Multi-stream Heat Exchanger Networks Synthesis With Genetic/Simulated Annealing Algorithm

Multi-stream Heat Exchanger Network is a new type of heat exchanger networks. Compared with traditional two-stream heat exchangers, multi-stream heat exchangers possess many advantages such as high efficiency, compact structure and low cost. Although multi-stream heat exchangers are widely used in process industries such as gas processing and petrochemical industries, much work during the last two decades is focused on conventional two-stream heat exchanger networks. Few studies have been done on mathematical models and their solution technique for heat exchanger network (HEN) synthesis with multi-stream heat exchangers.Supported by the Deutsche Forschungsgemeinschaft (DFG, No. RO294/9) and Liaoyang Petrochemical Co. Ltd., we done theoretical and engineering application study on multi-stream heat exchanger network synthesis problem. The work in this paper involves following subjects:1) Based on concept of stage-wise heat exchanger network superstructure, a synthesis model of heat exchanger network with multi-stream heat exchangers supporting non-isothermal mixing of splits is established. The assumption of isothermal mixing in literature reduces non-linearity, eases solution difficulty, but also narrows the problem space, leading to local optima. The presented model does not rely on any heuristics such as pinch technology, and no constraint for process stream heat transfer film coefficients is needed. Through solving the model, we can optimize utility cost, exchangers' area, number of units and stream split fractions simultaneously.2) The synthesis of HEN with multi-stream heat exchangers is modeled as an MINLP problem. Traditional gradient-based optimization technique fails to find the global optima due to the non-convexity and non-linearity and many local optima of this kind of problem. Alternatively, genetic algorithm (GA) and simulated annealing (SA) provide a promising approach for this problem. In the paper, to solve the synthesis problem with an algorithm (GA/SA), some combination of algorithm with the specific synthesis problem is considered:(1) Genetic algorithm provides only a general framework for solving complex optimization problem. The genetic operators are often problem-dependent and are of critical importance for successful use in practical problem. Specifically, to the synthesis problem of HEN with multi-stream heat exchangers, an approach for initial HEN generation, heat load determination of a match within superstructure are given. Some operators such as crossover operator, mutation operator, OCX (Orthogonal Crossover) and EC (Effective Crowding) operators are appropriately designed to adapt to the HENS problem.(2) Another difficulty for genetic algorithm is the constraints handling. During genetic evolution, the individual of the population often turn into some infeasible solution after manipulated by genetic operators. This often leads to failing to find a feasible solution during evolution, especially to the strict constraints optimization problem. Hence, some strategy should be contrived for constraints guarantee inIIIgenetic computation. The HENS problem of multi-stream heat exchangers is a more lage scale combinatorial optimization problem with more strict constraints and complexity. It brings forth more difficulty for constraints handling. According to characters of the heat exchanger network of multi-stream heat exchangers, we design an operator to transform the infeasible solution to feasible ones. Some strategies related with the network operability and cost-reducing are also devised in the paper. The feasibility of proposed GA/SA approach for HENS with multi-stream heat exchangers is demonstrated successfully through varying scale synthesis problems.3) The economical advantage of multi-stream heat exchangers network over traditional two-stream heat exchangers network is illustrated through calculations. At last, as engineering practice, we applied our approach to an industrial case, a heat exchangers network synthesis problem for crude oil pre-heating. Using our program...