Pub Date : 2023-03-03DOI: 10.13052/dgaej2156-3306.38311
Venkatasupura Vemulapati, Y. Vijaykumar, N. Visali, K. Kumar
The current power transmission system for Indian railways facing difficulties with voltage unbalance, harmonics and circulation of negative sequence current throughout the power transmission line. In addition, the existence of neutral sections between two adjacent traction substations will cause the speed reduction and is considered as the main limitation for high speed. Traction load is a single phase in nature and it is very difficult to estimate the power flow from adjacent substations to locomotive as well as the location of the train. In this paper advanced common phase traction power transmission system is designed which is much appropriate for high speed railway (HSR) by eliminating neutral sections (NS) and overcome all the fore mentioned power quality (PQ) issues. A simplex algorithm is proposed to estimate the power flow and location of the train. The simulation results are analysed and low scale prototype model is built to validate the simulation outcomes. The results obtained are satisfactory and indicates the system suitability for high speed railway network.
{"title":"Modular Multilevel Converter Based Advanced Traction Power Transmission Substation for High Speed Railway Network in India","authors":"Venkatasupura Vemulapati, Y. Vijaykumar, N. Visali, K. Kumar","doi":"10.13052/dgaej2156-3306.38311","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.38311","url":null,"abstract":"The current power transmission system for Indian railways facing difficulties with voltage unbalance, harmonics and circulation of negative sequence current throughout the power transmission line. In addition, the existence of neutral sections between two adjacent traction substations will cause the speed reduction and is considered as the main limitation for high speed. Traction load is a single phase in nature and it is very difficult to estimate the power flow from adjacent substations to locomotive as well as the location of the train. In this paper advanced common phase traction power transmission system is designed which is much appropriate for high speed railway (HSR) by eliminating neutral sections (NS) and overcome all the fore mentioned power quality (PQ) issues. A simplex algorithm is proposed to estimate the power flow and location of the train. The simulation results are analysed and low scale prototype model is built to validate the simulation outcomes. The results obtained are satisfactory and indicates the system suitability for high speed railway network.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87775289","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 : 2023-03-03DOI: 10.13052/dgaej2156-3306.3837
Adithya Ballaji, Ritesh Dash
The performance of the solar charge controller depends largely on the maximum power point (MPPT) tracking algorithms. The review paper emphasis on the factors that influence the selection of MPPT, and performance of the charge controller employed in PV system. An efficient MPPT technique can achieve the purpose of energy saving, better extraction of power from solar. This paper presents a literature review on the basic MPPT techniques in detail along with their variants published by various researchers. The detailed study of MPPT techniques for improving the PV system performance, has been presented in this paper with emphasis on design and future MPPT techniques based on Moving Average Filter.
{"title":"A Comprehensive Review on Latest State of the Art Practices in MPPT Algorithm","authors":"Adithya Ballaji, Ritesh Dash","doi":"10.13052/dgaej2156-3306.3837","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3837","url":null,"abstract":"The performance of the solar charge controller depends largely on the maximum power point (MPPT) tracking algorithms. The review paper emphasis on the factors that influence the selection of MPPT, and performance of the charge controller employed in PV system. An efficient MPPT technique can achieve the purpose of energy saving, better extraction of power from solar. This paper presents a literature review on the basic MPPT techniques in detail along with their variants published by various researchers. The detailed study of MPPT techniques for improving the PV system performance, has been presented in this paper with emphasis on design and future MPPT techniques based on Moving Average Filter.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88644875","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 : 2023-03-03DOI: 10.13052/dgaej2156-3306.3834
Chandrasekhar Reddy Gade, W. Sultana
In this paper sizing the powertrain of battery electric tractor (BET) including major farming implements are investigated for various real world driving patterns. Powertrain components are modelled using torque-load characteristics which are function of speed, acceleration, plowing implement and depth of plowing and texture of the soil. Effect of load variations on powertrain performance and energy consumption are also explained in detail. In this powertrain design major farming implements like chisel plough, mould board plough, field cultivator, sweep plough are considered. Tractor hauling a trailer carrying goods with 2000 kg weight is also considered for powertrain design. Typical operating velocities of 18, 15 and 25 kmph are taken for sand, tillage and asphalt surfaces respectively for tractor trailer applications and 7 kmph for plowing applications. The dynamic model of the powertrain is modelled in MATLAB/SIMULINK. PMSM is selected as a traction motor and its performance is evaluated in MATLAB/SIMULINK. Same has been verified using real-time Hardware in loop (HIL) simulator with help of OPAL-RT (OP5700).
