Inappropriate machine learning application in real power industry cases

Khalyasmaa, Alexandra I.; Matrenin, Pavel; Eroshenko, Stanislav A.

doi:10.11591/ijece.v12i3.pp3023-3032

Cited by 3 publications

(4 citation statements)

References 23 publications

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“…The authors of [16] present the experience in the development and implementation of decision support systems based on machine learning algorithms in various tasks of the electric power industry, analyze the main errors and the consequences of their influence on the results of the operation of such systems in the electric power industry. This is done on the example of the problem of predicting the photovoltaic generation introduced into the technological activities of electric power network [16].…”

Section: Short Response Time To Changes In Measured Valuesmentioning

confidence: 99%

“…The effectiveness of these functions was shown when describing the situations and generating advice for dispatching personnel in emergencies. These functions use the platform of expert systems, and the formalism of forming the reasoning models of technologists is applied [16]. The real-time operation of the ADCS complex requires that the architecture of the software of this complex be considered.…”

Section: Short Response Time To Changes In Measured Valuesmentioning

confidence: 99%

“…It uses information about the actuation of relay protection and automatic devices. IA2 (agent "repair") is initiated at events disconnecting equipment (which are fixed by IA1 and processed in IA4), given (emergency) shutdown requests for the respective items of equipment, and adjustment, where necessary, the appropriate limitations of operating conditions [12,[16][17][18][19][20][21][22][23][24][25][26].…”

Section: Short Response Time To Changes In Measured Valuesmentioning

confidence: 99%

See 2 more Smart Citations

Principles of Constructing Artificial Intelligence Systems and their Application in Electrical Power Industry

Хренников¹,

Lyubarsky²,

Khrennikov

2021

Energy Systems Research

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The paper considers two historically established directions of building artificial intelligence systems: expert systems and neural networks. The consideration is given to parallels and analogies between the work of neural networks and the work of the human brain, the hierarchical structure of the brain, the history of the neurocybernetics development, and the theoretical foundations of neural networks. Models of reasoning of specialists are used in expert systems based on production rules (expressions of the form "if ..., then"). The main semantic elements in neural networks are models of neurons and layers of neurons (input, output, intermediate). Large amounts of data are associated with neuron models (the so-called "big data").The paper gives examples of using neural networks and artificial intelligence systems in the electric power industry for the electrical equipment state monitoring, operational dispatch control of electrical networks, for the analysis of emergencies, and intelligent functions of automated dispatch control systems (ADCS).

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Section: Short Response Time To Changes In Measured Valuesmentioning

confidence: 99%

Section: Short Response Time To Changes In Measured Valuesmentioning

confidence: 99%

Section: Short Response Time To Changes In Measured Valuesmentioning

confidence: 99%

See 1 more Smart Citation

Principles of Constructing Artificial Intelligence Systems and their Application in Electrical Power Industry

Хренников¹,

Lyubarsky²,

Khrennikov

2021

Energy Systems Research

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“…Intelligent inter-distance control [4] in vehicle convoy has the main objective of developing and implementing preventive assistance to keep a safe distance between the reference vehicle and the vehicle in front [5], which ensures the stability of the vehicle and passenger com-fort. This work contributes to the application of new intelligent control [6] laws for a vehicle. The scientific researchers show that the control strategies used for inter-distance control are based on the laws of physics [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Intelligent Control of Inter Distance in Convoy of Vehicles Using Model-Free Control and Algebraic Filter

Bouras,

Bekaik

2024

IJTDI

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Road accidents are the leading cause of death; this increase is usually due to speeding. For road safety, intelligent systems have been designed to keep a constant speed and a safe distance between vehicles in a convoy. This article focuses on the synthesis of an interdistance control system using intelligent methods and algorithms. The main idea presented in this article is to implement a model-free control for physical model "spring-damper" known as intelligent control based on an algebraic filter. Our comparative analysis extends beyond comparing the use of a simple derivative and an algebraic filter for intelligent control. We also take into account the effect of noise directly affecting the model's behaviour to demonstrate the robustness of our approach. Through MATLAB simulations, we highlight that our approach exhibits better robustness and stable tracking in the interdistance control system.

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Review of Existing Tools for Software Implementation of Digital Twins in the Power Industry

Iumanova,

Matrenin,

Khalyasmaa

2024

Inventions

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Digital twin technology is an important tool for the digitalization of the power industry. A digital twin is a concept that allows for the creation of virtual copies of real objects that can be used for technical state analysis, predictive analysis, and optimization of the operation of power systems and their components. Digital twins are used to address different issues, including the management of equipment reliability and efficiency, integration of renewable energy sources, and increased flexibility and adaptability of power grids. Digital twins can be developed with the use of specialized software solutions for designing, prototyping, developing, deploying, and supporting. The existing diversity of software requires systematization for a well-informed choice of digital twin’s development tool. It is necessary to take into account the technical characteristics of power systems and their elements (equipment of power plants, substations and power grids of power systems, mini- and microgrids). The reviews are dedicated to tools for creating digital twins in the power industry. The usage of Digital Twin Definition Language for the description data of electromagnetic, thermal, and hydrodynamic models of a power transformer is presented.

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Inappropriate machine learning application in real power industry cases

Cited by 3 publications

References 23 publications

Principles of Constructing Artificial Intelligence Systems and their Application in Electrical Power Industry

Principles of Constructing Artificial Intelligence Systems and their Application in Electrical Power Industry

Intelligent Control of Inter Distance in Convoy of Vehicles Using Model-Free Control and Algebraic Filter

Review of Existing Tools for Software Implementation of Digital Twins in the Power Industry

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