adaptability to various renewable energy conversion devices, this methodology extends its utility beyond solar energy. Practical tests have confirmed the efficacy of this strategy. Future research in this field should scrutinize the effect of PWM on system stability and harmonic distortion, explore advanced modulation methods, align PWM approaches with upcoming power electronics technologies, and work towards improving system efficiency.
Copyright (c) 2025 Jalil Akaaboune, Bouazza El Mourabit, Mohamed Oulaaross, Mohamed Benchagra http://creativecommons.org/licenses/by-sa/4.0
Frequency control of hybrid power system with fractional order secondary controller using improved biogeography-based krill herd algorithm
To meet the demand of electrical power, structural changes of the power system from the generation side are necessary by integrating the renewable sources into the existing system. In the presence of renewables, the active power imbalances caused by both generation and demand are reduced with the classical units (like thermal) since the wind speed and irradiance (inputs of wind and solar plants) are volatile and nonlinear in nature. The frequency deviations triggered by such active power imbalances of the hybrid power system integrated with both conventional and renewable energy plants are minimized with better secondary control schemes. Therefore, this article suggests fractional order secondary controller (FOSC) for conventional units of the interconnected power system to strengthen the frequency stability of the system during the demand perturbations. The optimal gains of the FOSC are identified with an improved biogeography-based krill herd optimizer with the help of the performance indicator integral square error. To elevate the improvements of FOSC, comparisons are provided with classical controllers during the simple, random load perturbations with and without generation changes. Furthermore, sensitivity analysis on system parameters is performed to show the robustness of the FOSC over classical control strategies.
Copyright (c) 2025 Kukkamalla Kiran Kumar, Gobinathan Balaji, Kanta Rao Pedakota, Majahar Hussain Mahammad, Syed Suraya http://creativecommons.org/licenses/by-sa/4.0
Optimal placement and sizing of DG and DSTATCOM in order to mitigate power losses in electrical distribution system
The emphasis is now shifting away from conventional methods of power generation and towards unconventional distributed energy resources (DERs) located at distribution voltage level due to the rapid depletion of fossil fuel supplies and significant environmental pollution. Emphasis on research into the applications of DERs found scope in microgrids and active distribution networks. The placement of DERs close to load centers aids with providing clean, reliable power to additional customers, reduce electricity losses along transmission and distribution lines and in event of faults it allows to operate in islanded mode. This manuscript focuses on power smoothing, which implies reduction of power loss, improved voltage levels, and voltage stability. This study aims to optimize the capacities and placements of distributed generations (DGs) and distribution static compensators (DSTATCOMs) in order to reduce real power loss and improve the voltage profile. The problem of voltage from undistributed energy resources can best be solved by DSTATCOM. The goal function of the direct load flow technique, which also makes use of voltage deviation and the loss sensitivity factor, is used in this study to pinpoint the ideal placement for the DG and DSTATCOM on the MATLAB platform. The method is tested using the 33 and 69 bus routes. When the results are compared to recent methodologies, they show encouraging results.
Copyright (c) 2025 Smrutirekha Mahanta, Manoj Kumar Maharana http://creativecommons.org/licenses/by-sa/4.0
Power smoothing in electrical distribution system using covariance matrix adaptation evolution strategy of aquila optimization
This study introduces a novel hybrid optimization approach covariance matrix adaptation evolution strategy of aquila optimization (CMAESAO) to enhance power smoothing and minimize power losses in electrical distribution systems through the optimal allocation of D-STATCOMs. The method is tested on standard 33-bus and 69-bus systems. The CMAESAO algorithm efficiently identifies optimal locations and sizes of D-STATCOMs to achieve system performance improvements under constant power (CP), constant current (CC), and constant impedance (CI) load models. The results show that, for the 69-bus system, installing two D-STATCOMs yields optimal performance, reducing real power loss from the base value to 149.6368 kW, while three D-STATCOMs yield a slightly better voltage profile and VSI but only marginal additional power loss reduction (147.8951 kW), making two units more cost-effective. For the 33-bus system, three D-STATCOMs provide the best improvement in power quality and loss minimization. Voltage and current profiles confirmed improvement in voltage stability and reduced branch currents with optimized placements. Compared to other optimization techniques, CMAESAO demonstrates faster convergence and superior accuracy in minimizing losses, establishing its effectiveness for such multi-objective optimization problems. The study's novelty lies in integrating CMA-ES with aquila optimization to combine strong global search with adaptive exploration, resulting in robust and efficient power system enhancement. The proposed methodology contributes to smarter, more reliable distribution systems, supporting grid resilience and energy efficiency.
