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Seasonal and diurnal variations of wet scintillation in tropical region Malaysia

10.11591/ijeecs.v42.i3.pp721-728
Ibtihal Fawzi El-Shami , Jafri Din , Ali I. Elgayar , Ahlaam Miftah Saed
This paper investigates the seasonal and diurnal variations of wet tropospheric scintillation in a tropical region to support the design and optimization of fade margin in satellite communication systems. A one-year Ku-band propagation measurement campaign was conducted in Johor Bahru, Malaysia, using a direct broadcast receiver (DBR) and an automatic weather station (AWS) to capture both signal and meteorological data. A comprehensive signal processing technique was applied to separate scintillation effects from rain attenuation, enabling accurate statistical characterization. The analysis was performed based on monsoon seasons and different time intervals of the day. The results indicate that higher scintillation fades are most likely to occur during the afternoon period, particularly between 3:00 pm and 6:00 pm. In addition, the inter-monsoon season exhibits a higher rate of variation in scintillation intensity due to increased convective activity, whereas the southwest monsoon shows relatively lower variability under drier conditions. The findings also demonstrate that diurnal scintillation behavior is strongly influenced by seasonal patterns, with peak intensity typically observed in the late afternoon across different monsoon periods. Unlike many existing models developed for temperate regions, this study provides experimental insights into scintillation characteristics under equatorial climatic conditions. These results offer valuable guidelines for system designers to improve fade margin allocation and enhance the reliability of satellite links in tropical environments.
Volume: 42
Issue: 3
Page: 721-728
Publish at: 2026-06-10

Adaptive fractional-order PID-controlled DVR optimized by zebra algorithm for harmonic suppression

10.11591/ijeecs.v42.i3.pp786-796
Milind Paraye , Rajendra G. Sutar
Dynamic voltage restorers (DVRs) are widely employed to mitigate power quality disturbances in modern power grids. Existing DVR control strategies frequently struggle to adequately suppress harmonic distortions and voltage sags due to nonlinear grid behaviour, rapidly varying disturbances, and limited tuning flexibility. We suggest a grid-connected DVR with an adaptive fractional order proportional integral derivative (FOPID) controller whose parameters are improved using an improved zebra algorithm (IZA) in order to close this gap. The IZA algorithm is used to improve the FOPID controller parameters, ensuring rapid convergence and superior accuracy. The effectiveness of the proposed system is assessed under two different operating conditions. In case 1, the harmonic compensation is analyzed, in which the DVR reduces systemic harmonic disturbances. The results reveal that the proposed controller reduces the total harmonic distortion (THD) from 1.36% to 0.01% while maintaining a constant voltage amplitude of around 0.9986 V, demonstrating strong harmonic suppression capability. Voltage sag mitigation is assessed in Case 2. The load voltage is effectively restored from 0.722 V to 0.9986 V by the DVR, which also reduces THD from 32.97% to 1.6% by injecting the required compensatory current. Overall, the results confirm that the adaptive FOPID–IZA controlled DVR significantly improves power quality and voltage stability in grid-connected systems by effectively mitigating both harmonic distortion and voltage sags.
Volume: 42
Issue: 3
Page: 786-796
Publish at: 2026-06-10

Grasshopper sound acoustic signal analysis using FFT and Butterworth filter

10.11591/ijeecs.v42.i3.pp708-720
Khairunnisa Khairunnisa , Sarifudin Sarifudin , Annisa Maulidia Damayanti
Grasshoppers are among the most destructive agricultural pests, making early detection essential to reduce crop losses while limiting excessive pesticide use. Acoustic monitoring provides a non-invasive and environmentally friendly approach for pest detection; however, its effectiveness is often constrained by strong environmental noise in open field conditions. This study proposes a structured acoustic signal analysis framework for grasshopper detection based on fast fourier transform (FFT) and Butterworth bandpass filtering. Grasshopper sound recordings were collected in rice field environments and pre-processed using Butterworth filters with empirically determined cutoff frequencies to suppress out-of band noise. FFT was applied to extract dominant spectral features, and signal quality was evaluated using both direct signal-to-noise ratio (SNR) and power spectral density (PSD)-based SNR estimated via the Welch method. Results indicate that grasshopper acoustic energy is consistently concentrated within the frequency range of approximately 5.8–9 kHz. Although direct time-domain SNR slightly decreases after filtering due to attenuation of out-of-band components, PSD-based SNR improves significantly, reaching 25–28 dB, demonstrating effective spectral concentration and noise suppression. The proposed approach is computationally efficient, interpretable, and suitable as a foundational module for low-cost, real-time acoustic pest detection systems in precision agriculture.
Volume: 42
Issue: 3
Page: 708-720
Publish at: 2026-06-10

