2 citations · 4 across the 5 of their papers we have counts for
8 papers
Reinforcement Learning for Optimal Control of a District Cooling Energy Plant
Zhong Guo, Austin R. Coffman, Prabir Barooah
District cooling energy plants (DCEPs) consisting of chillers, cooling towers, and thermal energy storage (TES) systems consume a considerable amount of electricity. Optimizing the…
A unified framework for coordination of thermostatically controlled loads
Austin Coffman, Ana Bušić, Prabir Barooah
A collection of thermostatically controlled loads (TCLs) -- such as air conditioners and water heaters -- can vary their power consumption within limits to help the balancing autho…
A model-free method for learning flexibility capacity of loads providing grid support
Austin R. Coffman, Prabir Barooah
Flexible loads are a resource for the Balancing Authority (BA) of the future to aid in the balance of power supply and demand. In order to be used as a resource, the BA must know t…
Control oriented modeling of TCLs
Austin R. Coffman, Ana Bušić, Prabir Barooah
Thermostatically controlled loads (TCLs) have the potential to be a valuable resource for the Balancing Authority (BA) of the future. Examples of TCLs include household appliances…
Predictive resource allocation for flexible loads with local QoS
Austin R. Coffman, Matthew Hale, Prabir Barooah
Loads that can vary their power consumption without violating their Quality of service (QoS), that is flexible loads, are an invaluable resource for grid operators. Utilizing flexi…
Characterizing capacity of flexible loads for providing grid support
Austin R. Coffman, Zhong Guo, Prabir Barooah
Flexible loads are a resource for the Balancing Authority (BA) of the future to aid in the balance of supply and demand in the power grid. Consequently, it is of interest for a BA…