Abstract:
Reduced order modelling of complex autonomous microgrid system is crucial to its small signal
modelling and stability concerns. To reduce the storage requirements and computational time,
the order of such microgrids can be reduced by Model Order Reduction (MOR) techniques. This
paper presents an optimal reduction technique, which retains dominant poles of the original
system and achieves subsequent error minimization through the Particle Swarm Optimization
algorithm (PSO). The 36th order complex microgrid system is reduced to 9th order approximant,
which retains the significant dynamics of the original system. The simulation results reflect the
superiority of the proposed method as compared to the balanced truncation method in terms of
the time and frequency domain analysis of the reduced order equivalents. State perturbation in
the state space model has also been considered in full as well as reduced order system dynamics
and eigenvalue analysis for system stability.
