Tạp chí Khoa học và Công nghệ Năng lượng
Tạp chí của Trường Đại học Điện lực
TRAJECTORY AND POWER OPTIMIZATION FOR UAV-ASSISTED COMMUNICATION USING RANDOM SEARCH ALGORITHM
Trong bài báo này, chúng tôi đề xuất một khung tối ưu đồng thời quỹ đạo bay và công suất phát cho hệ thống thông tin có UAV hỗ trợ sử dụng giao thức chuyển tiếp giải mã–chuyển tiếp (Decode-and-Forward, DF). Mục tiêu là cực đại hóa tốc độ truyền tích lũy trong khi vẫn đảm bảo các ràng buộc công suất phát tức thời và ràng buộc cơ động của UAV. UAV di chuyển từ vị trí khởi đầu xác định đến điểm đích cố định và đóng vai trò là trạm chuyển tiếp trên không giữa nguồn và đích mặt đất. Một thuật toán dựa trên Tìm kiếm Ngẫu nhiên (Random Search – RS) được xây dựng để đồng thời tối ưu quỹ đạo UAV và phân bổ công suất theo từng bước thời gian rời rạc. Phương pháp đề xuất được so sánh với phương pháp chuẩn trong đó UAV bay theo đường thẳng và sử dụng công suất cực đại cố định. Kết quả mô phỏng cho thấy phương pháp RS giúp cải thiện hiệu suất phổ tích lũy 14,58% so với phương pháp chuẩn, đồng thời thỏa mãn đầy đủ các ràng buộc vật lý và giảm công suất phát trung bình. Kết quả này khẳng định tính hiệu quả và độ phức tạp tính toán thấp của phương pháp đề xuất đối với hệ thống thông tin không dây có UAV hỗ trợ trong môi trường có suy hao phụ thuộc vị trí
Copyright (c) 2026 Tạp chí Khoa học và Công nghệ Năng lượng
DEMAND SIDE MANAGEMENT AND DEMAND RESPONSE IMPLEMENTATION STRATEGY FOR VIETNAM: LEARNING FROM INTERNATIONAL BEST PRACTICES AND DEVELOPING CONTEXT-SPECIFIC SOLUTIONS
This study synthesizes evidence from successful DSM/DR implementations in the United States, India, Australia, Japan, and Singapore to develop a context-specific framework for Vietnam. The analysis reveals that Vietnam's industrial-dominated energy consumption pattern, rapid economic growth, and evolving regulatory environment present both significant opportunities and unique challenges for DSM/DR deployment. Key findings indicate that Vietnam can leverage its centralized governance structure and strong state-owned enterprise presence to accelerate DSM/DR implementation, while addressing critical gaps in smart grid infrastructure, regulatory frameworks, and market mechanisms
Copyright (c) 2025 Tạp chí Khoa học và Công nghệ Năng lượng
PHÂN TÍCH ẢNH HƯỞNG CÁC SIÊU THAM SỐ CỦA MÔ HÌNH LIGHTGBM ĐẾN DỰ BÁO CÔNG SUẤT ĐIỆN MẶT TRỜI
This paper presents a study on the impact of certain hyperparameters in the LightGBM model on solar power generation forecasting accuracy. The considered hyperparameters include the maximum number of leaves in decision trees (num_leaves), learning rate (learning_rate), and the number of boosting rounds (n_estimators). Ten scenarios with different combinations of these hyperparameters were implemented and compared based on error metrics: RMSE, MAPE, and NMAPE, as well as training and inference time. The results show that adjusting these parameters could improve the forecasting performance of the model, as reflected in a slight reduction in forecasting errors for instance, the MAPE decreased from 90.67% to 82.94% when increasing num_leaves from 30 to 60. However, the improvements are insignificant, the error metrics only vary within a narrow range across scenarios. This indicates that the LightGBM model is relatively robust to changes in hyperparameters within the tested range, and moderate tuning of num_leaves, learning_rate, and n_estimators does not lead to dramatic changes in forecasting accuracy
Phạm Mạnh Hải, Nguyễn Tuấn Anh, Vũ Minh Pháp, Nguyễn Ngọc Trung, Vũ Thị Anh Thơ, Nguyễn Hữu Nguyện, Đỗ Quang Hiệp, Nguyễn Đức Quang
Hai Pham Manh, Tuan Anh Nguyen, Pham Vu Minh, Trung Nguyen Ngoc, Thơ Vu Thi Anh, Nguyen Nguyen Huu, Hiep Do Quang, Quang Nguyen Duc
THIẾT KẾ, CHẾ TẠO HỆ THỐNG ĐIỀU KHIỂN ĐÈN CHIẾU SÁNG CÔNG CỘNG DỰA VÀO ĐO CƯỜNG ĐỘ ÁNH SÁNG
The issue of efficient and energy-saving public lighting has received special attention from the Government, Ministries, and local authorities nationwide. Research and application of technological solutions for public lighting control are essential to reducing costs. This paper summarizes the design and development of a public lighting control system based on light intensity measurement aimed at saving energy and operational costs - an effective solution that has been practically implemented in Bac Ninh province
