A Novel Technique of Fuzzy Comparison for Generators' Optimal Maintenance Scheduling

Abstract

A key issue in solving fuzzy optimization problems is selecting an appropriate fuzzy comparison technique. This paper introduces a novel fuzzy comparison technique that can work with any fuzzy optimization problem. The new technique is employed to determine the best maintenance schedule (MS) of electric generators. To solve the MS problem, the new fuzzy comparison technique is implemented in conjunction with the use of the evolutionary programming. Unlike other fuzzy comparison techniques, the objective of the proposed technique is to compare between fuzzy numbers based on the midpoint and the upper limits for minimization problems. Which in turn controls the upper limit of the final solution and yields a better minimum solution for the problem. In this paper, the IEEE 30-bus system is used to test the proposed technique with fuzzy load and maintenance cost. Results of comparing the proposed technique with Chen's and Yager's approaches show lower cost compared to Chen's and slightly lower cost compared to Yager's techniques.