Self-Tuning Virtual Synchronous Machine: A Control Strategy for Energy Storage Systems to Support Dynamic Frequency Control

TLDR: In this paper, a virtual synchronous machine (VSM) is used to support dynamic frequency control in a diesel-hybrid autonomous power system, where self-tuning algorithms are used to continuously search for optimal parameters during the operation of the VSM in order to minimize the amplitude and rate of change of the frequency variations and the power flow through the ESS.

Abstract: This paper investigates the use of a virtual synchronous machine (VSM) to support dynamic frequency control in a diesel-hybrid autonomous power system. The proposed VSM entails controlling the grid-interface converter of an energy storage system (ESS) to emulate the inertial response and the damping power of a synchronous generator. In addition, self-tuning algorithms are used to continuously search for optimal parameters during the operation of the VSM in order to minimize the amplitude and rate of change of the frequency variations and the power flow through the ESS. The performances of the proposed self-tuning (ST)-VSM and the constant parameters (CP)-VSM were evaluated by comparing their inertial responses and their damping powers for different scenarios of load variations. For the simulated cases, the ST-VSM achieved a similar performance to that of the CP-VSM, while reducing the power flow through the ESS in up to 58%. Moreover, in all the simulated scenarios, the ST-VSM was found to be more efficient than the CP-VSM in attenuating frequency variations, i.e., it used less energy per Hertz reduced.