UNIT COMMITMENT PROBLEM FOR POWER SYSTEMS INTEGRATED WITH HYDROGEN ENERGY STORAGE CONSIDERING RENEWABLE ENERGY UNCERTAINTY AND POWER LOSS CONSTRAINTS
Unit Commitment (UC) is a critically important task in power system operation, aiming to meet load demand while satisfying technical and safety constraints, and minimizing the total operational cost of the system. This scheduling task becomes even more essential with the increasing integration of new types of power generation into the grid, alongside traditional power sources—such as renewable energy sources (RES) and energy storage systems. Although RES offer advantages such as environmental friendliness and an almost inexhaustible supply, they still pose significant challenges due to their inherent uncertainty, which complicates system operation. Given the diversity of generation sources and their unique characteristics, developing a detailed and optimal model for the UC problem is necessary. In this study, a day-ahead unit commitment model is proposed for a power system that integrates various generation sources, including thermal power, solar power, wind power, and a hydrogen energy storage system (HESS). The model incorporates the uncertainty of RES and considers power losses in the grid. The proposed approach is applied to the IEEE 24-bus test system to enhance practicality and demonstrate the effectiveness of the developed model
COMPARATIVE ANALYSIS OF INTERNATIONAL ELECTRICITY MARKET CRISES AND POLICY LESSONS FOR VIETNAM
This paper conducts a comparative analysis of three typical electricity market crises worldwide: the 2021 Texas crisis caused by Hurricane Uri, the 2022 suspension of the Australian National Electricity Market (NEM), and the European energy crisis during the 2021-2023 period. The study employs a case analysis methodology to identify the causes, impacts, and remedial measures of each crisis. The results demonstrate that all three crises originated from a combination of extreme weather factors, inappropriate market design, and insufficient contingency mechanisms. The Texas crisis resulted in $195 billion in damages and 210 deaths due to 48% of power generation capacity becoming inoperative. Australia was forced to suspend the entire NEM market when electricity prices exceeded control thresholds. Europe experienced a prolonged crisis with electricity prices increasing by 1000% due to geopolitical conflicts. The lessons learned include: the need to improve resilience against extreme weather, design appropriate pricing mechanisms, develop flexible sources, and strengthen international cooperation. For Vietnam, the study proposes a roadmap for electricity market reform aimed at increasing flexibility, diversifying supply sources, and completing the legal framework
INVESTIGATION OF THE INFLUENCE OF FLUX BARRIERS ON THE ELECTROMAGNETIC FORCE AND TORQUE IN A SYNCHRONOUS RELUCTANCE MOTOR
The Synchronous Reluctance Motor (SynRM) is a type of electric motor that operates on the principle of reluctance. The rotor of SynRM has no windings or permanent magnets. SynRMs are used in various applications: industrial drives, pumps and fans, compressors, HVAC systems. However, the disadvantage of SynRM is high vibration and noise. The electromagnetic force is the main component causing motor vibration. The electromagnetic parameters are calculated to minimize the radial electromagnetic force, which will reduce the vibration and noise, vibration, and harshness of the motor. The number and parameter of flux-barier determines the harmonic amplitude of electromagnetic force. This article aims analyzes the force density and harnomic electromagnetic force of the SynRM motor with 36 stator slot and 4 rotor poles. The electromagnetic forces are calculated by finite element method. Investigation of the influence of different flux barrier dimensions on the radial force and torque ripple of the SynRM. The results show that the dimensions of the magnetic flux barriers are parameters that have a direct impact on the electromagnetic force and torque of the SynRM. Optimizing the flux barrier dimensions can significantly reduce the torque ripple of the SynRM
A FOURTH-ORDER SIW BANDPASS FILTER WITH OPTIMIZED PASSBAND PERFORMANCE FOR MILLIMETER-WAVE APPLICATIONS
