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

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

Applied Energy 88 (2011) 4867–4873Contents lists available at ScienceDirect Applied Energy journal homepage: www.elsevier .com/locate /apenergyANN-GA based optimization of a high ash coal-fired supercritical power plant M.V.J.J. Suresh, K.S. Reddy ?, Ajit Kumar Kolar Heat Transfer and Thermal Power Laboratory, Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai 600 036, India a r t i c l e i n f o a b s t r a c tArticle history: Received 27 February 2011 Received in revised form 12 June 2011 Accepted 18 June 2011 Available online 20 July 2011 Keywords: Artificial neural network Genetic algorithm Supercritical power plant High ash coal Energy Exergy0306-2619/$ - see front matter 2011 Elsevier Ltd. A doi:10.1016/j.apenergy.2011.06.029 ? Corresponding author. Tel.: +91 44 2257 4702; fa E-mail address: ksreddy@iitm.ac.in (K.S. Reddy).The efficiency of coal-fired power plant depends on various operating parameters such as main steam/ reheat steampressures and temperatures, turbine extraction pressures, and excess air ratio for a given fuel. However, simultaneous optimization of all these operating parameters to achieve themaximumplant effi- ciency is a challenging task. This study deals with the coupled ANN and GA based (neuro-genetic) optimi- zation 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 th