Smart wireless charging architecture for electric vehicles using resonant inductive coupling and low-component design
A wireless power transfer system designed for electro-vehicle recharge and low-power device charging is explained in this document through resonant inductive coupling technology. Once switched on the pulse generator and IRF540 MOSFETs from the IC CD4047 drive high-frequency signals through the transmitter coil. IR sensors function as operational safety tools by detecting valid receivers which activate a relay control system for transmitter power management and reduce unnecessary energy consumption. A full-wave rectifier along with the 7805-voltage regulator enables the receiver unit to deliver fully stable 5 V DC output. System status is displayed through a user interface equipped with an LCD and real-time billing information runs on ThingSpeak IoT platform for visualization. Tests show that the system reaches a maximum power transfer efficiency of 90% alongside successful relay operation lasting less than 150 ms. The system provides an inexpensive solution to build smart wireless charging infrastructure networks that remain energy-efficient and expandable through its built-in control and monitoring functions.
Copyright (c) 2025 Devarakonda Mahidhar, Burthi Loveswara Rao, K. V. Govardhan Rao, C. H. Rami Reddy http://creativecommons.org/licenses/by-sa/4.0
A hybrid framework of IoT and machine learning for predictive analytics of a DC motor
Many industrial applications utilize direct current (DC) motor as an essential element. It functions as the backbone of several industries and global pillar of manufacturing applications. The predictive analytics of motor is primary for preventing unpredicted downtime, reducing protection costs, and improving system effectiveness. This paper presents a hybrid framework integrating the internet of things (IoT) and machine learning (ML) for real-time predictive analytics of DC motors. The leveraging of machine learning algorithms in predictive maintenance of DC motors has shown significant potential in reducing downtime and increasing the lifespan of the motor. Therefore, a system for predictive analytics with machine learning strategy is proposed and message queuing telemetry transport (MQTT messaging) is included for effective information transmission between sensors and gateways. The data received from the sensors is utilized to make prediction about the remaining useful life of the motor and generate alerts for maintenance before failures occur. So, the integration of machine learning algorithms in predictive maintenance of DC motors is a promising approach to increase the reliability and efficiency of DC motors. The highest performance is achieved in random forest with accuracy of 93.4%.
Copyright (c) 2025 Lalitha Kandasamy, Annapoorani Ganesan, M. Shunmugathammal http://creativecommons.org/licenses/by-sa/4.0
Improving the adaptability of an active power filter using linearization feedback input-output sliding mode
As more and more non-linear loads are used in industrial applications, power quality problems become more serious. To address this challenge, a robust nonlinear control strategy is introduced using an active power filter (APF) to enhance the power quality of the three-phase neutral voltage. The system employs a control algorithm tailored for a three-phase split-capacitor inverter, which eliminates high-order harmonics through a voltage source inverter (VSI) equipped with an LCL filter. The grid-side components of the LCL filter are incorporated into a sliding mode control framework to minimize oscillations while maintaining performance. Additionally, the d-q-0 transformation within the synchronous reference frame is applied to effectively manage the second harmonic component. In addition, the linear feedback input-output sliding mode facilitates the control system. This system can help decrease total harmonic distortion (THD) to meet IEEE-519 standards. This method demonstrates its effectiveness through simulation results, reducing THD to less than 5% and defeating previous methods despite still using simple algorithms.
