This use case is a technical explanation of how conductor slapping can be identified and predicted using Power Lines Pro. To learn more about conductor slapping, have a read of our ‘What is Conductor Slapping and its 3 Risks Worth Mitigating’ article.
To identify and rectify conductor slapping, a pilot project is first conducted. Here, utilities input different data to determine what spans have the highest risk of conductor slap in a specific known area. Then, the utilities can validate the results either by hand calculations or physical surveys and inspections of the identified spans.
The inputs required from the utility are GIS and classified LiDAR, along with ambient temperature at the time of LiDAR survey. This is combined with construction libraries of various overhead structures, conductors, and constructions, as well as estimates for fault current & fault duration and safety factors. This data together is used to build the digital twin which has the capability to identify and predict conductor slapping.
To do this, the model accurately simulates phase spacings, span lengths, and conductor sag under various operating conditions. Once these calculations are carried out under the relevant scenarios, it is assessed against the fault current and fault duration information provided by the utility to calculate conductor slapping risk.
This process can then be easily scaled up to run across the entire network at once. Identifying clusters of issues and prioritization of maintenance is easily managed grid-wide through the automated calculations of the model. The digital twin is fully customizable and editable, so solutions or corrections can be tested within the one platform. Adjustments or issues of interest can be instantly applied network-wide on the model, resulting in a highly efficient process for rectifying conductor slapping - or indeed any issue being assessed on the model.
If you have any questions about how to use PLP to manage your grid analysis, we’d be happy to discuss your specific use case - contact us via firstname.lastname@example.org