Event-Based Information Acquisition, Learning, and Control in High-Dimensional Cyber-Physical Systems

Abstract:

This year, we continued our research effort on designing optimal decentralized monitoring and control mechanisms for networked infrastructure systems providing demand response services by first focusing on the example of intelligent electric transportation systems. The results are highlighted in this poster. Electric Vehicles (EV) are emerging as one of the primary solutions to make electricity demand elastic. A common feature in most previous work is that the location and amount of charge requested and the time of plug--in is modeled as an exogenous random process. In our research work during the past year, we showed that designing a reliable EV demand management scheme requires considering the fact that EV loads can not only be shifted temporally but also geographically. Each EV owner needs to jointly decide on a travel plan (including path) and charging locations and associated charge amounts. At the system level, this joint planning for charge and path will introduce a connection between intelligent power and transportation systems that we studied in depth this year. Results are being extended to general networked infrastructure systems providing demand response services.