Some independent plants making up a chemical or petrochemical site are linked by process streams. Linking process streams are, in general, cooled in up-plants and reheated in down-plants to satisfy process requirements. These streams, even more, travel from up-plants to storage tanks and, then, to down-plants, which results in low energy-use efficiency. Up-plants with multiple hot discharges and down-plants with multiple hot feeds are proposed in this paper, and a T–Q graphic method is presented to target the temperature of multiple hot discharges/feeds between plants. The T–Q diagram is composed of a grand composite curve (GCC) and a composite curve that only involves process streams employed for hot discharge/feed. A mixed integer linear programming (MILP) model is formulated to minimize the total hot and cold utilities of up- and down-plants and to solve the temperature of hot discharge/feed and the heat transfer between plants. Some examples are utilized to demonstrate the performance of the presented method for multiple hot discharges/feeds between plants. Results show an obvious decrease in the total hot and cold utilities of up- and down-plants, along with less investment for equipment.

The refining and petrochemical industries generally own process plants and utility systems. Process plants are configured to finish the transformation and separation of materials, and utility systems supply the energy requirements for the process plants. Therefore, integrating two of them is more favorable than optimizing them individually. A coupling mixed integer nonlinear programming model is presented in this work to integrate process plants and utility systems; the objective is to minimize the energy costs to meet the requirements of the process operations and to maintain a steam balance in the total site. The mathematical model includes three parts: the heat integration of the process plants, the optimization of the utility system, and the coupling equations for the site-scale steam integration. The heat integration of the process plant is formulated on the basis of pinch analysis involving heat loads of the process heaters and steam generation and requirements. An optimization of the utility system is also proposed to provide the relationship between steam balance, power generation, and fuel requirements. Coupling equations are used to balance the steam streams in each level between the process plants and utility systems. Two real industrial examples are also investigated to demonstrate the performance of the presented mathematical model. The solution results indicate not only a more profitable integration scheme but also increases in energy utilization efficiencies and the operational capacities of the utility systems.

A sharp increase in worldwide energy requirements has forced people to exploit novel energy conservation technologies and new alternative energies. Heat integration, as a method of saving energy, is proposed in this paper in the form of integrating multiple hot discharges/feeds between plants and utility streams to reduce utility requirements and increase steam production for the total site. T–Q graphic methods are proposed to coordinate the temperatures of multiple hot discharges/feeds between plants and the steam production. The grand composite curve (GCC), the composite curve of the streams employed for hot discharges/feeds, and the curve of steam generation are combined into the T–Q diagram to obtain an insight into the interrelationship between these streams. A bilevel mixed integer linear programming (MILP) framework is presented to minimize the total hot and cold utilities of the up and down plants and to maximize the steam generation in the total site. The first level of the programming framework is formulated to target the utility requirements, and the second level of the programming framework is formulated to maximize the steam production. Two examples are investigated to demonstrate the performance of the proposed method, and the results show a decrease in the total hot and cold utilities of the up and down plants and also indicate an increase in steam production.

Low grade heat still widely exists in energy-intensive industrial parks, although good energy integration has been accomplished for individual processes or plants. Low grade heat is notably large but difficult to utilize because of the limitation of heat transfer and the scarcity of low grade heat sinks. Large scale utilization of low grade heat is very challenging for energy-intensive industries or industrial parks. A large scale low grade heat recovery, refrigeration, and utilization network system is introduced in this study to improve energy performance for industrial parks. In order to model the large scale system, the system is decomposed into three levels: pipe networks, refrigeration stations and absorption chillers. A mixed integer nonlinear programming model is presented that considers mass and energy networks, pipes, refrigeration stations, absorption chillers, and economic performance. The mathematical model is applied to the optimization and economic analysis for the low grade heat utilization in a petrochemical industrial park in China. The model can be solved in available time using the global solver. The solution results demonstrate the good economic performance of the new low grade heat recovery, refrigeration, and utilization network system for the industrial park.

Though toluene disproportionation is an important process for producing para-xylene, it is heavily energy intensive because of its high reaction temperature and the need to separate close boiling-point components. Pinch analysis is often used to target utility requirements for process systems. Nevertheless, the supply and final temperatures of process streams are all predetermined according to the sequential method indicated in the onion model. Therefore, the sequential method ignores the influences of outer level facilities on inner level facilities, which leads to suboptimal solutions. To tackle this problem, variable temperatures of process streams are taken into account in this study to simultaneously target the utility requirements of columns and heat exchanger networks in a toluene disproportionation plant. To this end, relevant equations representing the relationships between feed temperatures and heat duties of columns are first obtained based on simulation data. Second, the equations are integrated into a transshipment model. Meanwhile, variable temperatures are introduced into temperature intervals. As a result, a mixed integer nonlinear programming problem is formulated to minimize the utility requirement in the whole toluene disproportionation plant. Third, the solution results are discussed, providing insights into the optimal results and the sensitivity of utility requirement caused by process streams and separation columns.