摘要
燃煤锅炉燃用劣质煤已经非常普遍,带来的经济、环保问题越来越大。已有研究在锅炉燃用劣质煤方面主要关注锅炉飞灰含碳量、排烟温度或NO_(x)产量等单方面的经济性参数,而忽略了锅炉运行整体经济性优化,因此某方面的优化可能引起其他方面的损失。采用改进极限学习机算法构建了某350 MW超临界锅炉燃用劣质煤时的运行预测模型;全面考虑燃烧优化对燃煤成本、脱硫脱硝运行成本和锅炉辅机电耗成本等,建立了超临界锅炉运行整体经济性评价方法;在运行预测和整体经济性评价模型基础上,开展了锅炉运行整体经济性优化计算。结果表明,煤的发热量、锅炉一次风率和氧量对锅炉排烟温度、飞灰含碳量均具有较高影响权重,贡献率均大于10%。因此,进一步探究了上述因素对锅炉整体经济性的影响规律和优化方案。随煤发热量升高锅炉运行成本先降低后升高,存在最优发热量;在计算范围内锅炉运行成本随一次风率升高而升高;不同负荷下炉膛氧量也存在最佳值。构建的锅炉运行预测算法和整体经济性优化模型为超临界锅炉运行优化提供了新方法。
The prevalence of burning inferior coal in coal-fired boilers has led to increasingly significant economic and environmental issues.Existing research on the combustion of inferior coal in boilers has primarily focused on individual economic parameters such as boiler fly ash carbon content,flue gas temperature,or NO_(x)emissions.However,these studies have overlooked the holistic economic optimization of boiler operation,potentially leading to trade-offs between different aspects.This paper employs an improved Extreme Learning Machine algorithm to construct a predictive model of a 350 MW ultra-supercritical boiler burning inferior coal.Additionally,an overall economic evaluation method for the operation of ultra-supercritical boilers is established,which forms the basis for optimizing the boiler's overall economic performance.The results indicate that the heating value of coal,primary air rate,and oxygen content have high impact on the flue gas temperature and carbon content of fly ash in the boiler,with their contributions exceeding 10%.Consequently,the study further explores the influence and optimization measures of these factors on the overall economic performance of the boiler.As the heating value of coal increases,the operational cost of the boiler first decreases and then increases,indicating the existence of an optimal heating value.Within the scope of calculation for the boiler studied in this paper,the operational cost increases with an increase in primary air rate.Moreover,there is an optimal value of furnace oxygen concentration under different loads.The proposed boiler operation prediction algorithm and economic optimization model in this study offer a novel approach to optimizing the operation of ultra-supercritical boilers.
作者
隋炳伟
赵晓鹏
晁俊凯
许大鹏
SUI Bingwei;ZHAO Xiaopeng;CHAO Junkai;XU Dapeng(Ningxia Jingneng Ningdong Power Generation Co.,Ltd.,Lingwu 751400,China)
出处
《洁净煤技术》
CAS
CSCD
北大核心
2024年第S02期592-599,共8页
Clean Coal Technology
关键词
超临界燃煤锅炉
劣质煤
极限学习机
经济性评价
运行优化
Supercritical boiler
inferior coal
extreme learning machine
economic evaluation
optimal control
