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29,922 Article Results

Enhancing the dynamic stability of electric power systems through the coordinated tuning of generator predictive controllers

10.11591/ijpeds.v17.i1.pp211-222
Hristo Beloev , Yuri Bulatov , Andrey Kryukov , Konstantin Suslov , Yuliya Valeeva , Magdalena Dudek , Iliya Iliev
The paper presents a method for the coordinated tuning of automatic voltage regulation (AVR) and automatic speed control (ASC) systems for a group of generators operating in parallel at a power plant. The method also involves solving the optimization problem using a genetic algorithm. The possibilities of using lead-lag elements in AVR and ASC, which impart predictive properties and improve damping characteristics of the controllers, are also considered. A model of a power plant operating in parallel with an electric power system is presented. This model demonstrates effective damping of oscillations under large disturbances when the proposed method is used to adjust the AVR and ASC control coefficients, along with a self-tuning lead-lag element. In this case, voltage oscillations and frequency overshoot disappear, and there is a significant reduction in the maximum deviations of these parameters. In the illustrative case study, the coordinated tuning of the controllers provides a 6% increase in the transmitted power limit and, as a consequence, the enhancement of the stability margin of the electric power system.
Volume: 17
Issue: 1
Page: 211-222
Publish at: 2026-03-01

Hybrid renewable energy for cold chain in Indonesia: technical and economic evaluation

10.11591/ijpeds.v17.i1.pp674-682
I Made Aditya Nugraha , I Gusti Made Ngurah Desnanjaya , Anis Khairunnisa , Mahaldika Cesrany
Cold storage plays a crucial role in preserving temperature-sensitive products, particularly in the fisheries and food sectors. However, its operation is highly energy-intensive and often constrained by unstable electricity supply in many Indonesian regions. This study quantitatively evaluates a hybrid renewable energy system integrating photovoltaic (PV) panels, diesel generators, batteries, and the utility grid to ensure sustainable cold storage operations. Using measured load profiles, solar irradiation data, and annual operating costs, the system achieved a 60% reduction in diesel fuel consumption, 30-50% lower CO₂ emissions, and annual savings exceeding IDR 100 million compared to conventional generator-based systems. The system demonstrated 83.5% overall efficiency, with a payback period of 4.4 years and a positive net present value (NPV), confirming its economic viability. The novelty of this research lies in presenting the first comprehensive techno-economic analysis of a PV-diesel-battery-grid hybrid system specifically designed for fisheries-based cold storage facilities in Indonesia, considering local solar potential and grid reliability. Despite its feasibility, implementation challenges remain, including a lack of skilled technicians, limited financial incentives, and bureaucratic constraints. To overcome this, the study recommends PV subsidies, low-interest green loans, and public–private partnerships aligned with Indonesia's energy transition roadmap and cold chain development goals.
Volume: 17
Issue: 1
Page: 674-682
Publish at: 2026-03-01

Voltage compensation using fuel cell fed dynamic voltage restorer

10.11591/ijpeds.v17.i1.pp663-673
Ryma Berbaoui , Rachid Dehini
One of the basic tasks of the dynamic voltage restorer (DVR) is to maintain voltage stability in distribution systems by correcting any deviations or disturbances in the three-phase supply. Whether they are increases or decreases. However, one of its disadvantages is its power source, as it cannot supply itself with power from the electrical grid like parallel compensators, which obtain power directly from the grid. This article presents an energy study of a dynamic voltage regulator (DVR) when operated using a power source represented by fuel cells, which are considered a clean and renewable source. On the other hand, excess energy from the regenerator or fuel cells can be output and injected into the distribution network for utilization via a parallel compensator (CP). The parallel compensator also compensates for reactive energy on the reactive load side to increase the power factor measured at the source side of the distribution system. This integrated system also uses neural networks to identify voltage disturbances and determine the voltages (modules/arguments) that must be added to the voltages in the power grid for correction. This analytical study was completed using a simulation system to confirm the effectiveness of this integrated system. The distinctive feature of this study is the integration of fuel cells and neural network-based control in the DVR system, providing a sustainable and intelligent alternative to conventional configurations, which makes it different from traditional DVRs that operate with batteries and supercapacitors. Its efficiency in compensating for voltage drops and surges is evident, and it also improves the power factor and ensures reliable operation of voltage-sensitive devices.
Volume: 17
Issue: 1
Page: 663-673
Publish at: 2026-03-01

