학술논문

Artificial neural network predictor for induced draft fan power consumption in thermal power plants
Document Type
Conference
Source
2017 International Conference on Power and Embedded Drive Control (ICPEDC) Power and Embedded Drive Control (ICPEDC), 2017 International Conference on. :173-177 Mar, 2017
Subject
Power, Energy and Industry Applications
Robotics and Control Systems
Fans
Power demand
Coal
Artificial neural networks
Heating systems
Power generation
induced draft fan
auxiliary power
power consumption
steam generator
prediction
neural network
bayesian regularisation
Language
Abstract
Induced Draft (ID) fans have been employed in power plants for evacuating the flue gas from the furnace and send it through the chimney. Power consumption by ID fan power accounts for one-third of the total power consumption by all the in-house auxiliaries. In future, utilities have to correctly predict the power consumed by the in-plant auxiliaries to arrive at the total capacity available for selling and to estimate the operational cost. In this paper, an Artificial Neural Network (ANN) model has been created for prediction of ID fan power consumption. Operational data from fifty number of steam generators has been collected. The collected data have been utilised for the training and testing of the ANN model. The developed model shall help the plant operators and designers in accurately predicting the power consumed by ID fan