Research On Control Strategy For Interconnected Grid AGC Based On Adaptive Dynamic Programming

Frequency is an essential index of power quality.The frequency deviation of interconnected power system reflects the balance between active power and load.With the increasing scale of the interconnected power grid structure and the interconnection of different power grids,while the people’s power demand is demand,the deviation occurs,which threatens the stability of the operation of the interconnected power grid.Automatic generation control(AGC)is the secondary frequency regulation mode of interconnected power grid,which is of great significance to the stable and safe operation of power grid.AGC Objective:adjust frequency deviation;adjust generator output and load balance;distribute generator active power in control area to make tie line active power flow equal to planned value.Due to the scale expansion of interconnected power system,the traditional PID controller is used to control interconnected power grid,which has some problems,such as poor adaptive ability,poor robustness,long regulation time and so on.Action-Dependent Heuristic Dynamic Programming(ADHDP),Goal-representation Heuristic Dynamic Programming(Gr HDP)belongs to Adaptive Dynamic Programming(ADP)In recent years,it has been studied and applied in many fields,such as aerospace,power system,heating system and so on.In this paper,ADHDP algorithm and Gr HDP algorithm are applied to the load frequency control of interconnected power grid,in order to reduce the frequency deviation of interconnected power grid,shorten the frequency regulation time,and effectively improve the performance of interconnected power grid frequency control system.The main work of this paper is as follows:(1)Aiming at the problems of long regulation time,poor self-adaptive ability and robustness in the traditional frequency control system of interconnected power grid based on PID,a control scheme with PID as the main control and neuron variable structure PID as the auxiliary control is proposed.Neuron variable structure PID control uses one neuron model and proportional control to realize variable structure PID control,and then another neuron model to realize on-line adjustment function of variable structure PID controller parameters K_p,K_d and K_i.The results show that the proposed control scheme can effectively reduce the frequency deviation of interconnected power grid and accelerate the response speed of the system.(2)Based on the control scheme of PID as the main control,the design method of auxiliary controller using ADHDP algorithm is proposed.The executive network and evaluation network of ADHDP auxiliary controller are designed with three-layer BP neural network.Through online training,the adaptive ability of the controller is improved.The simulation shows that,compared with the neuron variable structure PID auxiliary control,the frequency deviation of the control strategy is smaller,the convergence speed is faster,and the frequency fluctuation can be effectively suppressed.(3)Based on the control scheme of PID as the main control,the design method of auxiliary controller using Gr HDP algorithm is proposed.The execution network,evaluation network and target network of Gr HDP auxiliary controller are designed by three-layer BP neural network.Compared with ADHDP algorithm,Gr HDP algorithm can generate internal reinforcement signals through the target network,which effectively improves its online learning ability and control strategy optimization ability.The simulation results show that the frequency deviation is the smallest,the convergence speed is the fastest and the stability is better.