Optimal operation of industrial aromatics extraction distillation process under uncertainty

In this paper, a method for optimizing the industrial aromatics extraction distillation process under the influence of uncertainty is raised. Firstly, the uncertainty optimization model of aromatics extraction distillation process is established based on chance constrained programming method for dealing with uncertainty constraint of raw material properties and inlet flow rate of the process. Then the optimization problem with uncertain constraint that satisfied certain confidence level probability is transformed into the equivalent deterministic optimization problem, and solved by the existing optimization techniques (eg. CPLEX Solver). The method proposed not only can reduce the optimization scale and ensure the overall optimization efficiency, but also ensure the feasibility of plant operation that greatly reducing energy cost. Meanwhile, the risk violation between objective function and constraint are compromised by introducing different confidence levels, so as to achieve the optimal tradeoff between the benefit and risk of optimization problem.