Pub Date : 2021-11-13DOI: 10.1109/USSEC53120.2021.9655734
S. Blair, I. Naumov, Alexander Shapeev
This paper is devoted to brief description of new yet having well proven track record experience of distributed fully passive optical sensors system application in the field of accurate, highly sensitive, adoptable and flexible measurement technology for power system equipment monitoring by means of real time current, voltage, temperature, vibration and strain data gathering. Both transmission and distribution power system application examples are discussed. Obstacles and ways of their overcoming are addressed, as well as practical on-hand international implementation experience in various countries (Scotland, Norway) mentioned. Investigation of several operation and maintenance functions for the relay protection systems, namely - fault location and multi-ended differential protection, executable smartly via usage of optical sensors system, carried out. Farther technology implementation for optical current and voltage sensing (as primary pattern) and strain measurement coupled with temperature and vibration (as secondary one) reviewed as a new step of power system equipment comprehensive monitoring and processes digitalization.
{"title":"Distributed Optical Sensor System for Comprehensive Power System Equipment Monitoring","authors":"S. Blair, I. Naumov, Alexander Shapeev","doi":"10.1109/USSEC53120.2021.9655734","DOIUrl":"https://doi.org/10.1109/USSEC53120.2021.9655734","url":null,"abstract":"This paper is devoted to brief description of new yet having well proven track record experience of distributed fully passive optical sensors system application in the field of accurate, highly sensitive, adoptable and flexible measurement technology for power system equipment monitoring by means of real time current, voltage, temperature, vibration and strain data gathering. Both transmission and distribution power system application examples are discussed. Obstacles and ways of their overcoming are addressed, as well as practical on-hand international implementation experience in various countries (Scotland, Norway) mentioned. Investigation of several operation and maintenance functions for the relay protection systems, namely - fault location and multi-ended differential protection, executable smartly via usage of optical sensors system, carried out. Farther technology implementation for optical current and voltage sensing (as primary pattern) and strain measurement coupled with temperature and vibration (as secondary one) reviewed as a new step of power system equipment comprehensive monitoring and processes digitalization.","PeriodicalId":260032,"journal":{"name":"2021 Ural-Siberian Smart Energy Conference (USSEC)","volume":"07 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115778797","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 : 2021-11-13DOI: 10.1109/USSEC53120.2021.9655749
V. Voronin, F. Nepsha, A. Ermakov
The growth of the power-to-weight ratio of coal mine equipment has resulted in the need for increasing energy efficiency. One of the most effective ways to fulfill this need is selecting and installing reactive power compensation devices (RPCDs). However, the existing methodologies cannot ensure the correctness of choosing RPCDs for coal mines because they don't take into account the harsh nature of reactive power consumption in coal mines. To solve this problem, it is necessary to model and analyze the reactive power consumption of the coal mine extraction area. This article discusses the main approaches to the development of a simulation model of a power supply system of a coal mine extraction area. The scenario approach has been used to model the operating modes of mining equipment. Based on the created model, the modeling of the main operating modes of mining equipment has been carried out. As a result, it made it possible to obtain active and reactive power consumption curves to select the optimal configuration of RPCDs. In conclusion, recommendations are given for installing regulated and unregulated RPCD in the power supply system of coal mines.