Reliability-constrained optimal scheduling of PV-based microgrids using deterministic time-series forecasting and load prioritization strategies

10.11591/ijpeds.v17.i1.pp250-266
Dunya Sh. Wais , Huda A. Abbood
This paper presents an advanced MPC-based energy scheduling framework for islanded microgrids operating under uncertain and dynamic conditions where photovoltaic (PV) generation and energy storage systems (ESS) are integrated, and load management is hierarchically prioritized. The framework employs a hybrid ARIMA and random forest forecasting model to improve day-ahead and intra-day predictions of PV generation and load demand, enabling intelligent demand response, prioritized load shedding, and adaptive storage operation. Moreover, the proposed framework incorporates time-of-use (TOU) pricing and load importance weighting to minimize operational costs while ensuring a reliable power supply for critical loads. Simulation results across four operational scenarios demonstrate that the proposed method achieves approximately 32% improvement in critical load protection, 30% reduction in total operating cost, and 33.3% decrease in total load shedding compared to conventional MPC-based approaches. The proposed approach, therefore, provides a comprehensive, dynamic, and cost-efficient solution for microgrid scheduling and can be extended to multi-microgrid cluster applications in future research.
Volume: 17
Issue: 1
Page: 250-266
Publish at: 2026-03-01

Improving photovoltaic efficiency: a systematic study of P&O and INC MPPT techniques

10.11591/ijpeds.v17.i1.pp728-739
Abdelkbir Jamaa , Ahmed Moutabir , Rachid Marrakh , Abderrahmane Ouchatti
Achieving high efficiency in photovoltaic (PV) systems under fluctuating irradiance and temperature conditions relies on effective maximum power point tracking (MPPT) techniques. Among the most commonly adopted approaches, perturb and observe (P&O) and incremental conductance (INC) are favored for their ease of implementation and operational flexibility. Nevertheless, a systematic comparison of their performance under dynamic conditions remains limited. This study conducts a comparative evaluation of P&O and INC algorithms using MATLAB/Simulink, with emphasis on tracking accuracy, convergence speed, and overall efficiency. A standard PV module is exposed to rapid variations in irradiance and temperature to examine algorithm robustness. The results indicate that although P&O achieves fast convergence in steady-state operation, it exhibits noticeable oscillations around the maximum power point, resulting in efficiency losses of up to 3%. Conversely, the INC method offers improved tracking precision and reduced oscillations, yielding efficiency gains of 2-4% over P&O in dynamic environments. These findings underline the trade-off between algorithmic simplicity and tracking accuracy, and provide practical guidance for selecting MPPT strategies in both grid-connected and standalone PV applications. 
Volume: 17
Issue: 1
Page: 728-739
Publish at: 2026-03-01

Solar power forecasting using a SARIMA approach for Indonesia's grid integration

10.11591/ijpeds.v17.i1.pp293-302
Ricky Maulana , Syafii Syafii , Aulia Aulia
Indonesia’s transition toward a renewable energy-dominated power grid is progressing to meet increasing energy demands while reducing dependence on fossil fuels. According to the National Energy General Plan, their goal is to have 23% of the energy mix come from renewables by 2025 and 31% by 2050. Accurate forecasting of photovoltaic (PV) power output is crucial to address the intermittent nature of solar energy and ensure grid stability. A seasonal autoregressive integrated moving average (SARIMA) model was developed to estimate day-ahead photovoltaic power output in Padang City, Indonesia. Using NASA solar irradiance data from March 1-31, 2024, the SARIMA(1,0,1)(4,0,3)24 model achieved high accuracy with an NRMSE of 4.19%. To evaluate its performance, a comparative evaluation was conducted between the SARIMA model and two machine learning methods, namely artificial neural network (ANN) and long short-term memory (LSTM), in which SARIMA achieved the lowest forecasting error. These findings indicate that SARIMA remains an effective and interpretable statistical method for short-term PV forecasting, supporting reliable energy planning and power grid operations towards Indonesia's renewable energy goals.
Volume: 17
Issue: 1
Page: 293-302
Publish at: 2026-03-01

