CPS: Synergy: Collaborative Research: Boolean Microgrid
Lead PI:
Panganamala Kumar
Abstract
The Boolean Microgrid (BM) emulates the Internet by supplying discrete power and discrete data over a network link that follows Boolean logic and is not continuous as in a conventional 60-Hz-ac or dc microgrid. BM is thus a highly integrated cyber-physical system (CPS) that features the convergence of control, communication and the physical plant. BMs realization poses the following research challenges that we plan to address: a) what is the most efficient, economic, power-dense, and reliable way of integrating the distributed energy sources and loads to the BM, and the BM to the utility grid, using power-electronic interfaces for seamless and on-demand distributed power delivery? b) what is the control-communication mechanism that optimizes BM nodal and network control performances under conditions of varying power generation and load demand and communication-network throughput and reliability? Our unique approaches to address these research challenges will encompass novel mechanisms based on high-frequency-link power conversion, dynamic-pricing based optimal network capacity and resource utilization, event-triggered sampling and communication, and optimal switching-sequence control. BM has the potential to influence next-generation systems including smart grid, vehicular microgrid, electric ships, military microgrid, electric aircraft, telecommunication systems, and residential, commercial, and critical-infrastructure (e.g., hospital) power systems. On the educational front, the proposed project will provide graduate- and post-graduate-level education to four researchers. Further, multiple undergraduate (including minority) students and middle-school students will be provided research/educational opportunities. The results of the research will be integrated into undergraduate and graduate courses at the collaborating universities including a dedicated course on CPS.
Panganamala Kumar
Performance Period: 10/01/2012 - 09/30/2016
Institution: Texas A&M Engineering Experiment Station
Sponsor: National Science Foundation
Award Number: 1239116