RSI Research Seminar
Resnick Sustainability Institute Research Seminar
Join us every other Monday at noon for two 30-minute research talks, presented by Resnick Sustainability Institute Graduate Fellows and Caltech researchers funded by the Resnick Sustainability Institute. To see the full schedule of speakers, visit the RSI Research Seminar web page. For more information and to get the Zoom login info, please reach out to email@example.com
Speakers for February 22:
Zachary Lee - Resnick Fellow - Scheduling and Pricing EV Charging Services with Demand Charge
Pricing electric vehicle (EV) charging services is difficult when the electricity tariff includes both time-of-use energy cost and demand charge based on peak power draw within a billing period, i.e. one month. In this talk, I will propose a pricing scheme that assigns a session-specific energy price to each charging session at the end of the billing period. The session price precisely captures the costs of energy, demand charge, and infrastructure congestion for which that session is responsible in that month while optimizing the trade-off between inexpensive time-of-use pricing and peak power draw. While our pricing scheme is calculated offline at the end of the billing period, we propose an online scheduling algorithm based on model predictive control to determine charging rates for each EV in real-time. We provide theoretical justification for our proposal and support it with simulations using real data collected from charging facilities at Caltech and JPL. Our simulation results suggest that the online algorithm can approximate the offline optimal reasonably well, e.g., the cost paid by the operator in the online setting is higher than the offline optimal cost by 9.2% and 6.5% at Caltech and JPL respectively. In the case of JPL, congestion rents are enough to cover this increase in costs, while at Caltech, this results in a negligible average loss of $18 per month.
Wenbo Wu - Callies group - Seismic Ocean Thermometry
As the major buffer of Earth's energy imbalance, the ocean plays a key role in regulating global climate and temperature changes. However, accurate estimation of global ocean temperature change remains a challenging sampling problem. To complement existing point measurements, we have developed a novel and low-cost method of using travel time changes of acoustic waves from repeating natural earthquakes to infer basin-scale average ocean temperature changes. In this study, we implement this method using a seismometer and CTBTO hydrophones in the eastern Indian Ocean to infer the large-scale ocean temperature changes with a high temporal resolution. We detect not only seasonal signals, which are generally consistent with that in previous oceanographic datasets of ECCO and Argo, but also more interesting features missing in ECCO and Argo. These results suggest that seismic ocean thermometry offers new opportunities for monitoring ocean warming.