Elizabeth Buechler
Ph.D. Student in Mechanical Engineering, admitted Spring 2018
Bio
Elizabeth (Lily) Buechler is a PhD candidate in mechanical engineering. She received her MS in mechanical engineering from Stanford in 2019 and her BS in mechanical engineering from Tufts University in 2017. She is broadly interested in the intersection of controls, optimization, and machine learning for energy and power systems. Her current research focuses on demand-side flexibility, residential electrification, and DER integration.
All Publications
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Improving the Load Flexibility of Stratified Electric Water Heaters: Design and Experimental Validation of MPC Strategies
IEEE Transactions on Smart Grid
2024
View details for DOI 10.1109/TSG.2024.3366116
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EV-EcoSim: A Grid-Aware Co-Simulation Platform for the Design and Optimization of Electric Vehicle Charging Infrastructure
IEEE Transactions on Smart Grid
2023
View details for DOI 10.1109/TSG.2023.3339374
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The Grid Under Extremes: Pandemic Impacts on California Electricity Consumption
IEEE Power and Energy Magazine
2022; 20 (6): 38-46
View details for DOI 10.1109/MPE.2022.3199846
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Global Changes in Electricity Consumption During COVID-19.
iScience
2021: 103568
Abstract
Understanding how the COVID-19 pandemic has altered electricity consumption can provide insights into society's responses to future shocks and other extreme events. We quantify changes in electricity consumption in 58 different countries/regions around the world from January-October 2020, and examine how those changes relate to government restrictions, health outcomes, GDP, mobility metrics, and electricity sector characteristics in different countries. We cluster the timeseries of electricity consumption changes to identify impact groupings that capture systematic differences in timing, depth of initial changes and recovery rate, revealing substantial heterogeneity. Results show that stricter government restrictions and larger decreases in mobility (particularly retail and recreation) are most tightly linked to decreases in electricity consumption, though these relationships are strongest during the initial phase of the pandemic. We find indications that decreases in electricity consumption relate to pre-pandemic sensitivity to holidays, suggesting a new direction for future research.
View details for DOI 10.1016/j.isci.2021.103568
View details for PubMedID 34877481
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Time and voltage domain load models for appliance-level grid edge simulation and control
ELECTRIC POWER SYSTEMS RESEARCH
2021; 190
View details for DOI 10.1016/j.epsr.2020.106750
View details for Web of Science ID 000594663300015
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Data-Driven Load Modeling and Forecasting of Residential Appliances
IEEE TRANSACTIONS ON SMART GRID
2020; 11 (3): 2652–61
View details for DOI 10.1109/TSG.2019.2959770
View details for Web of Science ID 000530243600071
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Probabilistic modeling of the indoor climates of residential buildings using EnergyPlus
JOURNAL OF BUILDING PHYSICS
2017; 41 (3): 225-246
View details for DOI 10.1177/1744259117701893
View details for Web of Science ID 000414739200003
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The value of demand response in Florida
The Electricity Journal
2017; 30 (9): 57-64
View details for DOI 10.1016/j.tej.2017.10.004