Advanced search
1 file | 1.54 MB

Voltage coordination in multi-area power systems via distributed model predictive control

Mohammad Moradzadeh (UGent) , René Boel (UGent) and Lieven Vandevelde (UGent)
Author
Organization
Abstract
This paper proposes a coordination paradigm for properly coordinating local control actions, taken by many communicating control agents (CAs), in order to maintain multi-area power system voltages within acceptable bounds. The proposed control scheme is inspired by distributed model predictive control (DMPC), and relies on the communication of planned local control actions among neighboring CAs, each possibly operated by an independent transmission system operator (TSO). Each CA, knowing a local model of its own area, as well as reduced-order QSS models of its immediate neighboring areas, and assuming a simpler equivalent PV models for its remote neighbors, performs a greedy local optimization over a finite window in time, communicating its planned control input sequence to its immediate neighbors only. The good performance of the proposed real-time model-based feedback coordinating controller, following major disturbances, is illustrated using time-domain simulation of the well-known realistic Nordic32 test system, assuming worst-case conditions.
Keywords
long-term voltage instability, optimization., tap changing transformers, load, Communication, model predictive control, distributed voltage control

Downloads

  • (...).pdf
    • full text
    • |
    • UGent only
    • |
    • PDF
    • |
    • 1.54 MB

Citation

Please use this url to cite or link to this publication:

Chicago
Moradzadeh, Mohammad, René Boel, and Lieven Vandevelde. 2013. “Voltage Coordination in Multi-area Power Systems via Distributed Model Predictive Control.” Ieee Transactions on Power Systems 28 (1): 513–521.
APA
Moradzadeh, M., Boel, R., & Vandevelde, L. (2013). Voltage coordination in multi-area power systems via distributed model predictive control. IEEE TRANSACTIONS ON POWER SYSTEMS, 28(1), 513–521.
Vancouver
1.
Moradzadeh M, Boel R, Vandevelde L. Voltage coordination in multi-area power systems via distributed model predictive control. IEEE TRANSACTIONS ON POWER SYSTEMS. 2013;28(1):513–21.
MLA
Moradzadeh, Mohammad, René Boel, and Lieven Vandevelde. “Voltage Coordination in Multi-area Power Systems via Distributed Model Predictive Control.” IEEE TRANSACTIONS ON POWER SYSTEMS 28.1 (2013): 513–521. Print.
@article{3070938,
  abstract     = {This paper proposes a coordination paradigm for properly coordinating local control actions, taken by many communicating control agents (CAs), in order to maintain multi-area power system voltages within acceptable bounds. The proposed control scheme is inspired by distributed model predictive control (DMPC), and relies on the communication of planned local control actions among neighboring CAs, each possibly operated by an independent transmission system operator (TSO). Each CA, knowing a local model of its own area, as well as reduced-order QSS models of its immediate neighboring areas, and assuming a simpler equivalent PV models for its remote neighbors, performs a greedy local optimization over a finite window in time, communicating its planned control input sequence to its immediate neighbors only. The good performance of the proposed real-time model-based feedback coordinating controller, following major disturbances, is illustrated using time-domain simulation of the well-known realistic Nordic32 test system, assuming worst-case conditions.},
  author       = {Moradzadeh, Mohammad and Boel, Ren{\'e} and Vandevelde, Lieven},
  issn         = {0885-8950},
  journal      = {IEEE TRANSACTIONS ON POWER SYSTEMS},
  keyword      = {long-term voltage instability,optimization.,tap changing transformers,load,Communication,model predictive control,distributed voltage control},
  language     = {eng},
  number       = {1},
  pages        = {513--521},
  title        = {Voltage coordination in multi-area power systems via distributed model predictive control},
  url          = {http://dx.doi.org/10.1109/TPWRS.2012.2197028},
  volume       = {28},
  year         = {2013},
}

Altmetric
View in Altmetric
Web of Science
Times cited: