Distributed Multi-Battery Coordination for Cooperative Energy Management via ADMM-based Iterative Learning

Yun Li, Tao Zhang, Quanyan Zhu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, a distributed price-responsive energy management algorithm is proposed for a smart residential energy system (RES) equipped with multiple energy storage devices. First, the future system states are predicted via an iterative learning approach based on the lifted domain representation. Then, RES management is formulated as an optimization problem by taking into account the time-varying electricity rate, battery properties, and system operational constraints. Finally, we adopt the Alternating Direction Method of Multipliers (ADMM) and compute the optimal charging/discharging actions of local batteries in a distributed manner to establish a flexible, scalable, and computation-efficient power network. Numerical simulation is provided to illustrate the performance of our proposed algorithm.

Original languageEnglish (US)
Title of host publication2020 American Control Conference, ACC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2232-2237
Number of pages6
ISBN (Electronic)9781538682661
DOIs
StatePublished - Jul 2020
Event2020 American Control Conference, ACC 2020 - Denver, United States
Duration: Jul 1 2020Jul 3 2020

Publication series

NameProceedings of the American Control Conference
Volume2020-July
ISSN (Print)0743-1619

Conference

Conference2020 American Control Conference, ACC 2020
CountryUnited States
CityDenver
Period7/1/207/3/20

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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    Li, Y., Zhang, T., & Zhu, Q. (2020). Distributed Multi-Battery Coordination for Cooperative Energy Management via ADMM-based Iterative Learning. In 2020 American Control Conference, ACC 2020 (pp. 2232-2237). [9147988] (Proceedings of the American Control Conference; Vol. 2020-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ACC45564.2020.9147988