Research On AGC Method Of Distributed Generation System Based On CPSO Parameter Optimization

The stochastic and intermittent characteristics of clean energy output in distributed generation system bring new challenges to the traditional automatic generation control(AGC).This challenge is mainly reflected in the requirement of the stochastic power output of distributed generation system for the dynamic adjustment ability of the controller.In this paper,taking the automatic generation control system of three-area interconnected power grid as an example,the feasibility and effectiveness of parameter optimization of fractional order PID controller based on improved chaotic particle swarm optimization algorithm are discussed while considering the load disturbance and the participation of photovoltaic and wind power.The main contents are as follows:Firstly,the mathematical model of three-area interconnected power grid automatic generation control system is constructed.Based on the power frequency deviation control mode of tie-line,the component models are analyzed and deduced.The mathematical models of photovoltaic and wind power output are described to show the stochastic characteristics of power output of distributed generation system.Then,Fractional order PID controller is designed to meet the dynamic performance requirements of the system with photovoltaic,wind power and other energy forms.New_fod()function and oustafod()function are designed to approximate the fractional-order PID controller,which is beneficial to the simulation and implementation of the system.Compared with the traditional PID controller,the designed controller has better dynamic performance characteristics.On this basis,particle swarm optimization(PSO)is introduced to optimize the parameters of fractional order PID controller.Aiming at the problem that the initial value of the basic particle swarm optimization algorithm is far from the global optimal solution and easy to fall into the local optimal solution,an improved chaotic method is proposed.In the prime of the algorithm,a better chaotic formula is chosen to make the initial distribution more uniform.When the algorithm is "premature",chaotic search is carried out on the premise of guaranteeing the optimal position,and chaotic particles are used to replace some of the original particles,thus increasing the possibility of the algorithm jumping out of the local optimal solution.Finally,ITAE is selected as the performance evaluation index.Considering pure load disturbance and grid-connected photovoltaic and wind power environments,the output is frequency offset and tie-line exchange power offset,and the controlled object is guaranteed to be the same.The dynamic response performance of particle swarm optimization(PSO)and chaotic particle swarm optimization(CPSO),integer-order PID controller and fractional-order PID controller are compared and analyzed to verify the correctness and effectiveness of the proposed control method.