DocumentCode :
2063961
Title :
Optimal generator start-up strategy for bulk power system restoration
Author :
Wei Sun ; Chen-Ching Liu ; Li Zhang
fYear :
2012
fDate :
22-26 July 2012
Firstpage :
1
Lastpage :
1
Abstract :
Summary form only given. During system restoration, it is critical to utilize the available black-start (BS) units to provide cranking power to non-black-start (NBS) units in such a way that the overall system generation capability will be maximized. The corresponding optimization problem is combinatorial with complex practical constraints that can vary with time. This paper provides a new formulation of generator start-up sequencing as a mixed integer linear programming (MILP) problem. The linear formulation leads to an optimal solution to this important problem that clearly outperforms heuristic or enumerative techniques in quality of solutions or computational speed. The proposed generator start-up strategy is intended to provide an initial starting sequence of all BS or NBS units. The method can provide updates on the system MW generation capability as the restoration process progresses. The IEEE 39-Bus system, American Electric Power (AEP), and Entergy test cases are used for validation of the generation capability optimization. Simulation results demonstrate that the proposed MILP-based generator start-up sequencing algorithm is highly efficient.
Keywords :
AC generators; combinatorial mathematics; integer programming; linear programming; power system restoration; starting; AEP; American Electric Power; BS units; Entergy test cases; IEEE 39-Bus system; MILP-based generator start-up sequencing algorithm; MW generation capability; NBS units; black-start units; bulk power system restoration; combinatorial optimization problem; generation capability optimization; initial starting sequence; linear formulation; mixed integer linear programming problem; nonblack-start units; optimal generator start-up strategy; optimal solution; overall system generation capability maximization; Educational institutions; Generators; Mixed integer linear programming; NIST; Optimization; Power system restoration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting, 2012 IEEE
Conference_Location :
San Diego, CA
ISSN :
1944-9925
Print_ISBN :
978-1-4673-2727-5
Electronic_ISBN :
1944-9925
Type :
conf
DOI :
10.1109/PESGM.2012.6345502
Filename :
6345502
Link To Document :
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