Pub Date : 2022-03-20DOI: 10.1109/SGRE53517.2022.9774145
A. N. Alquennah, M. Trabelsi, A. Krama, H. Vahedi, Mostefa Mohamed-Seghir
This paper proposes an auto-tuned finite control set-model predictive control (FCS-MPC) for a grid-tied singlephase crossover switches cell (CSC) inverter. The multilevel inverter (MLI) under study generates 9 voltage levels. The FCSMPCobjective is to minimize the total harmonic distortion (THD) of the current fed to the grid with unity power factor while regulating the capacitor voltage at its reference value to maintain the 9 voltage levels. The switching losses are reduced by managing the redundant switching states selection. Artificial Neural Network (ANN) based on the Bayesian regularized feedforward learning technique is applied to predict the optimal weighting factor of the FCS-MPC with respect to the measured reference current value. The effect of using a dynamic weighting factor on the current THD for different reference current peak values (ranging from 2A to 8A) is studied through MATLAB/Simulink simulation. The presented simulation is intended to show that the application of a dynamic weighting factor can significantly enhance the current THD compared to the use of a fixed weighting factor.
{"title":"ANN based Auto-Tuned Optimized FCS-MPC for Grid-Connected CSC Inverter","authors":"A. N. Alquennah, M. Trabelsi, A. Krama, H. Vahedi, Mostefa Mohamed-Seghir","doi":"10.1109/SGRE53517.2022.9774145","DOIUrl":"https://doi.org/10.1109/SGRE53517.2022.9774145","url":null,"abstract":"This paper proposes an auto-tuned finite control set-model predictive control (FCS-MPC) for a grid-tied singlephase crossover switches cell (CSC) inverter. The multilevel inverter (MLI) under study generates 9 voltage levels. The FCSMPCobjective is to minimize the total harmonic distortion (THD) of the current fed to the grid with unity power factor while regulating the capacitor voltage at its reference value to maintain the 9 voltage levels. The switching losses are reduced by managing the redundant switching states selection. Artificial Neural Network (ANN) based on the Bayesian regularized feedforward learning technique is applied to predict the optimal weighting factor of the FCS-MPC with respect to the measured reference current value. The effect of using a dynamic weighting factor on the current THD for different reference current peak values (ranging from 2A to 8A) is studied through MATLAB/Simulink simulation. The presented simulation is intended to show that the application of a dynamic weighting factor can significantly enhance the current THD compared to the use of a fixed weighting factor.","PeriodicalId":64562,"journal":{"name":"智能电网与可再生能源(英文)","volume":"16 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76556595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-20DOI: 10.1109/SGRE53517.2022.9774271
S. Vadi, R. Bayindir
In case of load change at the output of the converters, the inductor and capacitor sizes in the converters should also change. Otherwise, there will be distortions in the dynamic response of the converter in terms of performance criteria such as settling time, rise time and maximum overshoot amount. This paper presents to improve the control's performances optimization using particle swarm optimization (PSO) of the system consisting of a buck converter based on sliding mode control (SMC) under variable conditions. Thus, a stable control structure has created by calculating the optimal values of the coefficients in the sliding mode control structure with the PSO method. The input source is taken as direct source (DC) source voltage at variable conditions. Buck Converter output voltage has been tested on variable loads. The modeling is done in MATLAB/Simulink software.
{"title":"Performance Enhancement of SMC Based Buck Converter under Variable Conditions by Particle Swarm Optimization Algorithm","authors":"S. Vadi, R. Bayindir","doi":"10.1109/SGRE53517.2022.9774271","DOIUrl":"https://doi.org/10.1109/SGRE53517.2022.9774271","url":null,"abstract":"In case of load change at the output of the converters, the inductor and capacitor sizes in the converters should also change. Otherwise, there will be distortions in the dynamic response of the converter in terms of performance criteria such as settling time, rise time and maximum overshoot amount. This paper presents to improve the control's performances optimization using particle swarm optimization (PSO) of the system consisting of a buck converter based on sliding mode control (SMC) under variable conditions. Thus, a stable control structure has created by calculating the optimal values of the coefficients in the sliding mode control structure with the PSO method. The input source is taken as direct source (DC) source voltage at variable conditions. Buck Converter output voltage has been tested on variable loads. The modeling is done in MATLAB/Simulink software.","PeriodicalId":64562,"journal":{"name":"智能电网与可再生能源(英文)","volume":"122 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85261428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-20DOI: 10.1109/SGRE53517.2022.9774112
A. Kouzou, M. Morawiec, F. Wilczyński
This paper deals with the sensorless backstepping control of the multiphase induction motor under faulty operation mode. Indeed, the proposed control is based on a linearized model where decoupling problems associated with the nonlinear dq model are eliminated. Whereas, this model is obtained from the linearization of the machine vector model in the stationary reference frame $alpha-beta$ which is achieved by using a non-linearized transformation such as the Z-transformation proposed in this paper. Furthermore, this model can be extended to all planes $alpha(text{n})-beta(text{n})$, where the used backstepping technique allows ensuring independent torque and rotor flux stabilization in each plane. Finally, some experimental results are presented for the validation of the proposed control on a specific sensorless benchmark of a five-phase squirrel cage induction motor under fault conditions suchas open phase fault on one and two phases.
