Open Access
EPJ Web Conf.
Volume 217, 2019
International Workshop on Flexibility and Resiliency Problems of Electric Power Systems (FREPS 2019)
Article Number 01017
Number of page(s) 9
Published online 15 October 2019
  1. A.J. Wood, B.F. Wollenberg, Power generation, operation, and control (John Wiley & Sons, 2012) [Google Scholar]
  2. J.L. Willems, M. Pandit, Systems, Man and Cybernetics, IEEE Trans. 1(4), (1971) [Google Scholar]
  3. P. Kundur, J. Paserba, V. Ajjarapu, G. Andersson, A. Bose, C. Canizares, N. Hatziargyriou, D. Hill, A. Stankovic, C. Taylor, et al., Power Systems, IEEE Trans.19(3), 1387 (2004) [Google Scholar]
  4. A. Gajdukl, M. Todorovski, L. Kocarev, Stability of power grids: An overview, Eur. Phys. J. Special Topics 223, 2387-2409 (2014) [CrossRef] [EDP Sciences] [Google Scholar]
  5. M. Ribbens-Pavella, D. Ernst, D. Ruiz-Vega, Transient Stability of Power Systems: A Unified Approach to Assessment and Control, Vol. 581 (Springer, 2000) [CrossRef] [Google Scholar]
  6. Chiang, Direct Methods for Stability Analysis of Electric Power Systems (John Wiley & Sons, 2011) [Google Scholar]
  7. Chiang et al., High Performance Computing in Power and Energy Systems (Springer-Verlag, 2013) [Google Scholar]
  8. Machowski et al., Power system dynamics. Stability and control (John Wiley & Sons, 2012) [Google Scholar]
  9. S. Frank, I. Steponavice, S. Rebennack, Optimal power flow: A bibliographic survey I., Energy Systems, 3(3), 221-258, (2012) [CrossRef] [Google Scholar]
  10. D. Mehta, H.D. Nguyen, K. Turitsyn, Numerical Polynomial Homotopy Continuation Method to Locate All The Power Flow Solutions, IET Generation, Transmission & Distribution, 10(12), 2972-2980, (2016) [CrossRef] [Google Scholar]
  11. Ch. Zhai, H.D. Nguyen, Region of Attraction for Power Systems using Gaussian Process and Converse Lyapunov Function – Part I: Theoretical Framework and Off-line Study [arXiv:1906.03590] (2019) [Google Scholar]
  12. S. Boyd, L. Vandenberghe, Convex Optimization. (Cambridge University Press, 2009). [Google Scholar]
  13. P. A. Parrilo. Structured semidefinite programs and semialgebraic geometry methods in robustness and optimization. (PhD thesis, California Institute of Technology, 2000). [Google Scholar]
  14. D. Henrion, M. Korda, Convex computation of the region of attraction of polynomial control systems, IEEE Trans. on Automatic Control, 59(2), 297-312, (2014) [CrossRef] [Google Scholar]
  15. R. Bobiti, M. Lazar. A sampling approach to finding Lyapunov functions for nonlinear discrete-time systems, In Proc. of the European Control Conference (ECC), 561-566, (2016) [Google Scholar]
  16. F. Berkenkamp, R. Moriconi, A. P. Schoellig, A. Krause, Safe learning of regions of attraction for uncertain, nonlinear systems with Gaussian processes, In Proc. of the IEEE Conference on Decision and Control (CDC), 4661-4666, (2016) [Google Scholar]
  17. F. Berkenkamp, M. Turchetta, A. P. Schoellig, A. Krause, Safe model-based reinforcement learning with stability guarantees, In Proc. of the Conference on Neural Information Processing Systems (NIPS), 908-918, (2017) [Google Scholar]
  18. R. S. Sutton, A. G. Barto. Reinforcement Learning, (MIT Press, Cambridge, 2018). [Google Scholar]
  19. P. Jyothi, B. Mallika, M. Laxman Rao, Improve Wind Power Generation by using Servo Motor, IJATIR, 7(10), 1761-1768, (2015) [Google Scholar]
  20. N. Tomin, V. Kurbatsky, H. Guliev, Intelligent Control of a Wind Turbine based on Reinforcement Learning, in Proc. of XVI International Conference on Electrical Machines, Drives and Power Systems ELMA 2019, (2019) [Google Scholar]
  21. H. Yunhai, X. Bingfeng, L. Gen Ping, A Power Control Method for Inverted Pendulum Based on Fuzzy Control, In Proc. of the 2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, (2010) [Google Scholar]