This paper presents the design of a four-order substrate integrated waveguide (SIW) bandpass filter optimized for millimeter-wave wireless applications. SIW technology balances loss, cost, and integration capabilities while achieving high selectivity and a compact form factor in RF/Microwave filter design. Since SIW primarily operates in the dominant TE10 mode, the electric field E has a maximum value located on the vertical central plane and along the propagation direction. Therefore, the central plane can be considered an equivalent magnetic wall. The proposed filter is composed of four SIW resonators connected in series. The simulated results show that the fourth-order SIW filter has a center frequency of 26 GHz with 3 dB bandwidth of about 4.67 GHz. The achieved minimum insertion loss in the passband is 1.1 dB, and return loss is better than 20 dB. The passband ripple is significant reduced to below 1dB, while the out-band rejection is better than 20 dB from 22 to 23.1 GHz which improved the selectivity of the filter. This filter is suitable for millimeter-wave wireless systems such as 5G, automotive radar, and satellite communication due to its high selectivity, low loss, and compact size
NO2 GAS SENSING PROPERTIES OF RHOMBUS-SHAPED ZnO NANORODS SYNTHESIZED VIA A SIMPLE HYDROTHERMAL METHOD
In this study, rhombus-shaped ZnO nanorods were successfully synthesized via a simple hydrothermal method for potential application in toxic NO2 gas sensing. The crystal structure and morphology of the material were characterized using X-ray diffraction (XRD), field-emission scanning electron microscopy (FESEM), and Brunauer–Emmett–Teller (BET) surface area analysis, revealing a relatively large specific surface area of 8.67 m²/g. A gas sensor fabricated via a drop-coating technique using the synthesized material exhibited high sensitivity to NO2 in the low concentration range of 0.1–2.0 ppm at an optimal operating temperature of 200 °C, along with excellent selectivity against interfering gases. Moreover, the sensor demonstrated good repeatability over eight consecutive switching cycles between NO2 and dry air without significant degradation in response, indicating its strong potential for use in environmental NO2 monitoring systems
ENHANCING INDOOR LOCALIZATION ACCURACY FOR MOBILE ROBOTICS
This paper presents a proposal for an antenna design intended for use on mobile robots that require localization, with the goal of improving the accuracy of indoor object positioning systems. The system employs a smart antenna as the transmitter, where the antenna array consists of seven fixed directional beams. Object position estimation is based on a pattern analysis technique. The paper investigates different antenna types suitable for mobile robots and proposes an optimal antenna configuration to achieve high localization accuracy. The system was experimentally deployed in a cluttered laboratory environment with human activity, and achieved a positioning error as low as 0.72 m
DỰ ĐOÁN SUY HAO ĐƯỜNG TRUYỀN KHÔNG TRUNG - MẶT ĐẤT ĐA TẦN SỐ CHO UAV SỬ DỤNG HỌC MÁY
Unmanned Aerial Vehicles (UAVs) have emerged as a promising solution for modern wireless communication systems due to their flexibility, mobility, and ease of deployment. However, ensuring reliable air-to-ground (A2G) communication requires accurate channel modeling to support efficient power control and system planning. This study proposes a robust path loss prediction framework for A2G communication links using machine learning techniques, specifically the K-Nearest Neighbors (KNN) regression algorithm. The model is trained and evaluated using a publicly available dataset, with a focus on urban environments and tested across three carrier frequencies: 1 GHz, 2 GHz, and 5.8 GHz. Comparative evaluations against conventional A2G models demonstrate that the proposed approach achieves lower standard errors and narrower confidence intervals. These results highlight the model’s capability to deliver accurate path loss predictions, underscoring its potential for improving the reliability and performance of UAV-based communication systems, particularly in dense urban scenarios
EXPERIMENTAL EVALUATION OF VIBRATION EFFECTS ON QUADROTOR TILT ANGLE ESTIMATION USING A KALMAN FILTER AND MPU6050 SENSOR