A multicriteria collaborative decision support system for multidisciplinary medical coordination meetings

10.11591/ijeecs.v42.i3.pp753-766
Souad Madouri , Kaouter Labed , Kawther Makhlouf , Djamila Hamdadou , Anis Ayoub Amara , Aya Aouimer
Multidisciplinary team meetings (MDTMs) are central to cancer care. However, consensus can be hard to reach because specialists rely on diverse expertise and uncertain, multi-criteria clinical data. In this paper, we propose a group decision support system (GDSS) that integrates a multi-agent system (MAS) with multi-criteria decision making (MCDM) to structure interactions, aggregate expert preferences, enable real-time evaluation of options based on criteria, and transparently prioritize patients for discussion and intervention. Each specialist is represented by an agent that evaluates cases against shared criteria, while an embedded negotiation protocol enables exchanges and concessions to resolve conflicts and build consensus. We evaluated the GDSS using simulated breast cancer MDTM scenarios generated from a synthetic dataset of MDTM records. Experimental results demonstrate rapid convergence toward a consensual patient prioritization within a few negotiation iterations; in our experiments, agreement on the highest risk patient was reached after four rounds. Sensitivity analysis on subjective inputs, including criteria weights and preference profiles, produced minor changes in the resulting ranking, indicating robustness and stability to preference variations. The system maintains low computational complexity and short execution times, improving the transparency and consistency of MDTM recommendations. These outcomes confirm effectiveness and scalability for complex multidisciplinary clinical decisions.
Volume: 42
Issue: 3
Page: 753-766
Publish at: 2026-06-10

Metaheuristic optimization of wind turbine farm siting in power grids: a comparative study of PSO and GA

10.11591/ijeecs.v42.i3.pp666-677
Taha Rachdi , Yahia Saoudi , Larbi Chrifi-Alaoui , Ayachi Errachdi
This paper addresses the optimal integration of wind turbines into distribution networks with the aim of reducing active power losses and improving voltage stability. Two metaheuristic optimization methods genetic algorithm (GA) and particle swarm optimization (PSO) are applied to determine the optimal siting and sizing of wind turbines in the IEEE 14-bus system. The problem is formulated as a multi-objective function combining loss minimization and voltage profile enhancement under standard network constraints. Simulation results using MATLAB/PSAT show that both algorithms improve system performance compared to the base case, with PSO providing superior loss reduction and voltage stability. Wind variability is represented through a Weibull distribution to reflect realistic operating conditions. The study demonstrates the effectiveness of metaheuristic optimization for renewable integration and highlights PSO’s stronger robustness. The work contributes a comparative evaluation of GA and PSO, supported by stability analysis and realistic wind modelling.
Volume: 42
Issue: 3
Page: 666-677
Publish at: 2026-06-10

Mathematical modelling and automated control strategies for sugarcane crushing system of sugar factory

10.11591/ijape.v15.i2.pp554-564
Govind Singh Jethi , Sandeep Sunori , Surya Kant , Pradeep Juneja
Mathematical models form the basis of automation and digitalization. Control and optimization of industrial processes are important for increasing productivity and efficiency, especially in the sugar industry. This research focuses on modeling and controlling the juice extraction process, which is an important activity in sugar production. The mathematical model is obtained by creating a variable based on simple equations where the cane level in the Donnelly channel is the input and the juice output. The model captures the complexity of the process and provides a solid basis for the design of control systems. Two advanced control concepts: H-infinity control and model control (MPC) were used in MATLAB to meet the criteria. While H-infinity control provides performance in the presence of uncertainty and disturbances, MPC optimizes control performance by predicting future results. This paper observes and compares the results of two control systems to analyze their performance. This comparison highlights the advantages and limitations of each method. The research results are of great importance for increasing the efficiency and reliability of industrial processes in the sugar industry.
Volume: 15
Issue: 2
Page: 554-564
Publish at: 2026-06-01

