Email this article 
Genetic algorithm in problems of operational-technological control of electric networks in post-emergency modes
- Authors: Vlatskaya L.A.1, Semenova N.G.1, Semenov A.M.1
-
Affiliations:
- Orenburg State University
- Issue: Vol 31, No 12 (2025)
- Pages: 630-636
- Section: Modeling and optimization
- Published: 15.12.2025
- URL: https://journals.eco-vector.com/1684-6400/article/view/702028
- DOI: https://doi.org/10.17587/it.31.630-636
- ID: 702028
Cite item
Open Access
Access granted
Subscription or Fee Access
Abstract
Development of a software resource for selecting the best option for a post-emergency electrical network scheme in the context of digitalization of the electric power industry is one of the priority tasks of the Russian economy. The solution to this problem in the work is proposed to be implemented by means of a genetic algorithm adapted by the authors. It is proposed to select the best option for the topology of a post-emergency electrical network by means of a multi-criteria assessment of each of them. The article presents the results of software development that can be used by operational dispatch personnel to prevent and eliminate technological disturbances in the electrical network. Testing of the algorithm was performed, which showed the reliability of the developed software resource and an increase in the speed of the process of detecting an accident and making a decision on its elimination.
About the authors
L. A. Vlatskaya
Orenburg State University
Author for correspondence.
Email: l_sem@mail.ru
Cand. Tech. Sc., Associate Professor
Russian Federation, OrenburgN. G. Semenova
Orenburg State University
Email: ng_sem@mail.ru
Dr. Ped. Sc., Cand. Tech. Sc., Professor
Russian Federation, OrenburgA. M. Semenov
Orenburg State University
Email: ng_sem@mail.ru
Cand. Tech. Sc., Associate Professor
Russian Federation, OrenburgReferences
- Lubarski J. Y. Computer support for dispatching control of equipment in power systems. Methodological development, Moscow, IPK public services, 2004.
- Lubarski J. Y. Intelligent information systems, Moscow, Science, 1990.
- Reizlin V. I. Numerical methods of optimization: a tutorial, Tomsk, Publishing house of Tomsk Polytechnic University, 2011, 105 p.
- Semenova L. A., Inzhevatova A. O., Salimov R. M. Analysis of optimization methods in solving problems of selecting installation locations and power of compensating devices, University complex as a regional center of education, science and culture [Electronic resource]: materials of the All-Russian scientific and methodological conference, Orenburg, Publishing house of OSU, 2017, pp. 513—516.
- Delfanti M., Granelli G., Marannino P., Montagna M. Optimal Capacitor. Placement Using Deterministic and Genetic Algorithms, IEEE Trans. Power Systems, 2000, Aug, vol. 15, no. 3.
- Kremer O. B., Podvalny S. L. Software implementation of solving optimization problems using the genetic algorithm method, Vestnik of VSTU, 2017, pp. 23—24.
- Semenov A. M., Vlatskaya L. A. Fundamentals of artificial intelligence: P.2, Orenburg, Publishing house of OSU, 2023, 148 p.
- Mathew T. V. Genetic Algorithm. Indian Institute of Technology Bombay, Mumbai-400076. 2005, available at: https://docviewer.yandex.ru/view/2020955166/ (accessed: 13.12.2024).
- Semenova N. G., Dyakonov А. A. Software package for searching for disabled equipment in the ES, Electrical engineering systems and complexes, 2024, no. 2 (63), pp. 50—59.
- Semenova N. G., Dyakonov А. A. Optimization of the topology of the 6—10 kv electrical network based on genetic algorithms, Power engineering: state, problems, prospects: proceedings of the XIV All-Russian Scientific and Technical Conference, Orenburg, Publishing house of OSU, 2023, pp. 261—265.
- Semenova N. G., Dyakonov А. A. Formation of schemes of post-emergency and repair modes of operation of the electric network [electronic resource]: application program № 45016 09.07.2024, Orenburg, Publishing house of OSU, UFER, 2024.
- Platt E. L. Network Science with Python and NetworkX Quick Start Guide, Packt Publishing, 2019, 190 p.
Supplementary files
