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ANN-GA based optimization of a high ash coal-fired supercritical power plant
- Source :
- IndraStra Global.
- Publication Year :
- 2011
-
Abstract
- The efficiency of coal-fired power plant depends on various operating parameters such as main steam/reheat steam pressures and temperatures, turbine extraction pressures, and excess air ratio for a given fuel. However, simultaneous optimization of all these operating parameters to achieve the maximum plant efficiency is a challenging task. This study deals with the coupled ANN and GA based (neuro-genetic) optimization of a high ash coal-fired supercritical power plant in Indian climatic condition to determine the maximum possible plant efficiency. The power plant simulation data obtained from a flow-sheet program, " Cycle-Tempo" is used to train the artificial neural network (ANN) to predict the energy input through fuel (coal). The optimum set of various operating parameters that result in the minimum energy input to the power plant is then determined by coupling the trained ANN model as a fitness function with the genetic algorithm (GA). A unit size of 800. MWe currently under development in India is considered to carry out the thermodynamic analysis based on energy and exergy. Apart from optimizing the design parameters, the developed model can also be used for on-line optimization when quick response is required. Furthermore, the effect of various coals on the thermodynamic performance of the optimized power plant is also determined. � 2011 Elsevier Ltd.
- Subjects :
- Exergy
Engineering
Fitness function
Power station
business.industry
Mechanical Engineering
Mechanical engineering
Building and Construction
Management, Monitoring, Policy and Law
Turbine
Supercritical fluid
Artificial Neural Network
Climatic conditions
Coal-fired power plant
Design parameters
Developed model
Energy
Energy and exergy
Energy inputs
Excess air ratios
Extraction pressure
Fitness functions
High ash coal
Minimum energy
Neuro-genetic
Online optimization
Operating parameters
Plant efficiency
Plant simulation
Quick response
Simultaneous optimization
Steam pressures
Supercritical power plant
Thermo dynamic analysis
Thermodynamic performance
Coal
Computer simulation
Genetic algorithms
Neural networks
Optimization
Steam power plants
Thermoanalysis
Fossil fuel power plants
artificial neural network
ash
climate conditions
coal-fired power plant
developing world
energy efficiency
exergy
genetic algorithm
optimization
thermodynamics
India
General Energy
Genetic algorithm
Process engineering
business
Subjects
Details
- Language :
- English
- ISSN :
- 23813652
- Database :
- OpenAIRE
- Journal :
- IndraStra Global
- Accession number :
- edsair.doi.dedup.....c5a9fa60f5b24339753f098772fe3866