In most commercial quadrotor systems, the control boards are pre-integrated as closed systems, limiting user access to internal parameters and customization for specific applications or harsh operating conditions. To address this limitation and advance the capability to design custom control systems, this study introduces an experimental model implemented on a three-axis rotational stand. The platform enables investigation of attitude dynamics and development of control algorithms for angular motion channels of a quadrotor model. Angular orientation is measured using the MPU6050 sensor an integrated accelerometer and gyroscope and processed by a cost-effective STM32F303CCT6 microcontroller. The experimental setup is also employed to tune parameters of the Kalman filter, facilitating evaluation of the algorithm’s performance under real-world operating conditions. The proposed system serves as a foundation for customized controller design and is well-suited for educational and research purposes in unmanned aerial vehicle (UAV) control
AUTOMATIC SOLAR PANEL ORIENTATION SYSTEM WITH INTEGRATED MONITORING AND CONTROL USING IOT
The automatic solar panel orientation system with integrated monitoring and control using IoT is an intelligent monitoring and control system for solar panels, developed to optimize solar radiation capture efficiency through an automatic two-axis adjustment mechanism. The system uses an Arduino Uno R3 microcontroller combined with ESP8266 to collect data from sensors, communicate via the MQTT protocol, and monitor in real-time on the HiveMQ Cloud platform. The panel orientation mechanism is controlled by two SG90 servos based on data from four photoresistor light sensors, allowing the system to automatically position itself towards the strongest light (Auto mode). Additionally, the system supports manual control (Manual) via a Node-RED Dashboard interface, enabling users to directly adjust the X and Y axis angles using sliders. The solar panel orientation system utilizes seven types of environmental and performance sensors: DHT11 (temperature, humidity), TSL2561 (light intensity), MPU6050 (tilt angle), VEML6070 (UV radiation), and INA3221 (instantaneous voltage, current, and power for both a fixed and an automatically oriented panel), to provide comprehensive data on environmental conditions and system operation. Data is packaged in JSON format and transmitted via UART communication between Arduino and ESP8266, ensuring scalability and integration with other IoT monitoring systems. The system is designed to be compact, low-power, and easy to deploy, suitable for educational applications, IoT research, as well as the development of smart and sustainable energy solutions in practice
A COMPARISON OF NEURAL NETWORK ARCHITECTURES FOR ULTRA SHORT TERM WIND POWER FORECASTING: A CASE STUDY OF THAI HOA WIND FARM IN BINH THUAN
This paper proposes a comparison of three types of artificial neural networks, including the multilayer perceptron neural network (MLP), the radial basis function (RBF) neural network, and the Elman neural network, for ultra-short-term forecasting of wind turbine power generation. Experimental results, based on the power generation data from the 5MW wind turbines at the Thai Hoa, Binh Thuan wind farm, indicate that the multilayer perceptron neural network achieves optimal computational speed and accuracy. This research helps to provide a suitable method for the ultra-short-term forecasting of wind turbine power generation in cases with limited computational capacity and input data
ĐIỀU KHIỂN BÁM QUỸ ĐẠO CHO ROBOT DI ĐỘNG SỬ DỤNG ĐIỀU KHIỂN MỜ MAMDANI DƯỚI TÁC ĐỘNG CỦA NHIỄU
Bài báo này trình bày một chiến lược điều khiển mờ nhằm mục tiêu bám quỹ đạo cho robot di động dẫn động vi sai hoạt động trong môi trường có nhiều bất định. Một hệ suy luận mờ kiểu Mamdani được thiết kế với ba bộ điều khiển mờ độc lập để hiệu chỉnh sai số bám theo về vị trí và phương hướng. Bộ điều khiển sử dụng các hàm thành viên dạng tam giác cùng với một tập luật suy luận gọn nhẹ nhằm đảm bảo tính đơn giản và hiệu quả tính toán. Hiệu suất của phương pháp đề xuất được đánh giá thông qua mô phỏng trong cả hai điều kiện: không có nhiễu và có nhiều nhiễu. Trong trường hợp danh định, robot bám sát quỹ đạo hình sin đã được định trước với sai số xác lập nhỏ. Khi chịu tác động của các nhiễu bên ngoài, bộ điều khiển mờ vẫn duy trì khả năng bám quỹ đạo chính xác và tín hiệu điều khiển bị giới hạn, thể hiện độ bền vững và khả năng thích nghi cao. Phương pháp này không phụ thuộc vào mô hình động lực học chính xác của robot, từ đó tăng tính khả thi khi triển khai trong thực tế. Các kết quả thu được khẳng định tiềm năng của điều khiển mờ như một giải pháp hiệu quả cho bài toán dẫn đường robot di động trong điều kiện bất định
