Research And Application Of Optimization Objective Function Selection Method For Large Scale Thermal Power Plant

With the rapid economic development,the world is concerned about the increasingly sharp contradictions between energy and the environment,China will also be energy-saving emission reduction as an important issue facing sustainable development.In the thermal power generation,high efficiency,good environmental performance of large capacity units such as ultra-supercritical unit has been widely used,but because of its complex structure and the controlled object with a strong coupling,nonlinear and other characteristics,there is not a set of precision mathematical model of the ultra-supercritical unit for optimal control.Therefore,in this paper,the dynamic characteristics of each ultra-supercritical unit are researched deeply,and the optimization objective function of large-scale thermal power unit is established.It provides theoretical basis for exploring the optimization scheme of unit control quality,and optimizes the automatic control system of ultra supercritical unit.In this paper,we regard large-scale thermal power units as the research object,through establishing mathematical model during the study of the dynamic characteristics of the unit,and the objective function as the control system optimization objective,using empirical formula method,particle swarm optimization algorithm and other optimization methods to optimize the single-loop control system,cascade loop control system and coordinated control system.The coordinated control system has many characteristics such as multivariable,nonlinear,strong coupling,distributed parameter and so on.It is a typical difficult-to-control thermal engineering object in the representative industrial process control system,so the article focuses on the study of coordinated control system.Through the experiment,the optimized data curve and the control quality index are obtained,the results show that the control quality of the unit has been improved obviously,and the feasibility and effectiveness of using the objective function as a control system optimization objective function has been proved.