Modeling of an Industrial Oil-Fired Boiler Pant
Neural Network Based Model of an Industrial Oil Fired Boiler Plant
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One of the most effective means of boiler efficiency enhancement is an improvement of the steam generation control system. An essential tool for such an improvement is a valid boiler model. Methods of obtaining such a model, however, are not readily found in an open literature and are often specific to a particular plant. In this study, an oil-fired boiler system is modeled as a multi variable plant with two inputs (feed water rate and oil-fired flow rate) and two outputs (steam temperature and pressure). The plant parameters are modeled both by identification and artificial neural network, ba...
One of the most effective means of boiler efficiency enhancement is an improvement of the steam generation control system. An essential tool for such an improvement is a valid boiler model. Methods of obtaining such a model, however, are not readily found in an open literature and are often specific to a particular plant. In this study, an oil-fired boiler system is modeled as a multi variable plant with two inputs (feed water rate and oil-fired flow rate) and two outputs (steam temperature and pressure). The plant parameters are modeled both by identification and artificial neural network, based on experimental data collected directly from the plant. Furthermore, PID Controller was used to separately control both models. Simulation studies were carried out; the results obtained indicate the effectiveness of the technique. The controller was able to track the temperature and pressure set points steadily and rapidly. The simulation model obtained in this study can be used in training of boiler operators and control engineers. Furthermore, the techniques presented in this study will help researcher understand the complexity encountered in modeling Boiler Plant.
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