Pub Date : 2021-03-05DOI: 10.1109/ICEPE50861.2021.9404526
Nashida C, R. S, S. R.
The increase in electric power demand pushes the modern power system for more interconnected networks. It leads to a lack of inertia and creates more critical disturbances in the power system. It may not be adequately damped out and results in cascade tripping. Immediate detection of low-frequency oscillatory modes and their parameters will help the power system operator to act on a particular event without consuming much time. This paper proposes a dynamic method for the oscillatory mode parameter estimation in a power system using an Artificial Neural Network (ANN). An ANN model is created to analyze the power oscillation disturbance within the system, and it is trained using the Hilbert transform method to estimate the instantaneous parameters. Once the ANN model is trained for different power disturbance situations, it can be used for any events associated with the system. Simulation results are verified using two area Kundur system at different disturbance conditions.
{"title":"Prediction of Electromechanical Oscillatory Parameters in Power Systems Using ANN","authors":"Nashida C, R. S, S. R.","doi":"10.1109/ICEPE50861.2021.9404526","DOIUrl":"https://doi.org/10.1109/ICEPE50861.2021.9404526","url":null,"abstract":"The increase in electric power demand pushes the modern power system for more interconnected networks. It leads to a lack of inertia and creates more critical disturbances in the power system. It may not be adequately damped out and results in cascade tripping. Immediate detection of low-frequency oscillatory modes and their parameters will help the power system operator to act on a particular event without consuming much time. This paper proposes a dynamic method for the oscillatory mode parameter estimation in a power system using an Artificial Neural Network (ANN). An ANN model is created to analyze the power oscillation disturbance within the system, and it is trained using the Hilbert transform method to estimate the instantaneous parameters. Once the ANN model is trained for different power disturbance situations, it can be used for any events associated with the system. Simulation results are verified using two area Kundur system at different disturbance conditions.","PeriodicalId":250203,"journal":{"name":"2020 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124274044","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 : 2021-03-05DOI: 10.1109/ICEPE50861.2021.9404396
Nutan Saha, S. Panda, D. Sahoo
In this work metaheuristic technique such as modified Hybrid Whale Optimization Algorithm (mWOA) is used for control of speed along with ripple reduction in output torque of 75 KW, 4-phase 8/6 Switched Reluctance Motor (SRM) drive. The objective is to develop a controller for combined goal of speed control and ripple reduction in output torque of SRM. Various performance factors such as gain of proportional controller & integral controller of speed controller as well as of current controller commutation angle values are considered for performance assessment of SRM. A comparison is made of the performance of SRM with implementation of modified Whale Optimization Algorithm (mWOA) & Whale Optimization Algorithm (WOA). It is seen that coefficient of torque ripple, ISE of current and objective function is reduced by mWOA algorithm as compared to WOA.
{"title":"Modified Whale Optimisation Technique for Combined Objective of Torque Ripple Minimization & Speed Control of SRM Drive","authors":"Nutan Saha, S. Panda, D. Sahoo","doi":"10.1109/ICEPE50861.2021.9404396","DOIUrl":"https://doi.org/10.1109/ICEPE50861.2021.9404396","url":null,"abstract":"In this work metaheuristic technique such as modified Hybrid Whale Optimization Algorithm (mWOA) is used for control of speed along with ripple reduction in output torque of 75 KW, 4-phase 8/6 Switched Reluctance Motor (SRM) drive. The objective is to develop a controller for combined goal of speed control and ripple reduction in output torque of SRM. Various performance factors such as gain of proportional controller & integral controller of speed controller as well as of current controller commutation angle values are considered for performance assessment of SRM. A comparison is made of the performance of SRM with implementation of modified Whale Optimization Algorithm (mWOA) & Whale Optimization Algorithm (WOA). It is seen that coefficient of torque ripple, ISE of current and objective function is reduced by mWOA algorithm as compared to WOA.","PeriodicalId":250203,"journal":{"name":"2020 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117272473","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 : 2021-03-05DOI: 10.1109/ICEPE50861.2021.9404398
S. Deb, A. Goswami, Rahul Lamichane Chetri, Rajesh Roy
The demand of plug-in electric vehicle (PEV) raises simultaneous pressure on both transport and electrical sectors in recent time. The capability of large numbers of PEVs in grid-to-vehicle (G2V) at a time makes extra electrical load demand whereas; vehicle-to-grid (V2G) mode makes them popular as a power source. The congestion scenario arises as a result of uncoordinated G2V mode of large number of PEVs. The charging coordination of PEVs in the industrial node integrated with solar powered charging-cum-parking lot (SPCPL) has been considered in this work for congestion management in distribution system. The gradient boosting method (GBM) has been utilized at the beginning to forecast the state-of-charge (SOC) of PEVs. The tested network for this work is IEEE 38 bus radial distribution system.
