熵产最小化在篦冷机风量优化中的应用研究

Study on the Application of Entropy Generation Minimization in Air Volume Optimization of Grate Cooler

篦冷机冷却风量分配很大程度上决定着冷却机的热效率,而熵产分析可以评价换热过程的性质。通过建立篦冷机换热过程的熵产数学模型,量化了冷却风量与熵产的数值关系。并以最小化熵产数和风机功率为目标,使用多目标粒子群优化算法,迭代后得到了所求函数的最优Pareto前沿。通过最小距离法从最优解集中得到在5000t/d的水泥产量下最佳的风量分配方案。最后使用过程控制软件SIMATICPCS7绘制了篦冷机的操作画面,实现了篦冷机风量控制。在优化后的风量分配下,热工艺参数得到了改善,生产稳定。

To a large extent,the thermal efficiency of the grate cooler is determinedby cooling air distribution,and entropy generation analysis can evaluate the nature of the heat transfer process. By setting up the entropy production mathematical model for the heat transfer process of grate cooler,the numerical relationship between the cooling air flow and entropy generation was quantified. The multi-objective particle swarm optimization algorithm was used to obtain the optimal Pareto front aiming at minimizing entropy production and fan power. And the optimal air volume distribution is obtained from the optimal solution by the minimum distance method at the cement output of 5000t/d. At last,the operation screen of grate cooler is drawn by using the process control software SIMATIC PCS7,and the air volume controlis realized. Under the optimized air volume distribution,the thermal process parameters are improved and the production is stable.