Design optimization of industrial energy systems with energy consumption relaxation models for coupling process units and utility streams

Industrial energy systems, such as in the petrochemical and iron energy-intensive industries, are a utility hub to convert fuels into various forms of energy and then supply them to satisfy the energy requirements from process units. In conventional industrial energy systems design, the forms and quantity of energy required from process units are generally considered as deterministic. As a result, the optimization boundary of energy systems design is reduced in advance, leading to sub-optimal design results. In this study, energy interchangeability in process units is introduced to relax the bounds of energy requirements. These energy interchangeabilities can lead to different distribution patterns of energy requirement. In order to quantify the energy interchangeability of process units, energy consumption relaxation models (ECRMs) are presented. Two kinds of energy interchangeabilities are considered and investigated, one is the heat-based energy interchange between fuels and steam, another is the work-based energy interchange between electricity and steam. A candidate superstructure of industrial energy systems and a mixed integer nonlinear programming (MINLP) framework are then reformulated to conduct design optimization of the energy system to minimize the total annual cost (TAC). Lastly, the proposed method and MINLP optimization framework are applied to a large-scale refinery site for the design optimization of the energy system. Compared with the conventional optimized design, the TAC and annual CO2 emission are decreased by 10.96% and 19,845 tons, respectively.

Automated summary

In this study, the concept of energy interchangeability is introduced to optimize the design of industrial energy systems. The results show that introducing energy interchangeability can reduce the total annual cost and CO2 emissions.