e-Prime - Advances in Electrical Engineering, Electronics and Energy最新文献

{"title":"Virtual synchronous machine-based controller for multiple fast charging stations in grid stability support","authors":"Kabir Momoh ,&nbsp;Shamsul Aizam Zulkifli ,&nbsp;Petr Korba ,&nbsp;Felix Rafael Segundo Sevilla ,&nbsp;Alfredo Velazquez-Ibañez ,&nbsp;Arif Nur Afandi","doi":"10.1016/j.prime.2025.100925","DOIUrl":"10.1016/j.prime.2025.100925","url":null,"abstract":"<div><div>Ancillary based controller is an emerging concept for efficient power flow, voltage regulation, and frequency response stability, crucial for grid support at the point of common coupling (PCC) during EV battery charging process. This paper introduces an improved virtual synchronous machine (i-VSM) control concept using state-of-charge (SOC) voltage feedback as a key parameter to generate a virtual flux model within the fast-charging station (FCS) based rectifier converter. The i-VSM was modelled using VSM reactive power loop and the SOC-driven charging voltage as a reference input to the VSM. Through this approach, the i-VSM adjusts the virtual 's field excitation to produces the electromagnetic force fed to the pulse generator, which generates the switching signals to control the rectifier converter output to match grid response deviation during FCS operation. The i-VSM model was tested across 150 kW and 300 kW -rated multiple FCS setups. The comparison of the i-VSM with a conventional VSM-PI controller-based FCS, demonstrated the i-VSM's superior performance in accurately maintaining a steady power response flow, voltage tracking and frequency regulation at the rated values at PCC. The detailed voltage output variable response, stability analysis (Bode diagram) and current total harmonic distortion comparison are included in this paper. Conclusively, the i-VSM model showcase its advantages in plant stability, dynamic response tracking capacity and reactive power injection regulation, marking it as a robust alternative to VSM-PI based controller in grid-to-vehicle charging scenarios.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100925"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel hybrid machine learning approaches for prediction of greenhouse energy demand and production","authors":"Laila Ouazzani Chahidi ,&nbsp;Zineb Bounoua ,&nbsp;Abdellah Mechaqrane","doi":"10.1016/j.prime.2025.100944","DOIUrl":"10.1016/j.prime.2025.100944","url":null,"abstract":"<div><div>In response to the growing environmental complexities, the agricultural sector is actively integrating advanced technologies to fortify its adaptability and operational efficiency. A pivotal avenue of exploration centers on exploiting machine learning models for the prediction of greenhouse parameters. This study explores the prediction of greenhouse energy demand and production. For that, the study employs a new hybrid approaches (series and parallel), combining artificial neural networks and boosting trees, to predict air-conditioning electrical consumption and photovoltaic modules' electrical production. Model performance is evaluated based on statistical indicators, including the coefficient of correlation (R) and the normalized root mean square error (nRMSE). Results reveal that series and parallel hybrid models demonstrate acceptable to good performance (<span><math><mrow><mn>10</mn><mo>%</mo><mo>&lt;</mo><mi>n</mi><mi>R</mi><mi>M</mi><mi>S</mi><mi>E</mi><mo>&lt;</mo><mn>30</mn><mo>%</mo></mrow></math></span>), particularly during mid-August to mid-September, influenced principally by external temperature and solar radiation (models inputs). The hybrid model, including series and parallel approaches, exhibits variable performance compared to individual artificial neural networks and boosting trees methods.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100944"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Beyond encryption: How deep learning can break microcontroller security through power analysis","authors":"Ismail Negabi,&nbsp;Smail Ait El Asri,&nbsp;Samir El Adib,&nbsp;Naoufal Raissouni","doi":"10.1016/j.prime.2025.100947","DOIUrl":"10.1016/j.prime.2025.100947","url":null,"abstract":"<div><div>This paper investigates the application of convolutional neural networks (CNNs) for power analysis attacks (PAAs) on cryptographic systems, specifically targeting resource-constrained devices like microcontrollers. Vulnerabilities in these systems stem from unintended information leakage through side channels, such as power consumption during cryptographic operations. By utilizing CNNs, attackers can analyze these measurements to potentially extract secret keys. We propose a CNN-based PAA designed to recover Advanced Encryption Standard (AES) keys from microcontrollers. The CNN was trained on a dataset of 150,000 power consumption traces collected during AES encryption. This paper explores how our CNN-based method exploits information leakage to recover secret keys and compares its performance against existing approaches. Our method, implemented on an ASIC with 130 nm technology, successfully extracts keys using just 1100 traces, marking a substantial improvement over current state-of-the-art technique.