Our latest journal article from my energy modeling research at Santa Clara University has been published in the Applied Energy! The full text can be read here˺ until Dec 23, 2023. Our goal is to help policymakers, utility companies, and homeowners understand the impact of new and proposed electricity pricing plans where the price changes by time of day, total consumption, income level of the customer, or other factors. We developed a simulation framework for rapidly generating representative models for household energy usage and a method to evaluate the fairness of electricity pricing. We tested existing and proposed electricity tariffs for 5 household income levels and 3 geographic locations around the United States. For this work, I automated 150+ EnergyPlus simulations using Python and Java, and developed pre- & post-processing code to perform quantitative analysis on many different cases. I helped develop and test a fairness metric that considers the change in utility bill relative to a consumer’s ability to pay.
Special thanks to co-first author Hannah Covington for developing the modeling algorithm, and co-authors Chenli Wang, Thomas Roth, Cuong Nguyen, Yuhong Liu, Yi Fang, and Hohyun Lee.
H. Covington, B. Woo-Shem, C. Wang, T. Roth, C. Nguyen, Y. Liu, Y. Fang, H. Lee, “Method for Evaluating Fairness of Electricity Tariffs with Regard to Income Level of Residential Buildings.” Applied Energy. January 2024; 353B, 122130. DOI: 10.1016/j.apenergy.2023.122130. Full text here.