{"title":"Battery Electric Tractor Powertrain Component Sizing With Respect To Energy Consumption, Driving Patterns and Performance Evaluation Using Traction Motor","authors":"Chandrasekhar Reddy Gade, W. Sultana","doi":"10.13052/dgaej2156-3306.3834","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3834","url":null,"abstract":"In this paper sizing the powertrain of battery electric tractor (BET) including major farming implements are investigated for various real world driving patterns. Powertrain components are modelled using torque-load characteristics which are function of speed, acceleration, plowing implement and depth of plowing and texture of the soil. Effect of load variations on powertrain performance and energy consumption are also explained in detail. In this powertrain design major farming implements like chisel plough, mould board plough, field cultivator, sweep plough are considered. Tractor hauling a trailer carrying goods with 2000 kg weight is also considered for powertrain design. Typical operating velocities of 18, 15 and 25 kmph are taken for sand, tillage and asphalt surfaces respectively for tractor trailer applications and 7 kmph for plowing applications. The dynamic model of the powertrain is modelled in MATLAB/SIMULINK. PMSM is selected as a traction motor and its performance is evaluated in MATLAB/SIMULINK. Same has been verified using real-time Hardware in loop (HIL) simulator with help of OPAL-RT (OP5700).","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"147 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77106796","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 : 2023-03-03DOI: 10.13052/dgaej2156-3306.3839
C. Prasad, K. Subbaramaiah, P. Sujatha
The particle swarm optimisation and gravitational search optimisation algorithm (PSOGSA) is a hybrid algorithm which is used to determine size of optimal Distributed Generation (DG) in this paper. The PSOGSA integrates the social thinking ability (gbest) in PSO to capability of local search in GSA. The algorithm combines the searching capability of PSO and with enhanced exploration ability of GSA. Distributed generations are connected in distribution systems to consumers to reduce losses, enhance the voltage profile, reliability and economic benefits. DG optimal positioning and loss minimisation have a significant role for economic operation and overall reduction of energy costs. For evaluation of proposed algorithm, the test bus sets IEEE15, 33 and 69 are chosen. For considered objectives i.e., optimal DG sizing and economic analysis, this PSOGSA algorithm gives better results as compared to other methods and better outcomes has been achieved when DG unit of type III operates at power factor of 0.9 lag
{"title":"Economic Analysis by Optimal Placing of DGs in Distribution Networks by Particle Swarm Optimisation and Gravitational Search Optimisation Algorithm","authors":"C. Prasad, K. Subbaramaiah, P. Sujatha","doi":"10.13052/dgaej2156-3306.3839","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3839","url":null,"abstract":"The particle swarm optimisation and gravitational search optimisation algorithm (PSOGSA) is a hybrid algorithm which is used to determine size of optimal Distributed Generation (DG) in this paper. The PSOGSA integrates the social thinking ability (gbest) in PSO to capability of local search in GSA. The algorithm combines the searching capability of PSO and with enhanced exploration ability of GSA. Distributed generations are connected in distribution systems to consumers to reduce losses, enhance the voltage profile, reliability and economic benefits. DG optimal positioning and loss minimisation have a significant role for economic operation and overall reduction of energy costs. For evaluation of proposed algorithm, the test bus sets IEEE15, 33 and 69 are chosen. For considered objectives i.e., optimal DG sizing and economic analysis, this PSOGSA algorithm gives better results as compared to other methods and better outcomes has been achieved when DG unit of type III operates at power factor of 0.9 lag","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90905401","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 : 2023-03-03DOI: 10.13052/dgaej2156-3306.38314
Devisree Chippada, M. D. Reddy
