Laboratory Power System Model Designed for Testing Dynamic Processes
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Identification tests of dynamic and transient processes which occur in a power system are usually based on simulation. Structures of systems used for simulation testing are built from simplified models of power system components. Practically, in order to verify results obtained by simulation, they would have to be compared to data obtained in actual facilities. Research carried out at Kraków University of Technology and contained in the proposed paper shows that simplifications and assumptions used when constructing simulation models often cause a discrepancy between the simulation results and actual variability of the system state. This research was carried out using a five-node laboratory model of a power system built earlier. A full parameter identification process was carried out for this model, thus enabling construction of its computerised equivalent using the Mat lab software suite. The laboratory model which was used as a foundation for the simulation equivalent is a five-node system with a closed structure; it consists of four generation-load nodes and one load only node. Parameters of the components of the laboratory model, like power lines or generator outputs, have been selected in a process of power scaling. Experiments currently performed on the model are aimed at investigating dynamic processes occurring during and after a short-circuit, and at testing procedures for estimating power distribution at a static condition as well as fault containment procedures which are currently under development.
Potamianakis E.G., Vournas C.D.,
Modeling and Simulation of Small
Hybrid Power Systems, IEEE PowerTech
Andersson G., Modelling and
Analysis of Electric Power Systems,
ETH Zurich, 2009.
Cokkinides G.J., Mohagheghi S., A laboratory
setup of a power system scaled model
for testing and validation of EMS applications,
PowerTech, IEEE Bucharest, 2009.
Gomez-Exposito A., Conejo A.J.,
Canizares C., Electric Energy Systems:
Analysis and Operation, CRC Press, 2009.
Miller P., Wancerz M., Wpływ sposobu
wyznaczania parametrów linii 110 kV
na dokładność obliczeń sieciowych,
Przegląd Elektrotechniczny 2014, r. 90, nr 4.
Handke A., Mitkowski E., Stiller J., Sieci
Politechniki Poznańskiej, Poznań 1978.
Yoshihide H., Handbook of Power System
Engineering, Wiley 2007.
Mentor II User guide, Hòa Trinh,
nr 13, 2013.
Dynamic Models for Steam and Hydro
Turbines in Power System Studies, IEEE
Trans. Power Appar. Syst. 1904–1915,
Heffron W.G., Phillips P.A., Effect of
modern aplidyne voltage regulator on
under-excited operation of large turbine
generators, Power Apparatus and Systems,
Part III, Transactions of the American
Institute of Electrical Engineers, 1952,
Mak F.K., Design of nonlinear generator
exciters using differential geometric
control theories, Decision and Control,
Proceedings of the 31st IEEE Conference
Plamitzer A., Maszyny elektryczne,
Simulink Documentation, Simulation
and Model-Based Design, MathWorks.
Norma PN-78 E-04252.
Latek W., Badanie maszyn elektrycznych
w przemyśle, Wydawnictwo Naukowo-
Techniczne, Warszawa 1979.
Shi D. i in., Transmission line parameter
identification using PMU measurements,
European Transactions on Electrical
Power 2011, Vol. 21, s. 1574–1588.
Sanchez-Gasca J.J. i in., Trajectory sensitivity
based identification of synchronous
generator and excitation system parameters,
IEEE Transactions on Power Systems
, Vol. 3, s. 1814–1822.
Tumageanian A., Keyhani A.,
Identification of synchronous machine
linear parameters from standstill step
voltage input data, IEEE Transactions
on Energy Conversion 1995, Vol. 10,
Kacejko P., Machowski J., Zwarcia w systemach