Polygeneration systems offer the possibility of efficient, low-carbon production of different product streams from a single facility. Such systems take advantage of opportunities for integrating processes to achieve effective recovery of waste energy and material streams. Mathematical programming methods have proven to be valuable for the optimal synthesis of such polygeneration systems. However, in practice, numerical parameters used in optimization models may be subject to uncertainties. Examples include cost coefficients in volatile markets, and technical or thermodynamic coefficients in new process technologies. In such cases, it is necessary for the uncertainties to be incorporated into the optimization procedure. The target-oriented robust optimization (TORO) is a new methodology that is inspired by robust optimization. The use of this methodology leads to the development of a mathematical model that maximizes robustness against uncertainty, subject to the achievement of system targets. Its properties allow us to preserve computational tractability and obtain solutions to realistic-sized problems. To this end, we propose a methodology for the synthesis of polygeneration systems using TORO. We illustrate this new approach with an industrial polygeneration case study.
|Title of host publication||Chemical Engineering Transactions|
|Editors||Xia Liu, Petar Sabev Varbanov, Jiri Jaromir Klemes, Sharifah Rafidah Wan Alwi, Jun Yow Yong|
|Publisher||Italian Association of Chemical Engineering - AIDIC|
|Number of pages||6|
|Publication status||Published - 2015 Oct|
All Science Journal Classification (ASJC) codes
- Chemical Engineering(all)