ADP-based intelligent frequency control via adaptive virtual inertia emulation

This paper proposes a novel virtual inertia controller for converters in power systems, which can solve the system's nonlinearity for frequency support. First, the system dynamics are formulated as a nonlinear state-space, in which the reciprocal of inertia is modeled as control input. Correspondingly, a cost function is defined by considering frequency deviation and rate of change of the frequency, which can preserve a tradeoff between critical frequency limits and respective control energy. Following, the optimal frequency regulation problem is solved by using an online adaptive dynamic programming method, where the actor and critic neural networks are constructed to approximate the optimal control input and optimal cost function, respectively. After that, the small-signal analysis is provided to identify the stability of the converter under the proposed controller. Finally, simulation results verify that the frequency response of the system is significantly improved, while retaining more DC side energy.