Hybrid Transient Stability Analysis Solution for Power System Stability Studies

References

[1] Kundur Prabhashankar (1994), “Power System Stability and Control”, Electric Power Research Institute, Tata MacGraw Hill Publishing Company Ltd, 7 Patel Nager, New Delhi, India.

[2] Stagg G.W., and A. H. El-Abiad (1968), “Computer Methods in Power Systems” (New York:McGraw-Hill,).

[3] Kundur P. and J. Paserba (2004) “Definition and classification of power system stability,” IEEE Trans. on Power Systems, 19, 2, pp. 1387-1401.

[4] Lu Qiang, and Mei Shengwei (2000) “Important basic researches on powersystems facing 21 century,” Natural Science Development, vol. 10, no.10, pp. 870-876.

[5] BahbahA.G, and A. A Girgis (2004), “New method for generators angles and angular velocities prediction for transient stability assessment of multi-machine power systems using recurrent artificial neural network,” IEEE Transactions on Power Systems, vol. 19, no. 2, pp.1015-1022.

[6] Wu Wei, TANG Yong, SUN Huadong, and XU Shiyun (2012), “A Survey on Research of Power System Transient Stability Based on Wide-Area Measurement Information,” Power System Technology, vol. 36, no. 9,pp. 81-87.

[7] Dongrong Jiang, Zhao Li and Lian Zhang (2013), “Transient Stability Analysis of Power System Using Improved Least Square Method and Energy Function ”3rd International Conference on Electric and Electronics (EEIC Published by Atlantis Press.

[8] Ning Zhou, Daniel J. Trudnowski, John W. Pierre, and William A.Mittelstadt (2008), “Electromechanical Mode Online Estimation UsingRegularized Robust RLS Methods,” IEEE Transactions on PowerSystems, vol. 23, no. 4, pp. 1670-1681.

[9] Park R. H (1929), System Stability as a Design Problem. In AIEE Transactions, 48, pp. 170-194.

[10] Mania Pavella (1997), Power System Stability and Control Comparative Analysis, In IFAC Control of Industrial Systems, Belfort France.

[11] Pai M.A. (1981), Power System Stability Analysis by the Direct Method of Lyapunov. North-Holland Publishing Company, Amsterdam.

[12] Chiang H. D., F.F. Wu and P.PVaraiya (1994), A BCU method for Direct Analysis of Power System Transient Stability. In IEEE Transactions, PWRS-9, pp. 1194-2000.

[13] Grujic Lj.T, A.A. Martynyuk and M. Ribben-Pavella (1987). Large Scale Systems Stability Under Structural and Singular Perturbations. Lecture notes in Control and Information Sciences Series, Springer Verlag, Berlin Germany.

[14] Bergen A. R. and D.J. Hill (1981), A Structure Preserving Model for Power System Stability Analysis. In IEEE Transactions on PAS, PAS-100, pp.25-33.

[15] Athay T., R.R Sherkat, R. Podmore, S. Virmani and C. Puech (1979), Transient Energy Stability Analysis. In System Engineering for Power: Emergency Operating State Control- Section IV, US Dept. of Energy Publication, No CONF-790904-P1.

[16] Kakimoto N., Y. Ohsawa and M. Hayashi (1980), Transient Stability Analysis of Multimachine Power System with Field Flux Decays via Lyapunov’s Direct Method. In IEEE Transactions, PAS-99, pp. 1819-1827.

[17] Ribbens-Pavella M., P.G. Murthy and J.L. Horward (1981), An Acceleration Approach to Practical Stability Domain Estimation in Power System. In Electrical and Power System Modelling and Simulation (j. Robert and w. Midvidy, Eds), J.C BaltwerAgentina, Scientific Publishing Co., pp. 3-10.

[18] Pai. M.A (1989), Energy Function Analysis for Power System Stability. Kluwer Academic Publishers, Boston USA.