Copyright (c) 2025 Leminh Thien Huynh, Van-Cuu Ho, Thanh-Vu Tran http://creativecommons.org/licenses/by-sa/4.0
PD characteristics of polymer insulation for inverted-fed drives under sine and square waveforms
In recent years, adjustable speed drives power by power electronic converters have caused insulation failure in the electrical motors with stator windings. The repeating impulse voltages produced by IGBTs created insulation reliability problems in the stator winding. Overvoltage can cause partial discharge (PD), which can rapidly result in insulation system failure. To address this issue, IEC standards and technical specifications (TS) necessitate that a PD test on the motor insulation system is done at sinusoidal and square voltages. The PD characteristics obtained are used to evaluate insulation performance, enhancing insulation design. This work focuses on the PD characterization of twisted pair samples using high frequency sine and square waveforms at room temperature. The PD characteristics were investigated at 50 Hz, 1 kHz, 2.4 kHz, and 5 kHz. The result shows that there are fewer PD events with lower PD magnitudes and shorter delay times at higher frequencies. Further, at different temperatures of 30 °C, 60 °C, and 90 °C, the partial discharge inception voltage (PDIV) of twisted pair insulation was investigated using high-frequency sine and square waveforms. The results show that the corona inception voltage (CIV) (kV) decreases as ambient temperature increases. Furthermore, the conditions for PD occurrence in the insulation system were analyzed at higher switching frequencies. The electric field distribution of twisted pairs with a 0 mm air gap was modeled from 50 Hz to 5 kHz switching frequency using COMSOL software.
Copyright (c) 2025 S. Narasimha Rao, Elanseralathan Kasinathan, Ramanujam Sarathi http://creativecommons.org/licenses/by-sa/4.0
Eco-friendly innovation: green energy empowered by IoT
Energy demand is high globally, impacting daily life and promoting sustainable modernization. Goal 9 aims to build an elastic framework for economies, while Goal 15 of the Sustainable Development Goals (SDGs) emphasizes the preservation of terrestrial environment, sustainable woodland management, and biodiversity conservation. The International Energy Agency predicts a significant increase in global renewable capacity, with solar PV being two-third of this growth. Green technology is crucial to combat global warming and Industry 4.0, a digital transformation that aims to create a strong framework for sustainable modernization. The growth of the smart grid is vital, involving energy sources, control techniques, computation, generation, transmission, distribution, and more. Supercapacitors store and deliver energy at high capacity, while green energy transforms fossil fuels into eco-friendly sources using natural resources like hydro, solar, wind, thermal, and biomass. This study explores the efficient use of microprocessors in solar and wind energy, as well as the application of actuators in the green energy sector. Green energy is a sustainable solution to increasing energy needs, reducing dependence on fossil fuels. IoT technologies, including sensors, actuators, microprocessors, and microcontrollers, are used in energy generation, transmission, distribution, and composition.
Copyright (c) 2025 Nikita Amoli, Jitendra Singh, Rahul Mahala, Rajesh Singh, Anita Gehlot, Mahim Raj Gupta http://creativecommons.org/licenses/by-sa/4.0
Enhanced cheetah optimizer for demand side management in smart grids with demand response and renewable energy
For the effective operation of smart grids, it is critical to ensure that demand side management (DSM) includes strong two-way communication and addresses significant security and privacy issues. DSM success depends on the participation of customers who need a just system. The recent fairness studies in DSM have identified different definitions of fairness while this study presents an enhanced cheetah optimizer algorithm (ECOA) for solving complex dynamic economic dispatch (DED). The ECOA targets at minimizing operational costs as well as improving power system security. This research tests the ECOA performance by examining DED problem independently from DSM, and demonstrates its applicability on 10-unit and 20-unit test systems. These figures clearly show that ECOA decreases operational costs by about 0.24% and 0.43% respectively, once DSM is used. Thus, it is possible to conclude that DSM has the possibility of bringing down costs and enhancing economic efficiency. Considering the integration of renewable energy sources into microgrids with electric vehicles, ECOA’s adaptivity and dependability make it a potential approach to multi-objective energy management within such kind of networks.