{"title":"Sensorless Backstepping Control of Multiphase Induction Machines Under Fault Conditions","authors":"A. Kouzou, M. Morawiec, F. Wilczyński","doi":"10.1109/SGRE53517.2022.9774112","DOIUrl":"https://doi.org/10.1109/SGRE53517.2022.9774112","url":null,"abstract":"This paper deals with the sensorless backstepping control of the multiphase induction motor under faulty operation mode. Indeed, the proposed control is based on a linearized model where decoupling problems associated with the nonlinear dq model are eliminated. Whereas, this model is obtained from the linearization of the machine vector model in the stationary reference frame $alpha-beta$ which is achieved by using a non-linearized transformation such as the Z-transformation proposed in this paper. Furthermore, this model can be extended to all planes $alpha(text{n})-beta(text{n})$, where the used backstepping technique allows ensuring independent torque and rotor flux stabilization in each plane. Finally, some experimental results are presented for the validation of the proposed control on a specific sensorless benchmark of a five-phase squirrel cage induction motor under fault conditions suchas open phase fault on one and two phases.","PeriodicalId":64562,"journal":{"name":"智能电网与可再生能源(英文)","volume":"72 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86315657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-20DOI: 10.1109/SGRE53517.2022.9774114
Amani Fawaz, I. Mougharbel, H. Kanaan
The Energy Internet (EI) is a power system evolution that aims to incorporate renewable energy into the energy network, reduce the size and cost of energy storage devices, and improve energy efficiency. Furthermore, the development of the peer-to-peer energy trading market, which allows any subscriber to participate in the energy trading process, has raised the necessity of the energy routing process. Subscriber matching, energy-efficient paths, and transmission scheduling issues must all be considered throughout the energy routing process. Based on graph theory, this paper suggested a novel routing approach inspired by bees’ colony foraging behavior to address routing issues. The bees’ colony-inspired energy routing approach was developed to determine a non-congestion minimum loss path and the optimal energy producers to satisfy the consumer request while considering power and time restrictions. Furthermore, this technique supports singlesource consumers, multi-source consumers, and multiple consumers’ scenarios. The performance of the proposed protocol is compared to an existing method in the literature in terms of power losses, congestion management, and computation time. The suggested method’s performance and adaptability have been validated in several different scenarios.
{"title":"New Routing Application Using Bees Colony for Energy Internet","authors":"Amani Fawaz, I. Mougharbel, H. Kanaan","doi":"10.1109/SGRE53517.2022.9774114","DOIUrl":"https://doi.org/10.1109/SGRE53517.2022.9774114","url":null,"abstract":"The Energy Internet (EI) is a power system evolution that aims to incorporate renewable energy into the energy network, reduce the size and cost of energy storage devices, and improve energy efficiency. Furthermore, the development of the peer-to-peer energy trading market, which allows any subscriber to participate in the energy trading process, has raised the necessity of the energy routing process. Subscriber matching, energy-efficient paths, and transmission scheduling issues must all be considered throughout the energy routing process. Based on graph theory, this paper suggested a novel routing approach inspired by bees’ colony foraging behavior to address routing issues. The bees’ colony-inspired energy routing approach was developed to determine a non-congestion minimum loss path and the optimal energy producers to satisfy the consumer request while considering power and time restrictions. Furthermore, this technique supports singlesource consumers, multi-source consumers, and multiple consumers’ scenarios. The performance of the proposed protocol is compared to an existing method in the literature in terms of power losses, congestion management, and computation time. The suggested method’s performance and adaptability have been validated in several different scenarios.","PeriodicalId":64562,"journal":{"name":"智能电网与可再生能源(英文)","volume":"18 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75163307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-20DOI: 10.1109/SGRE53517.2022.9774214
V. Singh, T. Moger, D. Jena
Nowadays, renewable energy sources (REs) are increasingly integrated into electrical power networks. Among many REs, wind energy has emerged as a prominent source of electricity. However, rising wind power penetration has increased the system's net generation variability. Consequently, the ability to monitor and simulate the behavior of wind power generation (WPG) in detail is critical. Furthermore, the wind speed or wind power output of different wind farms can be highly interdependent and may not follow Normal distribution. This study proposes a probabilistic load flow (PLF) technique for modeling normally distributed loads and non-normally distributed WPG based on the modified point estimation method (PEM). This modification allows modeling dependent input random variables as a function of many independent ones using the Nataf transformation. By utilizing the findings of the Monte-Carlo method as a reference, the usefulness of the suggested technique is tested by conducting case studies on a 24-bus equivalent system of the Indian Southern region power grid. Simulation results indicate that the modified PEM can easily handle the correlation and have high processing efficiency.
