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Bayesian Optimization and Hierarchical Forecasting of Non-Weather-Related Electric Power Outages

Summary

This project focused on power outage time series forecasting. Our team utilized advanced techniques that leveraged the Prophet model in Bayesian optimization and hierarchical forecasting to develop time series forecasting models for non-weather related outages (NWO). To ensure the robustness of our models, we defined a metric specifically for NWO called the non-weather outage count index (NWOCI). We tested our models using six years of daily state- and county-level outage data in Massachusetts, and our results showed that our models outperformed other Bayesian and hierarchical model combinations of Prophet and Seasonal Autoregressive Integrated Moving Average (SARIMA) models in predicting NWOCI at both county and state levels.

More details can be found in the peer reviewed journal article: https://www.mdpi.com/1996-1073/15/6/1958

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Time Series Forecasting for Power Outages

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