[19] Fonseca L.G.S., and I.C Decker (1985), Iterative Algorithm for Critical Energy Determination in Transient Stability of Power System. In IFAC Symposium on Planning and Operation Electric Energy Systems, Rio de Janeiro, Brazil, South America.

[20] Rahimi F.A., and G. Schaffer (1987), Power System Transient Stability Indexes for Online Analysis of ‘Worst Case’ Dynamic Contingencies. In IEEE Transactions, PWRS-2, pp. 660-668.

[21] Xue Y., T.H Van Cutsem and M. Ribbens-Pavella (1988), A Simple Direct Method for Fast Transient Stability Assessment of Large Power Systems. In IEEE Transactions, PWRS-3, pp, 400-412.

[22] Maria G.A., C. Tang and J. Kim (1990), Hybrid Transient Stability Analysis. In IEEE transactions, PWRS-5, pp. 348-394.

[23] Zhang, Y., L. Wehenkel, P. Rousseaux and M. Pavella (1997). SIME: a Hybrid Approach to Fast Transient Stability Assessment and Contingency Selection. In International Journal of Electrical Power and Energy Systems, Vol. 19, No. 3, March, pp. 195-208.

[24] Wehenkel L, C. Lebrevelec, M. Trotignon and J. Batut (1997), A Probablistic Approach to the Design of Power System Protection Schemes against blackouts. Proceedings of IFAC/CIGRE Symposium on Control of Power System and Power Plants, Beiljing, China.

[25] Wehenkel L, and M. Pavella (1996), Why and Which Automatic Learning Approaches to Power System Security Assessment. In Proceeding of the IMACS-IEEE Conference on Computational Engineering in Systems Applications, Lille France.

[26] Vijay Vittal (1982), Power System Transient Stability using the Critical Energy of Individual Machines, Digital Repository, IOWA State University Capstones, Thesis and Dissertation.

[27] Gear C.W, (1971), Numerical Initial Value Problems in Ordinary Differential Equations, Prentice-Hall.

[28] Kimbark E. N (1948), Power System Stability, Vol. I, Elements of Stability Calculations, New York John Wiley and Sons Inc.

[29] Gore V. (1971), Criteria of Stability of Electric Power System, A report. Union Institute of Scientific and Technological Information and The Academy of Sciences U.S.S.R, Electric Technology an Electric Power Serries, Mosco.

[30] Magnusson P .C (1947), Transient Energy Method of Calculating Stability. AIEE Transactions, PAS-66 pg. 747-755

[31] Gless, G. E (1966), Direct Method of Lyapunov Applied to Transient Power System Stability. IEEE Transactions, PAS-85, pg. 164-179

[32] El-Abiad A. H and Nagappan K. (1966), Transient Stability Regions of Multi-machine Power System. IEEE Transactions PAS-85, pg. 158-168.

[33] Houben I., L. Wehenkel, and M. Pavella (1997), Genetic Algorithm based k-Nearest Neighbors. In Proceedings of Conference on Control of Industrial Applications, Belfort, France

[34] Jacquemart Y., L. Wehenkel, T. Van Custen an P. Pruvot (1995), Statistical Approaches to Dynamic Security Assessment: The database generation problem. In Proceeding of SIPOWER’95, 2nd IFAC Symposium on Control of Power Plants and Power Systems., pp. 234-246.

[35] Dy-Liacco T.E (1996), On the applicability of Automatic Learning to Power System Operation. In Revue E. Special Issue on Apprentissage Automatique, Applications aux Reseaux d’ Energie Electricque.

[36] Stevenson W. D (1975), Elements of Power System Analysis, 3rd Edition, McGraw Hills.

[37] Ferraro, Robert Matthew (2021), "Method of Modeling the Swing Equation Using Time Synchronized Measurements". Dissertations and Theses. Paper 5729. https://doi.org/10.15760/etd.7600

[38] Ralston A. and Wilf H.S. (1962), Mathematical Methods for Digital Computers, John Wiley and Sons.

