Machine Learning Approach to NOx Prediction for SCR Process of Thermal Power Plant

被引：1

作者：

Matsuzaki, A. ^{[1
]}

Kiribuchi, D. ^{[2
]}

Shimizu, K. ^{[1
]}

机构：

[1] Toshiba Energy Syst & Solut Corp, Yokohama, Kanagawa 2300045, Japan

[2] Toshiba Co Ltd, Kawasaki, Kanagawa 2128582, Japan

来源：

IFAC PAPERSONLINE | 2023年 / 56卷 / 02期

关键词：

Power plants and power systems; process control applications; artificial intelligence; regression; machine learning; CONTROL STRATEGY; MODEL;

D O I：

10.1016/j.ifacol.2023.10.1401

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents a machine learning application, to predict the formed nitrogen-oxides (NOx) in thermal power plants, and used in the control loops of the selective catalytic reduction (SCR) process. To deal with the big plant operation data, data reduction methods are also described. The predictions are applied for the feed-forward (FF) control and show improvement of control performance in the simulation study. Copyright (c) 2023 The Authors.

引用

页码：2858 / 2864

页数：7

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