(388f) A General Framework for Process and Utility Networks Synthesis

There are sub-systems in chemical plants that consist of a number of sinks with demand for a certain property and a number of alternative sources that can satisfy these properties to fulfil the sink demands. Examples of such sub-systems are heat exchanger networks [1], fuel gas networks [2], water networks [3], utility networks [4], etc. Properties that are exchanged can be energy in the form of heat as in heat exchanger networks, or in both work and heat form as in the utility networks. Although each subsystem has attracted significant attention, each synthesis problem requires a new superstructure to be postulated whenever a new problem is encountered. Similarly, separation network systems, such as membrane networks [5] and distillation sequences [6], have been a focus of attention, yet a new superstructure representation is needed for each problem. A unified superstructure representation for these different classes of synthesis problems will be highly advantageous. Recently, a systematic framework for process intensification based on building-block superstructure has been proposed based on the idea of dissecting various unit operations into fundamental building blocks [7]. The proposed method can be also used for automatic flowsheet generation.

In this work, we extend the approach to provide a general framework for the synthesis of different networks using a similar representation using building blocks. Here, each block has feed and product streams ensuring interaction with the surroundings and can be viewed as sources and sinks, respectively. Also, streams between blocks are equipped with compressors or expanders depending on the source and sink block pressures. Mass and energy flow within the superstructure are facilitated via block material and energy balances and heating and cooling requirements are decided accordingly. Separation operations, such as gas membrane separations, are represented via two neighboring blocks separated by a semi-restricted boundary. The decisions over the assignment of boundary types between blocks are enabled via use of decision variables. By using all of these features of the building block superstructure, several different process network synthesis problems can be accommodated in a single superstructure with n and m number of blocks in row and column respectively. It should be noted that for different network synthesis problem, the block superstructure size could be reduced to improve the computation performance, i.e, using 2×m superstructure to represent a pooling problem without intermediate pools. The overall process network synthesis problem is formulated as a mixed-integer nonlinear optimization (MINLP) problem where the nonlinear terms are due to splitting, energy balances and/or work calculations and discrete variables are for assigning alternative operations to each block and boundary in the superstructure. In this work, we will demonstrate that the proposed method is capable of unifying the superstructure representations for different class of process network synthesis problems via a range of literature problems.

References:

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[2] Hasan, M.F., Karimi, I.A. and Avison, C.M., 2011. Preliminary synthesis of fuel gas networks to conserve energy and preserve the environment. Industrial & Engineering Chemistry Research, 50(12), pp.7414-7427.

[3] Ahmetović, E. and Grossmann, I.E., 2011. Global superstructure optimization for the design of integrated process water networks. AIChE journal, 57(2), pp.434-457.

[4] Elia, J.A., Baliban, R.C. and Floudas, C.A., 2010. Toward novel hybrid biomass, coal, and natural gas processes for satisfying current transportation fuel demands, 2: Simultaneous heat and power integration. Industrial & Engineering Chemistry Research, 49(16), pp.7371-7388.

[5] Alnouri, S.Y. and Linke, P., 2012. A systematic approach to optimal membrane network synthesis for seawater desalination. Journal of membrane science, 417, pp.96-112.

[6] Giridhar, A. and Agrawal, R., 2010. Synthesis of distillation configurations: I. Characteristics of a good search space. Computers & chemical engineering, 34(1), pp.73-83.

[7] Demirel, S.E., Li, J., Hasan, M.M.F. Systematic Process Intensification using Building Blocks. Computers & Chemical Engineering, http://dx.doi.org/10.1016/j.compchemeng.2017.01.044.