A Data-driven Approach to Grid Impedance Identification for Impedance-based Stability
Challenge and objectiv
Instability caused by inappropriate damping design of grid-connected converters under specific grid impedance makes the grid impedance estimation a crucial issue.
Work performed
To guide the design of system controllers to reach a more stable and adaptive system. To deal with various operating conditions, a three-stage data-driven approach for grid impedance identification with three different frequency ranges is proposed. The motivation is to take advantage of massive data coming from measurement and/or simulation.
Significant results
Clustering is used to partition the processed impedance data.
A high order grid impedance model is generated for each frequency range, in accordance with the practice of resonance mitigation design.
Impact for distribution system innovation
A more stable and flexible system is achieved by an improved controller design and tuning.
