Pub Date : 2022-07-17DOI: 10.1109/PESGM48719.2022.9916985
C. A. C. Cambambi, L. Canha, Feksa L. Ramos, O. Adeyanju
This paper presents a model for operating commercial virtual power plant (VPP) composed of Distributed Energy Resources (DER) such as wind, photovoltaic generation, and energy storage system in the distribution system. The VPP has the objective to maximize profit in the daily energy market with the intention to reduce the overall CO2 emissions of distribution systems. The developed operational model relies on the capacity and energy conditions of the battery storage system and energy prices of the grid. A Genetic Algorithm (GA) is fitted to solve the operation interaction of the VPP and distribution system. The simulation results showed that the profitability of the VPP in the distribution system increased up to 2330 over the 24-hour operation horizon.
{"title":"Optimization of the virtual power plants through evolutionary algorithms","authors":"C. A. C. Cambambi, L. Canha, Feksa L. Ramos, O. Adeyanju","doi":"10.1109/PESGM48719.2022.9916985","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9916985","url":null,"abstract":"This paper presents a model for operating commercial virtual power plant (VPP) composed of Distributed Energy Resources (DER) such as wind, photovoltaic generation, and energy storage system in the distribution system. The VPP has the objective to maximize profit in the daily energy market with the intention to reduce the overall CO2 emissions of distribution systems. The developed operational model relies on the capacity and energy conditions of the battery storage system and energy prices of the grid. A Genetic Algorithm (GA) is fitted to solve the operation interaction of the VPP and distribution system. The simulation results showed that the profitability of the VPP in the distribution system increased up to 2330 over the 24-hour operation horizon.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114523524","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9916804
S. García, A. Ruiz, J. Mora-Flórez
This paper presents a convex optimization model for the power management of an active distribution network operating in islanded mode when there is a lack of generation. The proposed model minimizes the total unattended load considering the generation capacity and bounds of voltage and frequency. In this proposal, the distributed generation units consider inverse droops, commonly used for the primary control in grids with a high $r$ / $x$ ratio. The proposed model guarantees global optimum, uniqueness of the solution, and convergence of the algorithm.
{"title":"Optimal Operation of Active Distribution Networks Considering Deficit of Generation","authors":"S. García, A. Ruiz, J. Mora-Flórez","doi":"10.1109/PESGM48719.2022.9916804","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9916804","url":null,"abstract":"This paper presents a convex optimization model for the power management of an active distribution network operating in islanded mode when there is a lack of generation. The proposed model minimizes the total unattended load considering the generation capacity and bounds of voltage and frequency. In this proposal, the distributed generation units consider inverse droops, commonly used for the primary control in grids with a high $r$ / $x$ ratio. The proposed model guarantees global optimum, uniqueness of the solution, and convergence of the algorithm.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116168521","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9916898
E. Rebello, Marianne Rodgers, David Stanford, M. Fischer, Mouhcine Akki
Modern wind turbines are capable of providing more than low-cost energy - they are able to provide a wide array of ancillary services that can contribute to the stability of a changing grid. This work evaluates the performance of Enercon's E-82 wind turbines in providing two ancillary services - power-frequency response (frequency-watt response) and automatic generation control (AGC). Empirical data is gathered at the 50.6 MW Nuttby Mountain wind farm in Nova Scotia, Canada that consists of twenty two IEC Type 4 turbines. AGC data is from the entire farm responding as a single unit while power-frequency data is from a single wind turbine. We document and analyse the wind farm's ability to curtail power output in response to grid frequency increases at varying power levels and also present forty five minutes of AGC data. Empirical data such as these are useful to system operators in determining how to best utilise their existing wind power fleets. We report good performance with both ancillary services. Mean error for the power-frequency data is approximately 2% of rated turbine power. Performance scores for AGC are 97% via the California ISO method and 87% via the Midcontinent ISO method.