Wind direction based aggregation of wind power plants under exact wind speeds

10.11591/ijape.v15.i2.pp818-830
Ali M. S. Al-Bayati , Huda Hamza Abdulkhudhur
Modeling of a wind power plant (WPP) containing numerous wind turbines in a highly detailed manner requires a substantial computational cost. Further, the response and dynamic behavior of the WPP systems are significantly influenced by the dynamic nature of wind speed. This paper presents a methodology of aggregating WPP systems with consideration for wind speed directions. To attain a realistic aggregated model, an algorithm for calculating actual exact wind speed at each wind turbine within the WPP was proposed considering different wind speed directions. Furthermore, the best wind speed direction for a fixed site area that produces a minimum wind energy losses inside the WPP was also assessed and reported. The results revealed the importance of employing the exact wind speed calculations within the WPP to ensure that the aggregated WPP model accurately represents real-world conditions. The results of this paper highlighted the role of wind direction in determining the response of WPPs and provide guidance on maximizing the WPP throughput during the year under the prevailing wind speed direction at the site.
Volume: 15
Issue: 2
Page: 818-830
Publish at: 2026-06-01

Development of groundwater level sensor for internet of things-based peatland fire monitoring

10.11591/ijape.v15.i2.pp915-926
Abdul Muid , Nina Siti Aminah , Maman Budiman , Mitra Djamal
Monitoring groundwater levels in peatlands is crucial for mitigating forest and land fires, which frequently occur in tropical regions. Current peatland groundwater level monitoring systems generally have limitations in their sensing range. Additionally, the lack of electricity and internet infrastructure around the monitoring sites presents another challenge. To address these issues, in this study, we developed a groundwater level sensor based on a float integrated with an optocoupler as a rotary encoder to monitor changes in water levels in real-time. The system is connected to an internet of things (IoT) platform through a LoRa communication module, powered by solar panels, enabling continuous wireless data transmission over a large range. To overcome the sensing range limitation, we developed a rotary encoder with a pulley driven by a long rope. Testing was conducted using transparent pipes with varying water levels to evaluate the sensor's performance. Experimental results showed that the sensor could measure water levels with a resolution of ±3.33 mm. This research provides a technique for measuring groundwater levels with an extended measurement range. Additionally, it produces a peatland fire risk monitoring system based on groundwater level parameters. It is expected can support peatland fire mitigation efforts more efficiently and effectively.
Volume: 15
Issue: 2
Page: 915-926
Publish at: 2026-06-01

Impact of synchronous condensers on voltage stability in systems with high renewable energy penetration

10.11591/ijape.v15.i2.pp760-769
Juan Esteban Rodríguez Quiroga , Mario A. Rios
The rapid integration of renewable energy sources (RES) poses significant challenges to power system reliability, particularly regarding voltage stability and reduced loadability margins. This study investigates the impact of synchronous condensers as a mitigation strategy to enhance stability in grids with high renewable penetration. The research objective is to evaluate how these devices influence loadability margins while considering the inherent stochastic nature of RES. The methodology employs PV curves for static voltage stability assessment, utilizing the 2m+1 point estimate method (PEM) to model uncertainty with high computational efficiency. This approach allows for the calculation of statistical indicators, including mean values, standard deviations, and confidence intervals for loadability margins. Simulations were conducted on the IEEE reliability test system (RTS) using NEPLAN360 software. The results demonstrate that the deployment of synchronous condensers (SCs) significantly improves voltage stability by increasing load margins and reducing the standard deviation of uncertainty. Conclusions indicate that these devices are effective reactive power compensators that provide a more robust operational environment against RES variability. Future research will focus on the optimal sizing and placement of these compensators to further maximize grid security.
Volume: 15
Issue: 2
Page: 760-769
Publish at: 2026-06-01

Sliding mode control of a solar powered switched-inductor based quadratic DC-DC converter for sustainable EV battery charging application

