Electrical substation service-area estimation using Cellular Automata: An initial report

Abstract

The service areas for electric power substations can be estimated using a Cellular Automata (CA) model. The CA model is a discrete, iterative process whereby substations acquire service area by claiming neighboring cells. The service area expands from a substation until a neighboring substation service area is met or the substation`s total capacity or other constraints are reached. The CA-model output is dependent on the rule set that defines cell interactions. The rule set is based on a hierarchy of quantitative metrics that represent real-world factors such as land use and population density. Together, the metrics determine the rate of cell acquisition and the upper bound for service area size. Assessing the CA-model accuracy requires comparisons to actual service areas. These actual service areas can be extracted from distribution maps. Quantitative assessment of the CA-model accuracy can be accomplished by a number of methods. Some are as simple as finding the percentage of cells predicted correctly, while others assess a penalty based on the distance from an incorrectly predicted cell to its correct service area. This is an initial report of a work in progress.