This research is about tuning the automatic generator control (AGC) unit within the National Transmission System (NTG) and is intended to provide a set of key insights into problems related to generator control systems oscillations and the possible available solutions. The case study is the Baba Hydroelectric Power Plant in Ecuador. The aim is to model, simulate and validate the controls of the Baba generating units for an optimal and stable response. Both controllers, the Automatic Voltage Regulator (AVR) and Power System Stabilizer (PSS) were tuned using both a component-based approach using an object-orientated tool where the model structure resembles the original system, and a coexisting power flow tool in a signal orientated environment. A key part of this tuning is the adaptation of the model to different operating conditions by testing scenarios where signals ought to be defined before the start of the simulation and others be chosen for visualisation without any limitation, therefore, this paper is about finding a multi-framework environment. Also, the model was disturbed so to observe the field Voltage and terminal voltage values using a simplified and reduced part of the NTG. Results show that a high gain AVR helps the steady state and transient stabilities but may reduce the oscillatory stability and the PSS can provide significant stabilization of such oscillations. The validation strategy uses the average quadratic mean square error statistical method.

1. International Renewable Energy Agency, “Sustainable development goal 7: Energy indicators”. Technical Report. IRENA, 2017. URL: https://www.irena.org/IRENADocuments/Statistical_Profiles/SouthAmerica/Ecuador_SouthAmerica_RE_SP.pdf.
2. Food and Agriculture Organization of the United Nations, “Ecuador General Information”. Technical Report. FAO, 2021. URL: http://www.fao.org/3/Y4347E/y4347e0n.htm.
3. J.P. Hidalgo-Bastidas, R. Boelens, “Hydraulic order and the politics of the governed: The Baba dam in coastal Ecuador”. Water 11, 2019. URL: https://www.mdpi.com/2073-4441/11/3/409.
4. M. Ilic, J. Zaborszky, Dynamics and Control of Large Electric Power Systems. Wiley-IEEE Press, 2000.
5. IEEE Power Engineering Society, IEEE Recommended Practice for Excitation System Models for Power System Stability Studies. Technical Report, 2006.
6. NERC, Steady-State and Dynamic System Model Validation. Technical Report, 2017.
7. A. Elices, L. Rouco, H. Bourles, T. Margotin, “Design of robust controllers for damping interarea oscillations: application to the European power system”. IEEE Transactions on Power Systems 19, 1058-1067, 2004. doi:10.1109/TPWRS.2003.821612.
8. P. Verdugo, J. Játiva, “Metodología de sintonización de parámetros del Estabilizador del Sistema de Potencia -PSS” [Power System Stabilizer parameter tuning methodology -PSS]. Revista Técnica Energía 10, 2014.
9. NASPI, Model Validation Using Phasor Measurement Unit Data. Technical Report, 2015.
10. W. Vargas, P. Verdugo, “Validación e identicaciٕón de modelos de centrales de generación empleando registros de perturbaciones de unidades de medición fasorial, aplicación práctica Central Paute – Molino” [validation and identication of generation plants models using disturbance records from phasor measurement units, practical application Paute – Molino Power Plant]. Revista Técnica Energía 16., 2020.
11. A. Bartolini, F. Casella, A. Guironnet, et al., “Towards pan-european power grid modelling in Modelica: Design principles and a prototype for a reference power system library”, 13th International Modelica Conference, pp. 627-636, 2019.
12. F. P. Demello, C. Concordia, “Concepts of synchronous machine stability as affected by excitation control”. IEEE Transactions on Power Apparatus and Systems PAS-88, 316-329, 1969. doi:10.1109/TPAS.1969.292452.
13. P. Kundur, N.J. Balu, M.G. Lauby, Power system stability and control. New York: McGraw-Hill, 1994.
