Outlier Detection in Predictive Analytics for Energy Equipment

Andryushin, A. V.; Shcherbatov, Ivan; Dolbikova, N.S.; Кузнецова, А. В.; Tsurikov, Grigory

doi:10.1007/978-3-030-32579-4_15

Cited by 8 publications

(2 citation statements)

References 13 publications

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“…The proposed hardware and software complex is classed as embedded solutions, the development and debugging of which imposes a number of requirements. The most relevant issues are the application of basic universal structures, ensuring the flexibility and reconfigurability of the control system used, and the possibility of operational maintenance and predictive repair (Yudin et al, 2017;Khan et al, 2021;Andryushin et al, 2020). The hardware and software complex is built according to the agent-manager scheme; agent applications collect heterogeneous data from the sensor network elements and transfer them to management modules.…”

Section: Resultsmentioning

confidence: 99%

Predictive Control Algorithm for A Variable Load Hybrid Power System on the Basis of Power Output Forecast

Vlasov

Artemiev

Selivanov

et al. 2022

IJEEP

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Harmonious integration of renewable energy sources into current energy systems has taken on increasing importance amid the scarcity of carbon resources. Among the key problems is the imbalance in power consumption, power generation, and significant peak overloads. To deal with this issue, an intelligent software and hardware system is needed, which will effectively implement predictive control algorithms for various energy sources. The research examines the fundamental provisions of the concept of predictive control over a variable load hybrid power system on the basis of power output forecast. The analysis performed has allowed developing a method of predictive control over the power system in a small locality based on machine learning algorithms. The method was tested using an electric power complex simulation, which included four energy sources (solar panel, wind turbines, small hydrogenerator, and standard carbon-fueled generator). The proposed predictive control method has proved to be productive. The algorithms have allowed diversifying the reliability of power supply by ensuring the sustainability of the power grid.

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Section: Resultsmentioning

confidence: 99%

Predictive Control Algorithm for A Variable Load Hybrid Power System on the Basis of Power Output Forecast

Vlasov

Artemiev

Selivanov

et al. 2022

IJEEP

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“…-прогноз ресурса узлов и деталей. Системы предиктивной аналитики и мониторинга в своем развитии способствуют качественному переходу от системы планово-предупредительных ремонтов по регламентам к системе ремонтов по фактическому техническому состоянию, то есть от нормативных, формальных сроков ремонта -к рискориентированным, реально профилактическим, когда алгоритмы системы будут в постоянном режиме оценивать реальное состояние деталей, узлов, агрегатов в целом [7].…”

Section: безопасность труда и охрана здоровьяunclassified

Ensuring Energy Efficiency of Thermal Power Plants and Heating Networks by Means of Digital Transformation

Taranukha,

Ivanova,

Pankov

2023

Intellekt. Sist. Proizv.

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The article deals with the issue of state-of-the-art development of the energy industry enterprises of the Russian Federation with the introduction of innovative digital technologies. The relevance of the research on the chosen problem is due to the transformational processes in the energy industry, that occur under the influence of digital economy introduction and the development of digital technologies. A study of the current situation and features of domestic energy industry has been carried out to identify the main factors of low efficiency that encourage energy companies to digital transformation. One of the key directions of improving the production activities of energy sector enterprises of the Russian Federation for the development of energy efficiency management system due to digitalization processes is considered. Practical examples of the creation, implementation and development of digital technologies at existing thermal power plants and thermal networks aimed at reducing the energy intensity of electric and thermal energy production, the transition from a system of scheduled preventive repairs to repairs according to the actual condition of equipment: digital counterparts of thermal power plants, digital nodes of thermal networks, predictive analytics systems and remote monitoring. The purpose, functionality, principles and models of work, the effects obtained from the introduction of digital systems, promising directions for the development of digital technologies are considered. A comparative analysis was carried out to identify the advantages and disadvantages of foreign and domestic systems of digital doubles and predictive analytics developed under the sanctions of unfriendly countries. The key barriers hindering and constraining the processes of full-scale digital transformation of energy industry enterprises are presented. The necessary conditions and motivating factors of state support of domestic business for the successful implementation and development of digital technologies have been established.

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Development of a Cyber-Physical Subsystem for Support and Decision Making of Managing Oil Production and Transportation Processes Under Uncertainty Conditions

Sagdatullin

Degtyarev

2021

Studies in Systems, Decision and Control

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Outlier Detection in Predictive Analytics for Energy Equipment

Cited by 8 publications

References 13 publications

Predictive Control Algorithm for A Variable Load Hybrid Power System on the Basis of Power Output Forecast

Predictive Control Algorithm for A Variable Load Hybrid Power System on the Basis of Power Output Forecast

Ensuring Energy Efficiency of Thermal Power Plants and Heating Networks by Means of Digital Transformation

Development of a Cyber-Physical Subsystem for Support and Decision Making of Managing Oil Production and Transportation Processes Under Uncertainty Conditions

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