Automated Data–Driven Model Extraction and Validation of Inverter Dynamics with Grid Support Function

Subedi, Sunil; Poudel, Bidur; Aslami, Pooja; Fourney, Robert; Rekabdarkolaee, Hossein Moradi; Tonkoski, Reinaldo; Hansen, Timothy M.

doi:10.1016/j.prime.2023.100365

Cited by 4 publications

References 12 publications

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Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies

Subedi,

Vasquez‐Plaza,

Andrade

et al. 2024

IET Renewable Power Gen

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Electric distribution networks increasingly host distributed energy resources based on power electronic converter (PEC) toward active distribution networks (ADN). Despite advances in computational capabilities, electromagnetic transient models are limited in scalability because of their reliance on exact data about the distribution system and each of its components. Similarly, the use of the DER_A model, which is intended to examine the combined dynamic behavior of many DERs, is limited by the difficulty in parameterization. There is a need for improved dynamic models of DERs for use in large power system simulations for stability analysis. This paper proposes an aggregate model‐free, data‐driven approach for deriving a dynamic partitioned model (DPM) of ADNs. Detailed residential distribution feeders were first developed, including PEC‐based DERs and composite load models (CMLDs), from which the aggregated DPM was derived. The performance was evaluated through various case studies and validated against the detailed ADN model and state‐of‐the‐art DER_A model with CMLD. The data‐driven DPM achieved a of over 90%, accurately representing the aggregated dynamic behavior of ADNs. Furthermore, the DPM significantly accelerated the simulation process with a computational speedup of 68 times compared to the detailed ADN and a 3.5 times speedup compared to the DER_A CMLD model.

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Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies

Subedi,

Vasquez‐Plaza,

Andrade

et al. 2024

IET Renewable Power Gen

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Data-Driven Modeling of Grid-Forming Inverter Dynamics Using Power Hardware-in-the-Loop Experimentation

Guruwacharya,

Chakraborty,

Saraswat

et al. 2024

IEEE Access

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Recently, there is rapid integration of power electronic converter (PECs) into the power grid. Most of these PECs are grid-following inverters, where weak grid operation becomes an issue. Research is now shifting focus to grid-forming (GFM) inverters, resembling synchronous generators. The shift towards converter-based generation necessitates accurate PEC models for assessing system dynamics that were previously ignored in conventional power systems. Data-driven modeling (DDM) techniques are becoming valuable tools for capturing the dynamic behavior of advanced control strategies for PECs. This paper proposes using power hardware-in-the-loop experiments to capture dynamic GFM data in the application of DDM techniques. Furthermore, the paper derives an analytical approach to obtaining a mathematical model of GFM inverter dynamics and compares it with the DDM. A square-chirp probing signal was employed to perturb the active and reactive power of the load inside an Opal-RT model. The dynamic response of the GFM inverter, including changes in frequency and voltage, was recorded. This data was then used in a system identification algorithm to derive the GFM DDMs. The effectiveness of DDM is cross-validated with an analytical approach through experimental simulation studies, and the goodness-of-fit for both approaches is compared. Both approaches show more than 85% accuracy in capturing the dynamic response of GFM inverters under different loading conditions.INDEX TERMS Data-driven modeling, grid-forming inverter, power hardware-in-the-loop, power system dynamics, real-time digital simulator, system identification.

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Experimentation in Exploring Photovoltaic Inverter Dynamics Under Different Irradiance Levels Through a Data-Driven Approach

Poudel,

Guruwacharya,

Subedi

et al. 2024

IEEE Access

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Automated Data–Driven Model Extraction and Validation of Inverter Dynamics with Grid Support Function

Cited by 4 publications

References 12 publications

Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies

Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies

Data-Driven Modeling of Grid-Forming Inverter Dynamics Using Power Hardware-in-the-Loop Experimentation

Experimentation in Exploring Photovoltaic Inverter Dynamics Under Different Irradiance Levels Through a Data-Driven Approach

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