{"title":"Simulation and Analysis of Reactive Power Consumption of the Coal Mine Excavation Area","authors":"V. Voronin, F. Nepsha, A. Ermakov","doi":"10.1109/USSEC53120.2021.9655749","DOIUrl":"https://doi.org/10.1109/USSEC53120.2021.9655749","url":null,"abstract":"The growth of the power-to-weight ratio of coal mine equipment has resulted in the need for increasing energy efficiency. One of the most effective ways to fulfill this need is selecting and installing reactive power compensation devices (RPCDs). However, the existing methodologies cannot ensure the correctness of choosing RPCDs for coal mines because they don't take into account the harsh nature of reactive power consumption in coal mines. To solve this problem, it is necessary to model and analyze the reactive power consumption of the coal mine extraction area. This article discusses the main approaches to the development of a simulation model of a power supply system of a coal mine extraction area. The scenario approach has been used to model the operating modes of mining equipment. Based on the created model, the modeling of the main operating modes of mining equipment has been carried out. As a result, it made it possible to obtain active and reactive power consumption curves to select the optimal configuration of RPCDs. In conclusion, recommendations are given for installing regulated and unregulated RPCD in the power supply system of coal mines.","PeriodicalId":260032,"journal":{"name":"2021 Ural-Siberian Smart Energy Conference (USSEC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122599343","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 : 2021-11-13DOI: 10.1109/USSEC53120.2021.9655726
A. Serov, Y. Vishnyakova, Plamen M. Tzvetkov
At present, the active power within a given frequency band is considered as one of the most important and informative parameters of electric power distribution systems. Digital systems of active power measurement are widely spread. Such systems implement methods of polynomial interpolation of a sampled instant power signal. Simulation modeling shows that the polynomial interpolation can be successfully applied to measure active power of both sinusoidal and polyharmonic input signals. The paper considers application of zero, first and second order polynomial interpolation (the algorithms of active power measurement are considered). Analytic expressions that allow to evaluate active power measurement systematic error are derived. The influence of input signal parameters like amplitudes of voltage and current, frequency and frequency deviation, phase shift between voltage and current and measurement system parameters such as sampling frequency, total measurement time on active power measurement systematic error for interpolation polynomials of zero, first and second order are described. The measurement systems based on the polynomial interpolation of sampled signals are simulated in Matlab Simulink software. Zero systematic error conditions are formulated for the interpolation polynomials of the zero, first and second order. The method of the systematic error minimization by means of input signal frequency measurement and measurement time adjustment is developed.
{"title":"Application of Interpolating Polynomials for the Active Power Within a Given Frequency Band Measurement","authors":"A. Serov, Y. Vishnyakova, Plamen M. Tzvetkov","doi":"10.1109/USSEC53120.2021.9655726","DOIUrl":"https://doi.org/10.1109/USSEC53120.2021.9655726","url":null,"abstract":"At present, the active power within a given frequency band is considered as one of the most important and informative parameters of electric power distribution systems. Digital systems of active power measurement are widely spread. Such systems implement methods of polynomial interpolation of a sampled instant power signal. Simulation modeling shows that the polynomial interpolation can be successfully applied to measure active power of both sinusoidal and polyharmonic input signals. The paper considers application of zero, first and second order polynomial interpolation (the algorithms of active power measurement are considered). Analytic expressions that allow to evaluate active power measurement systematic error are derived. The influence of input signal parameters like amplitudes of voltage and current, frequency and frequency deviation, phase shift between voltage and current and measurement system parameters such as sampling frequency, total measurement time on active power measurement systematic error for interpolation polynomials of zero, first and second order are described. The measurement systems based on the polynomial interpolation of sampled signals are simulated in Matlab Simulink software. Zero systematic error conditions are formulated for the interpolation polynomials of the zero, first and second order. The method of the systematic error minimization by means of input signal frequency measurement and measurement time adjustment is developed.","PeriodicalId":260032,"journal":{"name":"2021 Ural-Siberian Smart Energy Conference (USSEC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134141497","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 : 2021-11-13DOI: 10.1109/USSEC53120.2021.9655722
Y. Soluyanov, A. Fedotov, A. Akhmetshin, V. Soluyanov
Research by the ““Roselectromontazh” Association” regarding the analysis of half-hour power profiles of kindergartens and schools showed that the actual measured power turned out to be significantly lower than that calculated according to regulatory technical documents. As shown by the estimates of the specialists of the ““Roselectromontazh” Association”, the actual measured power is 2 times lower on average. Updating the specific design electrical loads will lead to a decrease in the cost of technological connection to electrical networks. This task is extremely relevant for the country, since according to the National Project “Education” it is planned to create 230 thousand new students in schools by 2024, and according to the national project “Demography” by 2021 it is planned to create 255 thousand pupils in kindergartens for children under 3 years old, and by 2024 8.6 thousand groups in kindergartens up to 7 years old. In 2020, 737 kindergartens for more than 103 thousand pupils were commissioned in the country. For example, in the Republic of Tatarstan, over 60 schools and 240 kindergartens have been built in 10 years. This task can be accomplished by using smart electricity meters, which can also be used to: classify electricity consumers; forecast electricity demand; monitor the status of the distribution transformer; assess the state of the distribution system; forecast the demand for electricity, etc.
