Research On Thermal Economy Diagnosis Of Double Reheating Units And Cold End Optimization

With the rapid economic development,China’s demand for electricity continues to grow,this has caused a lot of energy and environmental problems.The double reheat unit,as a new generation unit with energy saving and high efficiency,has become an important choice in the future thermal power system,so the double reheat unit has a broad development prospect.The thermal economic diagnosis of the double reheat unit can provide technical guidance for the energy saving and optimization of the double reheat unit;the cold end system is an important auxiliary system which affects the thermal economy of the thermal power unit,and the optimization of the cold end of the unit is an important method to improve the unit economy.In this paper,the thermal economy diagnosis and cold end optimization of a 660MW double reheat unit are researched,the main work of this paper is as follows:1.Based on the energy level theory,the overall thermal economy of the unit is calculated through the energy level efficiency display matrix,and the energy level coupling problem of the double reheat unit is solved by expanding the energy level theory for partial quantitative analysis.Combined with the overall thermal economy and partial quantitative analysis,it provides technical guidance for improving the thermal economy of the unit.2.A steam turbine exhaust enthalpy prediction model based on PLS and MPGA-ELM is proposed,by using PLS to reduce dimensionality of the data,MPGA is used to optimize the weights and thresholds of ELM to build a new prediction model to predict steam turbine exhaust under different operating conditions,and compared with the prediction results of ELM,BP,etc,the results show that the prediction method has better generalization ability than other methods,the prediction error is smaller,and the prediction effect is better.Combined with the energy level theory and mechanism,the prediction of micro turbine exhaust enthalpy is improved the incremental power of steam turbine is modeled,and the incremental power of steam turbine under different working conditions is obtained through calculation of examples.3.An improved PSO-SVM cooling tower outlet water temperature prediction model is proposed,the penalty factor and kernel function parameters of the improved PSO optimized SVM are used to build a new prediction model to predict the cooling tower outlet water temperature under different working conditions,compare it with BP,SVM,etc,model comparison shows that the prediction model is more robust and has higher prediction accuracy.The back pressure calculation model of condenser is established by using mechanism modeling and empirical formula,and an example is given the back pressure under different working conditions is calculated.4.Through the pipeline characteristics and performance characteristic curve of circulating water pump,the flow power calculation model of constant speed pump is established.Combined with the similarity law,the flow power calculation model of variable frequency pump is obtained,and the flow power models of circulating water pump under different combinations are calculated.5.A hybrid optimization algorithm based on GA and PSO is proposed to optimize the whole cold end of the unit.The maximum net micro increase power as the objective function,the maximum net micro increase power and the optimal circulating water flow of the unit under different working conditions are optimized.Taking the optimal circulating water flow as the objective,the power consumption of different combination modes of circulating water pump is analyzed.The results show that the combination mode of double frequency conversion water pump can reduce energy consumption and bring certain benefits,which has certain guiding significance for cold end optimization.