OEDI SI/Scenarios/EMT Data Generation​ for high penetration grid

From Open Energy Information

EMT Data Generation​ for high penetration grid​ Summary

  • Date Created: 2024/06/26
  • Organization: ORNL
  • Objective: Provide Python scripts and documentations to generate EMT data using PSCAD software. The model is also provided in this scenario, which is an IEEE 9-bus power grid with 2 IBRs (Inverter Based Resources). The dataset generated using this scenario can be utilized to train and validate artificial intelligence(AI)/machine learning (ML) models for fault detection, identification, and classification.
  • Use Case: Electromagnetic transient (EMT) Data Generation
  • Methodology
    • Inputs
      • Outputs
        • Configuration


          Docker Container

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          Run Locally

          http://localhost:8080/edit_scenario?EMT Data Generation​ for high penetration grid
              Run Locally


          Input Data

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            Output Data

            Download output data at:

              References


                Back to Electromagnetic transient (EMT) Data Generation



                "Provide Python scripts and documentations to generate EMT data using PSCAD software. The model is also provided in this scenario, which is an IEEE 9-bus power grid with 2 IBRs (Inverter Based Resources). The dataset generated using this scenario can be utilized to train and validate artificial intelligence(AI)/machine learning (ML) models for fault detection, identification, and classification." cannot be used as a page name in this wiki.


              1. This scenario provides a Python script to generate EMT data using PSCAD software. The entire data generation process is automated and can be implemented with a single click of the Python script.
                The IEEE 9-bus system with two IBR models in PSCAD is used as input with the Python script. Users can modify the Python script by changing fault settings such as locations, fault types, fault durations, and fault impedance for different fault conditions. Additionally, they can modify the simulation time, output file name, plotting timestep, and simulation timestep directly from the Python script. Instantaneous voltages and currents at each bus in the IEEE 9-bus system are generated as the output of the Python script.
                The Python script includes:
                1. Opening PSCAD.
                2. Varying fault impedance, fault location, fault duration, and fault type.
                3. Generating comprehensive datasets for each fault condition.# Post-processing the output data to convert it into CSV format.
                4. Quitting PSCAD after the data generation is complete.
              2. IEEE 9-bus system with two IBR models in PSCAD
              3. Python script (download from: [1])
              4. PSCAD generates the data in its native format (.out)
              5. The Python script converts and stores the output dataset in CSV format (download from: [2])
              6. With the high penetration of IBRs in power grids, high-fidelity EMT simulation is necessary to analyze the interaction of inverters with the rest of the power grid. Research has shown that transient events in the power grid, where IBRs are affected, can be replicated using high-fidelity or detailed models of IBRs and the surrounding regions [1][2]. To replicate a similar behavior in a benchmark system, the IEEE 9 bus with 2 IBRs test system is designed. Two of the synchronous generators in the IEEE 9-bus benchmark system are modeled as synchronous condensers. These models replicate the typical behavior of the retired synchronous generators being used as the synchronous condensers. This system has a high penetration of renewables (~50% of renewable penetration). The PSCAD model of the IEEE 9 bus with 2 IBRs provided in this scenario consists of a high-fidelity or detailed switched system EMT dynamic model of the IBRs [1] and the EMT model of the IEEE 9 bus [3].
              7. No docker container available, model can be download from: https://code.ornl.gov/2qx/oedi/-/tree/main
              8. https://code.ornl.gov/2qx/oedi/-/tree/main
              9. https://code.ornl.gov/2qx/oedi/-/tree/main
              10. J. Choi and S. Debnath, "Electromagnetic Transient (EMT) Simulation Algorithm for Evaluation of Photovoltaic (PV) Generation Systems," 2021 IEEE Kansas Power and Energy Conference (KPEC), Manhattan, KS, USA, 2021, pp. 1-6, doi: 10.1109/KPEC51835.2021.9446234.
              11. S. Debnath et al., "EMT Simulation of Large PV Plant & Power Grid for Disturbance Analysis," 2023 IEEE PES Innovative Smart Grid Technologies Latin America (ISGT-LA), San Juan, PR, USA, 2023, pp. 345-349, doi: 10.1109/ISGT-LA56058.2023.10328215.
              12. IEEE 9 bus EMT model, convert from PSSE model [3]
                13. Retrieved from "https://openei.org/w/index.php?title=OEDI_SI/Scenarios/EMT_Data_Generation​_for_high_penetration_grid&oldid=1084887"