摘要
联合站实际运行过程中常存在能耗及运行费用过高的问题,需要对其进行优化。建立了以年最低运行费用为目标的优化函数,并提出采用改进的粒子群算法(Particle Swarm Optimization,PSO)获得最优相关温度、压力及加药浓度等决策变量,从而在一定程度上达到降低联合站运行费用的目的。将该优化方法应用于胜利油田某联合站,并与实际运行费用及标准遗传算法的优化结果进行对比,结果表明:采用该方法对联合站运行参数进行优化,可以提高联合站的能量利用率,从而达到节能降耗的目的,并产生一定的经济效益,对实际生产具有一定的指导意义。
In order to reduce energy consumption and operation cost, the practical operation of united station should be optimized. In this paper, an optimization function was established with the minimum yearly operation cost as the target. It was proposed to calculate the decision variables （e.g. optimal temperature, pressure and dosing concentration） by using the improved Particle Swarm Optimization （PSO）, so that the operation cost of united station could, to some extent, be reduced. This optimization method was applied in a united station in Shengli Oilfield, and its optimization results was compared with the actual operation cost and the optimization results obtained by the standard genetic algorithm. It is shown that the energy utilization ratio of united station can be ultimately increased so as to achieve the purpose of energy saving, consumption reduction and economic benefits when the operation parameters are optimized by means of this optimization method. This method plays an instructive role for the actual production.
作者
寇杰
孙思聪
李云
KOU Jie SUN Sicong LI Yun(China University of Petroleum（Huadong Infrastructure Management Department of Sinopec Shengli Oilfield Company)
出处
《油气储运》
CAS
北大核心
2016年第9期990-993,1013,共5页
Oil & Gas Storage and Transportation
关键词
联合站
优化设计
粒子群算法
效果
united stations, optimization design, PSO, effect
