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

TL;DR

This study tackles the challenge of accurately modeling grid-edge inverter-based resources (IBRs) amid evolving system dynamics and incomplete OEM data. It introduces measurement-driven User-Defined Models (UDMs) and a data-driven digital twin framework, built around an Auto-Regressive Moving Average with eXogenous inputs (ARMAX) surrogate, to continuously identify and validate IBR responses from real-time measurements. The approach is demonstrated in both phasor-domain and EMT-domain tests: a modified IEEE 68-bus network with 35 IBRs for GFM/GFL in the phasor domain, and a distribution feeder with residential loads, PV, and EVs for EMT simulations. Results show accurate tracking of $V$, $f$, $P$, and $Q$ (or currents) with low RMSE and the ability to recalibrate online when deviations occur, underscoring the method’s potential for real-time decision support and planning under uncertainty. The work advances data-driven, continual validation methods that support cyber-physical situational awareness and digital twin applications for grid-edge resources and consumer-side generation/load assets.

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).

Figures (13)

• Figure 1: IBR playback modeling- A User-Defined Model in python
• Figure 2: Multi-step time series recursive prediction modeling for IBRs
• Figure 3: Flowchart describes the step-by-step procedure to translate IBR measurements into a UDM using the proposed approach
• Figure 4: Schematic of the phasor-domain positive sequence test model (modified IEEE 68-bus network) with 35 IBRs co-located at the load buses, marked by circles. The network has 16 generators, marked by squares, across 5 different regions (marked by different colors).
• Figure 5: GFM IBR-1 response to a dynamic event in the network; Measurements are obtained from point of connection of IBR-1 with the network under a line trip event (event-A). The phasor domain response is in 1 ms resolution.