Optimization Of PID Parameters Of Hydraulic Turbine Governor Based On Improved Atomic Search Optimization Algorithm

Turbine regulating system is an important part of hydropower station.Its regulating performance will affect the quality of electric energy produced by hydropower station.At present,the hydraulic turbine regulating system in our country mostly adopts PID control,so the optimization of PID parameters is the key to improve the regulating ability of the hydraulic turbine regulating system.In the past,it takes a lot of work to determine the PID parameters,and it is impossible to judge whether the PID parameters are optimal.In order to solve the above problems,this thesis proposes an adaptive hybrid algorithm-AASOPSO,and uses the AASOPSO algorithm to optimize and tune the PID parameters of the turbine governor.Firstly,the thesis analyzes the basic task and principle of the hydraulic turbine regulating system.This thesis expounds the working principle,transfer function and mathematical model of PID hydraulic turbine governor.Then,the mechanical hydraulic system,pressure water diversion system,hydraulic turbine,generator and load in the hydraulic turbine regulating system are introduced successively,and the transfer function and mathematical model of each part are given respectively.A simplified mathematical model of hydraulic turbine regulating system is established,and the necessary explanation is given.Then,Atom Search Optimization(ASO),a new heuristic algorithm,is introduced.ASO presents a unique searching capability by simulating the interaction of potential energy and binding force between atoms.However,ASO still has the problems of local optimal stagnation and low search efficiency.Therefore,this thesis improves ASO and proposes a new adaptive hybrid optimization algorithm-AASOPSO.AASOPSO is a kind of atom search algorithm that combines adaptive and Particle swarm optimization(PSO),which improves the optimization ability of the algorithm by improving the defects of slow development speed and poor exploration ability of ASO in the later iteration.Finally,the simulation model of the hydraulic turbine regulating system is established in the Matlab /Simulink environment,and AASOPSO is embedded into the simulation model of the hydraulic turbine regulating system,respectively in the case of no-load frequency disturbance and load disturbance to optimize the PID parameters of the hydraulic turbine governor.The simulation results show that the hydraulic turbine regulating system optimized by AASOPSO can respond quickly and restore the stable state in a short time.And compared with several other common intelligent optimization algorithms,the AASOPSO optimized hydraulic turbine regulation system has shorter adjustment stability time and smaller overshoot.The results show that the AASOPSO algorithm has better performance than other intelligent optimization algorithms in searching the global optimal PID parameters of turbine governor.