改进PSO算法在蒸汽动力系统多周期运行优化中的应用

为了满足石化企业工艺过程对蒸汽和电力不断变化的要求，实现企业降低成本、节能降耗的目的，必须保证蒸汽动力系统在最优的状态下运行。针对这一问题在以往研究的基础上提出了包括设备维护和启停费用的改进的混合整数线性规划模型，利用改进的PSO算法对其求解，并通过实例证明了利用该模型、使用改进的PSO算法能很快得到最优的方案，并节省了大量的运行成本。

Optimal multi-period operational planning of steam power systems using improved particle swarm optimization method

The steam power system (SPS) should be operated under the optimal scheme to meet the varying demand for steam and power and to reduce cost and save energy for petrochemical industry.A mixed integer linear program (MILP) model was presented for multi-period operational optimization of utility system.The objective function of the model was to find the minimum annual operational cost of utility systems during the multiple periods, by considering fuel cost, feed-water cost, maintenance cost and startup/shutdown charge.An improved particle swarm optimization(PSO) was employed to obtain the optimum solution of the MILP model.This improved PSO utilized two linearly changing inertia weights to make particles have the tendency to reach global optimum.The application of the proposed optimization approach was illustrated through one case study.