{"title":"Probabilistic Load Flow Considering Load and Wind Power Uncertainties using Modified Point Estimation Method","authors":"V. Singh, T. Moger, D. Jena","doi":"10.1109/SGRE53517.2022.9774214","DOIUrl":"https://doi.org/10.1109/SGRE53517.2022.9774214","url":null,"abstract":"Nowadays, renewable energy sources (REs) are increasingly integrated into electrical power networks. Among many REs, wind energy has emerged as a prominent source of electricity. However, rising wind power penetration has increased the system's net generation variability. Consequently, the ability to monitor and simulate the behavior of wind power generation (WPG) in detail is critical. Furthermore, the wind speed or wind power output of different wind farms can be highly interdependent and may not follow Normal distribution. This study proposes a probabilistic load flow (PLF) technique for modeling normally distributed loads and non-normally distributed WPG based on the modified point estimation method (PEM). This modification allows modeling dependent input random variables as a function of many independent ones using the Nataf transformation. By utilizing the findings of the Monte-Carlo method as a reference, the usefulness of the suggested technique is tested by conducting case studies on a 24-bus equivalent system of the Indian Southern region power grid. Simulation results indicate that the modified PEM can easily handle the correlation and have high processing efficiency.","PeriodicalId":64562,"journal":{"name":"智能电网与可再生能源(英文)","volume":"128 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73884206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-20DOI: 10.1109/SGRE53517.2022.9774176
S. Patra, S. Khadem, M. Basu, H. Komurcugil, S. Bayhan
In order to improve the compensating capabilities of shunt active power filters (APF) coupled with renewable energy integrated microgrid network, this research offers a Recursive Least Square Bacterial Foraging optimization (RLSBFO) based estimation approach for the reference current generation. The suggested approach can improve the compensation of current harmonics in a selective/collective (global) manner. Furthermore, the RLS-BFO-based reference generation approach eliminates the necessity for a PLL based synchronization circuit, which helps to reduce computation latency. The instantaneous active and reactive power theory (PQ theory) and the Kalman filter-based estimation approach are also implemented and compared to assess the suggested controller’s effectiveness. The MATLAB based simulation results, followed by the quantitative analysis demonstrate the efficacy of the estimation algorithm.
