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Portable solar photovoltaic systems for post-disaster emergency power supply: a comprehensive review

10.11591/ijape.v14.i4.pp1071-1084
Tole Sutikno , Wahyu Sapto Aji , Mochammad Facta , Hendril Satrian Purnama , Tri Wahono
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.
Volume: 14
Issue: 4
Page: 1071-1084
Publish at: 2025-12-01

Frequency response-based optimization of PID controllers for enhanced fluid control system performance

10.11591/ijape.v14.i4.pp1058-1070
Herri Trisna Frianto , Syahrul Humaidi , Kerista Tarigan , Dadan Ramdan , Doli Bonardo
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.
Volume: 14
Issue: 4
Page: 1058-1070
Publish at: 2025-12-01

Antecedents and consequences of memorable experience in the airline industry: service robots versus human staff

10.11591/ijra.v14i4.pp409-417
Jinsoo Hwang , Ja Young (Jacey) Choe , Kyuhyeon Joo , Jinkyung Jenny Kim
The study aims to examine the type of service providers, such as service robots and human staff, as a potential moderator in the relationship between SERVQUAL and memorable experience in the airport industry. In order to verify 15 hypotheses, data were collected from 313 travelers who acquired information from service robots and 313 travelers who acquired information from human staff at the airport. The results of data analysis revealed that the five sub-dimensions of SERVQUAL, including tangibles, reliability, responsiveness, assurance, and empathy, enhance memorable experience. In addition, a memorable experience has a positive effect on customer satisfaction, which subsequently influences attitude and intention to use. In addition, the type of service providers moderated the links between i) responsiveness and memorable experience and ii) empathy and memorable experience.
Volume: 14
Issue: 4
Page: 409-417
Publish at: 2025-12-01

A hybrid framework of IoT and machine learning for predictive analytics of a DC motor

10.11591/ijape.v14.i4.pp870-878
Lalitha Kandasamy , Annapoorani Ganesan , M. Shunmugathammal
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%.
Volume: 14
Issue: 4
Page: 870-878
Publish at: 2025-12-01

Transmission line fault detection using empirical mode decomposition in presence of wind intermittency

10.11591/ijape.v14.i4.pp960-969
Venkata Krishna Bokka , E. R. Biju , Sai Veerraju Mortha , Majahar Hussain Mahammad , Shaik Mohammad Irshad
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.
Volume: 14
Issue: 4
Page: 960-969
Publish at: 2025-12-01

Improving the adaptability of an active power filter using linearization feedback input-output sliding mode

10.11591/ijape.v14.i4.pp879-892
Leminh Thien Huynh , Van-Cuu Ho , Thanh-Vu Tran
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.
Volume: 14
Issue: 4
Page: 879-892
Publish at: 2025-12-01

A fuzzy logic approach to sustainable energy management in standalone microgrids

10.11591/ijape.v14.i4.pp999-1010
Suganthi Neelagiri , Srinivas Babu , Siddalingappagouda Biradar
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.
Volume: 14
Issue: 4
Page: 999-1010
Publish at: 2025-12-01

Enhanced cheetah optimizer for demand side management in smart grids with demand response and renewable energy

10.11591/ijape.v14.i4.pp912-922
Lakshmi Haveli , M. P. Flower Queen
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.
Volume: 14
Issue: 4
Page: 912-922
Publish at: 2025-12-01

Improve the thermal performance of the combined water-paraffin hot storage tank in the absorption cooling cycle

10.11591/ijape.v14.i4.pp1011-1022
Maki Haj Zaidan , Thamir Khalil Ibrahim , Hussam S. Dheyab
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.
Volume: 14
Issue: 4
Page: 1011-1022
Publish at: 2025-12-01

Speed control of 3-phase induction motor with modified DTC using HTAF-ANN

10.11591/ijpeds.v16.i4.pp2197-2211
Arpita Banik , Raja Gandhi , Chandan Kumar , Achyuta Nand Mishra , Rakesh Roy
In this research paper, an artificial neural network (ANN) algorithm is implemented with modifications to enhance the performance of a direct torque controlled (DTC) induction motor drive. Since the main challenge in the conventional DTC technique is to tune the PI controller appropriately therefore in this work, an ANN technique is incorporated in place of the conventional PI controller. Sudden changes in speed and loading in induction motor drives lead to sharp fluctuations and disturb the motor performance. In order to overcome these issues, a trained ANN controller is initially used here to enhance motor drive performance. Subsequently, the performance is further improved by modifying the activation function in the ANN controller. Here, motor parameters at rated and variable speed with various loading conditions have been analyzed and compared for the DTC with a conventional PI controller with ANN, and a proposed ANN controller. Simulation of the complete model with the conventional and proposed controllers is done using MATLAB/Simulink platform to observe the various speed responses for different conditions, and the experimental setup is used to demonstrate the effectiveness and performance of the proposed system.
Volume: 16
Issue: 4
Page: 2197-2211
Publish at: 2025-12-01

Design and development of a modular magnetic wheeled robot for out-pipe inspection

