Dynamic modeling approach for coal mill parameter estimation in thermal power plant (Record no. 4894)

MARC details
000 -LEADER
fixed length control field 02016nam a22001937a 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220107122807.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 151125b xxu||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Transcribing agency
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Megha Jacob (93514009)
9 (RLIN) 8128
245 ## - TITLE STATEMENT
Title Dynamic modeling approach for coal mill parameter estimation in thermal power plant
500 ## - GENERAL NOTE
General note Mini Project Report, Mphill CS
502 ## - DISSERTATION NOTE
Degree type Mphill. Computer Science
Name of granting institution 2014-2015
Year degree granted INT
-- Elizabeth Sherly
520 ## - SUMMARY, ETC.
Summary, etc. Nowadays 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. Coal mills are the negligible part of the thermal power plant, in this paper we using a computational intelligent algorithm to estimate the unknown coefficients that are used in the coal milling model. 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) 8129
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element MODELING AND SIMULATION
9 (RLIN) 8130
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element MODEL DEVELOPMENT AND ANALYSIS
9 (RLIN) 8131
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Total Checkouts Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     IIITM-K Kerala University of Digital Sciences, Innovation and Technology Knowledge Centre 25/11/2015   R-615 25/11/2015 25/11/2015 Project Reports