Distributed Generators (DGs) play a key role in existing power distribution networks together with significant innovations in smart grid technology. It is now more essential to evaluate the various types of DGs within the system. Renewable energy types of DGs such as PV and wind promise low emissions and abundant availability. When it comes to the installation of DG, the size, location, and type of DG should be given high importance because improper placement of DG units leads to reducing the benefits of the distribution system and even endangers the entire system operation. If DG size exceeds a certain value limit, power loss at that bus becomes negative. This situation must be avoided. As a result, optimal DG placement aids in the reduction of losses, improvement of voltage profiles, reliability, and overall system efficiency. Considering this, in this paper, a Simultaneous Particle Swarm Optimization (PSO) algorithm is implemented for placement allocation and sizing of multiple types and multiple numbers of DGs in power distribution systems with the objectives of minimization of active and reactive power loss and enhanced voltage profile. Along with the meta-heuristic optimization algorithm, sensitivity techniques such as index vector, loss sensitivity factor, and voltage stability margin methods have been analysed. The outcomes are obtained using the aforementioned sensitivity-related methods on the IEEE 15, 33, 69, and 85-radial bus systems and compared with simultaneous PSO for efficacy.
{"title":"Optimal Placement and Sizing of Renewable and Non-Renewable Resources in Smart Grid","authors":"Devisree Chippada, M. D. Reddy","doi":"10.13052/dgaej2156-3306.38314","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.38314","url":null,"abstract":"Distributed Generators (DGs) play a key role in existing power distribution networks together with significant innovations in smart grid technology. It is now more essential to evaluate the various types of DGs within the system. Renewable energy types of DGs such as PV and wind promise low emissions and abundant availability. When it comes to the installation of DG, the size, location, and type of DG should be given high importance because improper placement of DG units leads to reducing the benefits of the distribution system and even endangers the entire system operation. If DG size exceeds a certain value limit, power loss at that bus becomes negative. This situation must be avoided. As a result, optimal DG placement aids in the reduction of losses, improvement of voltage profiles, reliability, and overall system efficiency. Considering this, in this paper, a Simultaneous Particle Swarm Optimization (PSO) algorithm is implemented for placement allocation and sizing of multiple types and multiple numbers of DGs in power distribution systems with the objectives of minimization of active and reactive power loss and enhanced voltage profile. Along with the meta-heuristic optimization algorithm, sensitivity techniques such as index vector, loss sensitivity factor, and voltage stability margin methods have been analysed. The outcomes are obtained using the aforementioned sensitivity-related methods on the IEEE 15, 33, 69, and 85-radial bus systems and compared with simultaneous PSO for efficacy.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89073009","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 : 2023-03-03DOI: 10.13052/dgaej2156-3306.3832
K. Suresh, I. Kumaraswamy, R. Arulmozhiyal
Multimodal single/dual stage conversion (BSDC) based on a new solid-state DC-AC transformer (SDAT) is proposed. The suggested conversion can perform variable or constant DC voltage operation. A variable DC voltage is controlled dynamically in response to changes in DC input side voltage, allowing the DC-DC conversion stage to always operate at its best. New DC-AC power conversion of 2 port two-way choppers (TBDC) and two-way rectifier/inverter conversion (BRIC) was planned for the implementation of the proposed SDAT. SDAT, consisting of a bi-directional step-down-step-up converter and a bi-directional step-up-step-down converter, has been used as a prototype model to check the suggestion system. Functional concepts of this BSDC converter with TBDC are designed and simulated on the MATLAB/simulink environment network. PWM and control methods have been applied for SDAT to accomplish a wide variety of voltage and power loss reduction in the proposed device. Test bench model hardware is designed and tested to validate the effectiveness and benefits of the proposed approach.
