Classification of Distribution System Modeling Inaccuracies and Their Effects on Planning Studies

The fidelity and robustness of the models is critical for the efficacy of modern distribution system planning studies, serving as the foundation for strategic decision-making. However, systemic inconsistencies, incomplete datasets, and improper model data structuring introduce significant computational and operational complexities in power flow simulations, which are at the foundation of power system analyses and planning studies (such as hosting capacity evaluations). This paper presents a comprehensive analysis of prevalent inaccuracies and data anomalies that pervade distribution system models, categorizing them based on their impact on network topology, electrical parameter accuracy, and computational feasibility. The study investigates connectivity discrepancies, absent or misclassified asset characteristics, erroneous transformer-load associations, and data schema mismatches, elucidating their potential to distort system behavior and compromise reliability assessments. Furthermore, the paper highlights the imperative for adaptive data governance frameworks, advanced validation techniques, and automated rectification mechanisms to enhance distribution system model integrity.