Light Hydrocarbon Recovery Fractionation Procedure Optimization Theory And Technology Research

It was necessary for an enterprise to reduce production costs and enhance production quality by optimizing production and operation scheme when global competition becoming harder and harder. From the view of whole large system, it was difficult to solve optimization problems for light hydrocarbon recovery system because of complex technics flow and constrained conditions. Fractionation system was a key part which consumed energy mostly. It was crucial for the optimization of light hydrocarbon recovery system to optimize the operation of fractionation system.Currently, large-scale optimization based on rigor model was the main trend for process optimization. However, there were many difficulties existed in studies and applications because of high complexity, nonlinearity, conjunction and uncertainty existed in studied object. In this dissertation, the process model was built and some technics treatments were adopted. Accordingly, varied algorithms were induced to optimize the operation of fractionation system.The research works of this dissertation consisted of the following major parts:(1) According to the target problem, the current operation status of a typical light hydrocarbon recovery system was analyzed. The major controllable independent variables, dependent variables and the object function of optimization problem were formed.(2) The building and solution of process model were studied. Simulation was carried out to test the models built above.(3) Mapping models were built based on the multiple linear regression of simulation results. Uniform design and stepwise regression were adopted to ensure the veracity of mapping models.(4) Rigorous model was reduced. The dimension of variables and equations decreased, the solution of optimization problem became feasible.(5) Algorithm applying sparse matrix techniques in conjunction with Sequential Quadratic Programming (SQP) was discussed. It's realization was studied and tested. Based on the works introduced above, it was applied to optimize fractionation system.(6) Varied optimization algorithms were adopted as to varied types of models. Results gotten by different ways were analyzed and varied optimization strategies were acquired.