{"title":"The Concept of Optimizing the Efficiency of the Calculation of the Electrical Loads of Kindergartens and Schools","authors":"Y. Soluyanov, A. Fedotov, A. Akhmetshin, V. Soluyanov","doi":"10.1109/USSEC53120.2021.9655722","DOIUrl":"https://doi.org/10.1109/USSEC53120.2021.9655722","url":null,"abstract":"Research by the ““Roselectromontazh” Association” regarding the analysis of half-hour power profiles of kindergartens and schools showed that the actual measured power turned out to be significantly lower than that calculated according to regulatory technical documents. As shown by the estimates of the specialists of the ““Roselectromontazh” Association”, the actual measured power is 2 times lower on average. Updating the specific design electrical loads will lead to a decrease in the cost of technological connection to electrical networks. This task is extremely relevant for the country, since according to the National Project “Education” it is planned to create 230 thousand new students in schools by 2024, and according to the national project “Demography” by 2021 it is planned to create 255 thousand pupils in kindergartens for children under 3 years old, and by 2024 8.6 thousand groups in kindergartens up to 7 years old. In 2020, 737 kindergartens for more than 103 thousand pupils were commissioned in the country. For example, in the Republic of Tatarstan, over 60 schools and 240 kindergartens have been built in 10 years. This task can be accomplished by using smart electricity meters, which can also be used to: classify electricity consumers; forecast electricity demand; monitor the status of the distribution transformer; assess the state of the distribution system; forecast the demand for electricity, etc.","PeriodicalId":260032,"journal":{"name":"2021 Ural-Siberian Smart Energy Conference (USSEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130758317","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 : 2021-11-13DOI: 10.1109/USSEC53120.2021.9655717
I. R. Rao, J. Gonda, Surya Teja Surampudi
The economic load scheduling of thermal generating units in a power system is aimed at optimally allocating a stipulated load demand from the load dispatch center, among the several generating units in operation, in a power plant, with the objective of minimizing the overall cost of the generation, while satisfying all the equality (load-generation balance) and inequality (limits on the generating units) constraints of the plant. In the power system parlance, this is famously called as the economic load dispatch without losses, and generally considered cost curves for the thermal units are quadratic approximations. There are several algorithms in use, all of them being iterative in nature, like the λ-iteration technique. This paper presents a matrix formulation of the same problem, that yields a matrix-based non-iterative, direct solution, with a matrix inversion. This technique is elegant and gives quick and accurate results. It is direct for the cases of schedule without violation of limits and requires minimal adjustments for cases of violating the limits. Few examples are considered, to demonstrate the effectiveness of the technique implemented in MATLAB® R2019a, and the results are presented.
{"title":"A Matrix Inversion-Based Algorithm for Economic Scheduling of Power Outputs of Thermal Units in an Electric Power System Without Losses","authors":"I. R. Rao, J. Gonda, Surya Teja Surampudi","doi":"10.1109/USSEC53120.2021.9655717","DOIUrl":"https://doi.org/10.1109/USSEC53120.2021.9655717","url":null,"abstract":"The economic load scheduling of thermal generating units in a power system is aimed at optimally allocating a stipulated load demand from the load dispatch center, among the several generating units in operation, in a power plant, with the objective of minimizing the overall cost of the generation, while satisfying all the equality (load-generation balance) and inequality (limits on the generating units) constraints of the plant. In the power system parlance, this is famously called as the economic load dispatch without losses, and generally considered cost curves for the thermal units are quadratic approximations. There are several algorithms in use, all of them being iterative in nature, like the λ-iteration technique. This paper presents a matrix formulation of the same problem, that yields a matrix-based non-iterative, direct solution, with a matrix inversion. This technique is elegant and gives quick and accurate results. It is direct for the cases of schedule without violation of limits and requires minimal adjustments for cases of violating the limits. Few examples are considered, to demonstrate the effectiveness of the technique implemented in MATLAB® R2019a, and the results are presented.","PeriodicalId":260032,"journal":{"name":"2021 Ural-Siberian Smart Energy Conference (USSEC)","volume":"37 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134368872","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 : 2021-11-13DOI: 10.1109/USSEC53120.2021.9655761
A. Cheremnykh, A. Sidorova, A. Rusina
The paper provides a summary of approaches to the calculation of electric power modes and describes the actual of the topic under consideration. The paper contains a calculation of two identical electric power modes with one network configuration. The calculation was carried out in two different software: the RastrWin3 software and Python. Modeling and calculation were carried out in order to demonstrate the possibility of calculating the electric power mode in a programming language with dynamic strong typing. The reference calculation of electric power modes was performed in the RastrWin3 software. The results obtained were exported to Python and a similar calculation was performed. The iterative calculation of the electric power mode was performed in RastrWin3 software and Python environment by Newton's method. Python has extensions that allow approaching the analysis of electrical power mode in more detail. The result of modeling the power system and calculating its electric power mode is shown a high accuracy of reproducing the calculation in the Python environment. The identity of the calculation and the insignificant difference in the numerical results suggests that Python can be used as an alternative tool for calculating the electric power modes of any power system.
