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.
Design of a Production Process for Poly(oxymethylene) Dimethyl Ethers from Dimethyl Ether and Trioxane