10.11591/ijape.v15.i2.pp712-723
Jawahar Marimuthu , Edward Rajan Samuel Nadar
The growing demand for sustainable transportation and fast charging solutions requires efficient power conversion technologies for solar electric vehicles or electric vehicles (SEVs/EVs). A non-isolated solar-powered switched-inductor quadratic DC-DC converter is proposed here to achieve high voltage gain in a practical way under reduced stress on power devices. A switched-inductor network blended with CCM operation avoids the extremely high duty cycles and high electromagnetic interference in conventional boost converters. A sliding mode control (SMC) strategy is applied here to improve robustness against parameter variations, ensure stable operation against dynamic load variations, and extract maximum power during solar-powered charging operation. This makes the topological platform proposed in this study especially suitable for a wide variety of applications, such as for SEVs and fast-charging applications of EVs. Detailed MATLAB/Simulink analyses along with a laboratory-scale prototype verify the performance of the converter under practical operation conditions and confirm the high efficiency of 91-96% at varied irradiance, low voltage ripple of 0.5-1.5% of output voltage and input current ripple of 5-12% of input current, reduced switching losses of 1-4%, and suitability of the presented converter for renewable-energy-based transportation systems.
Volume: 15
Issue: 2
Page: 712-723
Publish at: 2026-06-01

Analyzing the ability of capacitor energy in a modular multilevel converter to support inertia in an AC system

10.11591/ijape.v15.i2.pp646-662
Dunya Sh. Wais , Huda A. Abbood
Flexible DC transmission systems based on modular multilevel converters have the potential to support the inertia of AC power grids by using sub-module capacitor energy storage. However, existing studies generally believe that the inertia provided by flexible DC systems is limited by their energy storage time constants, which is weaker than that of synchronous motors, and lacks quantitative indicators to measure their support strength. Introducing the flexible-DC equivalent inertia constant (FDEIC) as a precise metric for assessing inertia support under different management schemes, this research presents a new analytical framework based on frequency responses. Results show that the inertial response is influenced by control bandwidth, DC-voltage dynamics, and circulating-current behaviour. A more generalized multi-terminal FDEIC is created to account for the impact of raised total capacitor energy, and the theory is further expanded to cover DC grids with more than one terminal. A three-terminal flexible DC grid simulation model is built in the PSCAD environment, and the simulation results verify the effectiveness of the proposed quantitative analysis method.
Volume: 15
Issue: 2
Page: 646-662
Publish at: 2026-06-01

Super-twisting sliding mode control for enhanced performance of grid-connected PV systems with H-bridge multilevel inverter

10.11591/ijape.v15.i2.pp464-479
CH. Venkata Amarnadh , T. Vijay Muni , T. Anuradha Devi , Rakesh Teerdala , M. Kiran Kumar , Kambhampati Venkata Govardhan Rao
This paper presents an enhanced control strategy for a grid-connected photovoltaic (PV) system employing a novel H-bridge multilevel inverter (MLI). The key contribution of this work lies in replacing the conventional proportional-integral (PI) controller with a super-twisting sliding mode controller (STSMC) for DC-link voltage regulation. Unlike earlier approaches that suffer from slow response, steady-state errors, and limited robustness under varying solar and temperature conditions, the proposed STSMC ensures faster transient response, finite-time convergence, and strong disturbance rejection without the chattering problem of classical sliding mode controllers. Another distinctive aspect of this study is the integration of STSMC with direct model predictive control (DMPC) for grid current regulation, enabling accurate reference current generation and improved synchronization. The novel H-bridge MLI topology further enhances system efficiency by reducing the number of switches while producing a seven-level output with lower total harmonic distortion (THD). Simulation results demonstrate that the proposed strategy achieves superior performance compared to the conventional PI-based system, with improvements in voltage stability, current quality, and reduced THD. These findings confirm the novelty and effectiveness of the proposed control scheme for reliable and efficient PV grid integration.
Volume: 15
Issue: 2
Page: 464-479
Publish at: 2026-06-01

Moth flame optimization based super twisting sliding mode MPPT controller for grid connected PV system

