Enforced Coherent Dynamic Interaction of Grid-forming Inverters in Low Inertia Systems

The primary focus of this dissertation is to address the challenges for stable and resilient operation of low inertia power systems (LIPS) dominated by grid-forming inverters (GFMI) with inherent heterogeneity. A cluster of droop-controlled GFMI with heterogeneous parameters such as dissimilar filter parameters, different power ratings, and varying controller gains is analyzed to investigate the dynamic behavior of this heterogeneous cluster. Moreover, the shortcomings of existing control schemes for heterogeneous GFMIs are analyzed during disturbances and transients. Then a forced enclave homogenization (FEH) scheme is proposed to enforce coherent dynamics within the heterogeneous cluster. This control method involves autonomously determining the equivalent inertia of the cluster and then adjusting the droop characteristics to enforce coherency in the cluster of heterogeneous GFMIs. The proposed FEH scheme is validated via multiple case studies that involve various levels of grid disturbance and cluster reconfigurations. It is demonstrated that the proposed FEH scheme is able to effectively enforce coherency in heterogeneous cluster of GFMIs that enables resilient operation of LIPS dominated by GFMIs. Additionally, the seamless merging of two heterogeneous clusters of GFMIs is achieved with minimal synchronization time and without significant frequency and voltage fluctuations after closing the breaker between the clusters. This research is further extended to LIPS involving virtual synchronous generator control (VSG) and droop controlled GFMIs, showcasing that enforcing coherent dynamics mitigates undesired reactive power circulation, active power oscillations, and frequency fluctuations during disturbances. The proposed enforced coherency approach is then applied for determination of accurate aggregate reference model of a cluster of GFMIs, thus enabling accurate representation of multiple GFMIs in a grid cluster with a “single machine” model. Conventional reduced order model technique for network of GFMIs fails to mimic the true dynamics of the heterogeneous network. The proposed insightful aggregate reference model finds applications in different LIPS analysis and operational domains as discussed briefly in this dissertation. The aggregate model is validated by comparing it with full-order circuit model, the results demonstrate that the aggregate reference models accurately capture the system dynamics. This dissertation extends the coherency-based control scheme during fault and post-fault conditions in LIPS, incorporating effective fault detection logic (FDL). The main contribution here is enabling resilient operation of GFMIs in LIPS during large-scale disturbance such as short-circuit fault. The proposed scheme prevents transient instability by inhibiting the acceleration of voltage angle of GFMIs during short-circuit fault. It was shown via hardware-in-loop experimental results that the proposed control scheme facilitates a timely detection of the short-circuit fault and coordinates with voltage restoration scheme and control of GFMI to enable effective fault-ride through operation. Moreover, when the fault is cleared, a seamless transition from fault to normal operation is achieved among the cluster of GFMIs in LIPS. Overall, this dissertation contributes to the understanding and enhancement of the stable and resilient operation of LIPS dominated by GFMIs in various operational conditions.