Machine Learning Based Online Estimation of Power Plant Participation Factors for Automatic Generation Control

Machine Learning Based Online Estimation of Power Plant Participation Factors for Automatic Generation Control

Détails bibliographiques
Parent link:	Relay Protection and Automation (RPA 2019): proceedings 2nd International Youth Scientific and Technical Conference, Moscow, October 24-25, 2019/ Moscow Power Engineering Institute. [12 p.].— , 2019
Auteur principal:	Tsydenov E. A. Evgeny Aleksandrovich
Collectivité auteur:	Национальный исследовательский Томский политехнический университет Инженерная школа энергетики Отделение электроэнергетики и электротехники (ОЭЭ)
Autres auteurs:	Prokhorov A. V. Anton Viktorovich, Khaustov P. A. Pavel Aleksandrovich
Résumé:	Title screen Despite of fast going integration of information technologies into power systems and resulting emergence of more efficient, faster and accurate automatic tools for analysis and control, still there are many tasks that require involvement and rely on the experience of the dispatching personnel. Режим доступа: по договору с организацией-держателем ресурса
Publié:	2019
Sujets:	электронный ресурс труды учёных ТПУ машинное обучение электростанции автоматический контроль
Accès en ligne:	https://doi.org/10.1109/RPA47751.2019.8958172
Format:	Électronique Chapitre de livre
KOHA link:	https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=661739

Documents similaires

Online Estimation of Plant Participation Factors for Automatic Generation Control in Power Systems with Variable Energy Resources
par: Tsydenov E. A. Evgeny Aleksandrovich
Publié: (2022)

Advancement of automatic generation control in power systems with large share of variable energy resources
par: Tsydenov E. A. Evgeny Aleksandrovich
Publié: (2021)

Bumpless switch from manual to automatic control in the automatic control system of steam boiler’s feed water drum
par: Batyashov S. V. Sergey Vladimirovich
Publié: (2016)

Adaptive pseudolinear compensators of dynamic characteristics of automatic control systems
Publié: (2016)

Hybrid Real-Time Simulator for Setting of Automatic Secondary Frequency and Active Power Control
Publié: (2020)

Marketing analysis of the global market using machine learning
par: Gubin E. I. Evgeny Ivanovich
Publié: (2021)

Machine learning model for evaluating the effectiveness of treatment for erysipelas
par: Zhurman D. А.
Publié: (2020)

The evaluation of functional heart condition with machine learning algorithms
Publié: (2017)

Solar photovoltaic power output forecasting using machine learning technique
par: Dinh Van Tai
Publié: (2019)

Simple machine learning model about predicting the price of gold
par: Zhang Weijia
Publié: (2020)

Color segmentation of TV images for automatic object detection
par: Aksenov S. V. Sergey Vladimirovich
Publié: (2021)

Statistical and machine learning models comparison for demand forecasting
par: Koryakina T. V.
Publié: (2022)

Formation classification based on the well logs data with the use of machine learning
par: Kanaev I. S.
Publié: (2019)

Principles of electric power generation based on the self-excited electrical machines using the perspectives of the automatic control theory
par: Garganeev A. G. Alexander Georgievich
Publié: (2013)

A machine learning approach for grain crop's seed classification in purifying separation
par: Vlasov A. V. Andrey Vladimirovich
Publié: (2017)

Methods and Approaches for Automatic Processing and Storage of High-Potential Electrocardiogram Registered by Hardware and Software Complex on Nanosensors
Publié: (2018)

Introduction to Instrumentation, Sensors, and Process Control
par: Dunn W. C. William C.
Publié: (Boston, Artech House, 2006)

Fuzzy Logic, Identification and Predictive Control
par: Espinosa J. Jairo
Publié: (London, Springer, 2005)

Machine Learning Clustering of Reservoir Heterogeneity with Petrophysical and Production Data
Publié: (2020)

Automatic pressure control in the oil pipeline
par: Gromakov E. I. Evgeny Ivanovich
Publié: (2014)

Automatic identification of problematic online discussions
par: Zaida A. V. Artur Vitaljevich
Publié: (2025)

Segmentation of sentinel satellite images: comparison of machine learning and deep-learning-based models
par: Tokareva O. S. Olga Sergeevna
Publié: (2021)

Machine learning algorithm for formation properties prediction based on well log data
par: Kanaev I. S.
Publié: (2020)

Singular Perturbation Methods in Control. Analysis and Design
par: Kokotovic P. Petar
Publié: (Philadelphia, SIAM, 1999)

Crowd-Machine Collaboration for Item Screening
Publié: (2018)

Software and hardware platform for testing of Automatic Generation Control algorithms
par: Vasilev A. S. Alexey Sergeevich
Publié: (2017)

Automatic Control with Experiments
par: Hernández-Guzmán, Victor Manuel, et autres
Publié: (2024)

Automatic Control with Experiments
par: Hernández-Guzmán, Victor Manuel, et autres
Publié: (2019)

PID Control. New Identification and Design Methods. with 285 Figures
par: Johnson M. A. Michael A
Publié: (London, Springer, 2005)

System two-position control of liquid level in industrial tanks
par: Zakamaldin A. A.
Publié: (2016)

The New Algorithms Of Machine Learning For Education People With Special Needs
par: Khaperskaya A. V. Alena Vasilievna
Publié: (2018)

Machine-learning predictions CO2 solubility and residual trapping indexes
par: Davoodi Sh. Shadfar
Publié: (2023)

Automatic Control Systems With MATLAB /
par: Palani, S.
Publié: (2022)

Problems of exploration of steam generators in nuclear power plant
par: Bondarenko E. A. Evgeny Anatolievich
Publié: (2015)

System two-position control of liquid level in industrial tanks
par: Zakamaldin A. A.
Publié: (2014)

Machine Learning Techniques for Online Social Networks
Publié: (2018)

Dynamic Modeling and Control of Engineering Systems
par: Kulakowski B. T. Bohdan T.
Publié: (New York, Cambridge University Press, 2007)

Oil production rate prediction after treatment operations using machine-learning techniques
par: Melnikov M. O. Maksim Olegovich
Publié: (2022)

Plant Transcription Factors Methods and Protocols /
Publié: (2011)

Plant Transcription Factors Methods and Protocols /
Publié: (2018)