A Probabilistic Framework for Prioritizing Wood Pole Inspections Given Pole Geospatial Data

Managing the widely distributed wood pole assets owned by typical electric power utilities in the USA is challenging in the absence of appropriate analytical tools. The traditional method of inspecting poles by headquarters or strictly age is insufficient for effective management since natural hazards cause the largest instantaneous pole replacements. A probabilistic framework is developed and presented in this paper to address this issue. Fragility assessment is conducted using Latin hypercube sampling to estimate pole failure probabilities conditional on wind speed intensities. Failure probability estimates are obtained using age-dependent fragility functions and appropriate distribution functions for maximum 3 s wind gust speeds. Pole locations from an electric power utility´s database management system were imported into ArcMap, a component of Environmental Systems Research Institute geospatial processing program. Age distributions were extracted by county and used to estimate expected pole failures. A sort-algorithm on the failures-the inspection order indices gives the proposed appropriate order of pole locations to be inspected. These calculated values were added as a data layer into ArcMap generating a geospatial visualization of both the orders of pole inspections and probabilistic pole loss estimates for the electric utility by counties. Applying the framework will increase utilities´ visibility into the vulnerability of their pole plants. Emergency preparedness will also improve, strengthening customer-perception on utilities´ maintenance efforts.