Copyright (c) 2025 Lakshmi Haveli, M. P. Flower Queen http://creativecommons.org/licenses/by-sa/4.0
Three-phase power flow solution of active distribution network using trust-region method
Distribution systems or networks are inherently unbalanced. As a result, single-phase power flow methods are generally no longer valid for such systems. Therefore, to obtain accurate results, unbalanced systems should be analyzed using three-phase power flow methods, which are far more complicated than the single-phase methods. Moreover, at present, the penetration of distributed generation (DG) in the distribution network has significantly increased. DG integration will increase the complication of the power flow analysis as it changes the network's basic configuration from passive to active system. This computational burden will significantly be higher if the power flow calculation has to be conducted several times (for example, in feeder reconfigurations or service restorations). This paper investigates the utilization of the trust-region method in obtaining the solution to the three-phase power flow problem of an active distribution network (i.e., distribution network embedded with DG). Trust-region computation algorithm is robust and powerful since the optimization technique is employed in finding new solutions in the iteration process. Results obtained from three representative unbalanced distribution networks (i.e., 10-node, 19-node, and 25-node networks) verify the validity of the proposed method. The effects of DG installation on distribution network steady-state performances are also investigated in the present paper.
Copyright (c) 2025 Rudy Gianto, M. Iqbal Arsyad, Managam Rajagukguk http://creativecommons.org/licenses/by-sa/4.0
A novel WSSA technique for multi-objective optimal capacitors placement and rating in radial distribution networks
Minimizing power loss while keeping the voltage profile within acceptable limits is a great challenge for the distribution system operators. Properly sized and optimally placed shunt capacitors (SCs) in radial distribution networks (RDNs) can enhance system efficiency and offer both technical and economic benefits. This paper presents a novel meta-heuristic technique, the weight salp swarm algorithm (WSSA) as a modified version of the original SSA algorithm by incorporating an inertia weight parameter to improve precision, speed, and consistency in solving the optimal capacitor placement (OCP) problem. The proposed method minimizes power loss, annual total costs, and improves the voltage profile of RDNs, ensuring practical applicability. Two RDNs, IEEE 33-bus and a real Iraqi 65-bus in Sadat Al-Hindiya, Babel Governorate, Iraq, were used to evaluate WSSA's performance. Comparative analysis with recently published approaches demonstrates WSSA’s superiority in reducing power loss, lowering costs, and improving voltage profiles. For the IEEE 33-bus, power loss is decreased by 34.81%, and the total cost is lessened by 29.08% (savings of $30,965.33). For the Iraqi 65-bus, WSSA reduces power loss by 32.03% and decreases the total cost by 29.51% (savings of $69,201.57). These results confirm WSSA’s effectiveness in achieving OCP with enhanced technical and economic benefits.
Copyright (c) 2025 Omar Muhammed Neda http://creativecommons.org/licenses/by-sa/4.0
A hybrid one step voltage-adjustable transformerless inverter for a one-phase grid incorporation of wind and solar power
This paper presents a hybrid one-step voltage-adjustable transformerless inverter designed to efficiently integrate both solar photovoltaic (PV) and wind energy sources into a single-phase grid. The primary objective is to enhance power conversion efficiency while minimizing system complexity and cost. The proposed architecture combines a buck-boost DC-DC converter with a full-bridge inverter in a compact and modular design, enabling voltage regulation across a wide input range typical of hybrid renewable systems. By grounding the PV negative terminal, the system effectively eliminates leakage currents and ensures compliance with IEEE harmonic standards. The inverter operates with reduced switching losses and supports multiple operational modes tailored for variable solar and wind conditions. Simulation of a 300 W prototype demonstrates reliable performance, achieving a total harmonic distortion (THD) below 1%, validating its compatibility with grid requirements. Key contributions include the development of a unified topology for hybrid energy sources, in-depth analysis of energy storage components, and implementation of efficient modulation strategies. This work addresses significant challenges in renewable energy integration and provides a scalable solution for next-generation grid-connected hybrid power systems.
