Thermal Power Unit Multi-objective Optimization Coordinated Control Based On Particle Swarm Optimization

For the thermal power unit coordinated control is a relatively complex multi-variable control system, the automatic power generation control can be achieved by optimal design of thermal power boiler-turbine coordinated control system which can effectively improve the level of thermal automation. The unit operation needs a variety of control objectives to be met, such as:fast track to ensure the output power meet the unit load instruction, the energy conservation (reduced fuel consumption), reduced throttling losses and other operating goals. The sliding pressure operation mode is widely used when unit load is changing. But the sliding pressure operation curve is often obtained by people practical experience. So the control effect is difficult to guarantee. So optimizing multiple objectives can be considered to obtain better control settings.In this paper, particle swarm optimization is used to make a research and analysis of the thermal power unit coordinated control of multi-objective optimization from the aspects of control system setting value optimization and controller (strategy) adjustment. Particle swarm optimization is a kind of bionic optimization algorithm developed in recent years, it has been successfully applied in many fields due to its simple principle and better robustness. Based on the standard particle swarm optimization, constructed the inertia weight and introduce the natural selection mechanism to form an improved particle swarm optimization Then established a optimization model of multi-objective coordination control Use the improved particle swarm optimization proposed in this paper to optimize the Astrom-Bell third-order nonlinear unit dynamic model, The main pressure set point of multi-objective optimization not only can met the requirements of the control objectives, it can also provide reference to the determination of sliding pressure operation curve. In the last, the boiler-turbine coordinated control program based on the one-way static decoupling is introduced, and the improved particle swarm algorithm is applied to the intelligent optimization tuning of controller parameters in this program. Simulation results show that the optimized controller tuning parameters make the control system achieve good results, not only the unit can quickly follow changes in the external load instruction, the impact of the main steam pressure is also small.