Substations technical state assessment using the artificial neural networks methods on the basis of technical diagnostics

Эта работа посвящена вопросам оценки технического состояния оборудования на электрических подстанциях напряжением 35-220 кВ с помощью методов искусственных нейронных сетей на основе данных технической диагностики. В работе рассматриваются принципы формирования математической модели для автоматизированной системы оценки технических активов сетевых предприятий. Представлена методика определения характеристических функций принадлежности к категории состояния оборудования, а также получение обобщенной оценки технического состояния оборудования.This research is devoted to the assessment of the electrical equipment technical state at substations of 35-220 kV using the methods of artificial neural networks based on the technical diagnostics. This paper discusses the power equipment technical state assessment principles for the Enterprise Asset Management (EAM) systems of grid companies. Presents a methodology of determining the membership functions to the category of equipment state and obtaining the generalized assessment of the equipment technical state.Программа развития УрФУ на 2013 год (п.2.1.1.1

Fuzzy neural networks' application for substation integral state assessment

This paper addresses the problems connected with fuzzy neural networks' application in equipment technical state assessment problems at electrical substations. This paper discusses the main principles of fuzzy neural network formation and its construction algorithm. Also, the case study for the determination of fuzzy neural network synaptic weights for the unit "disconnector" on the basis of technical diagnostic statistical data and tests is presented. © 2014 WIT Press.International Journal of Safety and Security Engineering;International Journal of Sustainable Development and Planning;WIT Transactions on Ecology and the Environmen

Fluid Dynamics Calculation in SF6 Circuit Breaker during Breaking as a Prerequisite for the Digital Twin Creation

The requirements to switching the capacities of SF6 circuit breakers submitted by Russian Grid companies are difficult to satisfy. The first limitation is related to material and financial costs in order to create a new requirement-satisfying switching device. The second limitation is dictated by the necessity of calculating complex physical processes in a circuit braker interrupter during fault–current making or breaking before creating a prototype. The latter task is reduced to the problem of simulating the processes of interaction between the switching arc and the SF6 gas flow. This paper deals with the solution of the problem both analytically by a special method and numerically by a numerical software package through the creation of a mathematical model of the interaction process. The switching arc is taken into account as a form of a temperature source, based on experimental data on measuring the temperature of the arc column. The key feature of the research is to use the finite element method based on a moving mesh—the Arbitrary Lagrangian Eulerian (ALE) method. Such a problem statement allows us to take the contact separation curve of the circuit breaker into account as the input data of the model. The calculations were carried out during fault-current breaking by a 110 kV SF6 dead-tank circuit breaker. The calculations of pressure and mass flow in the under-piston volume change, gas flow speed, and temperature depending on the contact separation are given. The proposed model of the switching arc was used to simulate the process of 25 kA symmetrical fault–current breaking and was compared with an experiment. © 2023 by the authors.Ministry of Education and Science of the Russian Federation, Minobrnauka: FEUZ-2022-0030The research was carried out within the state assignment with the financial support of the Ministry of Science and Higher Education of the Russian Federation (subject No. FEUZ-2022-0030 Development of an intelligent multi-agent system for modeling deeply integrated technological systems in the power industry)

Review of the Digital Twin Technology Applications for Electrical Equipment Lifecycle Management

Digital twin is one of the emerging technologies for the digital transformation of the power industry. Many existing studies claim that the widespread application of digital twins will shift the industry to a principally new level of development. This article provides an extensive overview of the industrial application experience of digital twin technologies for solving the problems of modern power systems with a particular focus on the task of high-voltage power equipment lifecycle management. The latter task contours one of the most promising areas for the application of the digital twins in the power industry since it requires deep analysis of the technological processes dynamics and the development of physical, mathematical and computer models that cover all the potential benefits of the digital twin technology. At the moment, there is a lack of reliable data on the problems of assessing and predicting the technical state of high-voltage power equipment. The use of digital twin technology in modern power systems will allow for aggregating data from a variety of real objects and will allow the automatization of collecting and processing of big data by implementing artificial intelligence methods, which will ultimately make it possible to manage the life cycle of the power equipment. The article puts to scrutiny the industrial experience of digital twins creation, considering the technical solutions suggested by the largest manufacturers of electrical equipment. A classification of digital twins, examples and main features of their application in the power industry, including the problem of managing the life cycle of high-voltage electrical equipment, are considered and discussed. © 2023 by the authors.Ministry of Education and Science of the Russian Federation, MinobrnaukaThe research funding from the Ministry of Science and Higher Education of the Russian Federation (Ural Federal University Program of Development within the Priority-2030 Program) is gratefully acknowledged

