Using incentive mechanisms and societal networks for reducing congestion-related costs in transportation, both public and private.
End Use/Efficiency: Sensors & Data
The proliferation of sensors—smart meters, motion detectors, infrastructure monitors—and the enormous amount of data they produce have created big opportunities to reduce energy waste at individual and system levels. One set of projects in this area helps utilities better match businesses and households with energy saving programs by using smart meter data to segment customers based on consumption patterns. Another project develops inexpensive wind sensors and software to better integrate wind power. A third advances wireless technology, including channel modeling, multi-user communications, signal processing and system design, for use in smart grids, automated highways and intelligent home electronics. Other research topics at Stanford in this area include learning algorithms for electricity network forecasting and scheduling, and decentralized message passing to constantly optimize a large network of distributed electricity sources and sinks.
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Civil & Environmental Engineering
Making renewable energy economical. Reducing wind power costs by improving forecasts and buying replacement power later. Matching solar supply with businesses that have price-sensitive demand.
Precourt Energy Efficiency Center
Understanding energy efficiency behavior selection and plasticity, and tests of adoption. Affective, cognitive and social web interfaces for reducing energy use. Real-time feedback and its affects.
Precourt Energy Efficiency Center
Applying behavior change techniques to reduce energy use. Using pervasive sensor data to measure relevant behaviors and to evaluate efficacy of interventions. Scaling up effective behavior change techniques in energy and climate.