[39] Kundur Prabhashankar, (1967), Digital Simulation and Analysis of Power System Dynamics Performance, PhD Thesis, University of Toronto Canada.

[40] Carnahan B, Luther H.A and Wilkes J.O. (1969), Applied Numerical Methods, John Wiley and Sons.

[41] Chi-Keung Tang (1984), Evaluation of Direct Method for Power System Transient Stability Analysis, M. Eng, degree thesis, University of Toronto, Canada.

[42] Snapp R. (2000), CS 295: Pattern Recognition, Course Notes, Department of Computer Science, University of Vermont, (http://www.cs.uvm.edu/~snapp/teaching/CS295PR/whatispr.html).

[43] Tutorials Point (2021), Artificial Neural Network: Quick guide. Retrieved 25/12/21, https://www.tutorialspoint.com/artificial_neural_network/artificial_neural_network_quick_guide.htm.

[44] Sauer P. W. and Pai M. A., (1998), Power System Dynamics and Stability Upper Saddle River, New Jersey: Prentice Hall.

[45] Zhang Q. J., F. Wang and V. K. Devabhaktuni (1999), “Neural Network Structure for RF and Microwave Applications” IEEE AP-S Antennas and Propagation Int. Symp., Orlando Fl, pp. 2576-2579.

@article{1703300,
      author = {Anionovo Ugochukwu Edebeani, Dr. Emmanuel C. Ezendiokwelu, Augustine Nonso Nwoye, Prof. Josiah C. Onuegbu},
      title = {Hybrid Transient Stability Analysis Solution for Power System Stability Studies},
      journal = {Iconic Research And Engineering Journals},
      year = {2022},
      volume = {5},
      number = {9},
      pages = {437-458},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/17033002.pdf},
      abstract = {Power system transient instability has become inevitable in recent times, due to geometrically increasing electrical energy demand leading to more complex networks. This is of paramount importance to power system utility engineers and other energy players in the industry. In lieu of this, this article carried out a complete survey of power system transient stability methods developed over the past ten decades. The research revealed that, the following methods; the Time Domain Simulation Method (TDSM), Direct Method (DM), and Automatic Learning Method (ALM) have so far been developed. While considering the strength and weakness of each method; hybrid solutions leading to combination of two methods which takes advantage of the merit of each method while evading their corresponding demerits were explored and developed. However, despite the maturity of all the methods developed so far, there is yet to exist a general-purpose transient stability analysis method because they were designed to operate independently. To fill this gap, this research article deployed structural design and algorithmic method to develop a novel Hybrid Transient Stability Analysis Solution (HTSAS) geared at taking advantage of the strength of the three methods so far developed; TDSM, DM, and ALM in conjunction with real-time computing through Supervisory Control and Data Acquisition (SCADA) System. The HTSAS structure was designed and an algorithm developed to illustrate the functionalities expected of the solution. These include, ability to sieve out power system network states, in the form of voltage, current and power delivery through the SCADA interface, parallel computation between TDSM//DM and seamless data storage to the associated database. The generated database is made available to the ALM module automatically, which then analyses them and produce accurate controllability and stability margins. This solution represents the first attempt to combine and synchronize TDSM, DM and ALM operations in a single solution. The programming languages used for the HTSAS development is web 3.0 languages which is a universal platforms that powers platform independent and mobile friendly solutions. The developed solution was tested in the laboratory using power system assembly which supplied current, voltage and power to the solution. The solution computed network parameters state and stored same with the associated data file in the control database. The output of the HTSAS unit was found to learn the pattern of network state variation and thus able to develop the necessary actuation signal required by the control unit.  Given these results and further future refinement and adaptation, this solution is envisaged to be a general-purpose transient stability analysis solution.},
      keywords = {Hybrid Transient Stability Analysis Solution, parallel computation, seamless data storage, database, real-time computing, software algorithm.},
      month = {March},
  }