Selecting the PID Controller Settings for an Automatic Generation Control Device in a Power System

  • Kahramon R. ALLAEV
  • Tohir F. MAHMUDOV
DOI: https://doi.org/10.24160/0013-5380-2023-2-50-59
Keywords: electric power system, automatic generation control, PID controller, particle swarm algorithm, stability

Abstract

The integration of renewable generation facilities into integrated power systems entails new challenges for maintaining a reliable and safe electric power infrastructure. It is necessary to expand the use of automatic generation control devices to ensure the ability to control the modes of power systems with a significant share of renewable energy sources. The generation control devices can be used not only for frequency control, but also for maintaining the inter-area wheeling in interconnected power systems. The article suggests application of the particle swarm method, which is one of evolutionary optimization methods, to find optimal parameter settings for proportional-integral-differentiating (PID) controllers of the automatic generation control device. The mathematical description of electric power system elements is given, and a structure of automatic generation control is given. The tuning parameters of the PID controllers of the automatic generation control device based on the particle swarm method, as well as some of classical optimization methods, have been determined. The results of tuning PID controllers obtained by different methods in the form of frequency variation characteristics in power system parts, as well as the torques of an equivalent steam turbine in response to power fluctuations in one of the power system parts are compared.

Author Biographies

Kahramon R. ALLAEV

(Tashkent State Technical University n.a. Islam Karimov, Tashkent, Uzbekistan) – Professor of the Power Plants, Networks and Systems Dept., Academician of the Academy of the Uzbekistan Republic Sciences, Dr. Sci. (Eng.).

Tohir F. MAHMUDOV

(Tashkent State Technical University n.a. Islam Karimov, Tashkent, Uzbekistan) – Associate Professor of the Power Plants, Networks and Systems Dept., PhD.

