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

Bidur Poudel, Nischal Guruwacharya, Sunil Subedi, Ujjwol Tamrakar, Felipe Wilches-Bernal, Hossein Moradi Rekabdarkolaee, Timothy M. Hansen, Reinaldo Tonkoski

Research output: Contribution to journalArticlepeer-review

Abstract

As conventional direct connections of synchronous generators are being phased out, inverter-based resources (IBRs) with grid support functions are increasingly being integrated into power systems. This transition requires the development of accurate dynamic models for IBRs to predict how power systems will adapt to varying levels of IBRs penetration, establish grid code requirements, and ensure compliance. This study introduces an active probing signal-based data-driven modeling technique to accurately derive the dynamics model of a smart photovoltaic inverter operating in Volt-Watt and Freq-Watt modes, in compliance with the IEEE 1547-2018 standard. The paper focuses on investigating how the dynamics of the PV inverter model respond to fluctuations in solar irradiance, utilizing real-time digital simulator experimentation. The experimental analysis demonstrates that the amplitude of dynamics fluctuates with changes in irradiance across both operational modes and confirms the active power's dependence on irradiance levels. Furthermore, the nature of inverter dynamics varies distinctly between the different modes of activation. Critically, our findings indicate that dynamic models require DC-gain adjustments to accommodate contrasting irradiance levels, highlighting a negative gradient linear relationship between the DC-gain of each model and the irradiance.

Original languageEnglish
JournalIEEE Access
DOIs
StateAccepted/In press - 2024

Funding

This work was supported in part by the U.S. Department of Energy Office (DOE) of Science, Office of Electricity Microgrid Research and Development Program, and Office of Energy Efficiency and Renewable Energy Solar Energy Technology Office through Established Program to Stimulate Competitive Research (EPSCoR) under Grant DE-SC0020281; and in part by the National Science Foundation (NSF) under Grant OIA-2316399. The work of Sunil Subedi was supported by Oak Ridge National Laboratory funded by the U.S. Department of Energy, Office of Electricity, and Office of Energy Efficiency and Renewable Energy under Contract DE-AC05-00OR22725. The work of Ujjwol Tamrakar was supported by Sandia National Laboratories funded by the U.S. Department of Energy, Office of Electricity (OE), Energy Storage Division under Grant SAND2024-15170J. This work is supported in part by U.S. Department of Energy Office (DOE) of Science, Office of Electricity Microgrid Research and Development Program, and Office of Energy Efficiency and Renewable Energy Solar Energy Technology Office under the EPSCoR Grant DE-SC0020281 and in part by NSF under Grant OIA-2316399. The work at Sandia National Laboratories (Ujjwol Tamrakar) is supported by the U.S. Department of Energy, Office of Electricity (OE), Energy Storage Division. The work at Oak Ridge National Laboratory (Sunil Subedi) is supported by the U.S. Department of Energy, Office of Electricity, and Office of Energy Efficiency & Renewable Energy under Contract DE-AC05-00OR22725.

FundersFunder number
U.S. Department of Energy Office
Oak Ridge National Laboratory
U.S. Department of Energy
Office of Electricity
Solar Energy Technologies OfficeDE-SC0020281
Sandia National LaboratoriesSAND2024-15170J
Established Program to Stimulate Competitive ResearchDE-SC0020281
National Science FoundationOIA-2316399
Office of Energy Efficiency and Renewable EnergyDE-AC05-00OR22725

    Keywords

    • Data-driven modeling
    • IEEE 1547-2018
    • PV inverter dynamics
    • real-time digital simulator
    • solar irradiance

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