{"title":"Python - Alternative Tool for Calculating Electric Power Modes of IPS","authors":"A. Cheremnykh, A. Sidorova, A. Rusina","doi":"10.1109/USSEC53120.2021.9655761","DOIUrl":"https://doi.org/10.1109/USSEC53120.2021.9655761","url":null,"abstract":"The paper provides a summary of approaches to the calculation of electric power modes and describes the actual of the topic under consideration. The paper contains a calculation of two identical electric power modes with one network configuration. The calculation was carried out in two different software: the RastrWin3 software and Python. Modeling and calculation were carried out in order to demonstrate the possibility of calculating the electric power mode in a programming language with dynamic strong typing. The reference calculation of electric power modes was performed in the RastrWin3 software. The results obtained were exported to Python and a similar calculation was performed. The iterative calculation of the electric power mode was performed in RastrWin3 software and Python environment by Newton's method. Python has extensions that allow approaching the analysis of electrical power mode in more detail. The result of modeling the power system and calculating its electric power mode is shown a high accuracy of reproducing the calculation in the Python environment. The identity of the calculation and the insignificant difference in the numerical results suggests that Python can be used as an alternative tool for calculating the electric power modes of any power system.","PeriodicalId":260032,"journal":{"name":"2021 Ural-Siberian Smart Energy Conference (USSEC)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127923899","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 : 2021-11-13DOI: 10.1109/USSEC53120.2021.9655754
A. Zhavoronkov, O. Aksyonova, E. Aksyonova
The development of distributed power supply systems, microgrids is recognized as relevant and requires intensive study. Research on microgrid management systems is inextricably linked with data science. The paper presents a study of the use of software for predicting the load consumed by a typical microgrid over a monthly interval. The formulation of the problem of forecasting time series, applied to classical stationary series, is described. The process of data processing using the open-source machine software libraries NumPy, Keras is presented. A class is developed in the Python environment based on the use of recurrent neural networks-long short-term memory, the applicability for the task is shown. The model was trained using iterative optimization of the series value, and the data sampling window. The satisfactory accuracy of forecasting based on the developed model is shown. The conclusions for further study of the applicability of this algorithm in the practice of managing distributed power supply systems are presented.
{"title":"Application of Long Short-Term Memory for Energy Load Prediction in the Microgrid Using Python Software","authors":"A. Zhavoronkov, O. Aksyonova, E. Aksyonova","doi":"10.1109/USSEC53120.2021.9655754","DOIUrl":"https://doi.org/10.1109/USSEC53120.2021.9655754","url":null,"abstract":"The development of distributed power supply systems, microgrids is recognized as relevant and requires intensive study. Research on microgrid management systems is inextricably linked with data science. The paper presents a study of the use of software for predicting the load consumed by a typical microgrid over a monthly interval. The formulation of the problem of forecasting time series, applied to classical stationary series, is described. The process of data processing using the open-source machine software libraries NumPy, Keras is presented. A class is developed in the Python environment based on the use of recurrent neural networks-long short-term memory, the applicability for the task is shown. The model was trained using iterative optimization of the series value, and the data sampling window. The satisfactory accuracy of forecasting based on the developed model is shown. The conclusions for further study of the applicability of this algorithm in the practice of managing distributed power supply systems are presented.","PeriodicalId":260032,"journal":{"name":"2021 Ural-Siberian Smart Energy Conference (USSEC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128028217","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 : 2021-11-13DOI: 10.1109/USSEC53120.2021.9655723
S. Mitrofanov, A. Svetlichnaya, A. Arestova, A. Rusina
The paper deals with the problem of optimizing the unit commitment and loading of hydro units at a hydropower plant. The optimal operating conditions of the hydropower plant equipment will ensure the required power quality in the peak area of the load schedule and increase the efficiency of the power plant. The problem of uneven loading of hydro units is relevant because of differences in equipment parameters, flow characteristics or uneven physical wear of hydropower plant elements. To improve the quality of optimization, it is required to verify the hydro unit parameters and their flow characteristics. The paper analyzes the methods of intra-plant optimization of unit commitment and presents the main optimization criteria, operational and technological constraints. The authors also propose an optimization algorithm and its software implementation using Matlab software. The algorithm was verified using the Sayano-Shushensky hydropower complex that includes two plants in a cascade. The software module provides three options for calculating the optimal unit commitment and loading of hydro units: optimization of instantaneous values, optimization on a daily interval, and optimization on a daily interval with the constraint on the number of start-stop operations.
