Modeling and Analysis of Power Supply Coal Consumption-Load Characteristics of Thermal Power Unit Based on Improved PCA Algorithm
Aiming at the problems of high coal consumption and poor analysis accuracy of power supply units in thermal power plants,a method for modeling and analysis of power supply coal consumption-load characteristics of thermal power units based on the improved PCA algorithm is studied.Based on the coal consumption-output function of the valve point effect of the thermal power unit,the load characteristics of the thermal power unit under sta-ble load output,increasing load output and decreasing load output are fully considered.The coal consumption-load characteristic model of thermal power units is constructed,and the Genetic Algorithms Back Propagation(GABP)is added on the basis of Principal Component Analysis(PCA)to generate an improved PCA algorithm.PCA was used to reduce the redun-dancy of network input variables and enhance the learning efficiency.GABP was used to opti-mize the weight of the neural network,and the optimal solution was obtained by training the neural network to analyze and solve the coal consumption-load characteristic model of power supply for thermal power units.The experimental results show that the coal consumption rate of power supply analyzed by this method is low,and the energy saving effect is good.The average total coal consumption cost is 102,500 yuan,which can accurately display the ac-tual operation of thermal power units and provide a theoretical basis for reducing power sup-ply coal consumption of thermal power units.
improved PCA algorithmthermal power unitcoal consumption of power supplyload characteristicsmodeling analysisthe total coal consumption
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