Maintenance Scheduling of Composite Generation and Transmission Systems Using Multi-Objective Evolutionary Optimization

Abstract:

Reducing the overall cost and improving the reliability are two primary but often conflicting objectives for composite generation and transmission system . Scheduling of appropriate preventive maintenance requires optimization among multiple objectives. In this paper, a systematic and integrated methodology with three functional blocks is proposed. In the first block, the stochastic deterioration process of individual components is formulated as a continuous-time Markov model, in which transition rates incorporate the influences of the aging of components and two (minor and major) maintenance extents. Reliability of a composite generation and transmission system is dependent upon its topology as well as its load and generation profiles, and is evaluated in the second block. In the third block, Pareto-based multi-objective evolutionary algorithm is proposed because of its proven ability to search towards the optimum among a large number of potential solutions for providing a holistic view of conflicting relationships among multiple objectives. The proposed approach is applied to the IEEE reliability test system (IEEE-RTS), and the reliability, maintenance and failure costs of the entire IEEE-RTS are optimized. The successful application to IEEE-RTS demonstrates its potential of handling complex systems.

• Periodical: Applied Mechanics and Materials (Volume 274)
• Pages: 28-32
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.274.28
• Online since: January 2013
• Authors: Hai Tao Sang, Guo Quan Wang, Yu Qu Wu
• Keywords: Continuous-Time Markov Model, Inspection Frequency Optimization, Minimum Cut Sets, Pareto-Based Multi-Objective Evolutionary Algorithm, Representation of Solution.

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