Modeling a gas-turbine unit with prognostic regulators of voltage and speed

Object. The article presents the results of computer research, the purpose of which was to develop dynamic models of low-power twin-shaft gas turbine units (GTU) equipped with automatic excitation and speed regulators with predictive links. Methods. Setting up the regulators of the commissioned gas turbine requires complex calculations. The use of algorithms that make it possible to improve the classical regulators with minimal costs allows us to effectively solve the problems of their settings. These include prognostic algorithms that allow you to configure the automatic control system using one parameter - forecast time. The models presented in the article are implemented using the Simulink package of the MATLAB system. Results. The influence of prognostic algorithms on the quality of controlling the voltage and rotor speed of a gas turbine generator in the modes of connecting and dumping loads is studied. Studies have shown that increasing the coefficient of the amplifier of the auto-predictive speed regulator can significantly reduce overshoot and the transition process, and also has a positive effect on voltage regulation. Conclusions. The results made it possible to formulate the following conclusions: the use of prognostic regulators when connecting an additional load to the gas turbine allows you to remove the oscillation, reduce voltage dips, reduce the transient time by 2.5 s; with a sharp load shedding due to the use of prognostic algorithms, it is possible to completely remove the oscillation, reduce the overshoot of the rotor speed and overvoltage at the generator terminals, and also significantly reduce the transient time for speed compared to classical regulators; the use of prognostic algorithms allows us to obtain acceptable quality indicators of transients without the use of complex regulator tuning procedures.

distributed generation, gas turbine units, automatic regulators of excitation and speed, prognostic algorithms

1. Merkuryev GV, Shargin YuM. Ustojchivost' energosistem. In 2 volumes. St. Petersburg: NOU «Centr podgotovki kadrov energetiki», 2008. V. 2. 376 p.

2. Asainov DN, Gusev YuP. Research of dynamic stability and electrodynamic resistence of the gas turbine plants. Bulletin of the Moscow Power Engineering Institute. 2010; 2: 55-61.

3. Ilyushin PV, Filippov SP, Novikov NL. Trebovaniya k manevrennosti gazoturbinnyh i gazoporshnevyh generiruyushchih ustanovok. Metodicheskie voprosy issledovaniya nadezhnosti bol'shih sistem energetiki. 2019;1:343-352.

4. Pikina GA. Princip upravleniya po prognozu i vozmozhnost' nastrojki sistem regulirovaniya odnim parametrom. New in Russian electric power industry. 2014;3:5-13.

5. Bulatov YuN, Kryukov AV, Nguyen Van Huan. Automatic prognostic regulators of distributed generators. International Multi-Conference on Industrial Engineering and Modern Technologies (October 03–04, 2018). Vladivostok: IEEE, 2018;463:1–4. https://doi.org/10.1109/FarEastCon.2018.8602718

6. Centeno P, Egido I, Domingo C, .et al. Review of gas turbine models for power system stability studies. 9th Spanish Portuguese Congress on Electrical Engineering, 2005.

7. Rowen WI. Simplified Mathematical Representations of singleshaft gas turbines in mechanical drive services. Turbo Mach. Int., 1992;33(5):26–32.

8. Oparin DA, Kavalerov BV. O modelirovanii gazoturbinnyh ustanovok pri upravlenii elektrostanciyami maloj i srednej moshchnosti. Bulletin of Perm National Research Polytechnic University. 2014; 12: 5-13.

9. Mohammad Reza Bank Tavakoli, Behrooz Vahidi, Wolfgang Gawlik. An Educational Guide to Extract the Parameters of Heavy Duty Gas Turbines Model in Dynamic Studies Based on Operational Data. IEEE Trans. Power Syst. 2009;24 (3):1366-1374.

10. Bakhmisov OV, Kuznetsov ON. Methods of Simulation of Heavy Duty Gas Turbine Units and Combined Cycle Power Plants for Power Systems Studies. Electricity. 2016;5: 27-34.

11. Meegahapola L. and Flynn D. Characterization of Gas Turbine Lean Blowout During Frequency Excursions in Power Networks. IEEE Trans. Power Syst. 2014; 99: 1–11.

12. Shalan H., Hassan M., Bahgat A. Comparative Study on Modeling of Gas Turbines in Combined Cycle Power Plants. Proc. of the 14th International Middle East Power Systems Conference (MEPCON’10). 2010, pp. 970-976.

13. Bulatov Yu.N, Kryukov AV. Optimization of automatic regulator settings of the distributed generation plants on the basis of genetic algorithm. 2nd International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM). IEEE Conference Publications. 2016. pp. 1-6. doi: 10.1109 / ICIEAM.2016.7911456.

14. Bulatov YuN, Kryukov AV, Huan NV. Methodology of determining forecasting controllers of distributed generation plants. Proceedings of the higher educational institutions. ENERGY SECTOR PROBLEMS. 2016;11-12:84-95.

15. Bushuev VV, Lizalek NN, Novikov NL. Dinamicheskie svojstva energosistem. Moscow: Energoatomizdat. 1995. 320 p.