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采取300 MW循环流化床锅炉现场试验,研究循环流化床锅炉床温、床压随一次风量、二次风量、给煤量及回料阀开度的阶跃响应和锅炉负荷的阶跃响应。利用粒子群优化算法智能辨识,构建了床温、床压和锅炉负荷在不同工况下的阶跃响应模型。分析结果与前期学者仿真理论研究保持一致,并为300 MW循环流化床锅炉燃烧系统控制策略和不同负荷工况运行提供了优化参考依据。
A 300 MW circulating fluidized bed boiler field test was carried out to study the step response of the bed temperature and bed pressure of the circulating fluidized bed boiler as a function of the primary air volume, the secondary air volume, the coal feed volume, the valve opening degree and the step response of the boiler load . Particle swarm optimization algorithm is used to intelligently identify and construct the step response model of bed temperature, bed pressure and boiler load under different conditions. The analysis results are consistent with previous research on simulation theory of scholar, and provide an optimal reference for control strategy of 300 MW circulating fluidized bed boiler combustion system and operation under different load conditions.