| Title | Optimisation of Water-Energy Networks in Process Industry: Implementation of Non-Linear and Multi-Objective Models |
|---|---|
| ID_Doc | 13036 |
| Authors | Oliveira, MC; Vieira, SM; Iten, M; Matos, HA |
| Title | Optimisation of Water-Energy Networks in Process Industry: Implementation of Non-Linear and Multi-Objective Models |
| Year | 2022 |
| Published | |
| Abstract | The improvement of water and energy use in the industrial sector is an important concern to improve the overall techno-economic performance of single plants. The most recent EU strategy for energy system integration has been treating these issues in the redaction of its first pillar, which is based on the relations between the promotion of circular economy and energy efficiency and it has as specific objectives the promotion of waste heat recovery and energy recovery from wastewater. Although on the context of research and industrial appliance both waste heat recovery and water recycling and reuse have been extensively explored, it is still verifiable a lack of comprehension and application of methods to simultaneously improve the use of both water and energy in a plant. In this work, two approaches for the solving of an optimisation problem related to the improvement of water and energy use in a process industry plant (three water-using processes) are implemented. These approaches consist on the development of a mixed-integer non-linear programming (MINLP) model and a multi-objective programming (MOP) model using the Python language. In addition, a complementary approach based on the development of a non-linear programming (NLP) model for further heat integration is also developed. Within the three applied methodologies (MINLP, MOP and integrated MINLP and NLP), the integrated MINLP and NLP model was the one in which the most favourable results were obtained, with 33.7% freshwater savings, 73.2% energy savings and 67.2% total economic savings. |
| https://www.frontiersin.org/articles/10.3389/fceng.2021.750411/pdf |
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