{"title":"More than power from wind: Emperical data from a wind farm providing power-frequency response and automatic generation control","authors":"E. Rebello, Marianne Rodgers, David Stanford, M. Fischer, Mouhcine Akki","doi":"10.1109/PESGM48719.2022.9916898","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9916898","url":null,"abstract":"Modern wind turbines are capable of providing more than low-cost energy - they are able to provide a wide array of ancillary services that can contribute to the stability of a changing grid. This work evaluates the performance of Enercon's E-82 wind turbines in providing two ancillary services - power-frequency response (frequency-watt response) and automatic generation control (AGC). Empirical data is gathered at the 50.6 MW Nuttby Mountain wind farm in Nova Scotia, Canada that consists of twenty two IEC Type 4 turbines. AGC data is from the entire farm responding as a single unit while power-frequency data is from a single wind turbine. We document and analyse the wind farm's ability to curtail power output in response to grid frequency increases at varying power levels and also present forty five minutes of AGC data. Empirical data such as these are useful to system operators in determining how to best utilise their existing wind power fleets. We report good performance with both ancillary services. Mean error for the power-frequency data is approximately 2% of rated turbine power. Performance scores for AGC are 97% via the California ISO method and 87% via the Midcontinent ISO method.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121625924","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9917239
Stefano Giacomuzzi, Giovanni de Carne, S. Pugliese, G. Buja, M. Liserre, A. Kazerooni
The Smart Transformer (ST) is a power electronicsbased transformer, which operates as grid-forming converter in the low voltage-fed grid. It synthesizes the voltage waveform with magnitude, phase and frequency independently from the main power system. If a meshed operation of the ST with a conventional transformer is required, to improve the power flow control and to control the voltage profile, the voltage waveforms between the two grids have to be synchronized. The switching under different voltage magnitude, phase or frequency, can lead to a large power in-rush. This work proposes a synchronization strategy that enables a seamless transition of the ST to parallel operations with conventional transformers. Differently from classical communication-based methods, this work addresses a more realistic implementation case with limited communication infrastructure. The ST relies only on local measurements and on its advanced control capability to determine the effective switch to parallel operations. The performance of the proposed strategy has been proved analytically and through simulations in a PLECS/Matlab environment, and validated experimentally by means of Power-Hardware-In-Loop (PHIL) evaluation.
{"title":"Synchronization of Low Voltage Grids Fed by Smart and Conventional Transformers","authors":"Stefano Giacomuzzi, Giovanni de Carne, S. Pugliese, G. Buja, M. Liserre, A. Kazerooni","doi":"10.1109/PESGM48719.2022.9917239","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9917239","url":null,"abstract":"The Smart Transformer (ST) is a power electronicsbased transformer, which operates as grid-forming converter in the low voltage-fed grid. It synthesizes the voltage waveform with magnitude, phase and frequency independently from the main power system. If a meshed operation of the ST with a conventional transformer is required, to improve the power flow control and to control the voltage profile, the voltage waveforms between the two grids have to be synchronized. The switching under different voltage magnitude, phase or frequency, can lead to a large power in-rush. This work proposes a synchronization strategy that enables a seamless transition of the ST to parallel operations with conventional transformers. Differently from classical communication-based methods, this work addresses a more realistic implementation case with limited communication infrastructure. The ST relies only on local measurements and on its advanced control capability to determine the effective switch to parallel operations. The performance of the proposed strategy has been proved analytically and through simulations in a PLECS/Matlab environment, and validated experimentally by means of Power-Hardware-In-Loop (PHIL) evaluation.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114694216","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9917124
K. Utkarsh, F. Ding
This paper presents a distributed peer-to-peer market control strategy to manage and to enable resource sharing of behind-the-meter distributed energy resources in a residential community. In the proposed strategy, each consumer or prosumer determines the flexibility of their point of connection to the power network such that the obtained flexibility is network-feasible. Based on the feasible flexibility, the consumers and the prosumers trade power among each other at each time instance to fulfil their preferred load requirements while maximizing their payoffs and helping to regulate node voltages inside the community. Because the problem to be solved is non-convex, a distributed particle swarm optimization algorithm is used to coordinate the consumers/prosumers in a fully autonomous manner without any centralized or hierarchical coordination. Numerical simulations performed on a community of 48 homes demonstrate the efficacy of the proposed approach.
