Using 0/1 mixed integer linear programming to solve a reliability-centered problem of power plant preventive maintenance scheduling

The problem of power plant preventive maintenance scheduling is studied in this paper. A reliability perspective is considered. This problem consists of ascertaining which generating units must halt production to be examined regularly for safety. It is very important because a failure in a power sta...

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Bibliographic Details
Published in:Optimization and engineering Vol. 12; no. 3; pp. 333 - 347
Main Author: Perez Canto, Salvador
Format: Journal Article
Language:English
Published: Boston Springer US 01.09.2011
Springer Nature B.V
Subjects:
Control
Electric power generation
Electric power plants
Engineering
Environmental Management
Failure
Financial Engineering
Linear programming
Mathematics
Mathematics and Statistics
Mixed integer
Operations Research/Decision Theory
Optimization
Preventive maintenance
Scheduling
Systems Theory
Scheduling
Maintenance
0/1 mixed integer linear programming
Power plant
Reliability
Optimization
ISSN:1389-4420, 1573-2924
Online Access:Get full text
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Summary:The problem of power plant preventive maintenance scheduling is studied in this paper. A reliability perspective is considered. This problem consists of ascertaining which generating units must halt production to be examined regularly for safety. It is very important because a failure in a power station may cause a general breakdown in an electric network. The main consequence is that the electricity demand of customers will not be satisfied in such cases. Therefore, reliability is the key point used in the methodology presented. The problem is approached under the operations research perspective as an optimization issue. 0/1 mixed integer linear programming is used to solve the model reached. An application study is included. The model is put to use in a real power plant setting, representative of the Spanish one. The result obtained is a schedule that allows the efficient organization of preventive maintenance over a specific time horizon.
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ISSN:1389-4420
1573-2924
DOI:10.1007/s11081-011-9146-2