USING GENETIC ALGORITHMS TO SOLVE OPTIMIZATION PROBLEMS IN POWER ENGINEERING
Keywords:
Genetic algorithms, Power engineering, Optimization, Natural selection, Power quality, Mathematical modelingAbstract
Against the backdrop of continuous productivity growth in the electric power industry, the implementation of advanced technologies and the improvement of various technological process control systems have become critical issues. One of the most promising developmental directions is the application of optimization algorithms based on the principles of natural selection
References
1.Tsoy, Yu. R., & Spitsyn, V. G. (2006). Genetic Algorithm / Knowledge Representation in Information Systems: a tutorial. Tomsk: TPU Publishing House.
2. Panchenko, T. V. (2007). Genetic Algorithms: a teaching manual (Y. Y. Tarasevich, Ed.). Astrakhan: "Astrakhan University" Publishing House.
3. Kureychik, V. M. (1998). Genetic Algorithm. Izvestiya SFedU. Engineering Sciences, (2).
4. Tsoy, Yu. R. (2006). On Mathematical Models of Evolutionary Algorithms. Perspective Information Technologies and Systems, (2), 42-47.
5. Voronin, V. A. (2015). On Optimization of Power Quality Indicators. Bulletin of the Kuzbass State Technical University, (4), 110.
6.Tarasenko, V. V. (2010). Determining Possible Ways of Developing the Power Supply System of the SUSU Campus Based on a Genetic Algorithm. Bulletin of the South Ural State University, (32), 208.
8.Polubotko, D. V., & Chukreev, Yu. Ya. (2009). Using the Genetic Algorithm Method to Find the Optimal Location of PMU Recorders. Elektro Journal, (2). Available at: [http://www.elektro-journal.ru]
9.Popescu, M. C. O. S., Mastorakis, N. E., & Popescu-Perescu, L. (2009). Applications of Genetic Algorithms in Electrical Engineering. International Journal of Mathematical Models and Methods in Applied Sciences, (3).
10.Momoh, J. A., El-Hawary, M. E., & Adapa, R. (1999). A Review of Selected Optimal Power Flow Literature to 1993. IEEE Transactions on Power Systems, 14(1), 96–111. — Demonstrates the use of aggregated cost functions in power system optimization problems.


