Algorithms to detect and damp power oscillations in electric power systems

Examensarbete för masterexamen

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Typ: Examensarbete för masterexamen
Master Thesis
Titel: Algorithms to detect and damp power oscillations in electric power systems
Författare: Ullah, Nayeem Rahmat
Olasumbo, Okuboye
Sammanfattning: In this thesis algorithms to detect, characterize and damp power oscillations in electric power systems, in the area of 0.1 10 Hz were designed. The algorithms were based on local measurements of V & I only as well as on both local measurements and phase angle differences between voltage vectors in different parts of the power system. A synchronized Phasor Measurement Unit (PMU), provided by ABB, was used to obtain the phase angle difference between two buses, and in this way, power oscillations could be detected. To create power oscillations, three-phase faults were applied. In addition, measurements on a 400V-power system model available at the department were carried out. In order to damp power oscillations, load switching i.e. breaking resistors was used. Time domain simulations were done in SIMPOW to verify the algorithms. The power system model of the department was modeled in SIMPOW as a 400kV system and simulations were carried out on it. Three phase faults were applied to obtain transient instabilities. These instabilities were characterized and were damped out. These studies were done offline. It was found that the angle difference signal derived from PMU proved to be a reliable indicator of power swing. Moreover, a result was that resistive load switching with appropriate value improves both transient stability margin and damping of the power swing.
Nyckelord: Elektroteknik och elektronik;Electrical Engineering, Electronic Engineering, Information Engineering
Utgivningsdatum: 2004
Utgivare: Chalmers tekniska högskola / Institutionen för elteknik
Chalmers University of Technology / Department of Electric Power Engineering
URI: https://hdl.handle.net/20.500.12380/2668
Samling:Examensarbeten för masterexamen // Master Theses



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