Approaches for Oscillation Monitoring and Damping of Wind Integrated Power Grid
1 online resource (205 pages) : PDF
University of North Carolina at Charlotte
Wind energy has emerged as one of the major choice of sustainable energy especially due to lower generation cost and push for alternative sources of clean energy. How- ever, the technological difference in wind generation is certain to create changes in dynamics of the power system that is mostly dominated by synchronous generators. For example, the dynamic stability of the system can be affected by wind genera- tors such as Doubly Fed Induction Generators (DFIG) due to reduced inertia, new transmission lines, lower number of Power System Stabilizers (PSS) and so on. It is, therefore, essential to carefully analyze the impact of growing wind penetration on the stability of power system. This dissertation will focus specifically on the impact of DFIG based wind generation on power system stability. The ability to rapidly control the active and reactive power makes DFIG a dynamic source that can support the grid during disturbances and thus, can be used to enhance the dynamic stability of the system. In this research, first, modal analysis of DFIG integrated power grid is investigated. Second, based on the modal analysis and signal selection, active and reactive power PSS is designed. Then a power system oscillation damping controller design for DFIG is investigated. Various approaches for power oscillation damping is evaluated using local signals or remote signals. Moreover, to address the uncertainty in power system model used in planning, a measurement based approach for estimat- ing the proper power system model is designed. The modal analysis of the estimated model can be used as an analytical tool to predict the performance of the system in time-domain. Further, a control approach is designed and implemented using the proposed identification on a small-scale and large-scale power grid.
DOUBLY FED INDUCTION GENERATORDYNAMIC STABILITYOSCILLATION DAMPING CONTROLPOWER SYSTEMSYSTEM IDENTIFICATIONWIND POWER
Kakad, YogendraCox, RobertYoung, David
Thesis (Ph.D.)--University of North Carolina at Charlotte, 2018.
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