Advanced High-Fidelity Lumped EMT Grid Modelling & Comparison

Conference · Fri Nov 01 04:00:00 EDT 2019

OSTI ID:1615801

Debnath, Suman ^[1]; Xia, Qianxue ^[2]; Saeedifard, Maryam ^[2]; Arifujjaman, Md ^[3]

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1. ORNL
2. Georgia Institute of Technology, Atlanta
3. Southern California Edison (SCE)

There is increased interest in performing electromagnetic transient (EMT) studies of large power grids for stability purposes. The large power grids may not represent the entire grid, but portions of interest. For example, studies are being performed to identify the impact of extreme events on solar power plants in California that requires the EMT model of the grid in California, but not the complete western interconnection (WI) grid model to which the grid in California is connected. The EMT models of grids are necessary to perform integration studies of large power electronics systems like utility-scale photovoltaic (PV) systems, high-voltage direct current (HVdc) systems, flexible alternating current transmission systems (FACTs), and others. Traditionally, models of grids available to utilities are the transient stability (TS) models. Hence, it assumes significance to identify methods of developing high-fidelity EMT models for portions of the grid (of interest) from the information available in the existing TS models of the entire grid. In this paper, a conversion mechanism along with upgradation based on data-driven methods is applied to develop EMT models of grids. The conversion mechanism utilizes information from TS models of grids to generate EMT models of grids. These models can be extracted for the required portion of the grid. While these models adequately represent the local voltage behaviour of the grid, they are inadequate in representing the frequency behaviour of the grid. The data-driven methods are applied to identify frequency dynamics of the grid, and the EMT models are upgraded with the data-driven methods. The resulting upgraded EMT models of grids can perform the studies mentioned above. These models are tested under contingencies of interest to validate the developed models.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE; USDOE Office of Energy Efficiency and Renewable Energy (EERE)
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1615801
• Country of Publication: United States
• Language: English