{"title":"Design and Analysis of Solid State DC-AC Transformer","authors":"K. Suresh, I. Kumaraswamy, R. Arulmozhiyal","doi":"10.13052/dgaej2156-3306.3832","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3832","url":null,"abstract":"Multimodal single/dual stage conversion (BSDC) based on a new solid-state DC-AC transformer (SDAT) is proposed. The suggested conversion can perform variable or constant DC voltage operation. A variable DC voltage is controlled dynamically in response to changes in DC input side voltage, allowing the DC-DC conversion stage to always operate at its best. New DC-AC power conversion of 2 port two-way choppers (TBDC) and two-way rectifier/inverter conversion (BRIC) was planned for the implementation of the proposed SDAT. SDAT, consisting of a bi-directional step-down-step-up converter and a bi-directional step-up-step-down converter, has been used as a prototype model to check the suggestion system. Functional concepts of this BSDC converter with TBDC are designed and simulated on the MATLAB/simulink environment network. PWM and control methods have been applied for SDAT to accomplish a wide variety of voltage and power loss reduction in the proposed device. Test bench model hardware is designed and tested to validate the effectiveness and benefits of the proposed approach.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84487291","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 : 2023-03-03DOI: 10.13052/dgaej2156-3306.3833
Srinivas Singirikonda, Y. Obulesu
In an electric vehicle (EV), the battery management system (BMS) is crucial for managing the health and safety of the battery. The accurate estimation of battery state of charge (SOC) offers critical information about the battery’s remaining capacity. The SOC of the battery mainly depends on its non-linear internal parameters, battery chemistry, ambient temperature, aging factor etc. So, accurate SOC estimation is still a significant challenge. Many researchers have developed several model-based methods that are more complex to develop. Another approach is a data-driven based SOC estimation algorithm, which is less complex but requires more data and it may be inaccurate. In this context, this paper presents a robust and accurate SOC estimation algorithm for a Lithium-ion battery using a deep learning feed-forward neural network (DLFFNN) approach. The proposed algorithm accurately characterizes the battery’s non-linear behavior. To develop a robust SOC estimation algorithm, data is collected at different temperatures with 5% error in data (4 mV-voltage, 110 mA-current, 5∘C temperature) is added to battery datasets. The obtained results demonstrated that the performance of the proposed DLFNN is robust and accurate on different drive cycles with 1.14% Root mean squared error (RMSE), 0.66% mean absolute error (MAE), and 6.65% maximum error (MAX).
