TY - GEN
T1 - Planning with MIP for supply restoration in power distribution systems
AU - Thiébaux, Sylvie
AU - Coffrin, Carleton
AU - Hijazi, Hassan
AU - Slaney, John
PY - 2013
Y1 - 2013
N2 - The next generation of power systems faces significant challenges, both in coping with increased loading of an aging infrastructure and incorporating renewable energy sources. Meeting these challenges requires a fundamental change in the operation of power systems by replacing human-in-theloop operations with autonomous systems. This is especially acute in distribution systems, where renewable integration often occurs. This paper investigates the automation of power supply restoration (PSR), that is, the process of optimally reconfiguring a faulty distribution grid to resupply customers. The key contributions of the paper are (1) a flexible mixed-integer programming framework for solving PSR, (2) a model decomposition to obtain high-quality solutions within the required time constraints, and (3) an experimental validation of the potential benefits of the proposed PSR operations.
AB - The next generation of power systems faces significant challenges, both in coping with increased loading of an aging infrastructure and incorporating renewable energy sources. Meeting these challenges requires a fundamental change in the operation of power systems by replacing human-in-theloop operations with autonomous systems. This is especially acute in distribution systems, where renewable integration often occurs. This paper investigates the automation of power supply restoration (PSR), that is, the process of optimally reconfiguring a faulty distribution grid to resupply customers. The key contributions of the paper are (1) a flexible mixed-integer programming framework for solving PSR, (2) a model decomposition to obtain high-quality solutions within the required time constraints, and (3) an experimental validation of the potential benefits of the proposed PSR operations.
UR - http://www.scopus.com/inward/record.url?scp=84896062850&partnerID=8YFLogxK
M3 - Conference contribution
SN - 9781577356332
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 2900
EP - 2907
BT - IJCAI 2013 - Proceedings of the 23rd International Joint Conference on Artificial Intelligence
T2 - 23rd International Joint Conference on Artificial Intelligence, IJCAI 2013
Y2 - 3 August 2013 through 9 August 2013
ER -