Neuro-Fuzzy Modeling of Superheating System of a Steam Power Plant
نویسندگان
چکیده
In this paper the superheating system of a 325MW steam power generating plant is modeled by usage of recurrent neuro-fuzzy networks and subtractive clustering. The experimental data are obtained from a complete set of field experiments under various operating conditions. Neuro-fuzzy models are constructed for each subsystem of the superheating unit. The nine fuzzy models are then constructed in a combination of series and parallel units in accordance with real power plant subsystems. Comparing the response of nonlinear neuro-fuzzy model of a subsystem with the response of its linear model obtained based on LSE method; shows that the nonlinear neuro-fuzzy model is more accurate than linear model in the sense that its response is closer to the response of the actual system. Since LSE is optimum modeling method for linear systems, it can be concluded that some of power plant subsystems are of nonlinear processes.
منابع مشابه
Model-based Approach for Multi-sensor Fault Identification in Power Plant Gas Turbines
In this paper, the multi-sensor fault diagnosis in the exhaust temperature sensors of a V94.2 heavy duty gas turbine is presented. A Laguerre network-based fuzzy modeling approach is presented to predict the output temperature of the gas turbine for sensor fault diagnosis. Due to the nonlinear dynamics of the gas turbine, in these models the Laguerre filter parts are related to the linear d...
متن کاملModeling and Neuro-fuzzy Controller Design of a Wind Turbine in Full-load Region Based on Operational Data
In this paper, dynamic modeling of a Vestas 660 kW wind turbine and its validation are performed based on operational data extracted from Eoun-Ebn-Ali wind farm in Tabriz, Iran. The operational data show that the turbine under study, with a classical PI controller, encounters high fluctuations when controlling the output power at its rated value. The turbine modeling is performed by deriving th...
متن کاملADAPTIVE NEURO-FUZZY INFERENCE SYSTEM AND STEPWISE REGRESSION FOR COMPRESSIVE STRENGTH ASSESSMENT OF CONCRETE CONTAINING METAKAOLIN
In the current study two methods are evaluated for predicting the compressive strength of concrete containing metakaolin. Adaptive neuro-fuzzy inference system (ANFIS) model and stepwise regression (SR) model are developed as a reliable modeling method for simulating and predicting the compressive strength of concrete containing metakaolin at the different ages. The required data in training an...
متن کاملThermodynamic modeling and comprehensive off-design performance analysis of a real integrated solar combined cycle power plant
In this paper thermodynamic modeling and comprehensive performance analysis of a real integrated solar combined cycle (ISCC) power plant are performed. Performance of the plant cycle is assessed in off-design condition and in two operation modes of power-boosting and fuel-saving. Such an approach has not been considered for an ISCC plant in the previous studies. Under studied ISCC which is loca...
متن کامل