输气管网稳态能耗数学模型是一个具有非线性约束条件、多维的、非凸的最优化问题,需要优化各节点的压力和流量使得压缩机功耗最小或经营效益最大.为了提高求解效率,提出管道流动方程约束的松弛处理方法,扩大最优问题解的可行域.对传统的模式搜索算法中的探测移动策略进行改进,允许搜索空间的大小反复变化,可以随机选择不同维的元素同时变化,提高局部寻优效率.结合粒子群算法,允许每代进化的粒子根据自身经验和社会知识在可行域内飞行.仿真结果表明:对于输气管网的非线性优化模型,在相同的初始条件和计算精度下,改进模式搜索算法可以在全局范围内寻找最优解,增强了模式搜索算法的智能性；求解结果优于传统的单纯形算法和积极集算法的结果.%The no-convex optimal mathematical model of networks includes nonlinear constraint conditions and multidimensional variables. The assignment of optimal values to flow and pressure variables of each node makes the minimal compressor power consumption or maximum operational benefit. To improve the solution efficiency, the relax method for pipe flow equation which enlarges the solution's feasible domain was imposed. The search mode was changed to improve the efficiency of local search. The search space could be changed repeatedly and the number of changing dimension was selected randomly. To improve this method intelligent, the particle swarm method was integrated. The particles could fly in the feasible domain according to their own experience and social knowledge. The simulation results show that the improved pattern search .method could search optimal solution in global space. Under the same initial conditions and accuracy requirements, the result of this algorithm is superior to the-results of simplex algorithm and the classic linear programming algorithm.
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