A Novel Algorithm for Statistical Assignment of Transmission Capacities in Synthetic Grid Modeling

Abstract

An appropriate synthetic grid model consists of at least three important components: a) the electrical grid topology; b) the generation and load settings which indicate their correlated placement and sizing; c) the transmission constraints which include the capacity limits of both transmission lines and transformers. In this paper the authors develop a statistics-based approach to accurately determine the transmission capacities for a synthetic power grid model with components (a) and (b) already resolved. The proposed approach takes into account the scaling property of total transmission capacity versus network size and the mutual dependence between the electrical parameters, as evident in real grid data of different size. The statistics of generation dispatch factor and transmission gauge ratio have been examined in terms of their marginal distribution and the correlation with corresponding capacity settings. Then a set of DC power flow solution and flow distribution in a given synthetic grid could be calculated with statistically assigned generation dispatch. Finally a statistically correct random set of transmission capacities will be calculated and assigned to each transmission branch according to the correlated transmission gauge ratios.