10.11591/ijra.v14i4.pp331-344
Sugin Elankavi Rajendran , Kuppan Chetty Ramanathan , Harish Kumar Guasekaran , Arun Kumar Pinagapani , Dinakaran Devaraj , Ramya Mathanagopal
This paper presents the design of a modular mobile robot capable of climbing and inspecting vertical ferromagnetic pipes using magnetic wheels. Mobile robots used for climbing ferromagnetic surfaces employ magnetic tracks, wheels, and magnets attached to the robot’s body. When it comes to ferromagnetic pipes, magnetic wheels and magnets attached to the body can be used. Among them, magnetic wheels are commonly used for inspecting ferromagnetic pipes. While current robots are suitable for large pipes, they are not practical for smaller ones. To address this gap, a small-sized robot equipped with a magnetic wheel system that ensures both strong attachment and smooth movement along vertical ferromagnetic surfaces is developed. The robot’s magnetic adhesion performance was analyzed through simulations using finite element method magnetics and validated through laboratory experiments. The results show an average error of only 8.25% between simulation and real-world tests, confirming the system’s reliability for external pipe inspection.
Volume: 14
Issue: 4
Page: 331-344
Publish at: 2025-12-01

Multi-objective energy management and environmental index optimization of a microgrid using swarm intelligence algorithm

10.11591/ijape.v14.i4.pp783-793
Ahmed Bahri , Nabil Mezhoud , Bilel Ayachi , Farouk Boukhenoufa , Lakhdar Bouras
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).
Volume: 14
Issue: 4
Page: 783-793
Publish at: 2025-12-01

Edge-aware distilled segmentation with pseudo-label refinement for autonomous driving perception

10.11591/ijra.v14i3.pp376-386
Novelio Putra Indarto , Oskar Natan , Andi Dharmawan
Achieving precise semantic segmentation is essential for enabling real-time perception in autonomous systems, yet leading approaches typically require substantial annotated data and powerful hardware, restricting their use on devices with limited resources. This work introduces an efficient segmentation framework that integrates pseudo-label refinement, knowledge distillation, and entropy-based confidence filtering to train compact student networks suitable for edge deployment. High-quality pseudo-labels are first produced by a robust teacher network, then further improved using a dense conditional random field to boost spatial consistency. An entropy-based selection mechanism removes unreliable predictions, ensuring that only the most trustworthy labels guide the student model's training. The use of knowledge distillation effectively transfers detailed semantic understanding from the teacher to the student, enhancing accuracy without added computational overhead. Experimental results with multiple EfficientNet backbones reveal that this pipeline improves segmentation accuracy and output clarity, while also supporting real-time or near real-time inference on CPUs with limited processing power. Extensive ablation and qualitative studies further confirm the method's robustness and flexibility for real-world edge applications.
Volume: 14
Issue: 3
Page: 376-386
Publish at: 2025-12-01

Energy resilience in disaster-prone regions: the role of portable and modular solar power systems

10.11591/ijpeds.v16.i4.pp2879-2894
Tole Sutikno , Mochammad Facta , Wahyu Sapto Aji , Lina Handayani , Watra Arsadiando , Hendril Satrian Purnama
Energy resilience is a critical requirement in disaster-prone regions, where electrical infrastructure is highly vulnerable to natural hazards and prolonged power outages. Portable and modular solar power systems have emerged as promising solutions for enhancing resilience by enabling decentralized, rapidly deployable, and grid-independent energy supply. This paper presents a comprehensive review of the role of portable and modular photovoltaic-based power systems in improving energy resilience from a power electronics perspective. The review synthesizes recent literature on resilience concepts, system architectures, and converter-based control strategies relevant to emergency energy applications. Particular emphasis is placed on DC-first and hybrid AC/DC architectures, modular converter topologies, battery management systems, and energy management strategies that support reliable and fault-tolerant operation under variable and uncertain conditions. Practical deployment and performance considerations, including scalability, robustness, monitoring, and usability in disaster environments, are also discussed. The findings indicate that well-designed portable and modular solar power systems can significantly reduce recovery time, improve operational continuity, and decrease reliance on centralized grids and fuel-based generators. This review identifies key technical challenges and research opportunities to guide future development of resilient power electronic-based energy systems for disaster response and recovery.
Volume: 16
Issue: 4
Page: 2879-2894
Publish at: 2025-12-01

Optimal battery sizing using modified spider monkey optimization in grid connected microgrids

10.11591/ijra.v14i3.pp356-365
Meraj Fatima , Manne Rama Subbamma
Microgrids (MGs) must have optimally sized storage and renewable energy sources to operate efficiently, economically, and reliably. MG may benefit from optimization techniques in their scheduling and sizing since they have a variety of energy sources with varying availability conditions and necessary costs. In this research, a novel modified spider monkey-based energy management system (MSM-EMS) has been proposed by increasing the photovoltaic (PV) or battery energy storage system (BESS) module capacity while minimizing grid connectivity dependency. The fundamental idea behind the proposed approach is greater dependability at the lowest feasible cost. By taking into account the BESS utilization factor and PV forced outage rates in a MG, the method becomes more realistic. Despite the absence of renewable energy sources and the grid, the proposed strategy provided critical loads according to schedule while maintaining reserve margins. Experimental findings demonstrate that the modified spider monkey optimization (MSMO)-based algorithm can determine the best BESS size and PV depending on cost. In comparison to particle swarm optimization (PSO) of $2756.1 and ABC of $2912.65, the ideal cost for EMS-MSMO is $2215.77 which is relatively low compared to the existing technique. As a result, the suggested MSMO algorithm and innovative energy management system has been optimized along with PV and battery dimensions.
Volume: 14
Issue: 3
Page: 356-365
Publish at: 2025-12-01
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