基于新型测温技术的电站锅炉燃烧优化

Combustion Optimization of Power Plant Boiler Based on New Temperature Field Measurement Techniques

为了提高锅炉效率,减少污染物排放,电站锅炉需要进行燃烧优化。以新型测温技术为基础,提出一种包含炉内温度场测量结果的燃烧优化模型,采用模拟退火算法作为燃烧优化控制算法进行优化。以某电厂300 MW锅炉为研究对象,采用仿真的方法对燃烧优化控制算法进行研究,通过对锅炉运行参数受到扰动时的工况进行燃烧优化,验证了模拟退火算法的优化性能。结果表明:在锅炉运行参数受到扰动时,模拟退火算法作为优化算法,能够给出有效的燃烧调整指令,解决扰动产生的问题,使炉膛燃烧状态保持设定的优化状态。

In order to improve boiler efficiency and reduce pollution,power plant boilers require combustion optimization.A boiler combustion optimization model,including temperature field measurement result in furnace,was proposed based on new temperature field measurement techniques.Simulated annealing algorithm was used as the combustion optimization control algorithm.Combustion optimization control algorithm was studied by using simulation method for a 300 MW power plant boiler.The optimization of simulated annealing algorithm was verified by optimizing the combustion conditions when boiler operating parameters were disturbed.The results indicate that simulated annealing algorithm is able to give effective combustion adjustment instructions when boiler operating parameters are disturbed and the instructions can solve the problems to make furnace combustion maintain an optimal state.