摘 要：钢铁企业根据日际生产计划，可以确定日际生产的副产煤气总体积、各煤气消耗设备的热量需求。为进一步确定各设备消耗的混合煤气中的煤气配比，使煤气产耗平衡，提出混合煤气逆向分解方法，将各设备消耗的混合煤气中所包含的单一煤气成分体积，表示为各设备获得热量与混合煤气热值的函数，在此基础上建立日际煤气最优混合配比算法模型。该模型以各设备的混合煤气热值及热量作为决策变量，以各煤气消耗设备的热量偏差最小为目标，综合考虑各煤气设备的热值要求、自备电厂的热值、热量要求及煤气体积守恒等约束条件。采用遗传算法求解，并利用遗传算法基因初始化的范围区间控制混合煤气的热值范围。算例结果表明：建立的日际煤气最优混合配比算法模型，在优化煤气分配的同时，显著减少了约束方程及决策变量的数量，为钢铁企业日际煤气平衡调度提供了理论支撑。

Abstract:The volume of the byproduct gas and the heat requirements of the gas consumption equipment can be determined by the daily production plan of the steel enterprise. For further determining the gas ratio of mixed gas for every equipment and making gas production balance,This paper proposes a method with the reverse decomposition of mixed gas. The volume of the single gas in the mixed gas used by each equipment is expressed as a function of the heat and the calorific value of the mixed gas. Then the optimal mixed ratio algorithm model is established. The model uses the mixed gas calorific value and heat as the decision variables to minimize the heat deviation of each gas consumption equipment,taking into account the gas Equipment calorific value requirements,self-owned power plant calorific value,heat requirements and gas volume conservation and other constraints. In this paper,genetic algorithm is used and the range of calorific value of mixed gas is controlled by the interval range of gene initialization. The result shows that the optimal mixed ratio algorithm model established in this paper significantly reduces the number of constraint equations and decision variables,and supports the daily coal gas balance scheduling for the iron and steel enterprises.

TK01+8

江苏省科技项目（BY2015070-23）