A self-interested distributed economic model predictive control approach to battery energy storage networks

Ruigang Wang, Xinan Zhang, Jie Bao

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In this work, a dissipativity based distributed economic model predictive control (DEMPC) approach is developed for the operation of battery energy storage (BES) networks in residential microgrids. With the presence of a microgrid power market (MPM), control of the BES systems is formulated as a self-interested distributed control problem, as individual DEMPC controllers minimize their local economic cost functions based on the price prediction of MPM. Due to the intermittent nature of photovoltaic (PV) power generations and load demands, the DEMPC without proper coordination or constraints may lead to excessive energy trading and price oscillations in MPM. To solve this problem, dissipativity theory with dynamic supply rates is adopted in this paper to deal with the interactions between individual users and the MPM. The microgrid-wide performance requirement of attenuation of the net power fluctuations with respect to time-varying PV generation and demands, is converted into the dissipative trajectory constraints imposed on individual DEMPC controllers. The proposed approach is scalable as it does not require online iterative optimizations across the controller network. A case study is presented to illustrate the proposed method.

Original languageEnglish
Pages (from-to)9-18
Number of pages10
JournalJournal of Process Control
Volume73
DOIs
Publication statusPublished - 1 Jan 2019
Externally publishedYes

Fingerprint

Microgrid
Energy Storage
Economic Model
Model predictive control
Model Predictive Control
Battery
Energy storage
Economics
Dissipativity
Controllers
Controller
Distributed Control Problems
Cost functions
Power generation
Storage System
Attenuation
Trajectories
Cost Function
Time-varying
Oscillation

Cite this

@article{0eb445d4f81b4049810cccf919173b63,
title = "A self-interested distributed economic model predictive control approach to battery energy storage networks",
abstract = "In this work, a dissipativity based distributed economic model predictive control (DEMPC) approach is developed for the operation of battery energy storage (BES) networks in residential microgrids. With the presence of a microgrid power market (MPM), control of the BES systems is formulated as a self-interested distributed control problem, as individual DEMPC controllers minimize their local economic cost functions based on the price prediction of MPM. Due to the intermittent nature of photovoltaic (PV) power generations and load demands, the DEMPC without proper coordination or constraints may lead to excessive energy trading and price oscillations in MPM. To solve this problem, dissipativity theory with dynamic supply rates is adopted in this paper to deal with the interactions between individual users and the MPM. The microgrid-wide performance requirement of attenuation of the net power fluctuations with respect to time-varying PV generation and demands, is converted into the dissipative trajectory constraints imposed on individual DEMPC controllers. The proposed approach is scalable as it does not require online iterative optimizations across the controller network. A case study is presented to illustrate the proposed method.",
keywords = "Dissipativity, Distributed battery energy storage systems, Distributed economic MPC, Residential microgrids",
author = "Ruigang Wang and Xinan Zhang and Jie Bao",
year = "2019",
month = "1",
day = "1",
doi = "10.1016/j.jprocont.2018.11.003",
language = "English",
volume = "73",
pages = "9--18",
journal = "Journal of Process Control",
issn = "0959-1524",
publisher = "Elsevier",

}

A self-interested distributed economic model predictive control approach to battery energy storage networks. / Wang, Ruigang; Zhang, Xinan; Bao, Jie.

In: Journal of Process Control, Vol. 73, 01.01.2019, p. 9-18.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A self-interested distributed economic model predictive control approach to battery energy storage networks

AU - Wang, Ruigang

AU - Zhang, Xinan

AU - Bao, Jie

PY - 2019/1/1

Y1 - 2019/1/1

N2 - In this work, a dissipativity based distributed economic model predictive control (DEMPC) approach is developed for the operation of battery energy storage (BES) networks in residential microgrids. With the presence of a microgrid power market (MPM), control of the BES systems is formulated as a self-interested distributed control problem, as individual DEMPC controllers minimize their local economic cost functions based on the price prediction of MPM. Due to the intermittent nature of photovoltaic (PV) power generations and load demands, the DEMPC without proper coordination or constraints may lead to excessive energy trading and price oscillations in MPM. To solve this problem, dissipativity theory with dynamic supply rates is adopted in this paper to deal with the interactions between individual users and the MPM. The microgrid-wide performance requirement of attenuation of the net power fluctuations with respect to time-varying PV generation and demands, is converted into the dissipative trajectory constraints imposed on individual DEMPC controllers. The proposed approach is scalable as it does not require online iterative optimizations across the controller network. A case study is presented to illustrate the proposed method.

AB - In this work, a dissipativity based distributed economic model predictive control (DEMPC) approach is developed for the operation of battery energy storage (BES) networks in residential microgrids. With the presence of a microgrid power market (MPM), control of the BES systems is formulated as a self-interested distributed control problem, as individual DEMPC controllers minimize their local economic cost functions based on the price prediction of MPM. Due to the intermittent nature of photovoltaic (PV) power generations and load demands, the DEMPC without proper coordination or constraints may lead to excessive energy trading and price oscillations in MPM. To solve this problem, dissipativity theory with dynamic supply rates is adopted in this paper to deal with the interactions between individual users and the MPM. The microgrid-wide performance requirement of attenuation of the net power fluctuations with respect to time-varying PV generation and demands, is converted into the dissipative trajectory constraints imposed on individual DEMPC controllers. The proposed approach is scalable as it does not require online iterative optimizations across the controller network. A case study is presented to illustrate the proposed method.

KW - Dissipativity

KW - Distributed battery energy storage systems

KW - Distributed economic MPC

KW - Residential microgrids

UR - http://www.scopus.com/inward/record.url?scp=85057114906&partnerID=8YFLogxK

U2 - 10.1016/j.jprocont.2018.11.003

DO - 10.1016/j.jprocont.2018.11.003

M3 - Article

VL - 73

SP - 9

EP - 18

JO - Journal of Process Control

JF - Journal of Process Control

SN - 0959-1524

ER -