Production Oprational Optimization Of Natural Gas Liquefaction Station

The Natural Gas Liquefaction Station mainly uses heat exchange method to product liquid natural gas. The natural gas is transferred to the station area by pipeline, and then it passes through pretreatment unit, liquefaction unit, storage unit and loading measurement unit. As the core of natural gas liquefaction station process, liquefaction process is PRICO which is patent technology developed by Black&Veatch Company. This is the first time to use this technology in Chinese liquefaction station without any experience. In order to improve the liquid production rate, reduce the consumption and optimize the production operation for this and other subsequence liquefaction stations, this thesis for production operational optimization of Natural Gas Liquefaction Station was studied.The thesis firstly introduced the production process of natural gas liquefaction station in detail, selected liquefaction unit and BOG unit as the optimization process, analysis the optimization objectives, operation variables and constraints in detail. Put forward to use the neural network to establish liquefaction unit and BOG unit production operational optimization models. Analyze the structure and training of neural network. Established the models by Basic Spline neural network and do the training. Subsequently this thesis introduced optimization technology of using interactive evolutionary algorithm to solve the problem of multi objective based on neural network and introduced the algorithm structure. Realize the algorithm in the multi objective models of liquefaction unit and BOG unit by MATLAB. Finish the simulation study by actual production data to search the optimal parameters to guide the production operation.