International Journal of Power Electronics and Drive Systems (IJPEDS)
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Islanding detection of integrated DG system using rate of change of frequency over reactive power
Get PDFThis paper offers a passive islanding detection method that is effective for distributed generation. When a distributed generator (DG) keeps a location powered even when access to the external electrical grid is lost, this circumstance is referred to as islanding. The power distribution system currently includes distributed generators (DGs), which provide inexpensive electricity and have fewer environmental impacts. Sometimes, these DGs continue to supply the nearby loads because of line outages and islands made by system separations. As a result, there are scenarios with unacceptable power quality. The islanding is identified if the result of the rate of change of frequency over reactive power exceeds the threshold value. The MATLAB test results from this study demonstrate the effectiveness of the suggested approach for different islanding and non-islanding scenarios
Advancing power quality via distributed power flow control solutions
Get PDFThe growing demand for enhanced power quality and reliable transmission has driven advancements in power flow control technologies. The distributed power flow controller (DPFC) represents an advancement over the unified power flow controller (UPFC). In contrast to the UPFC, the DPFC removes the DC link connecting the shunt and series converters, and redistributes the series converters along the transmission line as single-phase static series compensators. This modification enhances grid performance while maintaining full power flow control capabilities. The DPFC offers several advantages over the UPFC, including higher reliability, improved controllability, and greater cost-effectiveness. The system comprises a shunt converter in conjunction with multiple series converters, each with its own control circuit, all managed by a central control unit. This article presents the implementation of a DPFC model in MATLAB/Simulink. The simulation outcomes indicate that the DPFC significantly contributes to improved voltage stability and enhanced power transfer capability, thereby reinforcing system performance and reliability
Design of a static synchronous compensator for the north-south high-speed railway system
Get PDFThe modern high-speed rail system plays a crucial role in driving the nation’s economic development. The problem of voltage imbalance caused by intermittent load movements is a significant challenge for energy management and distribution. When electric trains are connected to the three-phase grid, power quality degradation occurs, resulting in distortion and imbalance of the three-phase grid current and voltage, which in turn increases operating costs. This paper has proposed a linear control method using a PI controller for a static synchronous compensator (STATCOM) to directly control the amount of reactive power loss for electric trains. This solution will also bring good and stable voltage quality to electric trains so that electric trains can operate for a long time. The STATCOM device in this paper is a three-phase voltage source converter with a simple structure and can be easily controlled. This is considered a simple and effective solution to balance voltage, improve power factor, and enhance harmonic quality for railway trains, thereby achieving an optimal operating solution. This discussion can be simulated using MATLAB/Simulink software to determine the operation and control steps for STATCOM, thereby improving the quality of the power system. The simulation results of current, voltage, and reactive power response are presented. The simulation results have demonstrated that the proposed algorithm successfully achieves the set goals of ensuring voltage stability and providing the necessary amount of reactive power for the train, thereby improving the quality of the power grid for the North-South high-speed train in Vietnam
Hybrid intelligent optimization algorithms-based power management for microgrid system
Get PDFThe integration of the photovoltaic (PV) and wind sources of power in microgrids is a beneficial method toward decentralized, efficient, and sustainable energy management. This research endeavors to develop and implement a novel hybrid control strategy that efficiently combines grey wolf optimization (GWO) and particle swarm optimization (PSO) algorithms for the optimization of renewable energy-based microgrids. The proposed method addresses three critical tasks under one integrated control mechanism: i) maximum power point tracking (MPPT) for PV and wind systems under fluctuating environmental conditions, ii) smart management of energy storage systems for batteries, and iii) adaptive load scheduling based on real-time availability of energy. By leveraging the complementary strengths of GWO and PSO, the system enjoys improved convergence rate, global search, and decision-making robustness. The hybrid controller is tested and validated through thorough testing in MATLAB/Simulink under dynamic simulation scenarios that mimic sudden weather and load variations. Comparative performance with conventional methods and benchmarking based on IEEE 516 standards demonstrates the improved reliability, responsiveness, and energy efficiency of the proposed system. This research contributes to the state-of-the-art of intelligent microgrid control through an integrated, bio-inspired solution toward resilient and optimized energy management
Design and development of AC motor speed controlling system using touch screen with over heat protection
Get PDFDesign and implementation of an AC motor speed control and monitoring system based on a touch screen interface with built-in overheat protection, utilizing Arduino, meets the increasing demand for efficient, user-friendly motor control in many industrial applications. This system offers an easy-to-use interface to manage the speed of an AC motor, with real-time feedback and adjustments through a touch screen display. The system employs an Arduino microcontroller, which accepts inputs from the touch screen and processes these to regulate the motor's speed through a pulse width modulation (PWM) method. The system also has an overheat protection system, which it is able to monitor the temperature of the motor via a temperature sensor. When the motor reaches a predetermined temperature, the system automatically shuts off power to avoid damage. The intuitive touch screen facilitates convenient monitoring of motor parameters like temperature, giving a smooth experience to operators. The modular design of the system provides scalability across applications, ranging from household appliances to large industrial systems, with reliability, energy efficiency, and safety in motor-driven processes