Study of neural controller based MPPT in comparison with P&O for PV systems

10.11591/ijpeds.v17.i1.pp797-808
Djaafar Toumi , Mourad Tiar , Abir Boucetta , Ikram Boucetta , Ahmed Ibrahim
This study investigated the performance of two prominent maximum power point tracking (MPPT) strategies: the established perturb and observe (P&O) technique and an artificial neural network (ANN)-based controller. Through simulations conducted in MATLAB/Simulink, a 50 W photovoltaic (PV) array was evaluated under dynamic irradiance and temperature variations. Notably, data generated by the P&O system served as the training dataset for the ANN model. The simulation results indicate that the ANN controller effectively and accurately identifies the PV system’s optimal operating point even amidst fluctuating environmental conditions. When compared to the conventional P&O method, the ANN approach demonstrated superior characteristics, including a significantly faster response, diminished oscillations around the maximum power point, and enhanced tracking accuracy during rapid environmental shifts. These findings underscore the substantial potential of ANN-based MPPT strategies for improving both the efficiency and operational stability of photovoltaic power systems.
Volume: 17
Issue: 1
Page: 797-808
Publish at: 2026-03-01

D-STATCOM control for distribution grids with distributed sources based on MMC structure using FCS-MPC algorithm

10.11591/ijpeds.v17.i1.pp425-437
Pham Viet Phuong , Le Hoai Nam , Pham Chi Hieu , Tran Hung Cuong
This paper proposes a D-STATCOM structure based on a modular multilevel converter (MMC) with the use of FCS-MPC control method for the purpose of compensating reactive power and stabilizing voltage in the distribution grid. The D-STATCOM is effectively used in cases involving non-sinusoidal and unstable voltages, which often occur in the distribution grid due to the effects of unbalanced nonlinear loads and power injection from renewable energy systems. The proposed structure also has the capability of reactive power compensating flexibility in fault conditions to stabilize the grid voltage. In this paper, a new control strategy, which is based on the combination of an outer PI controller and an inner FCS-MPC controller, was introduced. The outer PI controller is used to reduce static deviations in control values and to provide a reference value for the FCS-MPC controller. The inner FCS-MPC controller calculates the optimal switching state for the purpose of reducing the switching frequency of the MMC. The implementation process begins with the construction of a mathematical model and a control model. Simulations were carried out by MATLAB/Simulink to demonstrate the responsiveness of the control algorithm and the performance of D-STATCOM under the conditions of non-sinusoidal and unstable voltages.
Volume: 17
Issue: 1
Page: 425-437
Publish at: 2026-03-01

A novel hybrid PI and adaptive super-twisting sliding mode controller for high-performance integrated speed and flux regulation of IMDs

10.11591/ijpeds.v17.i1.pp414-424
Duc Thuan Le , Ngoc Thuy Pham
This paper presents a novel hybrid control strategy that integrates a proportional-integral (PI) regulator with an adaptive super-twisting sliding mode controller (ASTA) defined on a nonsingular terminal sliding mode control (NTSMC) surface for high-performance induction motor drives (IMDs). This enhanced hybrid PI-ASTA-NTSMC architecture jointly exploits the steady-state accuracy of PI control and the finite-time robustness of a higher-order sliding mode formulation. The adaptive mechanism of the super-twisting algorithm dynamically adjusts the switching gains according to the instantaneous sliding variable, ensuring consistent performance under time-varying loads and parameter variations. The NTSMC surface guarantees singularity-free finite-time convergence, while the adaptive ASTA law suppresses chattering and enhances disturbance rejection. Simulation results across multiple operating conditions show that the proposed controller significantly outperforms PI and PI-FOSMC schemes. It achieves the fastest transient, reducing settling time to 0.0407 s (39.4% and 31.5% faster than PI and PI-FOSMC), with overshoot lowered to 0.0091 rad/s and ISE/IAE minimized to 0.0035 and 0.0256, confirming its superior tracking precision. Additionally, reductions in the speed and torque RMSE indicate smoother control effort and improved closed-loop performance. The Lyapunov-based analysis confirms global finite-time stability of the overall system. With its enhanced robustness, low sensitivity to sampling noise, and continuous higher-order sliding structure that suppresses chattering, the proposed hybrid PI–ASTA–NTSMC offers a computationally efficient and practically attractive solution for integrated speed–flux control in industrial IM drives.
Volume: 17
Issue: 1
Page: 414-424
Publish at: 2026-03-01

