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Coordinated voltage control via distributed model predictive control

Mohammad Moradzadeh UGent, Lokesh Bhojwani and René Boel UGent (2011) 2011 23rd Chinese Control and Decision Conference (CCDC 2011). p.1612-1618
abstract
Over the past decades many voltage collapse incidents have occurred, caused by uncoordinated interactions of local controllers, following a major disturbance in electric power system operating closer and closer to their safety limits. Currently most voltage control schemes are rule-based and only rely on local measurements. However the availability of wide-area phasor measurements (WAMS/PMU) suggests that the risk of voltage collapse could be reduced by coordinating control actions in neighboring control regions of the network. This paper shows how distributed model predictive control (MPC) can be used in order to design such a coordinating controller. Local control agents carry out an on-line optimization by comparing the plant behavior over a finite window in time, for different possible switching sequences of the local tap changing transformer (LTC). The evolution of the plant behavior is obtained by a fast Modelica simulation of the hybrid systems model, using information on the tap switching sequences that neighboring control regions are planning to implement on their LTCs. Through simulation of a 12-bus power system this paper shows that the distributed MPC controllers can prevent, or at least postpone, voltage collapse in circumstances where classical uncoordinated controllers fail. The required communication exchange is very limited, making practical applications feasible. However extensions to larger systems will require consideration of modeling abstractions of neighboring control regions, so as to keep the simulation time for each local decision maker short.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
power system measurement, voltage control, power transformers, power system control, predictive control, distributed control
in
2011 23rd Chinese Control and Decision Conference (CCDC 2011)
pages
1612 - 1618
publisher
IEEE
place of publication
Piscataway, NJ, USA
conference name
23rd IEEE Chinese Control and Decision Conference (CCDC 2011)
conference location
Mianyang, PR China
conference start
2011-05-23
conference end
2011-05-25
Web of Science type
Conference Paper
Web of Science id
12143749
ISBN
9781424487370
9781424487387
DOI
10.1109/CCDC.2011.5968451
language
English
UGent publication?
yes
classification
C1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1996204
handle
http://hdl.handle.net/1854/LU-1996204
date created
2012-01-19 12:12:21
date last changed
2012-03-29 14:59:31
@inproceedings{1996204,
  abstract     = {Over the past decades many voltage collapse incidents have occurred, caused by uncoordinated interactions of local controllers, following a major disturbance in electric power system operating closer and closer to their safety limits. Currently most voltage control schemes are rule-based and only rely on local measurements. However the availability of wide-area phasor measurements (WAMS/PMU) suggests that the risk of voltage collapse could be reduced by coordinating control actions in neighboring control regions of the network. This paper shows how distributed model predictive control (MPC) can be used in order to design such a coordinating controller. Local control agents carry out an on-line optimization by comparing the plant behavior over a finite window in time, for different possible switching sequences of the local tap changing transformer (LTC). The evolution of the plant behavior is obtained by a fast Modelica simulation of the hybrid systems model, using information on the tap switching sequences that neighboring control regions are planning to implement on their LTCs. Through simulation of a 12-bus power system this paper shows that the distributed MPC controllers can prevent, or at least postpone, voltage collapse in circumstances where classical uncoordinated controllers fail. The required communication exchange is very limited, making practical applications feasible. However extensions to larger systems will require consideration of modeling abstractions of neighboring control regions, so as to keep the simulation time for each local decision maker short.},
  author       = {Moradzadeh, Mohammad and Bhojwani , Lokesh and Boel, Ren{\'e}},
  booktitle    = {2011 23rd Chinese Control and Decision Conference (CCDC 2011)},
  isbn         = {9781424487370},
  keyword      = {power system measurement,voltage control,power transformers,power system control,predictive control,distributed control},
  language     = {eng},
  location     = {Mianyang, PR China},
  pages        = {1612--1618},
  publisher    = {IEEE},
  title        = {Coordinated voltage control via distributed model predictive control},
  url          = {http://dx.doi.org/10.1109/CCDC.2011.5968451},
  year         = {2011},
}

Chicago
Moradzadeh, Mohammad, Lokesh Bhojwani , and René Boel. 2011. “Coordinated Voltage Control via Distributed Model Predictive Control.” In 2011 23rd Chinese Control and Decision Conference (CCDC 2011), 1612–1618. Piscataway, NJ, USA: IEEE.
APA
Moradzadeh, M., Bhojwani , L., & Boel, R. (2011). Coordinated voltage control via distributed model predictive control. 2011 23rd Chinese Control and Decision Conference (CCDC 2011) (pp. 1612–1618). Presented at the 23rd IEEE Chinese Control and Decision Conference (CCDC 2011), Piscataway, NJ, USA: IEEE.
Vancouver
1.
Moradzadeh M, Bhojwani L, Boel R. Coordinated voltage control via distributed model predictive control. 2011 23rd Chinese Control and Decision Conference (CCDC 2011). Piscataway, NJ, USA: IEEE; 2011. p. 1612–8.
MLA
Moradzadeh, Mohammad, Lokesh Bhojwani , and René Boel. “Coordinated Voltage Control via Distributed Model Predictive Control.” 2011 23rd Chinese Control and Decision Conference (CCDC 2011). Piscataway, NJ, USA: IEEE, 2011. 1612–1618. Print.