Copyright (c) 2025 Bonigala Ramesh, Madhubabu Thiruveedula, Rahul Inumula, C. Poojitha Reddy, Mohammad Abdul Khadar, K. Sri Sai Hareesh http://creativecommons.org/licenses/by-sa/4.0
Transmission line fault detection using empirical mode decomposition in presence of wind intermittency
The regular fault detection approaches are failed to detect the faults in wind integrated transmission networks due to intermittency nature of the wind energy. More reliable schemes are required to accomplish the detection of faults in presence wind. This article proposed empirical mode decomposition (EMD) based fault detection scheme to detect various faults in wind integrated transmission lines during the normal and stressed conditions of the system. The instantaneous current measurements available at either sending or receiving end are processed through EMD to decompose it into a series of intrinsic mode functions (IMFs) and IMF2 is identified as a dominated IMF with numerous case wise investigations. 1/4th cycle moving window is used to calculate the absolute sum of the IMF2 coefficients to detect the faults with the support of a predefined threshold. The efficacy of the method is tested on different types of faults during the normal condition in presence of wind and later extended to stressed conditions such as power swing. The method is reliable during the typical cases and includes remote end and high resistance faults. All the experiments are carried out in Simulink to generate the measurement data and programs are executed in MATLAB.
Copyright (c) 2025 Venkata Krishna Bokka, E. R. Biju, Sai Veerraju Mortha, Majahar Hussain Mahammad, Shaik Mohammad Irshad http://creativecommons.org/licenses/by-sa/4.0
Optimize the position of the distributed generator and capacitor bank in the distributed grid to minimize the generation cost
In this paper, we focus on determining the optimal position and size of multi-distributed generators and capacitor banks to minimize the generation cost of a distributed grid. The optimal position and size of distributed generators and capacitor banks are determined using a hybrid of conventional loss sensitivity factor and an improved one. The proposed algorithm has two stages. For each distributed generator, we prioritize its position and size. After that, we find the optimal position and size of the capacitor banks corresponding to this distributed generator installation to minimize the power loss. After considering all distributed generators, the optimal number, position, and size of the distributed generators and capacitor banks are determined based on the minimum generation cost value. This idea is developed in MATLAB and verified via sample distributed grids, including the IEEE-69 bus and IEEE-85 bus. The verifying results are evaluated and analyzed. By comparing those results to those of other methods, the performance of the newly introduced method is proven.
Copyright (c) 2025 Ngoc An Luu, Dinh Chung Phan http://creativecommons.org/licenses/by-sa/4.0
Effect on saturated and unsaturated fatty acids on various vegetable oils on droplet combustion characteristic
Vegetable oils have composed of triglycerides, which one consist of 3 fatty acids combined with glycerol. Each saturated and unsaturated fatty acid has a different effect on burning characteristics. This study aimed to investigated effect of fatty acids at ceiba pentandra and jatropha oils on the flame behavior of the droplet combustion process. The combustion characteristic was observed by an ignited droplet at the junction using a thermocouple and a high-speed camera (120 fps). Results showed that a higher saturated fatty acid content resulted in long-life and steady flames. This is because more oleic and linoleic acid carbon atoms leave the droplet area and react with air. Jatropha oil produces a higher temperature of 780 °C than ceiba pentandra oil. Temperature of a vegetable oils flame is influenced by number of carbon chains, double bond, and heating value. Ceiba pentandra oil has a higher burning rate of 0.185 mm/s than jatropha oil at 0.155 mm/s. The chain content of polyunsaturated fatty acids has significant effect on rate of combustion, which is due to the weak van der Waals dispersion forces, such that heat absorption is more active and energetic. The highest flame height for ceiba pentandra oil is 55.03 mm compared to for jatropha oil it is 46.82 mm. Long-chain unsaturated double bonds and glycerol cause micro-explosions. This micro-explosion caused the shape of the flame to split and expand so that evaporation occurred faster, thus increasing the size of the flame.
