燃煤电厂SCR脱硝系统精准控氨优化方法研究
摘要：针对燃煤电厂选择性催化还原(selective catalytic reduction，SCR)脱硝系统喷氨不均匀的问题，将智能前馈串级控制技术与分区控制技术相结合，提出了一种精准控氨优化方法。在智能前馈环节，采用预测精度更高的改进一维卷积神经网络模型，实现了SCR反应器入口NO x 质量浓度的预测，并将其作为智能前馈控制信号，实现了机组全工况下NO x 质量浓度的快速准确控制。在分区控制环节，采用分区巡测-多点同步取样测量技术与均衡控制策略相结合的方法，实现了各分区喷氨量的精准控制。该优化方法已应用于多个燃煤电厂，运行结果表明，机组全工况下实现了喷氨量的精准控制，SCR反应器出口断面NO x 质量浓度分布均匀，波动范围小，氨耗量降低明显，经济效益显著。
Abstract:In order to solve the problem of uneven ammonia injection in selective catalytic reduction (SCR) de-NO x system of coal-fired power plant, a precise ammonia control optimization method was proposed by combining the intelligent feed-forward cascade control technology with the partition control technology. In the intelligent feed-forward process, the improved one-dimensional convolution neural network model with higher prediction accuracy was used to predict the NO x mass concentration at the inlet of the SCR reactor, which was used as the intelligent feed-forward control signal to realize the fast and accurate control of the NO x mass concentration under the whole working condition of the unit. In the partition control process, the single sub area and multi-point synchronous sampling measurement technology and equalization control strategy were combined to realize the precise control of ammonia injection in each partition. The proposed optimization method has been applied to several coal-fired power plants. The operation results show that the precise control of ammonia injection amount is realized under the whole working conditions of the unit. The NO x mass concentration at the outlet section of SCR reactor is uniformly distributed. The ammonia consumption is obviously reduced and the economic benefit is significant.
标题：燃煤电厂SCR脱硝系统精准控氨优化方法研究
title:Research on Optimization Method of Precise Ammonia Injection in SCR de-NO x System of Coal-fired Power Plant
作者：罗志刚, 何成兵, 孟浩然, 刘国栋, 沈鹏, 张军, 张浩亮
authors:Zhigang LUO, Chengbing HE, Haoran MENG, Guodong LIU, Peng SHEN, Jun ZHANG, Haoliang ZHANG
关键词：燃煤电厂,SCR脱硝,精准控氨,改进一维卷积神经网络,分区控制,
keywords:coal-fired power plant,SCR de-NO x,precise ammonia injection,improved one-dimensional convolution neural network,partition control,
发表日期：2023-08-31
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