Robust Decentralized Dissipative Controller-Based Tie-Line Power Flow Regulation in Multi-Area Power System Networks

Deregulation, real-time markets, contingencies, and increased renewable energy integration often lead to congestion in power system networks. Traditional optimal power flow (OPF)-based methods for congestion mitigation are typically too slow for real-time power flow regulation during contingencies, resulting in conservative system operation. Robust controllers offer a viable alternative by regulating line flows within short timeframes. However, existing observer-based centralized controllers are often unsuitable for large-scale grids due to their reliance on state estimation and system-wide data. To address this, the paper proposes a measurement-based decentralized robust control strategy for power flow regulation in tie-lines. Large grids are partitioned into multiple control areas, each modeled as a polytopic uncertain system with external interconnections. Robust static output feedback controllers are then designed for each area to regulate intra-area and inter-area tie-line flows below specified thresholds. These decentralized controllers use dissipativity theory as a robustness measure and are synthesized using linear matrix inequalities (LMIs), relying solely on local data from each control area. For large-scale networks, the proposed controller can be deployed in real time within each control area by re-dispatching generators and battery energy storage systems (BESSs), using synchrophasor measurements from tie-lines. The paper also provides a theoretical analysis of dissipativity and asymptotic stability for the overall interconnected system. The effectiveness of the proposed decentralized robust controller is demonstrated through simulations on a 16-machine, 68-bus test system and Kundur's 4-machine, 2-area test system, showing its capability to deliver fast and automatic corrective actions for real-time power flow regulation.