The objective of this work is to study the impact of large scale wind integration in
the dynamic performance of power system. The variable nature of wind generation
has been driving power system operating conditions from a largely predictable one to
highly variable and stochastic. Such changes will have huge impact in the dynamic
performance of the system.
The limitation in dynamic performance is one of the constraints for effective
utilization of available transmission and generation resources. The thesis draws a
qualitative behavior of inter-area mode damping with increased wind penetration.
The factors such as changes in power flow and displacement of conventional
generators, resulting from large scale integration of wind are considered. Another
consequence of wind variability is the changes in controllability and observability
in the context of power system damping control when operating conditions vary
significantly. The modal controllability and observability decide the controller
performance, large variation of which can result in inefficient control effort and poor
stability margin. A controller design methodology using robust signal selection is
presented for power systems with increased variability in operating conditions. The
core of this method is based on stochastic error co-variance matrix of modal residue
due to large variation in operating condition. The work further explores possibility
of using wind farms for damping control using active and reactive power modulation.
Interaction of damping controller with torsional mode of wind turbines is analyzed
and a signal selection criteria is presented to reduce the interaction. Also, selection
of active or reactive power modulation of wind farm for damping control is discussed.
The outcome of this research offers deeper insight into the power system dynamic
problem in the presence of large asynchronous generation such as wind.