Application of Reconstructability Analysis to the NW Power Grid

This talk will focus on preliminary results from Reconstructability Analysis (RA) models, Bayesian Network (BN) models, and standard linear regression to predict dynamics on the bulk electric grid. The best possible prediction models were identified using exploratory RA and BN search algorithms that search the lattice of possible graphs structures to find the best model fit. Preliminary results show that RA and BN both outperform linear regression in overall prediction and prediction in the tails of the distribution, whereas BN marginally outperforms RA overall. In addition to preliminary results, the talk will offer explanations for differences in prediction performance as well as opportunities for extensions of the research.https://pdxscholar.library.pdx.edu/systems_science_seminar_series/1068/thumbnail.jp