{"title":"A Fast Predictive Reference Current Generation Algorithm for Shunt APF in DER Integrated Network","authors":"S. Patra, S. Khadem, M. Basu, H. Komurcugil, S. Bayhan","doi":"10.1109/SGRE53517.2022.9774176","DOIUrl":"https://doi.org/10.1109/SGRE53517.2022.9774176","url":null,"abstract":"In order to improve the compensating capabilities of shunt active power filters (APF) coupled with renewable energy integrated microgrid network, this research offers a Recursive Least Square Bacterial Foraging optimization (RLSBFO) based estimation approach for the reference current generation. The suggested approach can improve the compensation of current harmonics in a selective/collective (global) manner. Furthermore, the RLS-BFO-based reference generation approach eliminates the necessity for a PLL based synchronization circuit, which helps to reduce computation latency. The instantaneous active and reactive power theory (PQ theory) and the Kalman filter-based estimation approach are also implemented and compared to assess the suggested controller’s effectiveness. The MATLAB based simulation results, followed by the quantitative analysis demonstrate the efficacy of the estimation algorithm.","PeriodicalId":64562,"journal":{"name":"智能电网与可再生能源(英文)","volume":"20 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73957198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-20DOI: 10.1109/SGRE53517.2022.9774126
Ibrahim Alzubi, Hussein M. K. Al-Masri, Ahmad Abuelrub
Electrical power systems consist of many generation units with each unit is limited to its characteristics. These units must be operated such that their total output power meets the total system demand and system losses at the minimum operation cost. This problem is known as the economic load dispatch (ELD) problem. The cost function of generation units is non-smooth and non-linear. Therefore, metaheuristic techniques are employed to solve this non-convex optimization problem. In this paper, the particle swarm optimization (PSO) algorithm and three other modified versions of the PSO are used to solve this highly non-linear and constrained optimization problem. The modified versions of the PSO are weight enhanced particle swarm optimization (WEPSO), chaotic particle swarm optimization (CPSO), and time-varying acceleration coefficients particle swarm optimization (TVACPSO). These algorithms are applied to solve the ELD problem for IEEE 15-unit test system. Results show that the WEPSO algorithm gives the minimum system operation cost and has the highest convergence rate.
{"title":"Modified Particle Swarm Optimization Algorithms for Solving Economic Load Dispatch","authors":"Ibrahim Alzubi, Hussein M. K. Al-Masri, Ahmad Abuelrub","doi":"10.1109/SGRE53517.2022.9774126","DOIUrl":"https://doi.org/10.1109/SGRE53517.2022.9774126","url":null,"abstract":"Electrical power systems consist of many generation units with each unit is limited to its characteristics. These units must be operated such that their total output power meets the total system demand and system losses at the minimum operation cost. This problem is known as the economic load dispatch (ELD) problem. The cost function of generation units is non-smooth and non-linear. Therefore, metaheuristic techniques are employed to solve this non-convex optimization problem. In this paper, the particle swarm optimization (PSO) algorithm and three other modified versions of the PSO are used to solve this highly non-linear and constrained optimization problem. The modified versions of the PSO are weight enhanced particle swarm optimization (WEPSO), chaotic particle swarm optimization (CPSO), and time-varying acceleration coefficients particle swarm optimization (TVACPSO). These algorithms are applied to solve the ELD problem for IEEE 15-unit test system. Results show that the WEPSO algorithm gives the minimum system operation cost and has the highest convergence rate.","PeriodicalId":64562,"journal":{"name":"智能电网与可再生能源(英文)","volume":"64 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89503962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-20DOI: 10.1109/SGRE53517.2022.9774186
Mohsen Hosseinzadehtaher, M. Greidanus, Hassan Althuwaini, Kyle Sullivan, M. Shadmand, S. Mazumder
This paper proposes an efficient constant power generation (CPG) control scheme for photovoltaic systems (PV) by utilizing differential power processing (DPP) converters. The conventional CPG approaches will become nearly ineffective for PV modules under partial shading conditions; thus, resulting in propagation of disturbances in high PV penetrated grids. The goal of this paper is to realize a more effective dispatchable PV power generation under partial shading conditions to mitigate wide range of disturbances at the grid-edge. The proposed approach is to leverage DPP converters to improve power harvesting when the PV systems encounter partial shading while ensuring CPG for wide range of PV modules’ condition. Several case studies are presented to demonstrate the functionality of the proposed approach for achieving CPG. The provided comparison between the proposed and state-of-the-art CPG approaches demonstrates promising superiority for realizing grid-friendly PV systems.
