Numerical Methods Coupled with Richardson Extrapolation for Computation of Transient Power Systems
DOI:
https://doi.org/10.17230/ingciencia.13.26.3Keywords:
Power system transient stability, Richardson extrapolation, dynamic equationsAbstract
The numerical solution of transient stability problems is a key element for electrical power system operation. The classical model for multi-machine systems is defined as a set of non-linear differential equations for the rotor speed and the generator angle for each electrical machine, this mathematical model is usually known as the swing equations. This paper presents how to use direct Richardson extrapolation of several orders for the numerical solution of the swing equations and compares it with other commonly used implicit and explicit solvers such as Runge-Kutta, trapezoidal, Shampine and Radau methods. A numerical study on a simple three machine system is used to illustrate the performance and implementation of algebraic Richardson extrapolation coupled to several solution methods. Normally, the order of accuracy of any numerical solution can be increased when Richardson Extrapolation is used. A numerical example is provided for an electrical grid consisting of three machines and nine buses undergoing a disturbance. It is shown that in this case Richardson extrapolation effectively increases the order of accuracy of the explicit methods making them competitive with the implicit methods.
Downloads
References
M. Watanabe, Y. Mitani, K. Tsuji, A numerical method to evaluate power
system global stability determined by limit cycle, IEEE Transactions on
Power Systems 19 (4) (2004) 1925–1934. doi:10.1109/TPWRS.2004.836205.
J. H. Chow, K. W. Cheung, A toolbox for power system dynamics and
control engineering education and research, IEEE Transactions on Power
Systems 7 (4) (1992) 1559–1564. doi:10.1109/59.207380.
F. Milano, Semi-implicit formulation of differential-algebraic equations for
transient stability analysis, IEEE Transactions on Power Systems PP (99)
(2016) 1–10. doi:10.1109/TPWRS.2016.2516646.
L. Shampine, Solving 0 = f(t, y(t), y(t)) in matlab, Numerical Mathematics
(2002) 291 – 310. doi:10.1515/JNMA.2002.291.
E. Hairer, G. Wanner, Stiff differential equations solved by radau methods,
Journal of Computational and Applied Mathematics 111 (12) (1999) 93 –
doi:http://dx.doi.org/10.1016/S0377-0427(99)00134-X.
URL http://www.sciencedirect.com/science/article/pii/
S037704279900134X
A. Aubry, P. Chartier, On the structure of errors for radau ia methods
applied to index-2 daes, Applied Numerical Mathematics 22 (1) (1996) 23
– 34. doi:http://dx.doi.org/10.1016/S0168-9274(96)00023-2.
URL http://www.sciencedirect.com/science/article/pii/
S0168927496000232
K. S. Shetye, T. J. Overbye, S. Mohapatra, R. Xu, J. F. Gronquist, T. L.
Doern, Systematic determination of discrepancies across transient stability
software packages, IEEE Transactions on Power Systems 31 (1) (2016) 432–
doi:10.1109/TPWRS.2015.2393813.
A. Singh, S. Parida, A multiple strategic evaluation for fault
detection in electrical power system, International Journal
of Electrical Power & Energy Systems 48 (2013) 21 – 30.
doi:http://dx.doi.org/10.1016/j.ijepes.2012.11.033.
URL http://www.sciencedirect.com/science/article/pii/
S0142061512006862
A. Paul M. Anderson, Power System Control and Stability, Wiley, 2002.
W. John J. Grainger, Power system analysis, McGraw-Hill, 1994.
P. K. Iyambo, R. Tzoneva, Transient stability analysis of the ieee
-bus electric power system, in: AFRICON 2007, 2007, pp. 1–9.
doi:10.1109/AFRCON.2007.4401510.
A. Farraj, E. Hammad, D. Kundur, A cyber-physical control framework
for transient stability in smart grids, IEEE Transactions on Smart Grid
PP (99) (2016) 1–10. doi:10.1109/TSG.2016.2581588.
C. Rehtanz, X. Guillaud, Real-time and co-simulations for the de-
velopment of power system monitoring, control and protection, in:
Power Systems Computation Conference (PSCC), 2016, pp. 1–20.
doi:10.1109/PSCC.2016.7541030.
S. Teleke, Modeling and comparison of synchronous condenser and svc,
Master’s thesis, Chalmers University Of Technology (2006).
Z. Zlatev, K. Georgiev, I. Dimov, Studying absolute stability properties
of the richardson extrapolation combined with explicit runge kutta
methods, Computers & Mathematics with Applications 67 (12) (2014)
– 2307, efficient Algorithms for Large Scale Scientific Computations.
doi:http://dx.doi.org/10.1016/j.camwa.2014.02.025.
URL http://www.sciencedirect.com/science/article/pii/
S0898122114000960
Y. C, H. Dag, Detailed model for power system transient stability analysis,
Journal of Engineering & Computer Science IJECS-IJENS 13 (2) (2012) 1
– 5.
D. XIE, A new numerical algorithm for efficiently implementing implicit
runge-kutta methods, Department of Mathematical Sciences. University of
Wisconsin, Milwaukee, Wisconsin, USA (2009) 1 – 17.
R. Zarate-Minano, T. V. Cutsem, F. Milano, A. J. Conejo, Secur-
ing transient stability using time-domain simulations within an optimal
power flow, IEEE Transactions on Power Systems 25 (1) (2010) 243–253.
doi:10.1109/TPWRS.2009.2030369.
S. Sharma, S. Kulkarni, A. Maksud, S. R. Wagh, N. M. Singh, Transient
stability assessment and synchronization of multimachine power system
using kuramoto model, in: North American Power Symposium (NAPS),
, 2013, pp. 1–6. doi:10.1109/NAPS.2013.6666837.
S. Ekinci, A. Demiroren, Transient stability simulation of multi-machine
power systems using simulink, Electrical & Electronics Engineering 15 (2)
(2015) 1 – 8.
Q. M. R. M. A. Salam, M. A. Rashid, M. Rizon, Transient stability analysis
of a three-machine nine bus power system network, Engineering Letters
(1) (2014) 1 – 7.
F. Dorfler, F. Bullo, Kron reduction of graphs with applications to electrical
networks, IEEE Transactions on Circuits and Systems I: Regular Papers
(1) (2013) 150–163. doi:10.1109/TCSI.2012.2215780.
W. H. Press, S. A. Teukolsky, W. T. Vetterling, B. P. Flannery, Numer-
ical Recipes 3rd Edition: The Art of Scientific Computing, 3rd Edition,
Cambridge University Press, New York, NY, USA, 2007.
MATLAB, version R2015, The MathWorks Inc., Natick, Massachusetts,
J. C. Butcher, Implicit runge-kutta processes, Mathematics of Computation
(85) (1964) 50–64.
URL http://www.jstor.org/stable/2003405
D. Sli, Endre; Mayers, An Introduction to Numerical Analysis, Cambridge
University Press, 2003.
Digsilent powerfactory.
Downloads
Published
Issue
Section
License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).


Plagiarism Detection