ABSTRACT
Synthesis of heat exchanger network (HEN) of an actual chemical plant not only optimizes the total cost but also an important aspect of energy conservation. Pinch technology along with other strategies offer an effective and practical method for designing the HEN. While as an optimization tool, Genetic Algorithms (GA) is a search algorithm based on mechanics of natural selection and natural genetics. The pinch technology can be combined with the Genetic Algorithms to obtain hopefully, the better results.
Different case studies of HEN have been optimized by different investigators. Generally the stream data contains equal heat transfer coefficient of streams, requirement of single utility, use of non-uniform heat exchanger specification and other various simplicities. In real scenario, it is important to optimize the HEN with all the complexities to obtain the actual cost effective HEN for an actual chemical plant. The author has employed GA to optimize the HEN with complexities like unequal heat transfer coefficient, use of multiple utilities and non-uniform exchanger specification. The minimum flux approach as suggested by Rev and Fonyo [1] gives better results for HEN with such complexities like unequal heat transfer coefficients. The author has employed minimum flux approach along with GA to optimize different case studies having the data of an actual chemical plant and also to optimize the case studies considering the complexities. The results give indication that minimum flux approach along with GA gives better results for continuous targeting of HEN which may be a good start towards optimum HEN with complexities.
Keywords: Heat Exchanger Network, Minimum Flux Approach, Genetic Algorithms, Unequal Heat Transfer Coefficients, Multiple Utilities, Non-Uniform Heat Exchanger Specifications.