{"title":"A Peer-to-Peer Market-Based Control Strategy for a Smart Residential Community with Behind-the-Meter Distributed Energy Resources","authors":"K. Utkarsh, F. Ding","doi":"10.1109/PESGM48719.2022.9917124","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9917124","url":null,"abstract":"This paper presents a distributed peer-to-peer market control strategy to manage and to enable resource sharing of behind-the-meter distributed energy resources in a residential community. In the proposed strategy, each consumer or prosumer determines the flexibility of their point of connection to the power network such that the obtained flexibility is network-feasible. Based on the feasible flexibility, the consumers and the prosumers trade power among each other at each time instance to fulfil their preferred load requirements while maximizing their payoffs and helping to regulate node voltages inside the community. Because the problem to be solved is non-convex, a distributed particle swarm optimization algorithm is used to coordinate the consumers/prosumers in a fully autonomous manner without any centralized or hierarchical coordination. Numerical simulations performed on a community of 48 homes demonstrate the efficacy of the proposed approach.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124418249","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9917151
Zhebin Chen, Chao Ren, Yan Xu
In modern power systems, power system dynamic security assessment is a critical task against the risk of blackout. This paper aims to develop reliable recognition models for system real-time dynamic security assessment, where ensemble learning models consisting of extreme learning machine, stochastic configuration networks and random vector functional link have been constructed. The principle for decision making is carried out based on the optimized tradeoff between credibility and accuracy. Moreover, the AdaBoost.RA strategy is afterwards introduced into the modelling process, which allows these critical (instances to be assigned with larger weights and verifies that this proposed methodology could provide more convincing models. This results in a more reliable recognition system for dynamic security assessment.
{"title":"An Improved AdaBoost-based Ensemble Learning Method for Data-Driven Dynamic Security Assessment of Power Systems","authors":"Zhebin Chen, Chao Ren, Yan Xu","doi":"10.1109/PESGM48719.2022.9917151","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9917151","url":null,"abstract":"In modern power systems, power system dynamic security assessment is a critical task against the risk of blackout. This paper aims to develop reliable recognition models for system real-time dynamic security assessment, where ensemble learning models consisting of extreme learning machine, stochastic configuration networks and random vector functional link have been constructed. The principle for decision making is carried out based on the optimized tradeoff between credibility and accuracy. Moreover, the AdaBoost.RA strategy is afterwards introduced into the modelling process, which allows these critical (instances to be assigned with larger weights and verifies that this proposed methodology could provide more convincing models. This results in a more reliable recognition system for dynamic security assessment.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124517428","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9917033
Priyanka Shinde, Nitish Bharambe, M. Amelin
The increasing variable renewable energy sources in the power system have led to rise in the trading volumes in the electricity markets. In this paper, we extend an existing open source agent-based model for simulating the behavior and interactions of the renewable, consumer, thermal, and market operator agents in the continuous intraday (CID) electricity market by introducing the energy storage agents. Furthermore, the limitation of the earlier model to account for the CID trade of a single delivery product is relaxed by extending the model to consider the simultaneous trading of all the possible delivery products in a day. A realistic trading behavior is enabled by an user-defined parameter for the thermal and storage agents to choose the switching point in the trading timeline when the strategy of the trading agent navigates from increasing their profits by trading in the CID market to avoiding any imbalances by considering their physical constraints. Comparative case studies are performed to demonstrate the evolution of the trading behavior of the agents throughout the trading horizons for multiple delivery products with different switching instances.
