Real-time coal classification in thermal power plants

被引：6

作者：

Mukherjee, Tathagata ^{[1
]}

Gupta, Ashit ^{[1
]}

Deodhar, Anirudh ^{[1
]}

Runkana, Venkataramana ^{[1
]}

机构：

[1] Tata Consultancy Serv, TCS Res, Pune, India

来源：

CONTROL ENGINEERING PRACTICE | 2023年 / 130卷

关键词：

Soft sensing; Coal classification; Semi-supervised clustering; Digital twin; Thermal power plants; IDENTIFICATION;

D O I：

10.1016/j.conengprac.2022.105377

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Continuous variations in coal quality have a strong influence on operation of thermal power plants. However, in absence of real-time measurements of quality, the operators remain partially blind to the actual coal being consumed, leading to sub-optimal operation. A two-stage solution is proposed for real-time soft sensing of coal type. First, a novel semi-supervised cascaded clustering algorithm (SSCC) is utilized to extract coal classes from the historical sensor data of the plant and create a coal class library. The online stage includes a coal change detection algorithm to detect transition of coal and a SSCC-based coal classifier that enables real-time classification of coal using only the live sensor data. The algorithms are tested and verified with a set of synthetically generated industrial scale coal mill operation data. The real-time classification of coal can facilitate continuous optimum operation of plant vis-a-vis the emissions, efficiency and maintenance.

引用

页数：11

共 37 条

[1] A unified thermo-mechanical model for coal mill operation [J].