Intelligent control solutions for enhancing dual-fold Luo converter efficiency in EVs
Get PDFThis research proposes the design and application of a smart controller for a dual-fold Luo converter tailored specifically for E-vehicle applications. The dual-fold Luo converter, known for its ability to efficiently step up and step down voltage levels with reduced components, is augmented with a smart control strategy to enhance its performance in the context of electric vehicles. The smart controller utilizes advanced techniques, such as artificial neural networks or fuzzy logic, to adaptively regulate the converter's operation, thereby improving efficiency, transient response, and overall reliability. By leveraging real-time data from the E-vehicle system, the controller dynamically adjusts key parameters to optimize performance under varying load and operating conditions. Key design considerations include the selection and training of the smart controller to achieve desired voltage regulation, efficiency, and robustness in the face of uncertainties inherent in E-vehicle operation. The proposed design methodology is validated through simulation studies, demonstrating superior performance compared to conventional control techniques. The results illustrate the efficacy of the smart controller in enhancing the dynamic response of the dual-fold Luo converter, making it a promising solution for E-vehicle power management systems. This research contributes to the advancement of power electronics in electric transportation, facilitating the development of more efficient and reliable E-vehicle systems in the pursuit of sustainable mobility
Accurate state of health estimation using hybrid algorithm for electric vehicle battery pack performance and efficiency enhancement
Get PDFTemperature fluctuations, overcharging, and over-discharging are all issues that can cause fast deterioration, capacity loss, and thermal runaway in lithium-ion batteries (LIBs). To overcome these challenges, a hybrid model combining a stacked recurrent neural network (SRNN) and bidirectional long short-term memory (biLSTM) is presented for a reliable state of health (SoH) estimate. This model finds subtle patterns in battery data using SRNN layers to capture sequential dependencies and biLSTM modules to solve long-term temporal correlations while avoiding vanishing gradient concerns. The effectiveness of model is assessed by performance measures such as root mean square error (RMSE), mean absolute error (MAE), and maximum error (MAX), which demonstrate its superiority for precise SoH estimation. The stacked RNN-based SoH estimation achieves superior accuracy, with RMSE, MAE, and MAX error levels of 1.5%, 0.8%, and 4.84%, respectively, compared to GRU’s higher errors (3.8%, 3%, and 5.5%). Stacked RNN hierarchically processes sequential battery data, effectively capturing complex temporal relationships, and ensuring accurate and reliable SoH estimation for LIBs
Modeling and analysis of three-phase boost rectifier for DC fast EV charging
Get PDFThis research investigates the modeling and analysis of a three-phase boost rectifier for DC fast charging systems for electric vehicles (EVs). A mathematical model validated with MATLAB/Simulink simulations examines system behavior under various conditions. Performance analysis in the abc and dq coordinate systems reveals high consistency with theoretical calculations. The average voltage in the dq frame was found to be vd was 685 V and vq was 0 V, with a discrepancy of less than 0.1% from calculated values. However, the average current in the dq frame showed discrepancies due to cross-coupling effects and circuit impedance. Simulations reported id was 211.50 A and iq was 93.50 A, compared to calculated values of id was 151.97 A and iq was 0 V. For the output DC voltage and current, the average values were 983.05 V and 98.31 A, respectively. Three test cases were analyzed, consist of unbalanced three-phase conditions, voltage drops, and load step responses. Case 1 showed the highest total harmonic distortion (THD), Case 2 increased THD further, and Case 3 achieved the lowest THD, demonstrating improved stability under dynamic loads. These findings confirm the system’s minimal deviations from theoretical predictions, enhanced voltage quality, harmonic mitigation, and improved charging efficiency for EV fast charging applications
PSO-based adaptive sliding mode control of a bidirectional DC-DC converter with an improved reaching law
Get PDFThis paper explores the development of an adaptive sliding mode control (ASMC) that incorporates an improved optimal reaching law. We intend to use the proposed ASMC in DC microgrids or electric vehicle applications to regulate a bidirectional (two-way) buck-mode DC-DC converter. To initiate the design process, we develop a mathematical model of the converter operating in the charging mode. A particle swarm optimization is employed to help get the controller’s gains to better performance. By capitalizing on the benefits of an ASMC algorithm, the developed controller achieves improved reaching conditions, increased robustness, and strengthened stability. The efficacy of the suggested controller in comparison to conventional sliding mode control (CSMC) and ASMC is demonstrated through MATLAB/Simulink simulations conducted on the converter. The comparison demonstrates that the proposed controller achieves the intended transient response in steady-state conditions with minimal error and better reference tracking. The performance of the suggested controller is robust with regard to the rejection of variations in source voltage and load resistance. For applications involving DC microgrids or electric vehicles, the suggested controller will guarantee a consistent DC transit voltage
Torque ripples reduction and speed control of a switched reluctance motor based on artificial intelligence techniques
Get PDFThis paper proposes a technique for reducing torque ripples and speed control of switched reluctance motor (SRM) using artificial intelligence. The controller of SRM is developed based on a fuzzy logic controller using MATLAB/Simulink software. Fuzzy logic controller overcomes the nonlinearity and uncertainty of the SRM. The proposed controller is used for predicting torque ripples and speed control profiles. The machine performance using the proposed controller is compared with using a traditional PI controller. In addition, comparison of motor performance with and without the use of proposed controllers is highlighted. The motor performance is evaluated using the suggested different controllers. The simulation results show that the proposed method indicates a 65% to 75% reduction in torque ripples compared to the traditional PI method