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Power engineering: research, equipment, technology

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Online electric network capacity assesment

https://doi.org/10.30724/1998-9903-2020-22-3-51-59

Abstract

Reliability of power supply to consumers and the efficient use of energy resources are priority tasks in the process of operational dispatch control of the energy system. Limitations of the throughput capacity of the electric network increases the value of the non-released power reserve, which in case of violation of the normal mode at one electric power facility can lead to a system accident. The aim of the work is to develop an algorithm for assessing the throughput of the electric network. In this study of the steady-state operating modes of the power system, a method is proposed for online modeling of the parameters of the electric power regime and its verification in a real scheme for determining the throughput of the electric grid. To solve the tasks posed in the work, we used: the theory of multivariate experiment, the theory of systems of linear equations, methods of mathematical modeling, software and computer systems Cosmos. The regression function is used to simulate the power flow over a network element. The methods based on the linearized and complete models with the measured values are compared and estimated using the correlation coefficient. The method can be used in the practice of supervisory control and research organizations in solving problems of improving the characteristics of the regimes, planning and operating the power system in real time, as well as the development of electric networks and power systems. The efficiency of the proposed method was verified during the experiment.

About the Authors

A. I. Motovilov
Northern (Arctic) Federal University
Russian Federation
Aleksei I. Motovilov


I. I. Solovejev
Northern (Arctic) Federal University
Russian Federation
Ivan I. Solovejev


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For citations:


Motovilov A.I., Solovejev I.I. Online electric network capacity assesment. Power engineering: research, equipment, technology. 2020;22(3):51-59. (In Russ.) https://doi.org/10.30724/1998-9903-2020-22-3-51-59

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ISSN 1998-9903 (Print)
ISSN 2658-5456 (Online)