{"title":"Agent-Based Model to Simulate Multiple Delivery Products in Continuous Intraday Electricity Market","authors":"Priyanka Shinde, Nitish Bharambe, M. Amelin","doi":"10.1109/PESGM48719.2022.9917033","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9917033","url":null,"abstract":"The increasing variable renewable energy sources in the power system have led to rise in the trading volumes in the electricity markets. In this paper, we extend an existing open source agent-based model for simulating the behavior and interactions of the renewable, consumer, thermal, and market operator agents in the continuous intraday (CID) electricity market by introducing the energy storage agents. Furthermore, the limitation of the earlier model to account for the CID trade of a single delivery product is relaxed by extending the model to consider the simultaneous trading of all the possible delivery products in a day. A realistic trading behavior is enabled by an user-defined parameter for the thermal and storage agents to choose the switching point in the trading timeline when the strategy of the trading agent navigates from increasing their profits by trading in the CID market to avoiding any imbalances by considering their physical constraints. Comparative case studies are performed to demonstrate the evolution of the trading behavior of the agents throughout the trading horizons for multiple delivery products with different switching instances.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126255782","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9916736
Yubo Zhang, Songhao Yang, Qianrong Meng, Z. Hao
With the increase of wind power penetration and the participation of wind farm in frequency regulation, it is necessary to construct an accurate and efficient frequency response model of the wind farm for coping with the frequency related issues. This paper proposes a reduced-order frequency response model for doubly fed induction generator (DFIG)-based wind farms that participate in the system frequency regulation. Firstly, to avoid measurement error of the wind speed in open-loop control mode, a frequency response model of the DFIG based on closed-loop feedback control mode is constructed by linearization method, which involves the dynamic properties of the rotating part and the control unit of the DFIG. Then, based on the single DFIG model, the reduced-order frequency response model of the wind farm is derived by the balanced truncation (BT) algorithm. The reduced-order model is competent for the scenarios where the DFIGs operate in various states in the wind farm, as well as has a low computational burden. The effectiveness of the reduced-order frequency response model of the wind farm is verified through comparisons with the simulation result.
{"title":"Reduced-order Frequency Response Model for DFIG-based Wind Farm With Power Support","authors":"Yubo Zhang, Songhao Yang, Qianrong Meng, Z. Hao","doi":"10.1109/PESGM48719.2022.9916736","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9916736","url":null,"abstract":"With the increase of wind power penetration and the participation of wind farm in frequency regulation, it is necessary to construct an accurate and efficient frequency response model of the wind farm for coping with the frequency related issues. This paper proposes a reduced-order frequency response model for doubly fed induction generator (DFIG)-based wind farms that participate in the system frequency regulation. Firstly, to avoid measurement error of the wind speed in open-loop control mode, a frequency response model of the DFIG based on closed-loop feedback control mode is constructed by linearization method, which involves the dynamic properties of the rotating part and the control unit of the DFIG. Then, based on the single DFIG model, the reduced-order frequency response model of the wind farm is derived by the balanced truncation (BT) algorithm. The reduced-order model is competent for the scenarios where the DFIGs operate in various states in the wind farm, as well as has a low computational burden. The effectiveness of the reduced-order frequency response model of the wind farm is verified through comparisons with the simulation result.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132423983","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9916984
N. Kayedpour, Arash E. Samani, J. D. De Kooning, L. Vandevelde, G. Crevecoeur
This article presents an application of neural network-based Model Predictive Control (MPC) to improve the wind turbine control system's performance in providing frequency control ancillary services to the grid. A closed-loop Hammerstein structure is used to approximate the behavior of a 5MW floating offshore wind turbine with a Permanent Magnet Synchronous Generator (PMSG). The multilayer perceptron neural networks estimate the aerodynamic behavior of the nonlinear steady-state part, and the linear AutoRegressive with Exogenous input (ARX) is applied to identify the linear time-invariant dynamic part. Using the specific structure of the Cascade Hammerstein design simplifies the online linearization at each operating point. The proposed algorithm evades the necessity of nonlinear optimization and uses quadratic programming to obtain control actions. Eventually, the proposed control design provides a fast and stable response to the grid frequency variations with optimal pitch and torque cooperation. The performance of the MPC is compared with the gain-scheduled proportional-integral (PI) controller. Results demonstrate the effectiveness of the designed control system in providing Frequency Containment Reserve (FCR) and frequency regulation in the future of power systems.
