The PIMS Postdoctoral Fellow Seminar: Trisha Lawrence

The global population with access to electricity is constantly increasing from 84 to 92 percent. However, as the world continues to advance towards sustainable energy targets, there still exist 900 million people living without access to electricity.

In this talk, we provide a modeling framework for analyzing mini‑grid project performance and evaluating the economic impact of battery energy storage in competitive electricity markets. Using a dataset of 104 rural mini‑grid installations, we estimate the probability of project success through both a Probit regression model and a Bayesian hierarchical model. Community ownership and the presence of storage systems emerge as statistically significant predictors, with Bayesian posterior estimates closely aligning with frequentist results while providing improved predictive stability.

Furthermore, we analyze the bidding behavior of the Alberta electricity market and construct a mixed‑integer self‑scheduling model that determines optimal charging and discharging strategies. Through numerical experiments we demonstrate how storage can enhance arbitrage profitability, influence market clearing prices, and support system reliability.

Our results highlight the value of combining statistical inference with optimization‑based modeling to guide investment decisions.