Digital Identification Algorithms for Primary Frequency Control in Unified Power System

The article studies and develops the methods for assessing the degree of participation of power plants in the general primary frequency control in a unified energy system (UES) of Russia based on time series analysis of frequency and power. To identify the processes under study, methods of associati...

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Autores principales:	Natalia Bakhtadze, Evgeny Maximov, Natalia Maximova
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	general primary frequency control predictive diagnostics of generating equipment process knowledgebase inductive learning intelligent identification associative search Mathematics QA1-939
Acceso en línea:	https://doaj.org/article/5dfd7fcfdd9f41a8bff712104fa03655
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spelling	oai:doaj.org-article:5dfd7fcfdd9f41a8bff712104fa036552021-11-25T18:16:47ZDigital Identification Algorithms for Primary Frequency Control in Unified Power System10.3390/math92228752227-7390https://doaj.org/article/5dfd7fcfdd9f41a8bff712104fa036552021-11-01T00:00:00Zhttps://www.mdpi.com/2227-7390/9/22/2875https://doaj.org/toc/2227-7390The article studies and develops the methods for assessing the degree of participation of power plants in the general primary frequency control in a unified energy system (UES) of Russia based on time series analysis of frequency and power. To identify the processes under study, methods of associative search are proposed. The methods are based on process knowledgebase development, data mining, associative research, and inductive learning. Real-time identification models generated using these algorithms can be used in automatic control and decision support systems. Evaluation of the behavior of individual UES members enables timely prevention of abnormal and emergency situations. Methods for predictive diagnostics of generating equipment in terms of their readiness to participate in the primary frequency control are also proposed. In view of the non-stationarity of the load in electrical networks, the algorithms have been developed using wavelet analysis. Case studies are given showing the operating of the proposed methods.Natalia BakhtadzeEvgeny MaximovNatalia MaximovaMDPI AGarticlegeneral primary frequency controlpredictive diagnostics of generating equipmentprocess knowledgebaseinductive learningintelligent identificationassociative searchMathematicsQA1-939ENMathematics, Vol 9, Iss 2875, p 2875 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	general primary frequency control predictive diagnostics of generating equipment process knowledgebase inductive learning intelligent identification associative search Mathematics QA1-939
spellingShingle	general primary frequency control predictive diagnostics of generating equipment process knowledgebase inductive learning intelligent identification associative search Mathematics QA1-939 Natalia Bakhtadze Evgeny Maximov Natalia Maximova Digital Identification Algorithms for Primary Frequency Control in Unified Power System
description	The article studies and develops the methods for assessing the degree of participation of power plants in the general primary frequency control in a unified energy system (UES) of Russia based on time series analysis of frequency and power. To identify the processes under study, methods of associative search are proposed. The methods are based on process knowledgebase development, data mining, associative research, and inductive learning. Real-time identification models generated using these algorithms can be used in automatic control and decision support systems. Evaluation of the behavior of individual UES members enables timely prevention of abnormal and emergency situations. Methods for predictive diagnostics of generating equipment in terms of their readiness to participate in the primary frequency control are also proposed. In view of the non-stationarity of the load in electrical networks, the algorithms have been developed using wavelet analysis. Case studies are given showing the operating of the proposed methods.
format	article
author	Natalia Bakhtadze Evgeny Maximov Natalia Maximova
author_facet	Natalia Bakhtadze Evgeny Maximov Natalia Maximova
author_sort	Natalia Bakhtadze
title	Digital Identification Algorithms for Primary Frequency Control in Unified Power System
title_short	Digital Identification Algorithms for Primary Frequency Control in Unified Power System
title_full	Digital Identification Algorithms for Primary Frequency Control in Unified Power System
title_fullStr	Digital Identification Algorithms for Primary Frequency Control in Unified Power System
title_full_unstemmed	Digital Identification Algorithms for Primary Frequency Control in Unified Power System
title_sort	digital identification algorithms for primary frequency control in unified power system
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/5dfd7fcfdd9f41a8bff712104fa03655
work_keys_str_mv	AT nataliabakhtadze digitalidentificationalgorithmsforprimaryfrequencycontrolinunifiedpowersystem AT evgenymaximov digitalidentificationalgorithmsforprimaryfrequencycontrolinunifiedpowersystem AT nataliamaximova digitalidentificationalgorithmsforprimaryfrequencycontrolinunifiedpowersystem
_version_	1718411383112990720

Digital Identification Algorithms for Primary Frequency Control in Unified Power System

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