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ANN-GA based optimization of a high ash coal-fired supercritical power plant

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  • Suresh, M.V.J.J.
  • Reddy, K.S.
  • Kolar, Ajit Kumar

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 800MWe 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.

Suggested Citation

  • Suresh, M.V.J.J. & Reddy, K.S. & Kolar, Ajit Kumar, 2011. "ANN-GA based optimization of a high ash coal-fired supercritical power plant," Applied Energy, Elsevier, vol. 88(12), pages 4867-4873.
    • Handle: RePEc:eee:appene:v:88:y:2011:i:12:p:4867-4873
    DOI: 10.1016/j.apenergy.2011.06.029
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    1. Kalogirou, Soteris A., 2004. "Optimization of solar systems using artificial neural-networks and genetic algorithms," Applied Energy, Elsevier, vol. 77(4), pages 383-405, April.
    2. Sacco, Wagner F. & Pereira, Cláudio M. N. A. & Soares, Pius P. M. & Schirru, Roberto, 2002. "Genetic algorithms applied to turbine extraction optimization of a pressurized-water reactor," Applied Energy, Elsevier, vol. 73(3-4), pages 217-222, November.
    3. De, S. & Kaiadi, M. & Fast, M. & Assadi, M., 2007. "Development of an artificial neural network model for the steam process of a coal biomass cofired combined heat and power (CHP) plant in Sweden," Energy, Elsevier, vol. 32(11), pages 2099-2109.
    4. Wang, Jiangfeng & Sun, Zhixin & Dai, Yiping & Ma, Shaolin, 2010. "Parametric optimization design for supercritical CO2 power cycle using genetic algorithm and artificial neural network," Applied Energy, Elsevier, vol. 87(4), pages 1317-1324, April.
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