典型湿法脱硫系统存在的问题及人工智能在优化运行中的应用

doi:10.16085/j.issn.1000-6613.2019-1672

摘要/Abstract

摘要：

石灰石-石膏湿法烟气脱硫是我国最主要的脱硫方式，随着该法的不断改进与简化，脱硫系统运行更加稳定，造价也在不断降低，但运行过程中依然存在诸多问题。本文概括总结了石灰石-石膏湿法烟气脱硫系统运行过程中发生的典型问题，诸如结垢堵塞、腐蚀磨损、起泡溢流和石膏品质差等，指出了这些问题的具体分类类型以及主要影响因素；继而从系统运行机理角度阐述了这些问题的相互关系和交互影响，并将这些问题归因于脱硫系统的紊乱。随后结合电厂目前条件、当前研究基础以及可以实现的技术手段从四个方面论证了人工智能应用于脱硫系统的可行性，建议借助人工智能建立系统运行的诊断模型解决已有问题，并提出了基于人工智能的脱硫系统概念模型及具体实施思路。

关键词: 湿法烟气脱硫, 问题与对策, 人工智能, 优化运行

Abstract:

The limestone-gypsum wet flue gas desulfurization is the most important desulfurization method in China. With the continuous improvement and simplification of this method, the operation of the desulfurization system is more stable and the cost is also continuously reduced, but many problems in operation process still exist. This paper summarizes the common problems occur in the operation of limestone-gypsum wet flue gas desulfurization system, such as scaling and blockage, corrosion and wearing, foaming and overflow, and the poor gypsum quality, etc. and the specific types of these problems and the main influencing factors are pointed out; then, from the perspective of the system operation mechanism, the interrelationships and interaction effects of these problems are explained, and these problems are attributed to the disorder of the desulfurization system. This paper combines the current conditions of the power plant, the current research foundation and the achievable technical methods to verify the feasibility of artificial intelligence applied to desulfurization systems from four aspects. It is suggested that the diagnosis model of system operation should be established by artificial intelligence to solve the existing problems, and the conceptual model of desulfurization system based on artificial intelligence and concrete implementation ideas are put forward.

Key words: wet flue gas desulfurization, problems and countermeasures, artificial intelligence, optimum operation

中图分类号:

X784

曹建宗, 刘琦, 陈文通, 樊帅军, 要亚坤, 周权, 马采妮, 林宸雨, 马双忱. 典型湿法脱硫系统存在的问题及人工智能在优化运行中的应用[J]. 化工进展, 2020, 39(S1): 242-249.

Jianzong CAO, Qi LIU, Wentong CHEN, Shuaijun FAN, Yakun YAO, Quan ZHOU, Caini MA, Chenyu LIN, Shuangchen MA. Problems of typical wet desulfurization system and application of artificial intelligence in optimal operation[J]. Chemical Industry and Engineering Progress, 2020, 39(S1): 242-249.

图/表 4

图1 浆液pH对吸收剂利用率及脱硫率的影响

图2 各参数对WFGD典型问题交互影响

图3 基于人工智能的脱硫系统概念模型

图4 建立智能脱硫系统模型的整体思路

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