ĐÁNH GIÁ HIỆU SUẤT CÁC MÔ HÌNH HỌC MÁY TRONG DỰ ĐOÁN NGUY CƠ TIM MẠCH
Cardiovascular diseases (CVD) are a leading cause of illness and death worldwide, making it crucial to predict cardiovascular risk accurately for effective prevention and treatment. This study aims to evaluate the performance of several supervised machine learning algorithms in predicting cardiovascular risk using a dataset of clinical and demographic features. Six commonly used models—Random Forest, XGBoost, Logistic Regression, Support Vector Classifier (SVC), K-Nearest Neighbors (KNN), and Decision Tree—are tested based on their ability to predict risk and other important metrics such as accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC). The data is preprocessed using normalization and transformation techniques, such as Quantile Transformation and Standard Scaling, to ensure the best model performance. The results provide a detailed comparison of the models' performance, showing their strengths and weaknesses in predicting cardiovascular risk. The findings highlight the best-performing models for identifying high-risk individuals, which could help healthcare professionals prioritize early interventions. The study also discusses the broader role of machine learning in healthcare, especially in disease prediction and prevention
SWIPT-NOMA-D2D FOR 6G UAV NETWORKS: ENHANCING THROUGHPUT AND ENERGY EFFICIENCY
This paper investigates the integration of Simultaneous Wireless Information and Power Transfer (SWIPT) into UAV-assisted 6G networks by employing Non-Orthogonal Multiple Access (NOMA) and Device-to-Device (D2D) communications. The proposed system model aims to optimize throughput and energy efficiency (EE) through effective power allocation, energy harvesting, and interference management. A multi-objective optimization problem is formulated under practical constraints such as UAV mobility and channel uncertainty. To tackle the non-convex nature of the problem, a hybrid algorithm combining Deep Reinforcement Learning (DRL) and convex optimization is developed. Simulation results demonstrate significant improvements in EE and increased throughput compared to conventional OMA-based UAV networks. This study contributes to establishing a critical foundation for future sustainable and high-performance 6G UAV system
HARMONIC CURRENTS ANALYSIS OF A 15 KW SINGLE PHASE ROOFTOP SOLAR POWER IN FUNCTION OF SOLAR IRRADIANCE AND PANEL TEMPERATURE IN VIETNAM
This paper presents a study on the harmonic analysis of a 15 kW single-phase rooftop solar system under varying solar irradiance and photovoltaic (PV) panel temperature conditions. The simulation model is developed based on a Maximum Power Point Tracking (MPPT) algorithm employing the Perturb and Observe (P&O) method, integrated with a proportional-resonant (PR) controller. Harmonic distortion is evaluated across different operating scenarios influenced by changes in irradiance and panel temperature. The computed harmonic levels are then compared against the current regulatory limits on current harmonics as specified in Circular No. 05/2025/TT-BCT, dated February 1, 2025, issued by the Ministry of Industry and Trade: Regulations on Power Transmission, Distribution, and Energy Metering Systems. Based on the analysis, several recommendations are proposed to enhance compliance and system performance
SIMULATION INVESTIGATION ON REDUCING SINGLE-PHASE AUTO-RECLOSING TIME ON TRANSMISSION LINES USING SHUNT REACTOR AND HSGS
This paper focuses on modeling and simulating solutions to reduce the reclosing time of single-phase auto-reclosing (SPAR) circuit breakers on 500 kV transmission lines using EMTP-RV software. The dynamic arc model simulates the phenomenon based on the thermal balance method, incorporating U50% breakdown voltage of long air gap. This study investigates two approaches to reducing secondary arc duration: (1) the employment of a neutral shunt reactor, and (2) the installation of high-speed grounding switches (HSGS) at both ends of the line. The solutions reduce reclosing time to 0.77 s and 0.2 s, with corresponding transient recovery voltages (TRV) of 58.3 kV and 14.8 kV for the neutral shunt reactor and HSGS, respectively, ensuring successful SPAR operation. Simulation results demonstrate that the proposed model allows observation of transient processes of current and voltage of the secondary arc during a single-phase short-circuit on the transmission line