{"title":"Impact of Plug-in Electric Vehicle Integration in Distribution System Congestion Management","authors":"S. Deb, A. Goswami, Rahul Lamichane Chetri, Rajesh Roy","doi":"10.1109/ICEPE50861.2021.9404398","DOIUrl":"https://doi.org/10.1109/ICEPE50861.2021.9404398","url":null,"abstract":"The demand of plug-in electric vehicle (PEV) raises simultaneous pressure on both transport and electrical sectors in recent time. The capability of large numbers of PEVs in grid-to-vehicle (G2V) at a time makes extra electrical load demand whereas; vehicle-to-grid (V2G) mode makes them popular as a power source. The congestion scenario arises as a result of uncoordinated G2V mode of large number of PEVs. The charging coordination of PEVs in the industrial node integrated with solar powered charging-cum-parking lot (SPCPL) has been considered in this work for congestion management in distribution system. The gradient boosting method (GBM) has been utilized at the beginning to forecast the state-of-charge (SOC) of PEVs. The tested network for this work is IEEE 38 bus radial distribution system.","PeriodicalId":250203,"journal":{"name":"2020 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126779284","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 : 2021-03-05DOI: 10.1109/ICEPE50861.2021.9404536
Kishore Bingi, B. Prusty, Aaditya Kumra, Anurag Chawla
This paper focuses on developing a torque and stator temperature prediction model for permanent magnet synchronous motors using neural networks. The model can predict torque and four other temperature parameters at the permanent magnet surface, stator's yoke, tooth, and winding. The motor's torque and temperatures are predicted without installing any additional sensors into it. Using the training dataset with Levenberg-Marquardt optimization and Bayesian regularization algorithms, the predicted model has the best performance with the least mean square error and the best $R^{2}$ values. Also, the prediction of testing data shows that the estimated model follows closely with actual values. This is true for all the five output parameters.
{"title":"Torque and Temperature Prediction for Permanent Magnet Synchronous Motor Using Neural Networks","authors":"Kishore Bingi, B. Prusty, Aaditya Kumra, Anurag Chawla","doi":"10.1109/ICEPE50861.2021.9404536","DOIUrl":"https://doi.org/10.1109/ICEPE50861.2021.9404536","url":null,"abstract":"This paper focuses on developing a torque and stator temperature prediction model for permanent magnet synchronous motors using neural networks. The model can predict torque and four other temperature parameters at the permanent magnet surface, stator's yoke, tooth, and winding. The motor's torque and temperatures are predicted without installing any additional sensors into it. Using the training dataset with Levenberg-Marquardt optimization and Bayesian regularization algorithms, the predicted model has the best performance with the least mean square error and the best $R^{2}$ values. Also, the prediction of testing data shows that the estimated model follows closely with actual values. This is true for all the five output parameters.","PeriodicalId":250203,"journal":{"name":"2020 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130320779","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 : 2021-03-05DOI: 10.1109/ICEPE50861.2021.9404492
Syed Bilal Qaiser Naqvi, Bhim Singh
A grid-interactive photovoltaic array (PVA) system with multiple operating modes, is demonstrated in this work. The system prioritizes interruption free power supply to the local loads. The combination of single phase and three phase local loads, is considered. In line with the modern trend, the nonlinear loads are taken. At healthy grid conditions, the remaining power, after feeding the local loads, is dispatched to the grid. At PVA power shortage, the grid meets the deficit power. The sensitive loads are unaffected by the grid abnormalities, due to the swift switchover to an islanded mode. The inclusion of battery storage provides the dual benefits of optimum PVA power harvesting, and backup supply to the loads. The on-line grid resynchronization is achieved without disruption to the loads. The PVA interaction is controlled by a boost converter. The control structure ensures swift action at load changes and PVA power fluctuations. Moreover, the improved grid power quality, and suppressed neutral currents, are managed by the system.
