Optimization of Internal Thermally Coupled Distillation Columns of Nonideal Mixture

Internal thermally coupled distillation column(ITCDIC) is a frontier in energy saving distillation research. In this paper, the optimal assessment on the energy saving and the operating cost for ITCDIC of nonideal mixture is explored. An evaluating method is proposed, and the pertinent optimization model is then derived. The ethanol-water system is studied as an illustrative example. The optimization results show that the maximum energy saving in ITCDIC process is about 35% and the maximum operating cost saving in ITCDIC process is about 30%,as compared with a conventional distillation column(CDIC) under the minimum reflux ratio operating; the optimal operating pressure of the rectifying section is found to be around 0.25 MPa; the effects of the feed composition,operating pressure and the heat transfer rate on operation are also found and analyzed. It is revealed that ITCDIC process possesses high energy saving potential and promising economical prospect.

A Novel Scheduling Strategy for Crude Oil Blending

For those refineries which have to deal with different types of crude oil, blending is an attractive solution to obtain a quality feedstock. In this paper, a novel scheduling strategy is proposed for a practical crude oil blending process. The objective is to keep the property of feedstock, mainly described by the true boiling point (TBP) data, consistent and suitable. Firstly, the mathematical model is established. Then, a heuristically initialized hybrid iterative (HIHI) algorithm based on a two-level optimization structure, in which tabu search (TS) and differential evolution (DE) are used for upper-level and lower-level optimization, respectively, is proposed to get the model solution. Finally, the effectiveness and efficiency of the scheduling strategy is validated via real data from a certain refinery.

A novel two-stage Lagrangian decomposition approach for refinery production scheduling with operational transitions in mode switching

To address large scale industrial processes,a novel Lagrangian scheme is proposed to decompose a refinery scheduling problem with operational transitions in mode switching into a production subproblem and a blending and delivery subproblem.To accelerate the convergence of Lagrange multipliers,some auxiliary constraints are added in the blending and delivery subproblem.A speed-up scheme is presented to increase the efficiency for solving the production subproblem.An initialization scheme of Lagrange multipliers and a heuristic algorithm to find feasible solutions are designed.Computational results on three cases with different lengths of time horizons and different numbers of orders show that the proposed Lagrangian scheme is effective and efficient.

A continuous-time formulation for refinery production scheduling problems involving operational transitions in mode switching

In the refinery scheduling, operational transitions in mode switching are of great significance to formulate dynamic nature of production and obtain efficient schedules. The discrete-time formulation meets two main challenges in modeling: discrete approximation of time and large size of mixed-integer linear problem(MILP).In this article, a continuous-time refinery scheduling model, which involves transitions of mode switching, is presented due to these challenges. To reduce the difficulty in solving large scale MILPs resulting from the sequencing constraints, the global event-based formulation is chosen. Both transition constraints and production transitions are introduced and the numbers of key variables and constraints in both of the discrete-time and continuous-time formulations are analyzed and compared. Three cases with different lengths of time horizons and different numbers of orders are studied to show the efficiency of the proposed model.