Thomas Overbye

This letter presents an algorithm that efficiently and consistently represents, in the positive-sequence power flow, the phase shifts introduced by wye–delta-connected transformers. As is well known, wye–delta transformers impose fixed voltage and current phase shifts in multiples of 30 degrees. Because these shifts do not affect bus voltage magnitudes or branch power flows, they are frequently omitted or modeled inconsistently. However, non-uniform representation of transformer phase shifts can introduce artificial voltage-angle discontinuities that negatively impact Newton-based power flow convergence. To address this issue, the letter introduces the concept of Phase Shift Groups (PSGs), which enforce consistent voltage-angle representation across the power system model. The proposed PSG-aware initialization yields a physically consistent starting point that improves Newton-Raphson convergence robustness compared to conventional flat-start methods. Beyond initialization, PSGs provide a systematic mechanism for data-quality validation, flagging incomplete or inconsistent transformer connection data. Scalability is demonstrated on systems with up to 110,000 buses with negligible computational overhead.

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This letter uses sparse matrix statistics to highlight a structural gap between North American grid models and the synthetic cases commonly used in research. North American grids exhibit area-based modularity, characterized by dense intra-area links and limited inter-area connectivity. By contrast, synthetic grids often over-mesh across areas. Analysis shows that these surplus tie lines increase fills in the Jacobian factorization, which reduces realism and computational efficiency. The observations confirm that inter-area connectivity influences sparse matrix behavior. This work emphasizes the importance of incorporating modular structure into synthetic grid design.

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This paper introduces CaseBuilder, a modular, objectoriented workflow used to convert the EIA-860 database into a copper plate model of the generation fleet of the United States. Casebuilder improves on previous, more manual methods of creating cases from datasets. CaseBuilder includes a suite of data cleaning functions and multiple methods of interacting with the chosen power flow modeling software. It serves as the foundation for future, automated, case generation and modification workflows. In this example, using a publicly available generation inventory and power-flow modeling software, we recreated a case that researchers and engineers use to study the output of the US generation mix across both weather and time. We can now automate the production of updated versions of these cases, and to generate past versions of this case from previous versions of the dataset to examine what, if anything, has changed across the available timeframe. We can also rapidly iterate on this case, to explore potential changes to the generation fleet.

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