{"title":"Differential Power Processing-based Constant Power Generation towards Grid-friendly Photovoltaic System","authors":"Mohsen Hosseinzadehtaher, M. Greidanus, Hassan Althuwaini, Kyle Sullivan, M. Shadmand, S. Mazumder","doi":"10.1109/SGRE53517.2022.9774186","DOIUrl":"https://doi.org/10.1109/SGRE53517.2022.9774186","url":null,"abstract":"This paper proposes an efficient constant power generation (CPG) control scheme for photovoltaic systems (PV) by utilizing differential power processing (DPP) converters. The conventional CPG approaches will become nearly ineffective for PV modules under partial shading conditions; thus, resulting in propagation of disturbances in high PV penetrated grids. The goal of this paper is to realize a more effective dispatchable PV power generation under partial shading conditions to mitigate wide range of disturbances at the grid-edge. The proposed approach is to leverage DPP converters to improve power harvesting when the PV systems encounter partial shading while ensuring CPG for wide range of PV modules’ condition. Several case studies are presented to demonstrate the functionality of the proposed approach for achieving CPG. The provided comparison between the proposed and state-of-the-art CPG approaches demonstrates promising superiority for realizing grid-friendly PV systems.","PeriodicalId":64562,"journal":{"name":"智能电网与可再生能源(英文)","volume":"134 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77363764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-20DOI: 10.1109/SGRE53517.2022.9773332
F. Maurice
This paper presents an SAB converter for connecting a DC network to an electric vehicle battery for the purpose of rapid charging. The chosen topology provides galvanic isolation and uses a resonant circuit operating above the resonant frequency. This paper proposes a simple control law to control the battery charging current by acting on the frequency of the resonant circuit using a VCO. The non-linear behavior of the converter is identified by a least squares procedure and the control law is composed of a linear controller and a non-linearity compensation block Various simulation tests validate the proposal for a wide range of load currents.
{"title":"DC microgrids and battery charging","authors":"F. Maurice","doi":"10.1109/SGRE53517.2022.9773332","DOIUrl":"https://doi.org/10.1109/SGRE53517.2022.9773332","url":null,"abstract":"This paper presents an SAB converter for connecting a DC network to an electric vehicle battery for the purpose of rapid charging. The chosen topology provides galvanic isolation and uses a resonant circuit operating above the resonant frequency. This paper proposes a simple control law to control the battery charging current by acting on the frequency of the resonant circuit using a VCO. The non-linear behavior of the converter is identified by a least squares procedure and the control law is composed of a linear controller and a non-linearity compensation block Various simulation tests validate the proposal for a wide range of load currents.","PeriodicalId":64562,"journal":{"name":"智能电网与可再生能源(英文)","volume":"73 1 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72702617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-20DOI: 10.1109/SGRE53517.2022.9774107
Bayan Hussein, Abdulazeez Alsalemi, L. Ben‐Brahim
Conventional single-stage Power Factor Correction (PFC) rectifiers struggle with extreme duty ratio operation for low-voltage applications, like Low-speed Electric Vehicles (LSEV). This worsens the performance of the converter and degrades the operation with time. High-gain single-switch PFC rectifiers offer better performance in terms of the duty ratio, reduced size and cost due to single-stage operation, and increasing the power density, all while meeting the required standards and regulations. This paper presents a performance assessment of PFC for AC-DC rectifiers using various high-gain single-switch DC-DC converters for LSEVs, where the battery’s voltage is 48V. Particularly, conventional SEPIC, quadratic SEPIC, quadratic Buck, and B5 converters are compared. MATLAB/Simulink software tool was used for the validity of performance assessments. The performance of the converters assesses the converters’ gain, stresses, component count, and overall cost. Results show that the B5 converter has the best behavior in terms of these specifications.
{"title":"High-Gain Non-isolated Single-Switch DC-DC Converters in Power Factor Correction Rectifiers: A Performance Assessment","authors":"Bayan Hussein, Abdulazeez Alsalemi, L. Ben‐Brahim","doi":"10.1109/SGRE53517.2022.9774107","DOIUrl":"https://doi.org/10.1109/SGRE53517.2022.9774107","url":null,"abstract":"Conventional single-stage Power Factor Correction (PFC) rectifiers struggle with extreme duty ratio operation for low-voltage applications, like Low-speed Electric Vehicles (LSEV). This worsens the performance of the converter and degrades the operation with time. High-gain single-switch PFC rectifiers offer better performance in terms of the duty ratio, reduced size and cost due to single-stage operation, and increasing the power density, all while meeting the required standards and regulations. This paper presents a performance assessment of PFC for AC-DC rectifiers using various high-gain single-switch DC-DC converters for LSEVs, where the battery’s voltage is 48V. Particularly, conventional SEPIC, quadratic SEPIC, quadratic Buck, and B5 converters are compared. MATLAB/Simulink software tool was used for the validity of performance assessments. The performance of the converters assesses the converters’ gain, stresses, component count, and overall cost. Results show that the B5 converter has the best behavior in terms of these specifications.","PeriodicalId":64562,"journal":{"name":"智能电网与可再生能源(英文)","volume":"46 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72838296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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