Creating a Portfolio of Large-Scale, High-Quality Synthetic Grids: A Case Study

This paper provides a case study methodology for creating a portfolio of large-scale, high-quality, fictitious but realistic (synthetic) power grid models that are created based on the public generation and load data of 2019 and then upgraded based on predicted generation and load changes by 2030. As the power grids are constantly changing, instead of creating a case from scratch with future data, we present a strategy to upgrade the same grid, to mimic what is needed for real grid planning. The generators are updated based on proposed generators in the queue. The transmission grid is improved to adjust to the changes. The synthetic grid is created over Electric Reliability Council of Texas (ERCOT) footprint in the U.S. and the craeted grids do not disclose any non-public or protected data. For this model, Energy Information Administration (EIA) that provides all necessary details of generators in United States and ERCOT long-term plans are used. The craeted synthetic models are made available at [1] and can be used for research and comparisons in different studies on the future grid with the increased penetration of renewable resources. Visualization technics such as Geographic data views are used and metrics from the American real grids validate the developed grids.