{"title":"Lithium-Ion Battery State of Charge Estimation Using Deep Neural Network","authors":"Srinivas Singirikonda, Y. Obulesu","doi":"10.13052/dgaej2156-3306.3833","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3833","url":null,"abstract":"In an electric vehicle (EV), the battery management system (BMS) is crucial for managing the health and safety of the battery. The accurate estimation of battery state of charge (SOC) offers critical information about the battery’s remaining capacity. The SOC of the battery mainly depends on its non-linear internal parameters, battery chemistry, ambient temperature, aging factor etc. So, accurate SOC estimation is still a significant challenge. Many researchers have developed several model-based methods that are more complex to develop. Another approach is a data-driven based SOC estimation algorithm, which is less complex but requires more data and it may be inaccurate. In this context, this paper presents a robust and accurate SOC estimation algorithm for a Lithium-ion battery using a deep learning feed-forward neural network (DLFFNN) approach. The proposed algorithm accurately characterizes the battery’s non-linear behavior. To develop a robust SOC estimation algorithm, data is collected at different temperatures with 5% error in data (4 mV-voltage, 110 mA-current, 5∘C temperature) is added to battery datasets. The obtained results demonstrated that the performance of the proposed DLFNN is robust and accurate on different drive cycles with 1.14% Root mean squared error (RMSE), 0.66% mean absolute error (MAE), and 6.65% maximum error (MAX).","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80083309","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 : 2023-03-03DOI: 10.13052/dgaej2156-3306.38312
S. Saahithi, B. H. Kumar, K. J. Reddy, Ritesh Dash, V. Subburaj
A novel single input multioutput (SIMO) output DC-DC converter with circular capacitors is intended to function with a single independent source to create numerous transmissions to regulate the speed at the same switching intervals. A novel single input multi output (SIMO) output DC-DC converter employing circular capacitors is designed to work with a single independent source to create numerous transmissions. The proposed converter generates 7 outputs in total, with 4 outputs generated simultaneously for forward operation (speed transmission) using the preferred source (fuel cell/battery) and 3 other different outputs used for regenerative transmissions, with the battery being the preferred storage device. This converter can control the speed of an electric vehicle (EV) by using the SIMO is output voltage to regulate the vehicle is speed, allowing for higher accelerations and decelerations with minimal energy loss and degradation of the main battery pack. It can also be used to power electronic components such as LED lights, audio systems, and mobile charging etc. The energy recovered during regenerative braking is used to charge the battery via a buck/boost operation for varied speed transmission. In addition, simulation, modelling, and analysis are used to validate the proposed system. It is intended for a fixed voltage of 12 V and output voltages ranging from 12 to 48 V. The PSIM simulation tool is used to validate the system. The validation demonstrates the suggested converter is good evidence in both braking and regenerative braking operations.
{"title":"Four Speed Auto Transmission DC-DC Converter Control for E-Vehicle and Regenerative Braking Based on Simulation and Model Investigation","authors":"S. Saahithi, B. H. Kumar, K. J. Reddy, Ritesh Dash, V. Subburaj","doi":"10.13052/dgaej2156-3306.38312","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.38312","url":null,"abstract":"A novel single input multioutput (SIMO) output DC-DC converter with circular capacitors is intended to function with a single independent source to create numerous transmissions to regulate the speed at the same switching intervals. A novel single input multi output (SIMO) output DC-DC converter employing circular capacitors is designed to work with a single independent source to create numerous transmissions. The proposed converter generates 7 outputs in total, with 4 outputs generated simultaneously for forward operation (speed transmission) using the preferred source (fuel cell/battery) and 3 other different outputs used for regenerative transmissions, with the battery being the preferred storage device. This converter can control the speed of an electric vehicle (EV) by using the SIMO is output voltage to regulate the vehicle is speed, allowing for higher accelerations and decelerations with minimal energy loss and degradation of the main battery pack. It can also be used to power electronic components such as LED lights, audio systems, and mobile charging etc. The energy recovered during regenerative braking is used to charge the battery via a buck/boost operation for varied speed transmission. In addition, simulation, modelling, and analysis are used to validate the proposed system. It is intended for a fixed voltage of 12 V and output voltages ranging from 12 to 48 V. The PSIM simulation tool is used to validate the system. The validation demonstrates the suggested converter is good evidence in both braking and regenerative braking operations.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84019853","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 : 2023-03-03DOI: 10.13052/dgaej2156-3306.38310
R. Aravind, Sivaprasad Athikkal, Raviteja Meesala, K. J. Reddy, Ritesh Dash, V. Subburaj
Two input two output DC-DC converters with two switched inductor structure are widespread in DC micro grid and Electric Vehicle (EV) applications with merits of solid structure, lower cost and high-power density. However, owing to the low voltage levels of the non-conventional sources used in the above applications, the significance of step up type DC-DC converters is so high. In this paper, a step up converter that is expert to deliver two different voltages at the output side from two different input energy sources is proposed as a new topology. It mainly contains two inductors for improving the voltage conversion ratio. Thorough analysis of converter has been performed with support of necessary equations and circuits. The performance assessment of DC-DC converter is done with simulation and experimental platforms and required waveforms are presented. A comparative study of the proposed converter is also fulfilled to signify the better features of the converter.
