Based On Deep Peak Shaving Safety Load Distribution Optimization Of Coal Fired Units

In order to achieve the strategic goal of China’s carbon peak in 2030 and carbon neutral in 2060,and build a new power system with new energy as the main body,the new power system with renewable energy such as wind power and solar energy needs some flexible,efficient,safe and environmental protection thermal power units for operation support.The more flexible,safe and reliable the units are,the more peak shaving tasks they will undertake in this new power system.Under the condition of ensuring the safety of deep peak shaving of coal-fired units,it is very important to optimize and arrange the best peak shaving load according to the design and operation characteristics of units.With the promotion of power auxiliary service market,the enthusiasm of peak shaving of thermal power units has been improved.Many thermal power plants carry out unit flexibility and energy saving transformation to undertake the task of peak shaving.The purpose of this paper is to optimize the load distribution of each unit in the power plant,while reducing the coal consumption,considering the unit life loss and auxiliary service market income,in order to improve the economy and security of the power plant,and enhance the comprehensive competitiveness of the enterprise.Firstly,the objective function model of optimal load distribution and the constraints of the model are briefly introduced.By using the economic method,the fuel loss and life loss of units participating in peak load regulation are defined as money flow,and a new objective function model is established considering the benefits of units participating in auxiliary service market during peak load regulation.Secondly,considering the phenomenon of unit coal consumption characteristics change,based on the concept of big data analysis,combined with the gray correlation analysis method and neural network algorithm,the historical operation data is screened and trained,and the parameters with high correlation with coal consumption rate are selected and put into the neural network calculation model to realize the dynamic calculation of unit coal consumption.The maximum absolute error is 1.1 g/kW·h,and the average absolute error is 0.48 g/kW · h,so the calculation result is more accurate.Finally,considering the operation safety of the unit,the temperature field and stress field of the high-pressure rotor of the steam turbine under typical start-up conditions are obtained,the most serious part of the stress concentration is determined,the calculation model is simplified,and the life loss of the rotor under different variable load ranges is calculated.This paper briefly describes the mechanism and revenue model of power auxiliary service market,and determines the revenue calculation method.The constraints are incorporated into genetic algorithm to solve the optimal load distribution of plant level units,and an example is given.The calculation results show that the life loss of the rotor will be increased when the units participate in peak load regulation,but considering the income from participating in the auxiliary service market,the overall income will increase.