Optimization of united stations based on PSO

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.