Abstract: The multi-period operation of boiler steam system with decaying performance was formulated as a mixed-integer nonlinear program (MINLP).The objective function accounted for both the cost of fuel consumption and the cost of boiler cleaning and maintenance.To solve this problem,a method called steepest descent-approximate linear programming (SDALP) is proposed,which is based on the thought of purposeful search and rapid convergence from steepest descent method.The algorithm use the thought of the steepest descent to replace the role of the restricted step and the reduced coefficient in approximate linear programming (ALP).The algorithm also introduces the concept of the move-into vector and move-out vector and positive redundancy,and adjust the boundary of variables by the compound of this two vectors.By redefining the judgment conditions and the way of boundary adjustment of the algorithm,it can excludes the optimal solution out of the boundary condition,which is caused by the subjective choices of initial feasible point,step restriction and reduction coefficient of traditional approximate linear programming.After several test cases,numerical results shows that not only both of the accuracy and the speed of the algorithm are better than the previous one,but also the global solution.Apply the method in a real thermal power plant,the computation time for the SDALP method was proportional to the number of periods,but usefulness of the method shows that it also can achieves remarkable energy saving when compared with the original approaches.

Key words: cyclic cleaning scheduling of boiler, steepest descent approximate linear programming, nonlinear programming, linear constraints

摘要： 多操作周期的锅炉蒸汽系统是一个性能随时间衰减的混合整数非线性规划问题，其目标函数由燃煤量和锅炉清洗维护的费用构成。针对此类非线性问题，提出了最速下降近似线性规划（SDALP）的算法，利用最快速下降的目的性搜索思想，引入移入、移出向量和积极富裕量，通过对调整变量边界的判断条件和途径进行了新的定义，排除了传统近似线性规划方法中主观选择初始可行解、步长限制量以及缩小系数等变量可能导致的将最优解排除在变量边界之外的问题。将该算法应用于锅炉蒸汽系统循环清洗调度问题，实验结果表明，SDALP算法解出的调度方案优于原电厂调度方案，节能效果明显。

关键词: 锅炉循环清洗调度, 最速下降近似线性规划, 非线性规划, 线性约束