{"title":"Development of a Software Module of Intra-Plant Optimization for Short-Term Forecasting of Hydropower Plant Operating Conditions","authors":"S. Mitrofanov, A. Svetlichnaya, A. Arestova, A. Rusina","doi":"10.1109/USSEC53120.2021.9655723","DOIUrl":"https://doi.org/10.1109/USSEC53120.2021.9655723","url":null,"abstract":"The paper deals with the problem of optimizing the unit commitment and loading of hydro units at a hydropower plant. The optimal operating conditions of the hydropower plant equipment will ensure the required power quality in the peak area of the load schedule and increase the efficiency of the power plant. The problem of uneven loading of hydro units is relevant because of differences in equipment parameters, flow characteristics or uneven physical wear of hydropower plant elements. To improve the quality of optimization, it is required to verify the hydro unit parameters and their flow characteristics. The paper analyzes the methods of intra-plant optimization of unit commitment and presents the main optimization criteria, operational and technological constraints. The authors also propose an optimization algorithm and its software implementation using Matlab software. The algorithm was verified using the Sayano-Shushensky hydropower complex that includes two plants in a cascade. The software module provides three options for calculating the optimal unit commitment and loading of hydro units: optimization of instantaneous values, optimization on a daily interval, and optimization on a daily interval with the constraint on the number of start-stop operations.","PeriodicalId":260032,"journal":{"name":"2021 Ural-Siberian Smart Energy Conference (USSEC)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128538619","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 : 2021-11-13DOI: 10.1109/USSEC53120.2021.9655757
V. Fyodorova, D. Kornilovich, V. Kirichenko, G. Glazyrin, Alexandra Sidorova, Alexandra Litvinova
Synchronization is an actions algorithm to turn on synchronous generators for parallel operation with other synchronously rotating machines or an electric energy system (EES). This operation is a generation process composite part. At the moment there are two traditional ways of doing it: ideal synchronization and self-synchronization manually by personnel or using automatic devices. Synchronization can have various consequences: large equalizing current, power plant busbar de-energization, damage to switching equipment or synchronous generators. They depend both on the chosen implementation method and on the human factor influence. The unit starting possible consequences minimizing necessitates an automatic device development that excludes the human factor influence and some modernized synchronization method that eliminates the two traditional methods disadvantages. The creation of such a synchronization system will solve the problem of possible consequences from the synchronous generator inclusion in network.
{"title":"Synchronization Digital Device Development for Generators Automatic Connection to the Network by Various Methods","authors":"V. Fyodorova, D. Kornilovich, V. Kirichenko, G. Glazyrin, Alexandra Sidorova, Alexandra Litvinova","doi":"10.1109/USSEC53120.2021.9655757","DOIUrl":"https://doi.org/10.1109/USSEC53120.2021.9655757","url":null,"abstract":"Synchronization is an actions algorithm to turn on synchronous generators for parallel operation with other synchronously rotating machines or an electric energy system (EES). This operation is a generation process composite part. At the moment there are two traditional ways of doing it: ideal synchronization and self-synchronization manually by personnel or using automatic devices. Synchronization can have various consequences: large equalizing current, power plant busbar de-energization, damage to switching equipment or synchronous generators. They depend both on the chosen implementation method and on the human factor influence. The unit starting possible consequences minimizing necessitates an automatic device development that excludes the human factor influence and some modernized synchronization method that eliminates the two traditional methods disadvantages. The creation of such a synchronization system will solve the problem of possible consequences from the synchronous generator inclusion in network.","PeriodicalId":260032,"journal":{"name":"2021 Ural-Siberian Smart Energy Conference (USSEC)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121896741","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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