{"title":"Enhanced Power Quality Multi-Mode Grid Interactive PV-Battery System for Uninterrupted Power","authors":"Syed Bilal Qaiser Naqvi, Bhim Singh","doi":"10.1109/ICEPE50861.2021.9404492","DOIUrl":"https://doi.org/10.1109/ICEPE50861.2021.9404492","url":null,"abstract":"A grid-interactive photovoltaic array (PVA) system with multiple operating modes, is demonstrated in this work. The system prioritizes interruption free power supply to the local loads. The combination of single phase and three phase local loads, is considered. In line with the modern trend, the nonlinear loads are taken. At healthy grid conditions, the remaining power, after feeding the local loads, is dispatched to the grid. At PVA power shortage, the grid meets the deficit power. The sensitive loads are unaffected by the grid abnormalities, due to the swift switchover to an islanded mode. The inclusion of battery storage provides the dual benefits of optimum PVA power harvesting, and backup supply to the loads. The on-line grid resynchronization is achieved without disruption to the loads. The PVA interaction is controlled by a boost converter. The control structure ensures swift action at load changes and PVA power fluctuations. Moreover, the improved grid power quality, and suppressed neutral currents, are managed by the system.","PeriodicalId":250203,"journal":{"name":"2020 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126883668","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 : 2021-03-05DOI: 10.1109/ICEPE50861.2021.9404412
S KavyasreeRaj, S. K. V.
In this paper, an optimal state feedback controller is designed for a nonaffine nonlinear system. The nonaffine system is converted into affine system using mean value theorem, since the analysis of affine nonlinear system is easy compared to nonaffine systems. Feedback linearization is used for linearizing the affine system. Then a gradient descent algorithm-based optimization approach is designed for feedback linearized system for optimal performance. The performance of the proposed method is presented by conducting simulation study on magnetic levitation system. A significant reduction in the minimum value of cost function is obtained using proposed method compared with the conventional LQR technique and PSO method.
{"title":"Gradient based Optimal State Feedback Control design for Feedback Linearizable Nonlinear Nonaffine system","authors":"S KavyasreeRaj, S. K. V.","doi":"10.1109/ICEPE50861.2021.9404412","DOIUrl":"https://doi.org/10.1109/ICEPE50861.2021.9404412","url":null,"abstract":"In this paper, an optimal state feedback controller is designed for a nonaffine nonlinear system. The nonaffine system is converted into affine system using mean value theorem, since the analysis of affine nonlinear system is easy compared to nonaffine systems. Feedback linearization is used for linearizing the affine system. Then a gradient descent algorithm-based optimization approach is designed for feedback linearized system for optimal performance. The performance of the proposed method is presented by conducting simulation study on magnetic levitation system. A significant reduction in the minimum value of cost function is obtained using proposed method compared with the conventional LQR technique and PSO method.","PeriodicalId":250203,"journal":{"name":"2020 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121676077","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 : 2021-03-05DOI: 10.1109/ICEPE50861.2021.9404442
Ikhlaq Hussain, R. Agarwal, Bhim Singh
The dual-mode single-stage PV-DSTATCOM (Photovoltaic-Distributed Static Compensator) system tied to the AC grid is presented using a DLMS (Delayed Least Mean Square) based adaptive control technique. The proposed multifunctional PV-DSTATCOM system works under two main modes of operation: 1) DSTATCOM and 2) PV-DSTATCOM mode. In mode-1, when there is no PV power generation, it acts as a DSTATCOM for mitigating various power quality issues at Point of Common Coupling due to high Total Harmonic Distortion of load currents. In mode-2, it acts as a PV-DSTATCOM and transfers power to the AC grid and loads. For implementing the dual modes of operation, an intelligent DLMS based adaptive control algorithm is implemented on a developed laboratory prototype to carry out several experimental tests under varying conditions.