EXPONENTIAL REACHING LAW-BASED SLIDING MODE CONTROL FOR A 2-DOF PLANAR ROBOT: ROBUSTNESS TO DISTURBANCES AND MASS VARIATIONS
This paper presents a robust sliding mode control (SMC) strategy based on an exponential reaching law for a two-degrees-of-freedom (2-DoF) planar robotic manipulator. The proposed controller is designed to achieve fast and accurate convergence of tracking errors while mitigating the chattering effects typically associated with conventional SMC approaches. By incorporating an exponentially decaying term into the reaching law, the controller enhances the smoothness of the sliding motion and improves the transient performance of the system. The dynamic model of the robotic manipulator is derived using the Euler–Lagrange formulation to capture the system's nonlinear and coupled dynamics. A Lyapunov-based stability analysis is employed to establish the asymptotic stability of the closed-loop system. To evaluate the controller’s effectiveness, extensive simulation studies are conducted under various scenarios, including nominal conditions, the presence of external disturbances, and significant variations in link mass parameters. The simulation results confirm excellent trajectory tracking performance and strong robustness, thereby demonstrating the controller’s adaptability to both ideal and uncertain environments. These results underline the potential of the proposed control scheme for practical applications in advanced robotic systems
SIMULATION, OPERATIONAL ANALYSIS, AND PROPOSED SOLUTIONS TO ENSURE VOLTAGE QUALITY OF A MICROGRID IN ISLANDED MODE
This paper presents the simulation and analysis of a Microgrid operating in islanded mode. The study focuses on evaluating the effectiveness of integrating compensation capacitors to improve voltage quality within the system. A detailed simulation model of the Microgrid is developed using the MATLAB-Simulink, employing components from the Simscape Electrical library to accurately represent key physical elements such as photovoltaic (PV) systems, battery energy storage systems (BESS), diesel generators, loads, and power converters. A notable feature of the model is its inclusion of multiple nodes at both medium-voltage and low-voltage levels, interconnected through distribution lines, thereby more closely reflecting the structure of real-world distribution networks than models used in previous studies. The Microgrid is simulated under various loading scenarios in islanded mode, with a particular focus on assessing the performance of compensation capacitors under peak load conditions. Simulation results indicate that, under peak load in islanded operation, voltage levels at several buses tend to drop below acceptable limits. However, the addition of shunt capacitors at heavily loaded buses significantly mitigates voltage drops and restores voltage to permissible levels. This compensation approach also reduces the reactive power burden on the diesel generator, thereby enhancing the overall efficiency and reliability of the system
CONSTANT CURRENT CHARGING WITH LCC-P COMPENSATION AND MUTUAL COUPLING ESTIMATION IN DYNAMIC WIRELESS CHARGING FOR EVS
This study presents a constant current charging method for dynamic wireless charging (DWC) systems, incorporating an LCC-P compensation topology and a mutual coupling estimation technique between the transmitting and receiving coils. The charging current is precisely regulated through the control of the DC/AC converter on the transmitting side, while system efficiency across the entire load range is systematically analyzed. A DWC system has been designed, consisting of two main parts: the transmitting side and the receiving side. The transmitting side comprises a charging lane with adjacent transmitting coils integrated beneath the road surface, connected to a high-frequency inverter system via a transmitting-side compensation circuit. The receiving side includes a receiving coil, a receiving-side compensation circuit, and a rectifier, all of which are integrated into the vehicle. Simulation results indicate that the proposed estimation and control method achieves high accuracy, with an estimation error of less than 2%, while maintaining an efficiency exceeding 90% across the entire load range.
