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McKenna Peplinski

Ph.D. Student 

Hometown: Maple Grove, MN

Curriculum Vitae

McKenna was born and raised in the suburbs of Minneapolis. She attended the University of St. Thomas in Saint Paul, Minnesota where she played Division 3 soccer and served as a board member for the school’s chapter of Engineers for a Sustainable World. In 2019, she graduated Summa Cum Laude from St. Thomas with a bachelor’s degree in mechanical engineering and a minor in peace engineering. McKenna joined USC in the fall of 2019 to pursue a PhD in the Sonny Astani Department of Civil and Environmental Engineering. She defended her thesis, titled “Residential electricity demand in the context of urban warming: Leveraging high resolution smart meter data to quantify spatial and temporal patterns in electricity consumption, cooling demand, and heat vulnerability.”, in April of 2024.

Research Interests

McKenna’s dissertation work analyzes end-use electricity demand in the residential sector, specifically in the context of extreme heat. She has developed frameworks to better understand residential electricity use that 1) predict household electricity consumption using machine learning models, 3) characterize regional AC ownership and operation through statistical techniques, and 3) evaluate electricity demand during extreme heat and demand response events. The results of her research can be used by grid operators and utilities to plan for future energy needs, and by public health officials and environmental justice advocates to increase cooling access in vulnerable communities. Going forward, McKenna is interested in applying her expertise in demand-side analysis to address systems-scale challenges, such as how to meet the increasing demand for electricity while still achieving decarbonization goals.

 Awards and Honors

  • Behavior, Energy, and Climate Change Conference Student Fellowship- 2023
  • Recipient of WiSE top-off fellowship- 2019
  • Recipient of USC Viterbi fellowship- 2019
  • Drexel University IExE REU Program – 2018
  • Academic All-American- 2018
  • Michael and Rebecca Thyken Fellowship- 2018
  • Tommie Award Nominee- 2018
  • Alicia Dudley Geiger Fellowship- 2017


  • Doctorate of Philosophy, Environmental Engineering – University of Southern California (May 2024)
  • Master of Science, Green Technologies – University of Southern California (December 2023)
  • Bachelor of Science, Mechanical Engineering (Summa Cum Laude) – University of St. Thomas  (Sep 2015-May 2019)

Peer-Reviewed Journal Publications

McKenna Peplinski, M. Chen, B. Dilkina, G.A. Ban-Weiss, K.T. Sanders (2024). “A machine learning framework to estimate residential electricity demand based on smart meter electricity, climate, building characteristics, and socioeconomic datasets.” Applied Energy, 357, 122413

McKenna Peplinski, K.T. Sanders. (2023). “Residential electricity demand on CAISO Flex Alert days: A case study of voluntary emergency demand response programs.” Environmental Research: Energy, 1(1), 015002

McKenna Peplinski, Peter Kalmus, K.T. Sanders. (2023). “Investigating whether the inclusion of humid heat metrics improves estimates of AC penetration rates: a case study of Southern California.” Environmental Research Letters,18(10), 104054

Conference Presentations

McKenna Peplinski, K.T. Sanders. “CAISO Flex Alerts: How responsive are residential customers to voluntary demand response events?” Behavior, Energy, and Climate Change Conference. Sacramento, California. Nov. 2-5, 2023.

McKenna Peplinski, K.T. Sanders. “Are voluntary demand response programs effective at shedding load during emergency grid events? A study of CAISO’s Flex Alerts.” SoCal CEERS 2023. Los Angeles, California. Oct. 19-20, 2023.

McKenna Peplinski, K.T. Sanders. “Examining How Various Heat Metrics Influence Residential Cooling Demand and the Vulnerability of Populations to Urban Warming.” AGU Fall Meeting, Chicago, Illinois. Dec. 12-16, 2022.

McKenna Peplinski, G.A. Ban-Weiss, K.T. Sanders. “Characterizing patterns of residential AC ownership across Southern California in the context of urban warming.” AGU Fall Meeting, New Orleans, Louisiana. Dec. 13-17, 2021.

McKenna Peplinski, M. Chen, B. Dilkina, K.T. Sanders, G.A. Ban-Weiss. “Predicting changes in Southern California’s residential electricity consumption using machine learning models.” AGU Fall Meeting, Online. Dec. 7-11, 2020.

McKenna Peplinski, M. Chen, G.A. Ban-Weiss, B. Dilkina, K.T. Sanders “Projecting residential electricity consumption under future warming using machine learning models in conjunction with smart-meter data, building characteristics and weather data.” 2020 Duke University Energy Data Analytics Symposium, Online. December 8-9th, 2020.