Big Data, Consumer Behavior, Energy and Climate Change
Sunday, Jan. 6, 2019 10:15 AM - 12:15 PM
- Chair: Karen Palmer, Resources for the Future
Structural Approach to Dynamic Energy Pricing and Consumer Welfare
AbstractWith the proliferation of smart meters and associated enabling technologies like smart thermostats, there is growing interest in policies to manage electricity demand in real time and in response to hourly fluctuations in the cost of production. Dynamic pricing enables suppliers to charge a different marginal price for electricity for different hours of the day. We analyze a panel of 15 minute household level observations from a large scale randomized control trial conducted in the summer of 2011 in the US. Experimental treatments include two price structures, and four enabling technologies for information provision and demand response at the household level about the prevailing marginal cost of electricity. We build a penalized structural demand model for each hour of the day in order to derive a data driven selection strategy to identify the relevant cross hour price elasticities to which households respond. We focus on identifying the welfare impact of dynamic pricing in a setting with heterogeneous agents. Our model accounts for both heterogeneity due to observable demographics and also latent heterogeneity in consumer types.
Creating comfort in a warming world: The role of smart thermostats
AbstractRecent projections suggest ambient temperatures will increase substantially by 2100 as a result of climate change. Air conditioning may mitigate the worst impacts but with potential negative feedback effects on emissions. In this paper, we use a novel dataset of real-time information from smart thermostat users to explore the extent to which technologies can mitigate these feedback effects and also efficiently produce home comfort. We analyze (i) how outdoor temperatures affect indoor behavior and user interaction with thermostat settings; (ii) how “smart” features of a thermostat improve indoor comfort, measured using data from the thermostat; and (iii) the tradeoff between energy savings and comfort from the smart features.
Smart Thermostats, Social Information, and Energy Conservation: Distributional Evidence from a Field Experiment
AbstractCombining theory with a field experiment, we explore different channels through which smart-grid technologies may influence household energy demand. Our theory provides a simple empirical test to parse the competing models: measure higher moments of energy use. Results suggest that pro-social motivations are the primary channel through which our smart technology, a smart thermostat, impacts energy use. However, cross-sectional variation in this response illustrates the importance of selection in fully leveraging these motivations. Finally, counterfactual simulations of the wholesale electricity market highlight meaningful savings from adoption at scale, with changes in variance driving more than one-third of the savings.
- Q4 - Energy
- C5 - Econometric Modeling