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.