TY - JOUR
T1 - A Computationally Efficient Consensus-Based Multiagent Distributed EMS for DC Microgrids
AU - Ullah, Md Habib
AU - Babaiahgari, Bhanu
AU - Alseyat, Anas
AU - Park, Jae Do
N1 - Funding Information:
Manuscript received December 16, 2019; revised February 8, 2020 and March 23, 2020; accepted April 19, 2020. Date of publication May 7, 2020; date of current version February 17, 2021. This work was supported by the National Science Foundation under Grant ECCS-1554626. (Corresponding author: Jae-Do Park.) The authors are with the Department of Electrical Engineering, University of Colorado Denver, Denver, CO 80204 USA (e-mail: md.ullah@ucdenver.edu; bhanu.babaiahgari@ucdenver.edu; anas.alseyat@ucdenver.edu; jaedo.park@ucdenver.edu).
Publisher Copyright:
© 1982-2012 IEEE.
PY - 2021/6
Y1 - 2021/6
N2 - In this article, we present a fully distributed optimization approach for real-time energy management of dc microgrids. In the proposed approach, the energy management system (EMS) is formulated with a consensus algorithm based on incremental cost, which operates in a distributed manner for both generation and demand-side management. The proposed algorithm is privacy-preserving, scalable, plug-and-play capable, and robust against time-varying communication topologies. Furthermore, it converges very fast in terms of computation time and iterations. The scalability of the proposed algorithm was evaluated using IEEE bus systems in various sizes, number of agents, and communication topologies. A cooperative multilayered EMS optimally coordinated by multiple agents was also proposed in this article for integration. The effectiveness of the proposed system was validated through computer simulations and hardware experiments.
AB - In this article, we present a fully distributed optimization approach for real-time energy management of dc microgrids. In the proposed approach, the energy management system (EMS) is formulated with a consensus algorithm based on incremental cost, which operates in a distributed manner for both generation and demand-side management. The proposed algorithm is privacy-preserving, scalable, plug-and-play capable, and robust against time-varying communication topologies. Furthermore, it converges very fast in terms of computation time and iterations. The scalability of the proposed algorithm was evaluated using IEEE bus systems in various sizes, number of agents, and communication topologies. A cooperative multilayered EMS optimally coordinated by multiple agents was also proposed in this article for integration. The effectiveness of the proposed system was validated through computer simulations and hardware experiments.
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U2 - 10.1109/TIE.2020.2992015
DO - 10.1109/TIE.2020.2992015
M3 - Article
AN - SCOPUS:85101733441
VL - 68
SP - 5425
EP - 5435
JO - IEEE Transactions on Industrial Electronics
JF - IEEE Transactions on Industrial Electronics
SN - 0278-0046
IS - 6
M1 - 9089213
ER -