Application of Back Propagation Neural Network to Drum Level Control in Thermal Power Plants
The paper describes the development and testing of a neural network based drum level controller for sub-critical thermal power plant boilers. Experimental data obtained from an operational coal fired power plant (500MW Thermal Power Station, Korba, India) is used to train the neural network. This model proposes a simple training algorithm for a class of nonlinear systems, which enables the neural network to be trained with the output errors of the controlled plant. The only a priori knowledge of the controlled plant is the direction of its output response. Due to its simple structure and algorithm, and good performance, the proposed controller has high potential for handling difficult problems in process-control systems. The Artificial neural networks (ANN) modeling can significantly reduce the frequency of deviations and the degree of deviation of the water level in the drum. The ANN model to be applied for the boiler feed system in the power plant will not only increase the efficiency of the system but also shall considerably reduce the tripping of the power plant.
Keywords: Artificial neural network, Power plant, Boiler model, Boiler drum
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ABOUT THE AUTHORS
Preeti Manke
Preeti Manke Completed her B.E. in Computer Science from Visvesvaraya Regional Engineering College, Nagpur and her M.E. in Computer Science and Engineering in 2007 from S.G.B. Amravati University, India. Currently she is working as Reader (Associate Professor) in Institute of Technology, Korba since 2008 and has more than nine years of teaching experience. Her research interests currently include application of neural networks in thermal power plant, Interactive Content-Based Retrieval Using Fuzzy Classification and Relevance Feedback, and fuzzy set applications. She has presented more than nine research papers in International and National conferences.
Sharad Tembhurne
Sharad Tembhurne Received his B.E. in Mechanical Engineering from Regional Engineering College, Durgapur in 1999 and M.Tech. in Thermal Engineering from Indian Institute of Technology, Delhi, India. He is working as an Engineer, Operation and Maintenance Department in National Thermal Power Corporation since 2006. His research interests currently include process improvements in thermal power plant, energy security and environmental challenges, process optimization and designing of thermal equipments. He is winner of Advances in Energy Research Award in the International conference organized by IIT Bombay in 2007. He has presented more than six research papers in International and National conferences.
Preeti Manke
Preeti Manke Completed her B.E. in Computer Science from Visvesvaraya Regional Engineering College, Nagpur and her M.E. in Computer Science and Engineering in 2007 from S.G.B. Amravati University, India. Currently she is working as Reader (Associate Professor) in Institute of Technology, Korba since 2008 and has more than nine years of teaching experience. Her research interests currently include application of neural networks in thermal power plant, Interactive Content-Based Retrieval Using Fuzzy Classification and Relevance Feedback, and fuzzy set applications. She has presented more than nine research papers in International and National conferences.
Sharad Tembhurne
Sharad Tembhurne Received his B.E. in Mechanical Engineering from Regional Engineering College, Durgapur in 1999 and M.Tech. in Thermal Engineering from Indian Institute of Technology, Delhi, India. He is working as an Engineer, Operation and Maintenance Department in National Thermal Power Corporation since 2006. His research interests currently include process improvements in thermal power plant, energy security and environmental challenges, process optimization and designing of thermal equipments. He is winner of Advances in Energy Research Award in the International conference organized by IIT Bombay in 2007. He has presented more than six research papers in International and National conferences.
