Theoretical and Practical Investigation of Stability Performance for Power Regulation in Hydroelectric Power Plants

Öz

Hydroelectric power plants are the insurance of the interconnected system in order to provide fast energy to the system compared to other fossil fueled power plants. Hydroelectric power plants control the balance between the energy it supplies to the interconnected system and the pressurized water it uses with a system based on the fully automatic control principle. The quality of the energy supplied to the interconnected system depends entirely on this automatic control mechanism. In this study, mathematical models of the mechanisms that affect the automatic control system during the generation of energy in hydroelectric power plants are formed. Transfer functions of the obtained mathematical models are calculated by laplace transform. With the calculated transfer functions, the responses of the units of a hydroelectric power plant to the change of the amount of energy produced under different operating conditions are determined. The obtained data are compared with the actual conditions in a 1330 MW hydroelectric power plant with 8 Francis turbines. It is seen that the mathematical model and the turbine responses in real conditions are similar. In the calculations made at 115, 125, 135, 145 m. net head, the best stability conditions were obtained at 135 m. In addition, as a result of the calculations obtained under different operating conditions, ideal operating conditions are determined to minimize the fluctuations in energy production.

Anahtar Kelimeler

• Renewable Energy
• Hydroelectric Power Plants
• Automatic Control
• Mathematical Models
• Transfer Function

Kaynakça

1. Adhikari, R.C. and Wood, D.H. (2018). Computational analysis of part-load flow control for crossflow hydro-turbines. Energy for Sustainable Development 45:38-45. https://doi.org/10.1016/j.esd.2018.04.003
2. Doolla, S., Bhatti, T.S., and Bansal, R.C. (2011). Load Frequency Control of an Isolated Small Hydro Power Plant Using Multi-pipe Scheme. Electric Power Components and Systems 39. https://doi.org/10.1080/15325008.2010.513362
3. Gencoglu, C., Tor, O.B., Cebeci, E., Yilmaz, O., and Guven, A.N. (2010). Assessment of the effect of hydroelectric power plants' governor settings on low frequency inter area oscillations. In: International conference on power system technology (POWERCON). IEEE.
4. Gonzalez, W.G.,and Garces, A. (2019). Escobar A., Passivity-based control and stability analysis for hydro-turbine governing systems. Applied Mathematical Modelling 68:471-486. https://doi.org/10.1016/j.apm.2018.11.045
5. Gonzalez, W.G., and Montoya, O.D. (2020). Garces A., Standard passivity-based control for multi-hydro-turbine governing systems with surge tank. Applied Mathematical Modelling 79:1-17. https://doi.org/10.1016/j.apm.2019.11.010
6. Guo, W., and Yang, J. (2018). Modelling and dynamic response control for frequency regulation of hydro turbine governing system with surge tank. Renewable Energy 121:173-187. https://doi.org/10.1016/j.renene.2018.01.022
7. Guo, W., and Yang, J. (2018). Stability performance for primary frequency regulation of hydro-turbine governing system with surge tank. Applied Mathematical Modelling 54:446-466. https://doi.org/10.1016/j.apm.2017.09.056
8. Khodabakhshian, A., and Hooshmand, R. (2010). A new PID controller design for automatic generation control of hydro power systems. Electrical Power and Energy Systems 32:375-382. 10.1016/j.ijepes.2009.11.006.

9. Kundur, P., Balu, N.J., and Lauby, M.G. (1994. Power system stabi lity and control. New York: McGraw-Hill.
10. Liu, X., Kong, X., and Lee, K. (2016). Distributed model predictive control for load frequency control with dynamic fuzzy valve position modelling for hydro–thermal power system. IET Control Theory and Applications. 10. 2016. 10.1049/iet-cta.2015.1021.
11. Ming, B., Liu, P., Guo, S., Zhang, X., Feng, M., and Wang, X. (2017). Optimizing utility-scale photovoltaic power generation for integration into a hydropower reservoir by incorporating long- and short-term operational decisions. Appl Energy 204:432–45.
12. Munoz-Hernandez, G.A., Mansoor, S.P., and Jones, D.L. (2013). Modelling and Controlling Hydropower Plants. Springer. Doi 10.1007/978.1.4471.2291.3
13. Shanab, B.H., Elrefaie, M.E., and El-Badawy, A.A. (2020). Active control of variable geometry Francis Turbine. Renewable Energy 145:1080-1090. https://doi.org/10.1016/j.renene.2019.05.125
14. Sharif, A., Raza, S.A., Ozturk, I., and Afshan, S. (2019). The dynamic relationship of renewable and nonrenewable energy consumption with carbon emission: A global study with the application of heterogeneous panel estimations. Renewable Energy 133:685-691. https://doi.org/10.1016/j.renene.2018.10.052
15. Sharma, G., Nasiruddin, I., Niazi, K.R., and Bansal, R.C. (2018). ANFIS Based Control Design for AGC of a Hydro-hydro Power System with UPFC and Hydrogen Electrolyzer Units. Electric Power Components and Systems 46:2018. https://doi.org/10.1080/15325008.2018.1446197
16. Wang, W., Li, C., Liao, X., and Qin, H. (2017). Study on unit commitment problem considering pumped storage and renewable energy via a novel binary artificial sheep algorithm. Appl Energy 187:612–626.
17. Weixelbraun, M., Renner, H., Kirkeluten, O., and Lovlund, S. (2013). Damping low frequency oscillations with hydro governors. IEEE PowerTech (POWERTECH). Grenoble.
18. Weldcherkos, T., Salau, A.O., and Ashagrie, A. (2021). Modeling and design of an automatic generation control for hydropower plants using Neuro-Fuzzy controller. Energy Reports 7:6626-6637. https://doi.org/10.1016/j.egyr.2021.09.143
19. Yang, W., Norrlund, P., Bladh, J., Yang, J., and Lundin, U. (2018). Hydraulic damping mechanism of low frequency oscillations in power systems: Quantitative analysis using a nonlinear model of hydropower plants. Applied Energy 212:1138-1152. https://doi.org/10.1016/j.apenergy.2018.01.002
20. Yinsheng, S.U. (2013). Analysis on the CSG’s power oscillation events in recent years (in Chinese). Southern Power Syst Technol. 7:54–7.