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100947"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143551616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Super-wideband antenna with modified elliptical-shaped for broad spectrum capability in software-defined radio applications","authors":"Fitri Yuli Zulkifli ,&nbsp;Aditya Inzani Wahdiyat ,&nbsp;Thooriq Maulana ,&nbsp;Ali Hanafiah Rambe ,&nbsp;Nurhayati Nurhayati","doi":"10.1016/j.prime.2025.100933","DOIUrl":"10.1016/j.prime.2025.100933","url":null,"abstract":"<div><div>The rapid development of wireless communication technology has driven the need for integrating multiple devices into a single platform to improve connectivity. Software-Defined Radio (SDR) stands out as a promising solution but requires antennas with an exceptionally wide bandwidth. This study introduces a super-wideband microstrip antenna designed to meet these needs, covering a frequency range of 0.42 to 40 GHz. The antenna is made using a Taconic TLY-5 substrate, known for its low dielectric loss, and has a simple printed monopole microstrip design with dimensions of 160 × 260 mm². Experimental results demonstrate that the antenna operates efficiently over a broad frequency range of 0.42 to 35.96 GHz, achieving a remarkable bandwidth ratio of 1:85. The antenna exhibits a gain exceeding 2 dBi across the entire frequency range, with a peak gain of 11 dBi, and maintains a total efficiency of over 60 % across this wide frequency spectrum. Its ability to achieve resonance at extremely low frequencies, combined with a remarkable 1:85 bandwidth ratio, significantly contributes to the novelty and impact of this work. This design demonstrates a practical and efficient solution for next-generation communication systems, combining wideband performance with compactness and ease of fabrication.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100933"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Virtual vector-based neural network DTC scheme for dynamic performance improvement of dual-star induction motor drive","authors":"Guedida Sifelislam ,&nbsp;Tabbache Bekheira ,&nbsp;Nounou Kamal ,&nbsp;Nesri Mokhtar ,&nbsp;Abdelhakim Idir","doi":"10.1016/j.prime.2025.100938","DOIUrl":"10.1016/j.prime.2025.100938","url":null,"abstract":"<div><div>Recently, direct torque control (DTC) of the dual-star induction motor (DSIM) has been widely appreciated over other conventional control techniques due to its numerous advantages, notably its simple structure, good dynamic performance, and excellent robustness. However, despite these qualities, it is often confronted with torque ripples and harmonic currents that limit its operational efficiency. To overcome these challenges and improve the global control of the drive system, this paper proposes a novel study to improve the performance of DTC for DSIM based on a set of three techniques. Firstly, by appropriately selecting two voltage vectors at each sampling period, the impact of current harmonics is considerably reduced, but torque and flux ripples remain significant. Secondly, the method above is combined with a switching table featuring three virtual voltage groups, significantly reducing torque ripples and harmonic losses. Finally, an intelligent control based on artificial neural networks (ANNs) will replace the speed regulator, the above switching table, the two-level hysteresis flux regulator, and the seven-level hysteresis torque regulator to select an optimal virtual voltage vector. The performance of the final technique shows the following advantages: further reduction of torque and stator flux ripples, less overshoot in speed and torque, and almost complete suppression of harmonic currents. The simulation results presented in this article confirm the effectiveness of the proposed technique.