Undergraduate Research on Improving Power Grid Planning Models

Electric grids worldwide are changing and evolving as the grids are modernized and new technologies are introduced and adopted. Solar and wind energy are expected to dramatically increase by 2030, consumption of electricity will likely increase with the addition of electric vehicles and large loads such as bitcoin mining. Accordingly, it is helpful to create open-source grid planning models to reflect these transformations. This paper focuses on updates to a network planning for a Texas 2030 synthetic power system model. Transmission lines of an existing Texas 2016 synthetic power grid are modified to operate under future load and renewable generation scenarios for 2030. The process entails modifying a network model with DC power flow then performing AC Reactive Power Planning (RPP) for AC power flow convergence. In this work, various algorithms are utilized in making alterations to the 2016 grid, resulting in a well-functioning synthetic grid for 2030. Contributions are made towards the transition to clean energy and valuable power flow algorithms are added to the power systems community.