FINITE ELEMENT-BASED OPTIMIZATION OF THE LIGHTNING CONDUCTION STRUCTURE IN REINFORCED POLES FOR MEDIUM VOLTAGE DISTRIBUTION LINES
Lightning-induced overvoltages pose a significant threat to the reliability of medium voltage (MV) distribution lines in power system, particularly through their impact on line insulators. Among the key parameters influencing these overvoltages is the surge impedance of pole structures, especially reinforced concrete poles commonly used in MV networks. Traditional analytical methods for surge impedance calculation are limited to simple pole geometries and do not adequately address configurations that include external grounding wires. This paper proposes a finite element method (FEM)-based approach to accurately compute the surge impedance of more complex pole structures incorporating external grounding conductors. The proposed method enables the detailed modeling of electromagnetic interactions within the pole-ground system and facilitates the optimization of grounding designs. Simulation results demonstrate that the optimized grounding structure significantly improves lightning discharge performance, offering a practical implementation to enhance the resilience of MV distribution systems against lightning-induced transients.
COMPARISON, EVALUATION AND APPLICATION OF BASIC COMPENSATION TOPOLOGIES IN WIRELESS POWER TRANSFER SYSTEMS
Wireless power transfer (WPT) is an effective solution for applications where the use of physical connections is inconvenient or impractical, such as electric vehicle charging, biomedical implants, and industrial automation. However, the efficiency of systems is often limited by the low coupling coefficient and high leakage inductance between the transmitting and receiving coils. Moreover, maintaining high efficiency and stable output despite load and coil position variations is also a significant challenge. In addition to control interventions, choosing the appropriate compensation topologies is crucial. Basic compensation topologies (Series Series – SS, Series Parallel – SP, Parallel Series – PS, and Parallel Parallel – PP) are often chosen for systems that require compact size, easy deployment, and low cost. This paper analyzes and compares basic compensation topologies to evaluate the applicability of each structure, helping to improve efficiency, ensure stable output, and maintain system simplicity.
RESOURCE ADEQUACY MECHANISMS IN COMPETITIVE ELECTRICITY MARKETS IN THE WORLD
In recent years, Vietnam's power system has often faced a shortage of power capacity during peak summer heat periods when hydropower sources are disadvantaged by weather conditions. This has exposed the limitations of resource adequacy mechanism in Vietnam's competitive electricity market. This article reviews the resource adequacy mechanisms in competitive electricity markets around the world along with an analysis of the advantages and disadvantages of each mechanism. These analyses will be meaningful for improving the resource adequacy mechanism in Vietnam's competitive electricity market
PARTICLE SWARM OPTIMIZATION OF A KALMAN FILTER FOR SPEED ESTIMATION OF DC MOTOR
DC motors have many critical applications in our daily lives. They can be used in many fields, including electric vehicles and household appliances. Therefore, the demand for DC motor control, particularly in terms of speed, has increased over the years. To control DC motors, it is necessary to measure relevant parameters such as motor speed and armature current using sensors. However, the installation of sensors will increase the system's cost, and it is challenging for DC motors due to space and weight limitations. To overcome this problem, it is necessary to design a measurement system with fewer sensors. A new method for estimating DC motor speed without using speed sensors is described in this paper, utilizing the Kalman filter for motor speed estimation due to its resistance to external disturbances and its ability to predict states and parameters. The Kalman filter (KF) requires tuning for improved estimation, which can be a time-consuming and laborious process. For that reason, the swarm optimization algorithm is used to optimize the Kalman filter. This paper will present the application of a swarm optimization algorithm (PSO) in optimizing the Kalman filter to estimate the speed of a DC motor through simulation in MATLAB and Simulink. The simulation results have shown the effectiveness of the proposed method