Copyright (c) 2025 Dony Perdana, Muhamad Nur Rohman, Mochamad Choifin http://creativecommons.org/licenses/by-sa/4.0
Integration and optimization of grid through ANN-based solar MPPT and battery
Integration of solar energy into the grid is the most important aspect for achieving sustainable energy systems. This paper presents an artificial neural network-based maximum power point tracking (ANN-MPPT) system with battery storage to enhance grid efficiency. The proposed ANN-MPPT is dynamically adapted to the varying irradiance and temperature, hence ensuring optimal power extraction from the photovoltaic system. Excess energy is stored in batteries during high solar radiation and discharged when solar generation is low or grid demand is high, maintaining a stable power supply. This system enhances the grid performance in terms of supporting real-time energy exchange, load balancing, and grid stability. Efficient management of the energy fluctuations ensures reliability even at times of grid failures. Further, integration of ANN-based MPPT with battery storage reduces dependence on non-renewable sources and harmonizes solar energy utilization. It can be achieved through enabling smarter energy management and thus contributing to the resilience and efficiency of a grid for better integration of renewable energies. The proposed system can tolerate fluctuating grid demands apart from supporting the features of smart grid, hence viable for increasing stability and sustainability in the grid.
Copyright (c) 2025 Kolli Sujran, Ankala Sirisha, Ganapaneni Swapna, Malligunta Kiran Kumar, Kambhampati Venkata Govardhan Rao2 http://creativecommons.org/licenses/by-sa/4.0
A fuzzy logic approach to sustainable energy management in standalone microgrids
The fast development of worldwide energy consumption, driven by industrial growth and increasing dependence on fossil fuels, has led to higher carbon emissions and degradation of the environment. In response, renewable energy sources, such as solar, wind, and hydroelectric power, offer cleaner and sustainable replacements with insignificant carbon emissions. This paper examines the role of artificial intelligence (AI)-based techniques, particularly fuzzy logic, in developing energy management system. A fuzzy logic-based energy management system is proposed for a renewable-powered microgrid that incorporates a hybrid energy storage system. Fuzzy logic-based energy management, due to its capability to manage uncertainty and complexity, offers viable solutions for improving the generation and distribution of energy within microgrid systems. This system is compared to a dynamic cascaded dual-loop proportional-integral (PI) controller-based energy management system in standalone mode. The comparative analysis emphasizes the ability of fuzzy logic-based energy management to improve the efficiency and sustainability of microgrids. The research aims to advance the creation of more intelligent and dependable energy solutions that integrate renewable resources and enhance energy management practices.
Copyright (c) 2025 Suganthi Neelagiri, Srinivas Babu, Siddalingappagouda Biradar http://creativecommons.org/licenses/by-sa/4.0
Improve the thermal performance of the combined water-paraffin hot storage tank in the absorption cooling cycle
This research investigates the thermal performance of storage materials in a hot tank designed to extend the operation time of a 1.5-ton water ammonia absorption cooling system. Thermal energy is supplied by concentric parabolic solar collectors, which heat the absorption cycle generator during periods of sufficient solar radiation. When the water temperature exceeds the system’s operating threshold, the additional heat accumulates in the hot tank. It is later used to drive the generator during periods of low solar availability, such as in the afternoon or after sunset. The system is designed to provide air conditioning for a room; its load was calculated hourly. The suitable size of the storage tank and the corresponding collector area were determined based on simulations of the absorption system to achieve an optimal coefficient of performance (COP). The collector area was increased after the addition of paraffin phase change material (PCM) to enhance system performance, and a temperature control strategy was implemented to prevent the water in the hot storage tank from reaching the boiling point. This was achieved by incorporating a specific percentage of paraffin, a PCM, with a melting point of 85 °C. The size of the hot storage tank containing both water and a specified proportion of paraffin, in addition to the solar collector area, was optimized to maximize the tank temperature. These parameters were entered into the energy balance model as input data to ensure the effective operation of the absorption system under optimal conditions. A comprehensive system simulation was conducted by deriving and simplifying the heat balance equations for the hybrid hot storage tank, the solar collector, and the absorption system. The simulation aimed to identify the optimal wax ratio of 5% to 20% to maximize system performance. The optimal paraffin ratio was found to be 10% of the tank volume, which enabled an additional 4 hours of operation and extended the system’s uptime to its maximum potential.
