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Automatic damage type detection algorithm for main equipment based on digital twin technology
https://doi.org/10.15518/isjaee.2024.01.153-168
Abstract
The issues of using digital twin technology today are relevant in various areas of economic development, and the electric power industry is no exception. Electric power industry is an industry with a complex structure. People are not always able to quickly process a huge amount of data, identify dependencies and make the best decision, so without digital technologies it is impossible to compete in modern realities. The article discusses the development and application of algorithms for determining types of damage to main equipment based on digital twin technology. Determination of the damage mode is based on the method of analyzing analog and discrete signals present in the technological data transmission network. As a result of the research, algorithms for a digital twin of relay protection and automation at an operating hydroelectric power station were developed, tested and implemented. The digital twin is aimed at reducing the time for detecting and localizing faults and damage to main equipment, as well as increasing information content about the operating modes of relay protection and automation devices. The results obtained can be implemented into the existing automated control system of hydroelectric power plants to improve the decision-making process. Flexible configuration allows not only to adapt algorithms to any equipment, but also to expand their functionality.
About the Authors
A. V. Sidorova
Novosibirsk State Technical University
Russian Federation
Russian Federation
Sidorova Alena V. - researcher at the Interdepartmental Research Laboratory for Processing,
Analysis and Presentation of Data in Electric Power Systems (LDvEES),
K. Marx Avenue, 20, Novosibirsk, 630073
A. V. Shirokov
Novosibirsk State Technical University
Russian Federation
Russian Federation
Shirokov Aleksandr V. - postgraduate student of the department Electric Power stations and Electric power,
K. Marx Avenue, 20, Novosibirsk, 630073
A. G. Rusina
Novosibirsk State Technical University
Russian Federation
Russian Federation
Rusina Anastasia G. - Dr. Sc. (Engineering), Professor, Dean of the Energy Faculty,
K. Marx Avenue, 20, Novosibirsk, 630073
A. Y. Arestova
Novosibirsk State Technical University
Russian Federation
Russian Federation
Arestova Anna Yu. - Senior lecturer of Automated power systems Department,
K. Marx Avenue, 20, Novosibirsk, 630073
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Review
For citations:
Sidorova A.V., Shirokov A.V., Rusina A.G., Arestova A.Y. Automatic damage type detection algorithm for main equipment based on digital twin technology. Alternative Energy and Ecology (ISJAEE). 2024;(1):153-168. (In Russ.) https://doi.org/10.15518/isjaee.2024.01.153-168
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