{"title":"Delayed LMS Based Adaptive Control of PV-DSTATCOM System","authors":"Ikhlaq Hussain, R. Agarwal, Bhim Singh","doi":"10.1109/ICEPE50861.2021.9404442","DOIUrl":"https://doi.org/10.1109/ICEPE50861.2021.9404442","url":null,"abstract":"The dual-mode single-stage PV-DSTATCOM (Photovoltaic-Distributed Static Compensator) system tied to the AC grid is presented using a DLMS (Delayed Least Mean Square) based adaptive control technique. The proposed multifunctional PV-DSTATCOM system works under two main modes of operation: 1) DSTATCOM and 2) PV-DSTATCOM mode. In mode-1, when there is no PV power generation, it acts as a DSTATCOM for mitigating various power quality issues at Point of Common Coupling due to high Total Harmonic Distortion of load currents. In mode-2, it acts as a PV-DSTATCOM and transfers power to the AC grid and loads. For implementing the dual modes of operation, an intelligent DLMS based adaptive control algorithm is implemented on a developed laboratory prototype to carry out several experimental tests under varying conditions.","PeriodicalId":250203,"journal":{"name":"2020 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114829477","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 : 2021-03-05DOI: 10.1109/ICEPE50861.2021.9404476
Kristiyan Milev, F. Alshammari, V. Yaramasu, M. Durán, Kishore Yadlapati
A power conversion system based on a diode rectifier, three-level (3L) boost converter and 3L neutral-point clamped (NPC) inverter is a cost effective and reliable solution in contrast to the back-to-back connected NPC converter for the medium-voltage permanent magnet synchronous generator-based wind turbines. This paper investigates a novel predictive control scheme to operate the 3L boost converter and an NPC inverter with fixed switching frequency, high-speed tracking, and accurate locking in steady state. A dual decoupled control loop consisting of deadbeat current control and modulated model predictive current control has been developed for the 3L boost converter and NPC inverter, respectively. The controller for three-level boost converter performs dual functions such as neutral-point voltage control and inductor current control. The controller of NPC inverter regulates the grid currents in stationary frame for the simultaneous control of active and reactive powers.
{"title":"Predictive Control with Fixed Switching Frequency for Three-Level Boost and NPC Converters Interfaced PMSG Wind Turbine","authors":"Kristiyan Milev, F. Alshammari, V. Yaramasu, M. Durán, Kishore Yadlapati","doi":"10.1109/ICEPE50861.2021.9404476","DOIUrl":"https://doi.org/10.1109/ICEPE50861.2021.9404476","url":null,"abstract":"A power conversion system based on a diode rectifier, three-level (3L) boost converter and 3L neutral-point clamped (NPC) inverter is a cost effective and reliable solution in contrast to the back-to-back connected NPC converter for the medium-voltage permanent magnet synchronous generator-based wind turbines. This paper investigates a novel predictive control scheme to operate the 3L boost converter and an NPC inverter with fixed switching frequency, high-speed tracking, and accurate locking in steady state. A dual decoupled control loop consisting of deadbeat current control and modulated model predictive current control has been developed for the 3L boost converter and NPC inverter, respectively. The controller for three-level boost converter performs dual functions such as neutral-point voltage control and inductor current control. The controller of NPC inverter regulates the grid currents in stationary frame for the simultaneous control of active and reactive powers.","PeriodicalId":250203,"journal":{"name":"2020 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128031363","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 : 2021-03-05DOI: 10.1109/ICEPE50861.2021.9404454
P. Behera, Anurag Satpathy, M. Pattnaik
To ensure proper power flow while maintaining stability during grid disturbances and power quality enhancements the utility interface voltage source inverters (VSI) need vital current regulation and synchronization. For this kind of applications, the non-linear current control of VSI using hysteresis current regulation offers distinct advantages in contrast with linear current regulation scheme. In this paper, Hysteresis Current Control (HCC) strategy has been used to decide the switching pulse of the single-phase VSI with a fixed single hysteresis band. An instantaneous inductor current feedback loop along with the HCC is digitally incorporated in dSPACE RTI1103 controller to generate the switching pulses for the VSI. Both simulation and experimental results are provided to verify the feasibility and performance of this control technique. An LC filter is appended at $1-phi$ inverter output terminals to ensure low output current ripple and lower Total Harmonic Distortion (THD).
