摘要
针对锅炉受热面吹灰优化问题,研究了剩余时间预测及预防性吹灰最优决策问题,提出了一种基于剩余时间预测的燃煤电站锅炉吹灰优化策略。在锅炉受热面积灰分布函数未知的条件下,由已知的锅炉受热面的剩余时间分布函数预测其平均剩余时间,以平均剩余时间为阈值制定预防性吹灰策略。由更新过程理论,建立了以预测间隔、吹灰阈值为优化变量和最小平均吹灰费用为目标的优化模型。采用粒子群算法进行优化求解,得到锅炉最优的监测周期和吹灰阈值,并使锅炉长期运行的平均费用率最低。
Aiming at the problem of soot blowing optimization on boiler heating surface, the remaining time prediction and preventive soot blowing optimal decision problem were studied. A coal-fired power plant boiler soot ashing optimization strategy based on residual time prediction was proposed. Under the condition that the ash distribution function of the boiler heating area is unknown, the average remaining time is predicted from the known time distribution function of the boiler heating surface, and the preventive soot blowing strategy is formulated with the average remaining time as the threshold. Based on the update process theory, an optimization model with the prediction interval, the soot threshold value as the optimization variable and the minimum average soot cost is established. The particle swarm optimization algorithm is used to optimize the solution, and the optimal monitoring period and the dust blowing threshold of the boiler are obtained, and the average cost rate of the boiler’s long-term operation is the lowest.
出处
《电子测量与仪器学报》
CSCD
北大核心
2018年第10期59-64,共6页
Journal of Electronic Measurement and Instrumentation
基金
山西省青年自然科学基金(201601D021075)
山西省高等学校科技创新项目(2014143)
山西省回国留学人员科研项目(2015-083)
中北大学自然科学基金(2016032,2017025)资助项目
关键词
锅炉受热面
剩余时间
预防性吹灰
优化
boiler heating surface
remaining time
precautionary blowing ash
optimization
