TY  - JOUR
AV  - none
N1  - Available online: 20 Apr 2012
TI  - Assessment of non-centralised model predictive control techniques for electrical power networks
SP  - 1162
UR  - http://www.tandfonline.com/doi/abs/10.1080/00207179.2012.679972
A1  - Hermans, Ralph M.
A1  - Jokic, Andrej
A1  - Lazar, Mircea
A1  - Alessio, Alessandro
A1  - Van den bosch, Paul
A1  - Hiskens, Ian
A1  - Bemporad, Alberto
Y1  - 2012/04//
VL  - 85
KW  - Model Predictive Control
KW  -  decentralised control
KW  -  distributed control
KW  -  power systems
SN  - 0020-7179
ID  - eprints1264
EP  - 1177
N2  -  Model predictive control (MPC) is one of the few advanced control methodologies that have proven to be very successful in real-life applications. An attractive feature of MPC is its capability of explicitly taking state and input constraints into account. Recently, there has been an increasing interest in the usage of MPC schemes to control electrical power networks. The major obstacle for implementation lies in the large scale of these systems, which is prohibitive for a centralised approach. In this article, we therefore assess and compare the suitability of several non-centralised predictive control schemes for power balancing, to provide valuable insights that can contribute to the successful implementation of non-centralised MPC in the real-life electrical power system. 
JF  - International Journal of Control 
PB  - Taylor & Francis
IS  - 8
ER  -