COOLING ENERGY ASSESSMENT OF AN EXISTING DATA CENTER IN HANOI
Demand for information handling and processing applications has grown significantly in response to the exponential expansion of data trafficking, data processing, e-learning, social networking, digitization of services, and general shift to digital platforms. The enormous amounts of data produced and used daily are stored and handled on a data center, including servers, routers, firewalls, and storage devices. The deployment of data centers as essential assets for any organizations is growing and calls for attention on their lifetime and efficiency. After many years operating, it is particularly important to assess the critical facilities. The assessment is crucial for the operational capacity of the data center to be kept and optimized as well as for the assessment of its future development capacity to meet the growing needs. This paper describes a thorough approach for evaluating typical data center projects to find hazards and risks that might compromise the availability or safety of data centers. It also offers ideas for enhancing the dependability, resilience, and efficiency of present data center architecture with low operational disturbance. We aims to evaluate the energy efficiency and risk of present data centers so developing a plan for improving and preserving their performance in a society going more digital. The approach consists of a thorough analysis of the current DC’s infrastructure, the identification of possible weaknesses, and the formulation of plans to reduce the found hazards. The case study assessment helps data center operators to better run their facilities, so ensuring their resilience and robustness in the presence of changing needs and possible hazards. This pro-active data center assessment approach is essential to enable the continuous digital transformation deployment and protect the vital services modern of DC’s owners
Hai Minh Luong, Trong Toan Nguyen, Xuan-Truong Nguyen
OVERVOLTAGE SUPPRESSION OF MMC-HVDC OFFSHORE WIND FARM UNDER VALVE-SIDE SPG FAULT BASED ON MODEL PREDICTIVE CONTROL
In the midst of the world's rapidly accelerating energy transition, offshore wind power is one of the forefront technologies to be developed and implemented. With the advantage of having an extensive coastline, the potential for offshore wind power systems in Vietnam is enormous. To ensure a reliable and efficient power delivery system, modular multilevel converter high-voltage direct current (MMC-HVDC) transmission systems are being increasingly preferred. Considering onshore converter stations, occurrence of single-phase to ground (SPG) faults can cause DC line overvoltage, which triggers circuit breakers and interrupts the power transmission process. This paper proposes a method to suppress the overvoltage based on a model predictive control (MPC) controller for the onshore converter station. The simulated results are directly compared with a previously proposed zero-sequence voltage control method and show the superiority of the MPC model on controlling the DC line and the sub-modules’ voltages. Simulations were performed using Simulink/MATLAB software.
Nam Nguyen Hoang, Tung Nguyen Nhu, Son Tran Thanh, Tuyen Nguyen Duc
OBJECTIVE FUNCTION FOR POWER SYSTEM STATE ESTIMATION WITH PARTICLE SWARM OPTIMIZATION
Bài toán ước lượng trạng thái có mục tiêu là xác định trạng thái gần giống nhất của hệ thống dựa trên tập các giá trị đo đang có, giúp người vận hành đánh giá hệ thống và đưa ra những quyết định phù hợp. Để giải quyết bài toán, bài báo trình bày nghiên cứu sáu kết hợp giữa hai thuật toán (tối ưu bầy đàn, tối ưu bầy đàn với quá trình tách biến) và ba dạng hàm mục tiêu (bình phương cực tiểu có trọng số, cực tiểu trị tuyệt đối, cực tiểu trị tuyệt đối có trọng số). Bên cạnh đó, việc đánh giá giá trị các biến trạng thái được thực hiện trong thuật toán thay vì đưa hàm phạt vào hàm mục tiêu như các nghiên cứu trước đây. Các kết hợp được thực hiện mô phỏng cho lưới điện IEEE 14 nút và IEEE 30 nút với trường hợp giả sử dữ liệu đo từ thiết bị đo thông thường hoặc từ thiết bị PMU. Các kết quả mô phỏng cho thấy các thuật toán kết hợp với hàm bình phương cực tiểu có trọng số cho kết quả ước lượng tốt nhất trong các trường hợp nghiên cứu