Copyright (c) 2025 Maki Haj Zaidan, Thamir Khalil Ibrahim, Hussam S. Dheyab http://creativecommons.org/licenses/by-sa/4.0
Asymmetrical nine-level hybrid multilevel inverter design and analysis for electric vehicle applications
A novel type of single-phase hybrid multilevel inverter (HMLI) is proposed in this paper. A hybrid system is made up of a multilevel inverter coupled to an H-bridge unit and which can generate nine-level output. To synthesize an output voltage waveform with nine steps, this setup uses merely seven power switches, two diodes, and two DC supplies. A greater number of steps were achieved in output voltage through suggested circuit with a smaller number of components than other existing multilevel inverter (MLI) topologies. A finer output waveform that is closer to a sinusoidal shape is produced with less total harmonic distortion (THD) because of the greater number of steps in the output voltage. Furthermore, it prolongs the switches' lifetime and lowers the voltage stress across them, increasing reliability. In addition, the system produces fewer switches than necessary, resulting in lower power losses and increased efficiency. This guarantees the suggested system's small size and inexpensive cost. A comparison between the suggested topology and the most current MLI topologies has been conducted to highlight the key components of the proposed topology. The suggested topology has been controlled using three distinct controlling schemes are phase disposition-pulse width modulation (PD-PWM), phase opposition disposition-PWM (POD-PWM), and alternative phase opposition disposition-PWM (APOD-PWM).
Copyright (c) 2025 Gerri Ratnaiah, Ramya Ganesan http://creativecommons.org/licenses/by-sa/4.0
Techno-economic optimization of hybrid renewable energy systems for household energy management
Housing is a private palace that is safe, comfortable, and private. Techno-economic optimization of hybrid renewable energy systems and energy management for realizing green energy is a fundamental concept for ensuring security, comfort, and privacy in green housing for its residents, enabling them to carry out activities in their environment. The application of techno-economic optimization and renewable energy management to manage electrical energy so that it can be saved so that electricity costs can be reduced as one of the energy efficiency models. The problem of waste emissions and environmental pollution cannot be avoided. Therefore, a techno-economic optimization model for integrated power generation is needed, which is environmentally friendly and related to the housing problem discussed in this study. This study supports the concept that hybrid housing development is the best way to address environmental pollution, emissions, and waste in future housing and can be used as a benchmark for future housing development. In addition, the techno-economics of renewable energy used in households was also discussed.