{"title":"Model Predictive Control with a Cascaded Hammerstein Neural Network of a Wind Turbine Providing Frequency Containment Reserve","authors":"N. Kayedpour, Arash E. Samani, J. D. De Kooning, L. Vandevelde, G. Crevecoeur","doi":"10.1109/PESGM48719.2022.9916984","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9916984","url":null,"abstract":"This article presents an application of neural network-based Model Predictive Control (MPC) to improve the wind turbine control system's performance in providing frequency control ancillary services to the grid. A closed-loop Hammerstein structure is used to approximate the behavior of a 5MW floating offshore wind turbine with a Permanent Magnet Synchronous Generator (PMSG). The multilayer perceptron neural networks estimate the aerodynamic behavior of the nonlinear steady-state part, and the linear AutoRegressive with Exogenous input (ARX) is applied to identify the linear time-invariant dynamic part. Using the specific structure of the Cascade Hammerstein design simplifies the online linearization at each operating point. The proposed algorithm evades the necessity of nonlinear optimization and uses quadratic programming to obtain control actions. Eventually, the proposed control design provides a fast and stable response to the grid frequency variations with optimal pitch and torque cooperation. The performance of the MPC is compared with the gain-scheduled proportional-integral (PI) controller. Results demonstrate the effectiveness of the designed control system in providing Frequency Containment Reserve (FCR) and frequency regulation in the future of power systems.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133995254","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 : 2022-07-17DOI: 10.1109/PESGM48719.2022.9916883
O. Naidu, A. Pradhan, N. George
In this paper, a hybrid time-domain protection scheme for series compensated lines using incremental quantity combined with traveling wave principle is proposed. Each principle is assigned a zone of the protected section of the line to achieve fast protection. The incremental quantity-based method is assigned for close-in faults up to 35% and the traveling wave from 33.33% to 66.67% of the line from the relay end. The incremental quantity-based method compares a dynamic restraining quantity obtained from voltage and current to the operating quantity using current for the protection decision. The traveling wave-based method derives a decision by comparing the calculated line length, obtained using the first three arrival times measured at the relay location, to the actual line length. The proposed hybrid approach exploits the advantages of both principles to achieve better reliability and speed of protection for series compensated transmission lines. The proposed scheme is verified for a 400-kV, 300 km series compensated transmission line and results are compared with traditional impedance and incremental quantity-based methods.
{"title":"A Hybrid Time Domain Protection Scheme for Series Compensated Lines","authors":"O. Naidu, A. Pradhan, N. George","doi":"10.1109/PESGM48719.2022.9916883","DOIUrl":"https://doi.org/10.1109/PESGM48719.2022.9916883","url":null,"abstract":"In this paper, a hybrid time-domain protection scheme for series compensated lines using incremental quantity combined with traveling wave principle is proposed. Each principle is assigned a zone of the protected section of the line to achieve fast protection. The incremental quantity-based method is assigned for close-in faults up to 35% and the traveling wave from 33.33% to 66.67% of the line from the relay end. The incremental quantity-based method compares a dynamic restraining quantity obtained from voltage and current to the operating quantity using current for the protection decision. The traveling wave-based method derives a decision by comparing the calculated line length, obtained using the first three arrival times measured at the relay location, to the actual line length. The proposed hybrid approach exploits the advantages of both principles to achieve better reliability and speed of protection for series compensated transmission lines. The proposed scheme is verified for a 400-kV, 300 km series compensated transmission line and results are compared with traditional impedance and incremental quantity-based methods.","PeriodicalId":388672,"journal":{"name":"2022 IEEE Power & Energy Society General Meeting (PESGM)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134018768","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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