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Electrical substation service-area estimation using Cellular Automata: An initial report
Author(s) -
J.W. Fenwick,
L. J. Dowell
Publication year - 1998
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Reports
DOI - 10.2172/319895
Subject(s) - cellular automaton , service (business) , computer science , analytic hierarchy process , hierarchy , set (abstract data type) , population , reliability engineering , data mining , operations research , mathematics , algorithm , engineering , market economy , demography , economy , sociology , economics , programming language
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

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