Bilevel heat exchanger network synthesis with an interactive multi-objective optimization method

• Published in: Applied thermal engineering 2012-12, Vol.48, p.301-316
• Main Authors: Laukkanen, Timo, Tveit, Tor-Martin, Ojalehto, Vesa, Miettinen, Kaisa, Fogelholm, Carl-Johan
• Format: Article
• Language: English
• Subjects: Applied sciences; Decision making; Devices using thermal energy; Energy; Energy. Thermal use of fuels; Exact sciences and technology; GAMS; Grouping of process streams; Heat exchangers; Heat exchangers (included heat transformers, condensers, cooling towers); Heat transfer; Interactive; MINLP; Network synthesis; Networks; NIMBUS; Optimization; Pareto optimality; Streams; Synheat model; Theoretical studies. Data and constants. Metering; Thermal engineering
• ISSN: 1359-4311; 1873-5606
• DOI: 10.1016/j.applthermaleng.2012.04.058

Heat exchanger network synthesis (HENS) has been an active research area for more than 40 years because well-designed heat exchanger networks enable heat recovery in process industries in an energy- and cost-efficient manner. Due to ever increasing global competition and need to decrease the harmful effects done on the environment, there still is a continuous need to improve the heat exchanger networks and their synthesizing methods. In this work we present a HENS method that combines an interactive multi-objective optimization method with a simultaneous bilevel HENS method, where the bilevel part of the method is based on grouping of process streams and building aggregate streams from the grouped streams. This is done in order to solve medium-sized industrial HENS problems efficiently with good final solutions. The combined method provides an opportunity to solve HENS problems efficiently also regarding computing effort and at the same time optimizing all the objectives of HENS simultaneously and in a genuine multi-objective manner without using weighting factors. This enables the designer or decision maker to be in charge of the design procedure and guide the search into areas that the decision maker is most interested in. Two examples are solved with the proposed method. The purpose of the first example is to help in illustrating the steps in the overall method. The second example is obtained from the literature. ► Increased calculation efficiency for simultaneous heat exchanger network synthesis. ► Interactive multi-objective optimization with General Algebraic Modeling System. ► Bilevel decomposition applied.