Distributed Model Predictive Frequency Control of Inverter-Based Power Systems

The increasing dominance of inverter-based resources (IBRs) in power generation leads to significantly faster frequency dynamics in modern power systems. Therefore, the secondary control within the classical hierarchical structure must operate significantly faster. However, high communication burdens are inherent to centralized implementations of secondary control. This paper proposes a faster, distributed model predictive control (MPC) scheme for secondary frequency control of inverter-based power systems. The controller predicts the IBRs' local frequency dynamics by considering the impact of the primary control of nearby IBRs. To obtain an optimal model-predictive control problem consisting of distributable subproblems, we introduce a novel trimming procedure to the frequency divider concept, an analytical formulation that estimates the local frequency at system buses. These subproblems have a tunable degree of mutual coupling. The presented distributed MPC achieves fast, error-free frequency regulation in the presence of abrupt load changes while also being robust to communication losses of participating IBRs. By design, the distributed control relies on a sparse neighbor-to-neighbor communication structure and uses local MPC problems that do not scale in complexity with system size. Numerical simulations of the IEEE 39-bus system and an extended CIGRE medium voltage power system demonstrate the fast performance of the proposed distributed MPC scheme for secondary frequency control.