An NLP approach for evolution of heat exchanger networks designed by pinch technology

Common methods to design heat exchanger networks (HENs) by pinch technology, usually need an evolutionary step to reduce number of heat transfer units. This step is called loop breaking and is based on removal of exchangers that impose minimum increase on utility consumption. Identification and breaking loops is a tedious task and becomes more complicated in large networks. This paper presents a rapid non linear programming (NLP) formulation for evolution of HENs in which loop identification is not required. The objective of the NLP is minimization of HENs annual cost which is not considered in current methods. In this method a search is done to find the best units, elimination of which improves HENs annual cost. The search continues until the minimum number of units (MNU) is achieved and exchangers must be removed from the network are specified. The method was applied to some networks reported in literature and better results were obtained. Also convergence of the presented method is very fast and is applicable to large scale networks.

Keywords:

Heat exchanger networks (HENs) , Minimum number of units (MNU) , Loop breaking , Non linear programming (NLP)