In diesel-hybrid autonomous power systems, a reduced number of diesel generators supply the power to the load and control the frequency of the system in isolation from the utility grid. In these type of systems, frequency variations of consequence are more likely to occur than in large interconnected power grids, since they feature a relatively small generation capacity and rapid changes in power demand. If generators are not able to maintain frequency within prescribed operational limits during a transient, the assistance of other components is required in order to avoid major disruptions in the power system. In this thesis the use of a virtual synchronous machine (VSM) to support dynamic frequency control in a diesel-hybrid autonomous power system was investigated. The proposed VSM consisted in the control of the grid-interface converter of an energy storage system in order to emulate the inertial response and the damping power of a synchronous generator. Furthermore, the damping function of the proposed VSM used an estimated value of the stabilization frequency of the grid, which allowed it to provide proper damping power when the system operated in frequency droop mode. Theoretical and experimental results showed a satisfactory performance of the proposed VSM, which effectively reduced the frequency nadir in 34 %, on average, for different values of the droop factor of the grid-forming genset. Finally, self-tuning algorithms were designed to find optimal parameters for the VSM in order to minimize the amplitude and rate of change of the frequency variations, and the power flow through the energy storage. Simulations results showed that the self-tuning VSM achieved a performance similar to the constant parameters VSM, while reducing the power flow through the energy storage in up to 58 %.
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