Multi-objective optimization of industrial hydrogen plants

Operating hydrogen plants efficiently is a critical issue, central to any e nergy conservation exercise in petroleum refining and fertilizer industries . To achieve this goal, "optimal" operating conditions for improved unit pe rformance need to be identified. In this work, an entire industrial hydroge n plant is simulated using rigorous process models for the steam reformer a nd shift converters. An adaptation of the nondominated sorting genetic algo rithm (NSGA) is then employed to perform a multi-objective optimization on the unit performance. Simultaneous maximization of product hydrogen and exp ort steam flow rates is considered as the two objective functions for a fix ed feed rate of methane to the existing unit. For the specified plant confi guration, Pareto-optimal sets of operating conditions are successfully obta ined by NSGA for different process conditions. The results serve as a targe t for the operator to aim at, in order to achieve cost effective operation of hydrogen plants. (C) 2001 Elsevier Science Ltd. All rights reserved.