automated, flexible electricity consumption in buildings
The residential sector represents a significant potential source of flexible electricity consumption because 1) households comprise a substantial portion of energy demand and emissions; 2) domestic thermal applications (heating, cooling, water heating, and refrigeration) can be readily electrified and integrated with thermal storage using existing, cost-effective technologies; and 3) smart meters enable real-time communication between these technologies and electricity markets. This focus area explores how residential thermal applications can be electrified, integrated with thermal storage, and managed autonomously via energy management systems.
Neighborhood aggregation and district-scale technology
Individual building behavior is inconsequential to regional electric grid operations, but aggregating many buildings together can elevate their impact to a notable scale. This focus area aggregates individual households at the neighborhood scale to coordinate their behavior to respond flexibly to local and regional power sector signals and to integrate their operation with campus-scale technologies such as district heating and cooling.
Modeling the Power Sector
A major goal of my demand-side modeling work is to motivate cities to consume energy in ways that support power sector sustainability. I capture those impacts by representing the electric grid with power plant dispatch models. Coupling urban energy system and power sector models helps me investigate their interactions endogenously, in particular, by exploring the way energy technology utilization in both systems influence electricity prices and emissions.
Distributed optimization and systems aggregation Methods
My theoretical work combines distributed optimization with systems aggregation to coordinate independent agents’ behavior using dynamic prices. I am particularly interested in large systems where an abundance of agents makes it difficult to apply centralized control schemes. In these situations, distributed, aggregate methods can reduce computational and communication needs.
Data analysis of pilot projects
I use real-world pilot projects to calibrate my system models and test the strategies they generate. I explore the data from these projects using statistical analysis and visualization methods. I am also interested in developing new pilot projects - from sophisticated pilots that might install energy technology in neighborhoods to test its real-world utilization, to simpler projects that virtually engage consumers with dynamic prices, automation, and new technology using energy management games.