An application of a genetic-evolved fuzzy (GEF) system for maintenance scheduling of generating units is presented in this paper. In the proposed system, the fuzzy system was formulated with respect to multiple objectives and soft constraints, where genetic algorithms were applied to tune the membership functions in the solution process. In this way, parameters of membership functions can be optimally adjusted. The performance of the computation is also enhanced. The proposed approach has been tested on a practical Taiwan Power system (Taipower) through the utility data. The feasibility and effectiveness of the approach for generator maintenance scheduling applications were solidified through the test results.
|Number of pages||5|
|Journal||International Journal of Electrical Power and Energy Systems|
|Publication status||Published - 1998 Mar 1|
All Science Journal Classification (ASJC) codes
- Energy Engineering and Power Technology
- Electrical and Electronic Engineering