Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/62341
Title: Intelligent maintenance scheduling of distribution system components with operating constraints
Authors: Srinivasan, D. 
Liew, A.C. 
Chen, J.S.P. 
Chang, C.S. 
Keywords: distribution system
expert system
knowledge based system
maintenance scheduling
Issue Date: Apr-1993
Source: Srinivasan, D.,Liew, A.C.,Chen, J.S.P.,Chang, C.S. (1993-04). Intelligent maintenance scheduling of distribution system components with operating constraints. Electric Power Systems Research 26 (3) : 203-209. ScholarBank@NUS Repository.
Abstract: This paper presents an intelligent maintenance scheduling system, designed to solve complex scheduling problems, with the flexibility and robustness necessary for use in an actual operating environment on a power distribution system. The nature and complexity of various operating constraints make direct algorithmic approaches cumbersome to use with respect to various optimization criteria. The knowledge based system introduced in this paper overcomes this problem and takes the advantage of the flexibility offered by search based techniques to produce efficient and safe schedules. This intelligent maintenance scheduling system has been developed for use on a medium sized distribution network connected to a SCADA system. It takes into consideration various operational constraints due to loading, sequencing, priority, capacity, and availability of components. Once the schedule for maintenance of components has been prepared, the expert system generates an optimum switching sequence for their isolation and for transferring to other sources all the loads which would be adversely affected due to this switching. With this knowledge based approach, the optimum schedule and switching sequence can be generated in a very short time, thus making this approach effective for on-line applications. © 1993.
Source Title: Electric Power Systems Research
URI: http://scholarbank.nus.edu.sg/handle/10635/62341
ISSN: 03787796
Appears in Collections:Staff Publications

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