10.11591/ijape.v15.i2.pp703-711
Ujwala Gajula , Gouthami Eragamreddy , N. Malla Reddy , Remala Geshma Kumari , Veeranjaneyulu Gopu
Maximizing energy extraction while maintaining the stability of solar photovoltaic (PV) systems requires an effective and robust control strategy. This study proposes a novel control approach by integrating a super twisting sliding mode controller (STSMC) with the moth-flame optimization (MFO) algorithm to enhance battery energy management, power quality, and maximum power point tracking (MPPT) in grid-connected PV systems. The proposed MFO-STSMC controller combines the robustness of sliding mode control with the adaptive optimization capabilities of MFO, resulting in improved MPPT accuracy, reduced oscillations, and enhanced resilience to environmental disturbances and nonlinearities. Simulation results validate that the proposed method significantly outperforms conventional MFO-PI controllers, achieving accurate MPPT tracking under varying irradiance and temperature conditions, and ensuring stable operation. Moreover, the total harmonic distortion (THD) is reduced to 0.17% with MFO-STSMC, compared to 0.72% with MFO-PI, highlighting substantial improvement in power quality. The system is modeled and validated using MATLAB/Simulink, confirming the effectiveness of the proposed strategy in enhancing energy efficiency and grid stability.
Volume: 15
Issue: 2
Page: 703-711
Publish at: 2026-06-01

Adaptive P&O algorithm for fast and acurate maximum power point tracking for PV system

10.11591/ijape.v15.i2.pp590-599
Fathurrahman Fathurrahman , Rika Sri Utami , Akhyar Akhyar , Khairun Saddami
In this study, we proposed an adaptive perturb and observe (P&O) algorithm designed for efficient maximum power point tracking (MPPT) in photovoltaic (PV) systems. This method addresses key challenges in solar energy systems, including variability in solar irradiation and partial shading conditions. The proposed method introduced a dynamic and adaptive in adjusting the step size of the P&O as it nears the maximum power point (MPP), enhancing tracking precision and reducing energy losses. To show the ability of the proposed, we compared it with the conventional P&O and GWO & P&O. The proposed adaptive P&O MPPT algorithm consistently maintains near ideal tracking efficiency of ≈99.7% across various irradiance scenarios, significantly outperforming conventional P&O, which drops to 74.45% under partial shading. Overall, it achieves an average efficiency of 99.71%, surpassing hybrid P&O GWO (99.52%) and conventional P&O (91.30%), demonstrating superior reliability and energy harvesting performance. The results indicated that the proposed could reduce power deviations and obtain greater accuracy in detecting MPP. The study confirms the method's potential for optimizing energy extraction and suggests further refinement for broader applicability. This advancement represents a significant step in enhancing the reliability and efficiency of PV systems in both grid-connected and off-grid applications.
Volume: 15
Issue: 2
Page: 590-599
Publish at: 2026-06-01

Adaptive telematics integration for enhanced EV fleet management and data acquisition

10.11591/ijape.v15.i2.pp808-817
Kavitha Kumaraswamy , Pasumarthi Usha , S. Ashok Kumar , Deekshitha Arasa , Suganthi Neelagiri
Telematic control units (TCUs) and on-board diagnostics (OBD-II) systems are commonly used to monitor vehicles and enable real-time communication. However, traditional OBD-II systems provide limited data, making it difficult to accurately detect faults and analyze performance, especially in hybrid, flex-fuel, and electric vehicles. A TCU is an embedded system installed in vehicles that enables wireless communication with external networks. This paper introduces a standalone device designed to seamlessly integrate with electric vehicles (EVs) by utilizing TCU capabilities to enhance data acquisition. The TCU uses a combination of sensors to collect important real-time vehicle data, such as GPS location, battery charge level, and voltage levels. The collected data is processed to generate meaningful insights that support decision-making and system optimization. The proposed system uses the TCU as a core component to transmit real-time data to a fleet management system (FMS). By providing enhanced data to the FMS, the system improves diagnostic accuracy, strengthens EV safety monitoring, and enables more efficient fleet management across diverse vehicle types. This approach allows deeper monitoring of EVs and improves overall fleet efficiency. The framework offers a cost-effective and scalable solution for advanced monitoring and optimization of electric vehicle fleets.
Volume: 15
Issue: 2
Page: 808-817
Publish at: 2026-06-01
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