Identification of coal mill model parameters using genetic algorithm (Record no. 4911)

MARC details
000 -LEADER
fixed length control field 02079nam a22001937a 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220107122808.0
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fixed length control field 160226b xxu||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Transcribing agency
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Megha Jacob (93514009)
9 (RLIN) 8211
245 ## - TITLE STATEMENT
Title Identification of coal mill model parameters using genetic algorithm
502 ## - DISSERTATION NOTE
Degree type Master of Philosophy in Computer Science
Name of granting institution 2014-2015
Year degree granted INT
-- Elizabeth Sherly
520 ## - SUMMARY, ETC.
Summary, etc. <br/>Coal mill is a necessary part of the thermal power plant. They are now obliged to vary their output in response to changing electricity scenario. Now a days the demand of electricity is increasing but the conventional methods like hydroelectric power generation facing numerous difficulties. Therefore the urgency of the power plant is towering; these have impacted the coal mill and thermal power plant operation safety and reliability. This thesis is a study of dynamic responses of thermal power plants through mathematical modeling, identification, and simulation. Genetic Algorithm is chosen in this work as it is a stable algorithm for parameter identification, real-time and on-line implementation. The raw data used in modeling can be obtained without any extensive mill tests. The simulation results show a satisfactory agreement between the model response and measured value. The model is verified using on-site measurement data and on-line test. The mill-related features that affect milling performance include coal properties mainly calorific value, grind ability, abrasiveness, moisture content, mill types (low-speed mill, medium-speed mill, high-speed mill), pulverized coal distribution system that is presence of bifurcations and trifurcations, and control strategy, etc. We have tried to estimate the unknown parameter that affect the coal milling process at steady state condition implemented using Genetic Algorithm based on plant measurement data
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element COMPUTING METHODOLOGIES
9 (RLIN) 8212
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element MODELING AND SIMULATION
9 (RLIN) 8213
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element MODELING METHODOLOGIES
9 (RLIN) 8214
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element GENETIC ALGORITHM
9 (RLIN) 8215
942 ## - ADDED ENTRY ELEMENTS (KOHA)
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    Dewey Decimal Classification     IIITM-K Kerala University of Digital Sciences, Innovation and Technology Knowledge Centre 26/02/2016   R-628 26/02/2016 26/02/2016 Project Reports