Multi-objective Optimization of Power Supply System for Shipping Lng Off-loading Process Based on Switching Markov Chain and Genetic Algorithm

Renyou Zhang, Henry Tan

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The control of risks is crucial to process safety and loss prevention, such as for the shipping LNG off-loading process. As the transfer arm is the key factor during LNG off-loading process, and the power supply system is the insurance to ensure the transfer arms working normally, the reliability of power supply system for offloading arms should be quantitatively analyzed. Besides, the inefficient preventive maintenance (PM) plan may also drag the system into a low reliability region, and the budget of power supply system should also be considered to fulfill the low cost and high reliability. The objectives of this paper are to find the mathematical expression for the systematic reliability and cost evaluation, and the multi-objective optimization of this power
supply model. Switching Markov chain is adopted to identify the time depended reliability, and genetic algorithm (GA) is chosen to solve multi-objective optimization of power supply system with the consideration of failure rate, repair rate, probability of unsuccessful PM, and the cost. Finally, the best solutions of a power supply model for LNG off-loading arm are collected to meet the acceptable reliability and low cost.
Original languageEnglish
Pages (from-to)697-702
Number of pages6
JournalChemical Engineering Transactions
Volume48
DOIs
Publication statusPublished - 31 May 2016

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