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#
1. Guterres A. Carbon Neutrality by 2050: the World’s Most Urgent Mission [Electron. resource], URL: https://www.un.org/sg/en/content/sg/articles/2020-12-11/carbon-neutrality-2050-the-world’s-most-urgent-mission (Date of appeal 10.10.2022).
2. Allaev К.R. Sovremennaya energetika i perspektivy ee razvitiya (Modern Energy and its Development Prospects) / By Ed. akad. A.U. Salimov. Tashkent: Fan va tehnologiyаlar, 2021, 953 p.
3. Ullah K. et al. Automatic Generation Control Strategies in Conventional and Modern Power Systems: A Comprehensive Over-view. – Energies, 2021, 14 (9), DOI:10.3390/en14092376.
4. Daood E.A., Bhardwaj A.K. Automatic Load Frequency Control of Three-Area Power System Using ANN Controller with Parallel AC/DC Link. – International Journal of Emerging Trends & Technology in Computer Science, 2016, vol. 5 (4), pp. 127–131.
5. Bevrani H., Ghosh A., Ledwich G. Renewable Energy Sources and Frequency Regulation: Survey and New Perspectives. – Renewable Power Generation, IET, 2010, vol. 4, No.5, pp. 438–457, DOI:10.1049/iet-rpg.2009.0049.
6. Sahab M.G., Toropov V.V., Gandomi A.H. A Review on Traditional and Modern Structural Optimization: Problems and Techniques. – Metaheuristic Applications in Structures and Infrastructures, 2013, pp. 25–47? DOI:10.1016/B978-0-12-398364-0.00002-4.
7. Arain B.A. et al. Design of PID Controller Based on PSO Algorithm and Its FPGA Synthesization. – International Journal of Engineering and Advanced Technology, 2018, vol. 8 (2), pp.201–207, DOI:10.13140/RG.2.2.12639.10400.
8. Al-Saedi W. et al. PSO Algorithm for an Optimal Power Controller in a Microgrid. – IOP Conference Series: Earth and Environmental Science, 2017, vol. 73 (1), DOI: 10.1088/1755-1315/73/1/012028.
9. Nurmatov O. Large Pumping Stations as Regulators of Power Systems Modes. – Rudenko International Conference “Methodological Problems in Reliability Study of Large Energy Systems”, 2020, vol. 216, DOI.:10.1051/e3sconf/202021601097.
10. Devi N.R., Biate R.L. A New Displacement Based PSO Algorithm Optimized PI Controller for Speed Control of a DC Motor. – International Journal of Scientific & Engineering Research, 2016, vol. 7(4), pp. 1271–1277.
11. Allaev К.R., Mirzabaev A.M. Matrichnye metody analiza malyh kolebaniy elektricheskih sistem (Matrix Methods for the Analysis of Small Oscillations of Electrical Systems). Ташкент: Fan va tehnologiyаlar, 2016, 432 p.
12. Abdul-Lateef W.E., Huayier A.F. Recovery Energy Residual in Servo Pneumatic Systems by Using PID Controller Based on Particle Swarm Optimization (PSO). – Journal of Mechanical Engineering Research and Developments, 2020, vol. 43, No. 7, pp. 279–291.
13. Chouket M., Abdelkafi A., Krich L. Tuned Controller’s Gain Tested under Grid Voltage Sags Using PSO Algorithm. – Journal of Electrical Power & Energy Systems, 2018, vol. 2(1), pp. 6–18, DOI: 10.26855/jepes.2018.07.001.
14. Bhatt V.K., Bhongade S. Design of PID Controller in Automatic Voltage Regulator (AVR) System Using PSO Technique. – International Journal of Engineering Research and Applications, 2013, vol. 3 (4), pp.1480–1485.
15. Redoy M.S. et al. Load Frequency Control of an Inter Connected Power System Using PSO Based PID Controller. – International Conference on Advancement in Electrical and Electronic Engineering, 2022, DOI: 10.1109/ICAEEE54957.2022.9836435.
16. Tousi S.M.A., Mostafanasab A., Teshnehlab M. Design of Self Tuning PID Controller Based on Competitional PSO. – 4th Conference on Swarm Intelligence and Evolutionary Computation, 2020, DOI: 10.1109/CSIEC49655.2020.9237318.
17. Panda A. et al. A PSO Based PIDF Controller for Multiarea Multisource System Incorporating Dish Stirling Solar System. – International Conference on Intelligent Computing and Control Systems, 2019, pp. 1458–1462, DOI: 10.1109/ICCS45141.2019.9065804.
18. Nie W. et al. A Tuning Method for PID Controller Parameters Based on Particle Swarm Optimization (PSO). – Chinese Automation Congress (CAC), 2020, pp. 497–501, DOI: 10.1109/CAC51589.2020.9327536.
19. Francis G.S. et al. A Novel PSO Based Fuzzy Controller for Robust Operation of Solid-State Transfer Switch and Fast Load Transfer in Power Systems. – IEEE Access, 2022, vol. 10, pp. 37369–37381, DOI: 10.1109/ACCESS.2022.3165021.
20. Veerasamy V. et al. A Hankel Matrix Based Reduced Order Model for Stability Analysis of Hybrid Power System Using PSO-GSA Optimized Cascade PI-PD Controller for Automatic Load Frequency Control. – IEEE Access, 2020, vol. 8, pp. 71422–71446, DOI: 10.1109/ACCESS.2020.2987387.
21. Patel R.B. et al. Enhancing Optimal Automatic Generation Control in a Multi-Area Power System with Diverse Energy Resources. – IEEE Transactions on Power Systems, 2019, vol. 34 (5), pp. 3465-3475, DOI: 10.1109/TPWRS.2019.2907614.
22. Simpson-Porco J.W. On Area Control Errors, Area Injection Errors, and Textbook Automatic Generation Control. – IEEE Transactions on Power Systems, 2021, vol. 36(1), pp. 557–560, DOI: 10.1109/TPWRS.2020.3029418.
Published
2022-12-19
Issue
No 2 (2023): Issue № 2
Section
Article