Annika Todd-Blick
Publications
Viewing 25 of 38 publications
2024
At the nexus of equity and transportation modeling: Assessing accessibility through the Individual Experienced Utility-Based Synthesis (INEXUS) metric." Journal of Transport Geography 115 (2024) 103824.
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2021
Default Effects and Follow-On Behaviour: Evidence From an Electricity Pricing Program." The Review of Economic Studies 88.6 (2021) 2886–2934.
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Winners are not keepers: Characterizing household engagement, gains, and energy patterns in demand response using machine learning in the United States." Energy Research & Social Science 70 (2020).
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Accelerating demand for residential solar photovoltaics: Can simple framing strategies increase consumer interest?." Global Environmental Change Volume 53.November 2018 (2018) 68–77.
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Spillover as a cause of bias in baseline evaluation methods for demand response programs." Applied Energy 250 (2019) 344–357.
, , , and . "Evaluating the Effects of Missing Values and Mixed Data Types on Social Sequence Clustering Using t-SNE Visualization." Journal of Data and Information Quality 11.2 (2019) 1–22.
, , , , , and . "Describing the users: Understanding adoption of and interest in shared, electrified, and automated transportation in the San Francisco Bay Area." Transportation Research Part D: Transport and Environment 71 (2019) 283–301.
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Time Will Tell: Using Smart Meter Time Series Data to Derive Household Features and Explain Heter ogeneity in Pricing Programs." 2016 ACEEE Summer Study on Energy Efficiency in Buildings 2016.
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Data quality challenges with missing values and mixed types in joint sequence analysis." 2017 IEEE International Conference on Big Data (Big Data)2017 IEEE International Conference on Big Data (Big Data). Boston, MA, USA: IEEE, 2017.
, , , , , and . "Predicting Baseline for Analysis of Electricity Pricing." International Journal of Big Data Intelligence (IJBDI) Vol. 5.No. 1/2, 2018 (2017) 3–20.
, , , , , , and . "Comparison of Clustering Techniques for Residential Energy Behavior using Smart Meter Data." AAAI Workshops - Artificial Intelligence for Smart Grids and Buildings, March 2017. San Francisco, CA , 2017.
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Distribution-level electricity reliability: Temporal trends using statistical analysis." Energy Policy 49 (2012) 243–252.
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Insights from Smart Meters: Ramp-up, dependability, and short-term persistence of savings from Home Energy Reports. State and Local Energy Efficiency Action Network (SEE Action), 2015.
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2014
Insights from Smart Meters: Identifying Specific Actions, Behaviors and Characteristics that drive savings in Behavior-Based Programs. State and Local Energy Efficiency Action Network (SEE Action), 2014.
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