基于SUMT-MPSO算法的CFB机组联合脱硝系统经济优化研究

Study on economic optimization of CFB unit combined denitration system based on SUMT-MPSO algorithm

针对目前超低排放政策下循环流化床机组(Circulating Fluidized Bed,CFB)SNCR+SCR两级联合脱硝系统运行成本较高的问题,设计了一种基于罚函数法(Sequential Unconstrained Minimization Technique,SUMT)的改进型粒子群寻优算法(Modification Particle Swarm optimization,MPSO),通过引入随机衰减因子和收敛因子增加粒子群在粒子上下边界区间内的随机性,提高算法全局搜索能力和收敛性;再利用罚函数法实现MPSO寻优算法对联合脱硝系统有约束条件的一维目标规划模型求解,寻找CFB机组两级联合脱硝最佳脱除份额配比。通过对某300MW CFB机组联合脱硝现场实际运行数据进行经济性模型寻优求解,得出不同负荷下系统最优运行成本,为联合脱硝系统经济性运行调整提供理论指导。

Aiming at the problem of high operating cost of SNCR＋SCR two stage combined denitration system of circulating fluidized bed unit （CFB） under ultra low emission policy, an improved particle swarm optimization （MPSO） algorithm based on penalty function method （SUMT） is designed, by introducing the random attenuation factor and convergence factor to increase the randomness of particle swarm in the upper and lower bounds of particles, improve the global search ability and convergence; using the SUMT method to realize the MPSO optimization algorithm to solve the one-dimensional model of goal programming combined denitration system with constraints, searching for the best removal ratio of CFB two unit combined denitration. According to a 300MW CFB unit combined denitration field operation data of actual economic model optimization, the optimal operating cost of the system under different loads, and for joint economic operation to provide theoretical guidance to adjust the denitration system.