The adaptive under frequency load shedding (UFLS) can
be used to stabilize the system frequency by shedding an
appropriate amount of load depending on the disturbance
occurred. However, not only the total load to be shed is
not minimized in this scheme, but also it may be inaccurate
calculation of power deficit if the system is subjected to
cascading failures during the shedding process. In this
paper, a novel UFLS scheme is presented to minimize the
amount of load shedding and keep the minimum frequency
within the acceptable limit during severe disturbances and
cascading failures. The shed load is minimized using
genetic algorithm (GA) according to an objective function
based on the system frequency. Multi scenarios of
contingences are performed on the proposed system to
collect the training patterns for an artificial neural
network (ANN). The ANN can online determine the
minimum amount of load shedding and keep the frequency
within a safe margin. Although using the proposed scheme
may cause the minimum frequency of the system to be
below the minimum frequency of the adaptive scheme but
the proposed method can perform minimal load shedding
in various disturbance scenarios. Results are provided in
the form of time domain simulations via
MATLAB/SIMULINK. |
