Investigating maintenance costs using response feature analysis

Abstract: Svenska Kraftnät (Svk) is responsible for ensuring that Sweden has a safe, sustainable, and cost-effective transmission system for electricity. In an effort to reduce costs, Svk has participated in a study where it has been determined that there are mostly costs for common facilities that stand out cost-wise. The goal of this master thesis is to identify and assess what factors influence maintenance costs for the substations in the Swedish national grid for electricity. Response feature modeling was applied on longitudinal data for the substations (N=53) for years 2017-2020 to obtain individual intercepts with a common slope for further analysis. The factors included in the global model were based on Pearson correlation analysis and consultation with experts. Further attempts to improve upon the global model were made based on a stepwise variable selection made by comparing AIC, a log-transformation of the response, and by applying expert knowledge to attain a subset of predictors. all the resulting models were significant (P<0.001) with the best model having an R2 of 0.8376. Predictions for a proposed substation was made for the first fifty years of lifespan. Predictors that were found significant in multiple models includes variables regarding substation size and age. Factors that were not significant in any model related to substation fence length and location amongst others.