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100938"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143563215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced single-diode model for improved accuracy in photovoltaic cell characterization","authors":"Ismail Abazine,&nbsp;Mustapha Elyaqouti,&nbsp;El Hanafi Arjdal,&nbsp;Driss Saadaoui,&nbsp;Dris Ben Hmamou,&nbsp;Abdelfattah Elhammoudy,&nbsp;Souad Lidaighbi,&nbsp;Imade Choulli","doi":"10.1016/j.prime.2025.100935","DOIUrl":"10.1016/j.prime.2025.100935","url":null,"abstract":"<div><div>The single-diode model (SDM) is widely used to simulate the behavior of photovoltaic (PV) cells. In the conventional approach, these models, referred to as voltage-independent SDM (SDMvi), assume that their parameters remain constant regardless of the PV cell's operating voltage. While SDMvi models are fundamental for PV system analysis and design, this assumption may limit prediction accuracy, particularly when dealing with nonlinear and dynamic PV characteristics. This paper introduces an enhanced single-diode model (SDMvd) that accounts for the voltage dependence of its five parameters. To achieve this, two new variables, P1 and P2, are introduced to segment the I-V curve into three regions, each containing the three characteristic points: maximum power point (MPP), open-circuit voltage (Voc), and short-circuit current (Isc). A novel hybrid method, combining analytical and numerical approaches, is then proposed for parameter extraction in each segment. The effectiveness of the proposed model is evaluated using five PV cells/modules from different technologies and under various environmental conditions. The results demonstrate that the SDMvd significantly improves accuracy, achieving a Root Mean Square Error (RMSE) of 6.161168E-04 A for the PVM 752 GaAs and 1.15378E-03 A for the STM6–40/36 module.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100935"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143508491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modular multilevel converter for enhanced offshore windfarm integration to medium voltage DC microgrid","authors":"Lekshmi Babu,&nbsp;Mariamma Chacko","doi":"10.1016/j.prime.2025.100951","DOIUrl":"10.1016/j.prime.2025.100951","url":null,"abstract":"<div><div>The quality of power converters is crucial in integrating renewable energy sources into DC microgrids, as it ensures efficient energy transfer, voltage stability, and overall system reliability, making it a key focus of current research. This paper presents an application of enhanced Modular Multilevel Converter (MMC) proposed by the authors for integrating a Wind Energy Conversion System (WECS) into a Medium Voltage Direct Current (MVDC) microgrid. The system architecture involves a wind farm model connected to an MVDC grid via the MMC, with an Energy Storage System (ESS) integrated to support grid stability and manage energy flow. The key application of this configuration is to supply power to heavy-duty electric vehicles, such as electric trucks, making the system well-suited for industrial-scale electrification. The entire setup is simulated using MATLAB/SIMULINK to analyse its performance. The simulation results show several key improvements compared to MMC with conventional sorting algorithm. These include enhanced output DC voltage quality, faster short circuit fault clearing, better voltage balance across submodule capacitors, less Total Harmonic Distortion (THD) and reduced switching losses in the converter. These improvements make the proposed system highly efficient and reliable for modern renewable energy integration into MVDC microgrids, supporting the transition towards electric heavy vehicles while maintaining grid stability and efficiency.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100951"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143551617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Equipping suburban diesel–electric multiple unit with a hybrid power unit","authors":"Ievgen Riabov,&nbsp;Liliia Overianova,&nbsp;Dmytro Iakunin,&nbsp;Volodymyr Neshcheret,&nbsp;Kostiantyn Ivanov","doi":"10.1016/j.prime.2025.100949","DOIUrl":"10.1016/j.prime.2025.100949","url":null,"abstract":"<div><div>Improving the competitiveness of railway passenger transport requires low fuel and energy resource expenses. A promising direction in this regard is using energy storage in the traction systems of autonomous rolling stock. The paper considers the use of energy storage in the traction system of a diesel train for suburban transport. The modeling of a diesel train movement is carried out to determine the parameters of movement and consumption of fuel and energy resources. The movement of a diesel train on the Liubotyn-Boromlya section is considered. Three options for using an energy storage device in the traction system of a diesel train are investigated. It is established that the energy accumulation in the on-board storage device is 25 % of the energy consumed for traction. According to the results of the calculations, it was determined that using an energy storage device reduces fuel consumption by 22…28 %. In the case of charging the energy storage device of the plug-in traction system, the reduction in the cost of fuel and energy resources is 36.5…40.4 %. According to the study results, it is predicted that using a plug-in traction system is a priority for diesel trains engaged in suburban transport.