  22. S. M. Richards, F. Berkenkamp, A. Krause, The Lyapunov Neural Network: Adaptive Stability Certification for Safe Learning of Dynamical Systems [arXiv:1808.00924] (2018) [Google Scholar]
  23. F. L. Lewis, D. L. Vrabie, and V. L. Syrmos. Optimal Control (John Wiley & Sons, 2012) [CrossRef] [Google Scholar]
  24. [Google Scholar]
  25. P. Kundur, G. Rogers, D. Wong, L. Wang, M. Lauby, Power Systems, IEEE Trans. 5(4), 1076-1083 (1990) [CrossRef] [Google Scholar]
  26. L. Wang, A. Semlyen, Application of sparse eigenvalue techniques to the small signal stability analysis of large power systems, in Power Industry Computer Application Conference, 358-365, (1989) [CrossRef] [Google Scholar]
  27. W. Wang, Analysis and Damping Control of Power Systems Low-frequency Oscillations, (Springer, New-York, 2016) [CrossRef] [Google Scholar]
  28. Gibbard et al., Small signal stability, control and dynamic performance of power systems, (University Adelaide Press, 2015) [CrossRef] [Google Scholar]
  29. Verghese et al., IEEE Trans. On Power Apparatus and Systems, 101(9), 3126-3134, (1982) [CrossRef] [Google Scholar]
  30. Perez-Arriaga et al., Automatica, 26(2), 215-231, (1990) [CrossRef] [Google Scholar]
  31. Abed et al., Automatica, 36, 1489-1496, (2000) [CrossRef] [Google Scholar]
  32. H. Tawalbeh, Engineering Sciences, 37(2), 226-232, (2010) [Google Scholar]
  33. Arnoldi, Quarterly of Applied Mathematics 9, 17-29, (1951) [CrossRef] [Google Scholar]
  34. Martins, IEEE Trans. on Power Systems 12(1), 245-254, (1997) [CrossRef] [Google Scholar]
  35. Misrikhanov, Ryabchenko, Automation and Remote Control, 69(2), 198-222, (2008). [CrossRef] [Google Scholar]
  36. I. Gaglioti, Monitoring, Control and Protection of Interconnected Power systems. (Springer – Verlag, 2014) [Google Scholar]
  37. Yadykin, Automation and Remote Control, 71(6), 1011-1021, (2010) [CrossRef] [Google Scholar]
  38. Yadykin et al., Int. J. Robust Nonlin. Control, 24, 1361-1379, (2014) [CrossRef] [Google Scholar]
  39. Antoulas, Approximation of Large-Scale Dynamical Systems, (SIAM, Philadelphia, 2005) [Google Scholar]
  40. Baur et al., Archives of Computational Methods in Engineering, 21(4), (2014) [CrossRef] [Google Scholar]
  41. Moore, IEEE Trans. on Automatic Control, AC-26: 17-32, (1981) [CrossRef] [MathSciNet] [Google Scholar]
  42. Fernando, Nicholson, IEEE Trans. Circuits Syst., CAS-31(5), 504-505, (1984) [CrossRef] [Google Scholar]
  43. R. H. Byrne et al. Small Signal Stability of the Western North American Power Grid with High Penetrations of Renewable Generation, in Proc. of IEEE 43rd Photovoltaic Specialists Conference (PVSC), (2016) [Google Scholar]
  44. J.-N. Juang, R. S. Pappa, An eigensystem realization algorithm for modal parameter identification and model reduction, AIAA Journal of Guidance, Control, and Dynamics, 8(5), 620-627, (1985) [CrossRef] [Google Scholar]
  45. J.J. Sanchez-Gasca, J. H. Chow, Performance comparison of three identification methods for the analysis of electromechanical oscillations, IEEE Trans.of Power Syst., 14(3), 995-1002, (1999) [CrossRef] [Google Scholar]
  46. J.J. Sanchez-Gasca, Identification of power system low order linear models using the ERA/OBS method, in Proceedings of the 2004 IEEE PES Power Systems Conference and Exposition, 1, 392-397, (2004) [Google Scholar]
  47. L.L. Grant, M.L. Crow, Comparison of matrix pencil and prony methods for power system modal analysis of noisy signals, in Proc. of the North American Power Symposium (NAPS), (2011) [Google Scholar]
  48. K. Prabha, Power System Stability and Control, (McGraw-ill, Inc., 1994) [Google Scholar]
  49. J. D. Glover, M. S. Sarma, and T. J. Overbye, Power System Analysis and Design, 5th ed. Stamford, CT: Cengage Learning, (2012). [Google Scholar]
  50. RTE, ELIA, STATNETT, PEPITE, ICL, INESC, KTH, KUL, RSE, DTU, and Tractebel, “Formalization of a plausible functional solution,” iTesla Deliverable D1.2, 1–134, (2012). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.