Hierarchical Distributed Model-Predictive Stabilization Control of Multi-Scale Oscillations in Wind–Solar Hybrid Multi-Microgrids

Abstract

The transition from traditional power systems to smart grids has led to the widespread utilization of multi-microgrids (MMGs) as a medium for integrating renewable energy sources (RES). However, due to the weak damping and low inertia characteristics of interconnected systems, multi-scale oscillation problems inevitably arise during autonomous operation. In order to explore these undesirable oscillation characteristics and achieve effective suppression. Firstly, this paper establishes a wind-solar hybrid MMGs model considering the characteristics of primary energy side and uncertain disturbances, and further reveals the correlation between system states and dominant oscillatory modes through eigenvalue analysis. Meanwhile, modal controllability and observability quantification analysis are employed to optimize the selection of measurement and control signals for the stabilization controller. Secondly, a hierarchical distributed model predictive stabilization control (HDMPSC) strategy with two-level oscillation control loops is innovatively proposed, where lower-level controllers are designed to address local modes and upper-level controllers work collaboratively to effectively mitigate poorly damped inter-area modes. Besides, the operational constraints are included in all stabilization controllers, providing a more feasible and reliable solution space. Finally, time-domain simulation and hardware-in-the-loop (HIL) experimental results verify the effectiveness of the proposed control scheme.