Multi-objective optimization of industrial hydrogen plants

Operating hydrogen plants e$ciently is a critical issue, central to any energy conservation exercise in petroleum re"ning and fertilizer industries. To achieve this goal, ‘optimala operating conditions for improved unit performance need to be identi"ed. In this work, an entire industrial hydrogen plant is simulated using rigorous process models for the steam reformer and shift converters. An adaptation of the nondominated sorting genetic algorithm (NSGA) is then employed to perform a multi-objective optimization on the unit performance. Simultaneous maximization of product hydrogen and export steam #ow rates is considered as the two objective functions for a "xed feed rate of methane to the existing unit. For the speci"ed plant con"guration, Pareto-optimal sets of operating conditions are successfully obtained by NSGA for di!erent process conditions. The results serve as a target for the operator to aim at, in order to achieve cost e!ective operation of hydrogen plants. ( 2001 Elsevier Science Ltd. All rights reserved.

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