{"title":"Design and Implementation of a Single-Band Hysteresis Current Controlled H-Bridge Inverter","authors":"P. Behera, Anurag Satpathy, M. Pattnaik","doi":"10.1109/ICEPE50861.2021.9404454","DOIUrl":"https://doi.org/10.1109/ICEPE50861.2021.9404454","url":null,"abstract":"To ensure proper power flow while maintaining stability during grid disturbances and power quality enhancements the utility interface voltage source inverters (VSI) need vital current regulation and synchronization. For this kind of applications, the non-linear current control of VSI using hysteresis current regulation offers distinct advantages in contrast with linear current regulation scheme. In this paper, Hysteresis Current Control (HCC) strategy has been used to decide the switching pulse of the single-phase VSI with a fixed single hysteresis band. An instantaneous inductor current feedback loop along with the HCC is digitally incorporated in dSPACE RTI1103 controller to generate the switching pulses for the VSI. Both simulation and experimental results are provided to verify the feasibility and performance of this control technique. An LC filter is appended at $1-phi$ inverter output terminals to ensure low output current ripple and lower Total Harmonic Distortion (THD).","PeriodicalId":250203,"journal":{"name":"2020 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies","volume":"376 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115970741","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 : 2021-03-05DOI: 10.1109/ICEPE50861.2021.9404430
S. R. Paital, P. Ray, A. Mohanty, G. Panda
This article proposes an adaptive neuro-fuzzy sliding mode control based power system stabilizer (ANFSMC-PSS) with an aim to minimize low frequency oscillations (LFOs) arising due to disturbances in the power system. The proposed ANFSMC-PSS is a combination of sliding mode control (SMC) and neuro fuzzy system (NFS) to enhance stability of power system. Here, stability is assured through Lyapunov criterion. The proposed ASMT2NF-PSS considers both local signal (speed deviation) and remote signal (accelerating power) provided by PMUs as input signals and its efficacy is investigated in both single machine infinite bus (SMIB) and multimachine power system (MMPS) under various disturbance conditions. The simulation results clearly shows that the proposed ANFSMC-PSS gives superior oscillation damping performance as compared to that of fuzzy sliding mode control based PSS (FSMC-PSS), sliding mode control based PSS (FSMC-PSS) and conventional lead-lag based PSS (CPSS) under different disturbance conditions.
{"title":"Neuro-Fuzzy Sliding Mode Control based Wide Area Power System Stabilizer For Transient Stability Improvement","authors":"S. R. Paital, P. Ray, A. Mohanty, G. Panda","doi":"10.1109/ICEPE50861.2021.9404430","DOIUrl":"https://doi.org/10.1109/ICEPE50861.2021.9404430","url":null,"abstract":"This article proposes an adaptive neuro-fuzzy sliding mode control based power system stabilizer (ANFSMC-PSS) with an aim to minimize low frequency oscillations (LFOs) arising due to disturbances in the power system. The proposed ANFSMC-PSS is a combination of sliding mode control (SMC) and neuro fuzzy system (NFS) to enhance stability of power system. Here, stability is assured through Lyapunov criterion. The proposed ASMT2NF-PSS considers both local signal (speed deviation) and remote signal (accelerating power) provided by PMUs as input signals and its efficacy is investigated in both single machine infinite bus (SMIB) and multimachine power system (MMPS) under various disturbance conditions. The simulation results clearly shows that the proposed ANFSMC-PSS gives superior oscillation damping performance as compared to that of fuzzy sliding mode control based PSS (FSMC-PSS), sliding mode control based PSS (FSMC-PSS) and conventional lead-lag based PSS (CPSS) under different disturbance conditions.","PeriodicalId":250203,"journal":{"name":"2020 3rd International Conference on Energy, Power and Environment: Towards Clean Energy Technologies","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129993788","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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