An Innovative Study and Binary Modeling of Thermal Power Plant Using Artificial Neural Network and Multiple Linear Regression


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Abstract


The article presents modeling of a 40 MW power plant using the observed onsite data using ANN and MLR models. The four different structures of neural networks are employed in two stages which are then integrated into a single ANN model representing a complete model of the thermal power plant. The method is further compared with the multiple linear regression (MLR) method and their detailed statistical error analysis showed that the ANN models present a very good accuracy with correlation coefficient of 0.999209 which makes these models fast in response and easy to be updated with new plant data. These measures clearly demonstrated the efficient prediction accuracy of the neural networks in modeling of the 40 MW power plants.
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Keywords


Thermal Power Plant; Coal-Fired Boiler; Steam Turbine; Artificial Neural Network; Multiple Linear Regression

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References


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