14. P. Fritzson, Introduction to Modeling and Simulation of Technical and Physical Systems with Modelica. Wiley-IEEE Press, 2011.
15. Consorcio Hidronergético del Litoral, EIA definitivo Proyecto Hidroeléctrico Baba [EAI final Baba Hydroelectric project]. Technical Report, 2006
16. L. Qi, “Modelica Driven Power System Modeling, Simulation and Validation”. (Master’s thesis, Royal Institute of Technology, 2014).
17. T. Van-Cutsem, L. Papangelis, Description, Modeling and Simulation Results of a Test System for Voltage Stability Analysis. Technical Report, 2013.
18. M. Baudette, M. Castro, T. Rabuzin, J. Lavenius, T. Bogodorova, L. Vanfretti, “Openipsl: Open-instance power system library | update 1.5 to itesla power systems library (ipsl): A modelica library for phasor time-domain simulations”. SoftwareX 7, 34-36, 2018. URL: https://www.sciencedirect.com/science/article/pii/S2352711018300050, doi :https://doi.org/10.1016/j.softx.2018. 01.002.
19. D. Mota, Models for Power System Stability Studies, Thyricon(R) Excitation System. Technical Report, 2010.
20. K. Walve, “Modelling of power system components at severe disturbances”, International conference on large high voltage electric systems, 1986.URL: https://e-cigre.org/publication/38-18_1986-modelling-of-power-system-components-at-severe-disturbances.
21. IEEE Power and Energy Society, IEEE Recommended Practice for Excitation System Models for Power System Stability Studies (Revision of IEEE Std 421.5-2005). Technical Report, 2016.
22. K.E. Bollinger, S.Z. Ao, “PSS performance as affected by its output limiter”. IEEE Transactions on Energy Conversion 11, 118-124, 1996. doi:10.1109/60.486585.
23. P.M. Anderson, A.A. Fouad, Power System Control and Stability, Wiley-IEEE Press; 2nd edition, 2002.
24. V. Bari, E. Vaini, V. Pistuddi, A. Fantinato, B. Cairo, B. De-Maria, L.A. Dalla-Vecchia, M. Ranucci, A. Porta, “Comparison of causal and non-causal strategies for the assessment of baroreflex sensitivity in predicting acute kidney dysfunction after coronary artery bypass grafting”. Frontiers in Physiology 10, 2019.
25. E.V. Larsen, D.A. Swann, “Applying Power System Stabilizers part iii: Practical Considerations”. IEEE Transactions on Power Apparatus and Systems PAS100, 3034-3046, 1981. doi:10.1109/TPAS.1981.316411.
26. A. Baharev, A. Neumaier, H. Schichl, “Failure modes of tearing and a novel robust approach”, Proceedings of the 12th International Modelica Conference pp 15-17, 2017.
27. A. Pothen, C.J. Fan, “Computing the block triangular form of a sparse matrix”. ACM Transactions on Mathematical Software. 16, 303-324, 1990. URL: https://doi.org/10.1145/98267.98287, doi:10.1145/98267.98287.
28. P. Tauber, L. Ochel, W. Braun, B. Bachmann, “Practical realization and adaptation of Cellier’s Tearing Method”, Proceedings of the 6th International Workshop on Equation-Based Object-Oriented Modeling Languages and Tools, Association for Computing Machinery, New York, NY, USA. p. 11-19, 2014. URL: https://doi.org/10.1145/2666202.2666204,doi:10.1145/2666202.2666204.
29. M.J. Gibbard, P. Pourbeik, D.J. Bowles, “Small system stability, performance and control of power systems”. University of Adelaide Press, 2015. Adelaide.
30. A. Saltelli, P. Annoni, “How to avoid a perfunctory sensitivity analysis”. Environmental Modelling and Software 25, 1508-1517, 2010. URL: https://www.sciencedirect.com/science/article/pii/S1364815210001180, doi: https://doi.org/10.1016/j.envsoft.2010.04.012.
31. A. Hammer, “Analysis of IEEE Power System Stabilizer Models”. (Master’s Thesis. Norwegian University of Science and Technology, 2011). URL: https://ntnuopen.ntnu.no/ntnu-mlui/bitstream/handle/11250/257120/445805_FULLTEXT01.pdf?sequence=1.

Citations by Dimensions

Citations by PlumX

Crossref Citations

This paper is currently not cited.

No. of Downloads per Month

No. of Downloads per Country