基于燃煤电站运行数据的烟气脱硫系统性能预测研究
摘要：准确获取烟气环保系统性能是其优化调整及技术改造的前提。以某600 MW燃煤电站石灰石-石膏湿法脱硫系统为研究对象，运用数据挖掘获得了脱硫系统性能的关键因素集，在此基础上，融合回归分析技术的多种算法，研究并构建燃煤电站烟气环保系统性能的数据模型。研究结果表明，数据模型不仅能够高精度地复现不同负荷工况下的脱硫系统性能，还具有较好的灵活性和可拓展性，为燃煤电站环保系统的状态监测、趋势分析、运行优化提供坚实的基础。
Abstract:Accurate acquisition of flue gas environmental protection system performance is the premise of its optimal adjustment and technological transformation. Based on the limestone-gypsum wet sulfur removal system of a 600 MW coal-fired power station, the data mining was used to obtain the key factor set of desulfurization system performance. On this basis, a variety of algorithms of regression analysis technology were combined to study and construct the data model of the performance of the flue gas environmental protection system of coal-fired power station. The results show that the data model can reproduce the desulfurization system performance under different load conditions with high precision, and also has good flexibility and expandability, which provides a solid foundation for state monitoring, trend analysis and operation optimization of the environmental protection system.
标题：基于燃煤电站运行数据的烟气脱硫系统性能预测研究
title:Research on Performance Prediction of Flue Gas Desulfurization System Based on Operation Data of Coal-fired Power Station
作者：李存文, 王在华, 陈涛, 冯前伟, 徐克涛, 张杨
authors:Cunwen LI, Zaihua WANG, Tao CHEN, Qianwei FENG, Ketao XU, Yang ZHANG
关键词：燃煤电站,烟气脱硫系统,数据挖掘,数据模型,性能预测,
keywords:coal-fired power station,flue gas desulfurization system,data mining,data model,performance prediction,
发表日期：2022-08-31
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