Vibration problem solution of high-capacity hydropower units

This paper proposes hydro generator vibration observations under various conditions and solution of a problem of high vibration in upper guide bearing of 110MW hydro generator. Among the test, which were carried out to identify vibration origin of hydro generating unit were: Voltage drop tests, magnetic flux measurements, interferric gap measurements, turbine pressure pulsation measurements, etc. It was shown, that among other possible reasons, correct balancing, including pivot bearing adjustment was the most efficient measure to eliminate vibration in start-up modes of hydro power unit. According to the results of conducted step-by-step defect analysis, the corresponding recommendations were provided for service and maintenance regarding the generation unit No2 of Sangtuda-2 Hydro Power Plant, Tajikistan. © Published under licence by IOP Publishing Ltd

Decision support system for quality management of cosmetic products

The paper describes the structure and the mathematical core of the decision support system developed by the authors for assessing the quality of cosmetic products based on machine learning approaches. The main goal of the study was to improve the system of quality control of cosmetic products, in particular, the quality of perfumes and cosmetics using intelligent methods of data processing, formalization of knowledge and experience of the experts, thus providing automatization of the decision-making process. The practical-oriented goal of the study was to obtain knowledge-supported decisions regarding the quality of the cosmetic products using the developed system of quality assessment based on intelligent methods of data processing, providing the possibility of unsupervised learning and adjustment of the developed system when changing final product characteristics. © Published under licence by IOP Publishing Ltd

Grey Wolf Optimizer for RES Capacity Factor Maximization at the Placement Planning Stage

At the current stage of the integration of renewable energy sources into the power systems of many countries, requirements for compliance with established technical characteristics are being applied to power generation. One such requirement is the installed capacity utilization factor, which is extremely important for optimally placing power facilities based on renewable energy sources and for the successful development of renewable energy. Efficient placement maximizes the installed capacity utilization factor of a power facility, increasing energy efficiency and the payback period. The installed capacity utilization factor depends on the assumed meteorological factors relating to geographical location and the technical characteristics of power generation. However, the installed capacity utilization factor cannot be accurately predicted, since it is necessary to know the volume of electricity produced by the power facility. A novel approach to the optimization of placement of renewable energy source power plants and their capacity factor forecasting was proposed in this article. This approach combines a machine learning forecasting algorithm (random forest regressor) with a metaheuristic optimization algorithm (grey wolf optimizer). Although the proposed approach assumes the use of only open-source data, the simulations show better results than commonly used algorithms, such as random search, particle swarm optimizer, and firefly algorithm. © 2023 by the authors.Ministry of Education and Science of the Russian Federation, Minobrnauka: FEUZ-2022-0030The research was carried out within the state assignment with the financial support of the Ministry of Science and Higher Education of the Russian Federation (subject No. FEUZ-2022-0030 Development of an intelligent multi-agent system for modeling deeply integrated technological systems in the power industry)

Digital twin technology as an instrument for increasing electrical equipment reliability

The article describes the experience of practical realisation of digital twin technology for voltage and current measurement transformer 110 kV installed in real power station. In terms of the research electrical equipment state monitoring system has been developed as a set of sensors and diagnostic system, based on essentially different approaches of non-defective diagnostics. 3D model construction of the equipment under monitoring is also described as a part of digital twin concept. It is shown the valuable impact of digital twin technology application. © Published under licence by IOP Publishing Ltd.Russian Science Foundation, RSF: 18-79-00201The reported study was supported by Russian Science Foundation, research project No. 18-79-00201