(547g) Locating Heat Exchangers in an EIP-Wide Heat Integration Network

Eco-industrial parks (EIP) are a cluster of manufacturing facilities located at proximity. They share and utilize each other’s resources, utilities, by-products and services for environmental, social and economic benefits, thus promoting sustainability [1]. Heating and cooling accounts for 73% of European Union’s total industrial energy consumption. Hence, there is a potential for inter-plant heat integration in such eco-industrial parks to conserve utilities [2]. However, it entails several challenges in terms of locating exchangers, confidentiality of streams, additional capital and operating expenses, and flexibility in the operation of individual plants [3]. To overcome these challenges, the prospect of locating the heat exchanger network (HEN) at a shared location was studied earlier [4]. This may not always be a feasible and an economical option, especially in case of space constraints or high land prices in locations such as Singapore. Hence, we propose an alternative approach where exchangers can be located at plant sites in enterprises.

In this work, we propose the idea of a distributed HEN, in which heat exchangers can be placed at some selected sites or participating plants. By allowing a heat exchanger to be located at a plant, we can eliminate the movement of streams that already belong to that plant. A plant can host an exchanger, only if the plant owns at least one of the exchanging streams. A stream may split into one or more substreams after entering a plant, but the substreams must merge again before leaving that plant. This is to minimize the cost of transporting multiple substreams and avoidance of operational issues. Also, we use the existing in-plant heaters/coolers at the exit of HEN. These heaters/coolers for the streams are retained or retrofitted to provide operational robustness. Existing in-plant movers (pumps or compressors) for the streams are retained or retrofitted to transport streams internally. One new mover is installed for transporting streams to other plants.

We develop a mixed integer non-linear programming (MINLP) model to synthesize the heat exchanger network for the above system. The model optimizes the HEN based on utility costs, exchanger and piping costs, and pumping expenses using a single objective function, Net Present Value (NPV). The superstructure-based formulation allows non-isothermal mixing in a stage [5, 6]. The model allows arbitrary cost expressions for exchangers and pumps with both fixed and variable components and cost multipliers for material and installation considerations. The model gives the optimum location of each exchanger with the capital and operating expenses associated with it.

For the first case study from Nair, et al. [4], the centralised HEN has NPV = $1.84 million and Internal Rate of Return (IROR) = 78.8 %. In contrast, the distributed HEN has NPV = $2.39 million with IROR = 161.5 %. Thus, by optimally locating the exchangers, the distributed HEN increases NPV by 30 % and IROR by nearly 100 %. Only two streams flow out of their plants in the distributed HEN versus six in the centralized HEN. The lower transportation needs reduce CAPEX by 45.9 %, and increases NPV and IROR. However, the distributed HEN saves less energy (i.e. utility heating and cooling) than the centralized HEN. The restricted availability of streams at each plant has limited exchanges and reduced energy savings.

Thus, the distributed HEN model designs a HEN based on the optimal streams matching, heat exchanger locations, utilities costs and investments required for pipes, pumps, to maximize the NPV of an EIP-wide HEN. Locating exchangers at plants reduced the number of streams travelling, saving significant piping, pump, and transportation investment. The distributed HEN model can choose and have a mix of inter-plant and intra-plant heat exchange considering the potential utility cost savings, CAPEX and OPEX before engaging the enterprises. With heat exchanger and stream locations as a variable, the distance between the plants play a significant role in deciding the HEN. This highlights the importance of trading off CAPEX versus OPEX, and true costs rather that simple energy savings to give a better HEN. Thus, the model can provide an optimal collaboration between many plants of many enterprises.

[1] R. P. Côté and E. Cohen-Rosenthal, "Designing eco-industrial parks: a synthesis of some experiences," Journal of Cleaner Production, vol. 6, pp. 181-188, 1998.

[2] E. Commission, "An EU Strategy on Heating and Cooling," ed. Brussels, 2016.

[3] C.-L. Chen and C.-Y. Lin, "Design of Entire Energy System for Chemical Plants," Industrial & Engineering Chemistry Research, vol. 51, pp. 9980-9996, 2012/08/01 2012.

[4] S. K. Nair, Y. Guo, U. Mukherjee, I. A. Karimi, and A. Elkamel, "Shared and practical approach to conserve utilities in eco-industrial parks," Computers & Chemical Engineering, vol. 93, pp. 221-233, 2016.

[5] T. F. Yee and I. E. Grossmann, "Simultaneous optimization models for heat integration--II. Heat exchanger network synthesis," Computers & Chemical Engineering, vol. 14, pp. 1165-1184, 1990.

[6] K. F. Huang and I. A. Karimi, "Simultaneous synthesis approaches for cost-effective heat exchanger networks," Chemical Engineering Science, vol. 98, pp. 231-245, Jul 19 2013.