Analysis of different converter topologies for EV applications

10.11591/ijpeds.v17.i1.pp518-532
Bodapati Venkata Rajanna , Kondragunta Rama Krishnaiah , Sakimalla Prabhakar Girija , Shaik Hasane Ahammad , Mohammad Najumunnisa , Syed Inthiyaz , Gouthami Eragamreddy , Giriprasad Ambati , Nitalaksheswara Rao Kolukula
Electric vehicles (EVs) are gaining global prominence due to their high efficiency, low noise, and minimal carbon emissions. A critical aspect of EV performance lies in the interaction between energy storage systems (ESS) and power converters. Nonetheless, power delivery from storage units tends to be unreliable and needs strong converter units for effective and stable energy transmission. Several forms of direct current-to-direct current conversion systems used in electric vehicles are thoroughly examined in the paper, including both isolated and non-isolated designs such as those with the cuk, flyback, and push-pull architectures. The paper looks at converter categorization, control methods such as proportional-integral and artificial neural networks, as well as the method of modulation using unipolar and bipolar sinusoidal pulse-width modulation (PWM). Additionally, the role of optimization algorithms in improving converter performance is explored. Simulations were conducted using MATLAB/Simulink to evaluate each topology under varying load and input voltage conditions. The results demonstrate that the Push-Pull converter has the best efficiency for high-power applications, while the Cuk and Flyback converters are best for applications requiring continuous current and low-power, compact designs, respectively. This research offers insights for choosing optimal converter structures to improve energy efficiency and reliability of systems in electric vehicles.
Volume: 17
Issue: 1
Page: 518-532
Publish at: 2026-03-01

Development of numerical model-based photovoltaic emulator for half-cut cell PV panel with multiple peaks output characteristics curve emulation capability

10.11591/ijpeds.v17.i1.pp343-358
Jordan S. Z. Lee , Jia Shun Koh , Rodney H. G. Tan , Nadia M. L. Tan , Thanikanti Sudhakar Babu
This study introduces a photovoltaic (PV) emulator focusing on a developed numerical model specifically for half-cut cell PV panels under partial shading conditions (PSCs), addressing a gap in research focused on full-cell models. The emulator uses a DC-DC buck converter and PI control to accurately replicate half-cut cell PV panel characteristics. A cost-effective hardware prototype validated the model's effectiveness in emulating multi-peak PV behavior under dynamic PSCs with up to three peaks and user-defined shading. This flexible and affordable platform enables efficient testing of MPPT algorithms and grid integration for PV systems using increasingly prevalent half-cut cell technology. Simulation results show high accuracy, with MAPE in power as low as 0.175% under uniform irradiance conditions and less than 0.302% under multi-peaks PSCs. Hardware validation confirms reliability with low MAPE in the power of 0.499% under uniform conditions and below 0.614% multi-peak PSCs, demonstrating the developed half-cut cell PV panel numerical model's accuracy in reproducing dynamic shading effects for renewable energy research.
Volume: 17
Issue: 1
Page: 343-358
Publish at: 2026-03-01

A novel high-gain DC-DC converter with fuzzy logic control for hydrogen fuel cell vehicle applications

10.11591/ijpeds.v17.i1.pp617-628
Gaddala Anusha , A. V. V. Sudhakar , Shaik Rafikiran , Ram Ragotham Deshmukh , C. H. Hussaian Basha
Hydrogen fuel cell vehicles (HFCVs) are emerging as a sustainable alternative to conventional internal combustion engines due to their zero-emission characteristics and high energy efficiency. However, the low output voltage of fuel cells poses a significant challenge in meeting the high-voltage requirements of electric traction systems. To address this, this paper proposes a high-gain non-isolated switched-capacitor (SC) DC-DC converter integrated with a fuzzy logic controller (FLC) for efficient power management in hydrogen fuel cell vehicle applications. The proposed converter topology achieves a significant voltage step-up without the use of bulky magnetic components, making it lightweight and compact for automotive integration. A maximum power point tracking (MPPT) controller using fuzzy logic is used to recover optimum energy out of the fuel cell stack during different loads and conditions of the environment. MATLAB/Simulink simulation results validate the high voltage gain, stable operation, and improved dynamic response of the proposed converter under FLC control. The proposed intelligent control strategy enhances fuel cell utilization and ensures effective operation of HFCV powertrains.
Volume: 17
Issue: 1
Page: 617-628
Publish at: 2026-03-01

