Mathematical modelling for coal fired supercritical power plants and model parameter identification using genetic algorithms

被引：4
作者：
Mohamed O. [1 ]
Wang J. [1 ]
Guo S. [1 ]
Wei J. [1 ]
Al-Duri B. [2 ]
Lv J. [3 ]
Gao Q. [3 ]
机构：
[1] School of Electrical, Electronics, and Computer Engineering, University of Birmingham, Edgbaston
[2] School of Chemical Engineering, University of Birmingham, Edgbaston
[3] Department of Thermal Engineering, Tsinghua University, Beijing
来源：
Lecture Notes in Electrical Engineering | 2011年 / 90 LNEE卷
基金：
英国工程与自然科学研究理事会;
关键词：
Coal-fired power generation; Genetic algorithms; Mathematical modeling; Supercritical boiler;
D O I：
10.1007/978-94-007-1192-1_1
中图分类号：
学科分类号：
摘要：
The paper presents the progress of our study of the whole process mathematical model for a supercritical coal-fired power plant. The modelling procedure is rooted from thermodynamic and engineering principles with reference to the previously published literatures. Model unknown parameters are identified using Genetic Algorithms (GAs) with 600MW supercritical power plant on-site measurement data. The identified parameters are verified with different sets of measured plant data. Although some assumptions are made in the modelling process to simplify the model structure at a certain level, the supercritical coal-fired power plant model reported in the paper can represent the main features of the real plant once-through unit operation and the simulation results show that the main variation trends of the process have good agreement with the measured dynamic responses from the power plants. © 2011 Springer Science+Business Media B.V.
引用
收藏
页码：1 / 13
页数：12
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