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100949"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143580299","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced nonlinear sliding mode control technique for wind power generation systems application: Theoretical design and comparative study","authors":"Yattou El Fadili,&nbsp;Ismail Boumhidi","doi":"10.1016/j.prime.2025.100937","DOIUrl":"10.1016/j.prime.2025.100937","url":null,"abstract":"<div><div>Wind power generation systems (WPGSs) have emerged as a vital source of clean energy, appreciated for their renewable nature and zero fuel costs. However, controlling these systems is challenging due to their nonlinear dynamics, unpredictable disturbances, parameter uncertainties, and rapid wind speed fluctuations. To address these challenges, robust control strategies are essential. This study presents a novel robust nonlinear controller for regulating the electromagnetic torque of horizontal-axis, variable-speed WPGSs with three blades connected to the grid. The proposed controller is designed to enhance system efficiency and profitability by maximizing electricity production, reducing torque ripples, eliminating peak overshoots, and achieving precise setpoint tracking with optimal transient performance. The controller combines sliding mode (SM) control with fractional calculus (FC) to exploit the benefits of both methods. SM control, known for its effectiveness in controlling nonlinear systems, stabilizes the system and ensures finite-time convergence to the desired state. The incorporation of fractional-order operators into the sliding surface introduces greater flexibility, leveraging the long-term memory properties of FC to enhance system stability and robustness while mitigating chattering effects. The stability of the proposed controller is rigorously validated through Lyapunov theory. The simulation phase is carried out in MATLAB under various wind conditions and operating scenarios demonstrate the controller's superior performance. The results show its ability to reduce chattering phenomena, improve power quality, and minimize high peaks in the input controller by achieving reductions of 38.0856 KN.m in the first test and 280.2039 KN.m in the second test. Additionally, this controller ensures system stability, with a Lyapunov function standard deviation of 0.0105 and 0.1755 for the first and second tests, respectively. The controller also achieves a high efficiency of 47.45%, robustly driving the system to its desired state in finite time with tracking error standard deviations of 0.3171 in the first test and 0.1652 in the second test.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100937"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143519097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gradient search optimized interval type-2 fuzzy TID approach for stability enhancement of an islanded AC microgrid","authors":"Shibanika Panda,&nbsp;Alivarani Mohapatra,&nbsp;Byamakesh Nayak","doi":"10.1016/j.prime.2025.100927","DOIUrl":"10.1016/j.prime.2025.100927","url":null,"abstract":"<div><div>The islanded AC microgrid incorporates with low inertia and huge uncertainties, for which frequency instability issues are occurred under load dynamics and solar/wind uncertainties. This research paper proposed a resilient interval type-2 fuzzy tilt integral derivative (IT2-FTID) control strategy for obtaining frequency stability in the microgrid under various uncertainties. The model of an AC microgrid is developed with integrating multiple power-generating units based on renewable energy sources like solar and wind. These units, having capacities in the fractional megawatt range, form what is termed a microgrid. The microgrid's performance is influenced by significant load dynamics and uncertainties in wind speed and solar intensity, particularly affecting system frequency. To mitigate unwanted frequency fluctuations and maintain nominal frequency during various electrical disturbances, the resilient IT2-FTID controller operates as a secondary frequency control loop in the microgrid. Additionally, a novel Gradient-based Algorithm (GBA) with an effective objective function is applied to optimize the performance of the IT2-FTID controller. The effectiveness of the IT2-FTID approach is compared against basic type-1 fuzzy and conventional PID controllers, showing a frequency stability improvement of 111.76% and 205.88%, respectively. Finally, the convergence and optimization capabilities of the GBA are compared to Genetic Algorithm (GA) and standard Particle Swarm Optimization (PSO) for demonstrating superior performance.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"11 ","pages":"Article 100927"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}