Copyright (c) 2025 Faisal Irsan Pasaribu, Suwarno, Surya Hardi, Ahmad Taufik, Albert Panjaitan, Aimil Musfi Andri, Muhammad Reza Aulia http://creativecommons.org/licenses/by-sa/4.0
Systematic literature review on cyber-attacks and cyber defense strategies in smart grids
The smart grid is an advanced evolution of the traditional electrical power grid, developed to meet the increasing energy demands and requirements of the 21st century by incorporating digital technologies and data management systems to improve efficiency and reliability. Unlike conventional grids, the smart grid relies on a network of interconnected digital devices, sensors, and computerized controls that enable real-time monitoring and management of electricity distribution across vast geographic areas. However, the growing dependence on digital technologies also brings heightened cyber security concerns, since their integration can expose the grid to an increased risk of malicious intrusions. This systematic literature review investigates the nature and scope of cyber-attacks and cyber defense strategies in smart grids, which are critical to modern energy infrastructure. Following established research guidelines, this review rigorously examines existing studies by focusing on peer-reviewed articles and conference papers to understand the range of cyber security threats and defense mechanisms that smart grids face. The review uses a structured methodology to identify, evaluate, and synthesize key findings, revealing trends and gaps in current knowledge about smart grid security. The outcomes of this analysis offer valuable clarity on the specific weaknesses and operational challenges that affect smart grid infrastructures, contributing to the ongoing efforts to enhance cyber security measures and guide future research in this vital field.
Copyright (c) 2025 Anass Naqqad, Abdellah Boulal, Rachid Habachi http://creativecommons.org/licenses/by-sa/4.0
Frequency response-based optimization of PID controllers for enhanced fluid control system performance
Temperature and viscosity variations are known to affect the performance of proportional-integral-derivative (PID) controllers in fluid systems. However, there exist gaps in research relative to the thermal effects on the performance of PID based fluid systems. PID controllers are also utilized for fluid control to maintain stability and improve performance. This study aims to explore the influence of temperature and viscosity variations through frequency response analysis for the first time in this regard. Utilizing a controlled experimental setup, gain and phase values were measured across different temperature points. Bode and Nyquist plots were generated to observe system behavior, stability, and response to changes in temperature and fluid viscosity. The results show a clear inverse relationship between temperature and gain, with a notable phase lag increase as temperature rises. At 25 °C, the gain was measured at 15.83 dB with a phase of -52.63°, which gradually reduced to a gain of 13 dB and a phase of -61.53° at 80 °C. The Nyquist analysis revealed stable operation within this temperature range, but the shift in response indicates increased system vulnerability as viscosity decreases with rising temperature. The derived linear equations effectively model the gain-phase relationship, with an R² of 0.9985, suggesting a highly accurate fit. Overall, the study concludes that temperature-induced viscosity changes significantly impact PID-controlled fluid systems, emphasizing the need for adaptive control strategies in fluctuating environments.
Copyright (c) 2025 Herri Trisna Frianto, Syahrul Humaidi, Kerista Tarigan, Dadan Ramdan, Doli Bonardo http://creativecommons.org/licenses/by-sa/4.0
Portable solar photovoltaic systems for post-disaster emergency power supply: a comprehensive review
Natural disasters frequently disrupt electrical infrastructure, creating critical challenges for emergency response, healthcare delivery, and community recovery. Portable solar photovoltaic (PV) systems have emerged as a sustainable and rapidly deployable solution for off‑grid energy provision in disaster‑affected regions. This review provides a comprehensive synthesis of portable PV technologies for post‑disaster applications, encompassing system architectures, component selection, deployment configurations, and operational performance. Particular emphasis is placed on DC‑first designs, modular scalability, energy storage integration, and IoT‑enabled monitoring, which collectively enhance efficiency, reliability, and usability under harsh environmental conditions. The analysis highlights persistent challenges related to energy efficiency, storage resilience, system standardization, and user accessibility, while underscoring the importance of integration into broader emergency energy ecosystems. Research gaps are identified in areas such as efficiency optimization, human‑centered design, and scalability, providing guidance for the development of next‑generation portable PV systems. By consolidating technical and operational insights, this review establishes a foundation for advancing portable PV systems as robust emergency energy solutions, bridging the gap between immediate relief and long‑term resilience in disaster‑prone regions.
Copyright (c) 2025 Tole Sutikno, Wahyu Sapto Aji, Mochammad Facta, Hendril Satrian Purnama, Tri Wahono http://creativecommons.org/licenses/by-sa/4.0