Modeling and analysis of batteryless off-grid photovoltaic with adaptive multi-motor

10.11591/ijpeds.v17.i1.pp267-281
I Wayan Sutaya , Ida Ayu Dwi Giriantari , Wayan Gede Ariastina , I Nyoman Satya Kumara
This paper presents a model of a batteryless off-grid photovoltaic (PV) system with an adaptive multi-motor load. This model is developed as an effort to enhance the power output of batteryless off-grid PV systems for motor loads. Instead of using a single large-capacity motor, as commonly done in previous studies, the model distributes the load into several smaller motors and controls them adaptively. This approach allows for better control of the total load impedance to support maximum power point (MPP) tracking. A case study involving three three-phase induction motors, each with an operating power of 200 W, is conducted, where the power production of the proposed model is analysed by comparing it with the theoretical MPP and a fixed-load motor system that represents a single large motor. Under 1000 W/m² irradiance and using an 852 Wp PV array, the proposed model achieves a power output of 842 W, which corresponds to 98.83% of the MPP. In contrast, the system without this model only generates 298 W, or just 35.02% of the MPP. The testing process spans a 5-second period during the motor starting state. The power production analysis of the proposed model is presented in graphical form using MATLAB/Simulink.
Volume: 17
Issue: 1
Page: 267-281
Publish at: 2026-03-01

Enhanced adaptive reconfiguration for optimizing power generation and switching efficiency in PV arrays under PSC

10.11591/ijpeds.v17.i1.pp777-785
D. Manimegalai , Kandadai Nagaratnam Srinivas , Gayathri Monicka Subarnan
Photovoltaic (PV) arrays suffer significant power losses under partial shading conditions (PSC), which can degrade system performance. This paper proposes a novel weighted objective function that balances power output maximization with switching action minimization during dynamic PV array reconfiguration. An enhanced firebug swarm optimization (FSO) algorithm is employed to optimize this function efficiently. Simulation results under five shading patterns demonstrate approximately 6% improvement in power output over conventional methods, while also reducing the number of switch operations. The proposed approach enhances energy yield and extends device lifespan, offering a robust solution for real-time PV optimization under PSC.
Volume: 17
Issue: 1
Page: 777-785
Publish at: 2026-03-01

A three isolated port DC/DC converter for an energy storage system for renewable energy applications

10.11591/ijpeds.v17.i1.pp533-552
Faruk Ahmeti , Dimitar Arnaudov , Sabrije Osmanaj
The use of renewable energy sources like solar photovoltaic, wind, and fuel cells is gaining popularity due to growing environmental awareness, technological advancements, and declining production costs. Power electronic converters are usually used to convert the power from renewable sources to match the load demand and grid requirements. Among these, DC–DC converters are essential for improving system functionality and power density, especially in low-voltage renewable systems that require high voltage gain. This paper presents a systematic evaluation of five advanced DC-DC converter topologies: multi-port DC, boost multiport interleaved step-up, isolated bidirectional, voltage/current fed, and general resonant focusing on their structural complexity, component count, and potential application scenarios. In addition, a novel high-gain three-port resonant A DC-DC converter is proposed, incorporating galvanic isolation via a three-winding high-frequency transformer. The converter adopts a half-bridge resonant inverter and rectifier-based load port, resulting in a compact and cost-effective solution. A detailed analysis of the converter's operation, design considerations, and control strategy is conducted using PLECS simulation. Furthermore, an experimental setup is developed to validate the converter’s practical feasibility. The setup schematic and comprehensive comparative tables are included to support the evaluation and highlight the proposed design’s capabilities.
Volume: 17
Issue: 1
Page: 533-552
Publish at: 2026-03-01
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