This paper presents a novel virtual synchronous machine controller for converters in power systems with a high share of renewable resources. Using an LQR-based optimization technique, the optimal state feedback gain is determined to adaptively adjust the emulated inertia and damping constants according to the frequency disturbance in the system, while simultaneously preserving a trade-off between the critical frequency limits and the required control effort. Two control designs are presented and compared against the open-loop model. The proposed controllers are integrated into a state-of-the-art converter control scheme and verified through EMT simulations.
In this paper, the Unit Commitment (UC) problem in a power network with low levels of rotational inertia is studied. Frequency-related constraints, namely the limitation on Rate-of-Change-of-Frequency (RoCoF), frequency nadir and steady-state frequency error, are derived from a uniform system frequency response model and included into a stochastic UC that accounts for wind power and equipment contingency uncertainties using a scenario-tree approach. In contrast to the linear RoCoF and steady-state frequency error constraints, the nadir constraint is highly nonlinear. To preserve the mixed-integer linear formulation of the stochastic UC model, we propose a computationally efficient approach that allows to recast the nadir constraint by introducing appropriate bounds on relevant decision variables of the UC model. For medium-sized networks, this method is shown to be computationally more efficient than a piece-wise linearization method adapted from the literature. Simulation results for a modified IEEE RTS-96 system revealed that the inclusion of inertia-related constraints significantly influences the UC decisions and increases total costs, as more synchronous machines are forced to be online to provide inertial response.
A large-scale integration of renewable generation,usually interfaced to the network through power electronics,has led to an overall decrease in power system inertia. This paper presents novel insights on the fundamental stability properties of such systems. For that purpose, a uniform set of Differential-Algebraic Equations (DAEs) describing a generic,low-inertia power system has been developed. A full-order, state-of-the-art control scheme of both synchronous and converter-based generators are included, with the latter differentiating between the grid-forming and grid-following mode of operation. Furthermore, the dynamics of transmission lines and loads are captured in the model. Using modal analysis techniques such as participation factors and parameter sensitivity, we determine the most vulnerable segments of the system and investigate the adverse effects of the underlying control interference. Finally, the appropriate directions for improving the system stability margin under different generation portfolios have been proposed.
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