Data-driven Modeling for Grid Edge IBRs: A Digital Twin Perspective of User-Defined Models

TL;DR

This paper presents a data-driven approach to create accurate digital twin models of inverter-based resources (IBRs) for grid applications, addressing discrepancies between manufacturer models and real-world performance.

Contribution

It introduces a method to emulate IBR behavior using measurement data, enabling real-time and long-term system planning with user-defined models.

Findings

High accuracy in emulating IBR responses in both phasor and EMT domains

Effective for grid forming and grid following inverters under various conditions

Improves reliability of system studies by matching field measurements

Abstract

Recent Odessa disturbance events have brought attention to the challenges associated with the interaction between Inverter-Based Resources (IBRs) and the transmission and distribution system. The NERC event diagnosis report has highlighted several issues, emphasizing the need for continuous performance monitoring of these IBRs by system operators. Key areas of concern include the mismatch of control and protection performance of IBRs between the original equipment manufacturer (OEM)-provided models and field measurements. The inability to replicate the realistic response can result in incorrect reliability and resilience studies. In this paper, we developed an approach on how to emulate the behavior of an IBR using measurement data obtained for system operators to utilize in real-time and long-term planning. Two experiments are conducted in the phasor domain and electromagnetic transients (EMT) domain to emulate the behavior for grid forming and grid following inverters under various operating conditions and the effectiveness of the proposed model is demonstrated in terms of accuracy and ease of utilizing user-defined models (UDMs).