【摘要】 为了提高农业火电机组SCR烟气脱硝系统的效率，将自适应粒子群算法引入到了控制系统的设计上，提出了一种基于神经网络粒子群的PID控制器参数优化方法，并将其应用到了秸秆火力发电机组脱硝系统上。为了验证该方法的有效性，将3种不同的方法应用到了脱硝系统上，测试结果表明：采用神经网络粒子群优化的智能控制器得到的脱硝效果最好，对于提高农业火电机组脱硝系统的脱硝效率具有明显的效果。更多还原

【Abstract】 In order to improve the efficiency of SCR flue gas denitration system of agricultural thermal power unit, it introduced the adaptive particle swarm optimization algorithm into the design of control system.It proposed a parameter optimization method of PID controller based on neural network particle swarm optimization and applied the denitration system of straw to thermal power unit.In order to verify the effectiveness of this method, three different methods are applied to the denitration system.According to the test results, the denitration effect obtained by using the intelligent controller optimized by neural network particle swarm optimization is the best, which has an obvious effect on improving the denitration efficiency of the denitration system of agricultural thermal power units.更多还原