{"title":"Dual Inductor Based Two Input Two Output DC-DC Converter and its Analysis for DC Microgrid Application","authors":"R. Aravind, Sivaprasad Athikkal, Raviteja Meesala, K. J. Reddy, Ritesh Dash, V. Subburaj","doi":"10.13052/dgaej2156-3306.38310","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.38310","url":null,"abstract":"Two input two output DC-DC converters with two switched inductor structure are widespread in DC micro grid and Electric Vehicle (EV) applications with merits of solid structure, lower cost and high-power density. However, owing to the low voltage levels of the non-conventional sources used in the above applications, the significance of step up type DC-DC converters is so high. In this paper, a step up converter that is expert to deliver two different voltages at the output side from two different input energy sources is proposed as a new topology. It mainly contains two inductors for improving the voltage conversion ratio. Thorough analysis of converter has been performed with support of necessary equations and circuits. The performance assessment of DC-DC converter is done with simulation and experimental platforms and required waveforms are presented. A comparative study of the proposed converter is also fulfilled to signify the better features of the converter.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85046120","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 : 2023-03-03DOI: 10.13052/dgaej2156-3306.3831
R. Hiremath, T. Moger
The grid-connected doubly fed induction generator (DFIG) driven wind turbine (WT) system encounters voltage fluctuations due to severe grid faults. The rise in DC-link voltage imbalances the system under voltage sag condition. The system’s protection should ensure that the WT generator meets the grid requirements through a low voltage ride through (LVRT) technique. This paper proposed the modified 2nd order sliding mode (MSOSM) control with gain added super twisting algorithm (GAST) for LVRT enhancement under voltage sag. This controller adds the low positive gains to the switching functions of the super twisting (ST) algorithm. As a result, it maintains the proper variation margins and constant DC-link voltage of the WT-DFIG system under grid fault. The MSOSM controller suppresses the chattering effect, achieves better zero convergence, and eliminates the coordinate transformations. Moreover, the performance of the proposed controller is compared with existing controllers in the literature with the help of MATLAB/SIMULINK. The hardware-in-loop (HIL) validates these simulation results performed on the OPAL-RT setup. Based on the studies, it is found that the proposed controller enhances the performance of the WT-DFIG system under transient conditions.
{"title":"Improving the DC-Link Voltage of DFIG Driven Wind System Using Modified Sliding Mode Control","authors":"R. Hiremath, T. Moger","doi":"10.13052/dgaej2156-3306.3831","DOIUrl":"https://doi.org/10.13052/dgaej2156-3306.3831","url":null,"abstract":"The grid-connected doubly fed induction generator (DFIG) driven wind turbine (WT) system encounters voltage fluctuations due to severe grid faults. The rise in DC-link voltage imbalances the system under voltage sag condition. The system’s protection should ensure that the WT generator meets the grid requirements through a low voltage ride through (LVRT) technique. This paper proposed the modified 2nd order sliding mode (MSOSM) control with gain added super twisting algorithm (GAST) for LVRT enhancement under voltage sag. This controller adds the low positive gains to the switching functions of the super twisting (ST) algorithm. As a result, it maintains the proper variation margins and constant DC-link voltage of the WT-DFIG system under grid fault. The MSOSM controller suppresses the chattering effect, achieves better zero convergence, and eliminates the coordinate transformations. Moreover, the performance of the proposed controller is compared with existing controllers in the literature with the help of MATLAB/SIMULINK. The hardware-in-loop (HIL) validates these simulation results performed on the OPAL-RT setup. Based on the studies, it is found that the proposed controller enhances the performance of the WT-DFIG system under transient conditions.","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"72 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89421983","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：