Structure- & Physics- Preserving Reductions of Power Grid Models

The large size of multiscale, distribution and transmission, power grids hinder fast system-wide estimation and real-time control and optimization of operations. This paper studies graph reduction methods of power grids that are favourable for fast simulations and follow-up applications. We present systematic techniques that reduce the grid size while preserving basic functionality in the reduced grid. The reduction is achieved through the use of iterative aggregation of sub-graphs that include general tree structures, lines, and triangles. An important feature of our reduction algorithms is the efficient use of hash-tables to store the sequential reduction of the original grid in the reduced network. This allows for easy introduction of detailed models into the reduced conceptual network and makes the model backward compatible with varying resolution. The performance of our graph reduction algorithms, and features of the reduced grids, are discussed on a real-word transmission and distribution grid. We produce visualizations of the reduced models through open source libraries and release our reduction algorithms with example code and toy data.