Research On Frequency Control Strategy For Islanded Microgrid Based On RBF-MFAC

Microgrid inverters based on droop control cannot eliminate the static frequency deviation during the operation of an islanded microgrid,and the frequency must be stabilized with the help of secondary frequency control.The frequency response model of the microgrid needs to be used in the design of secondary frequency controller parameters.However,due to the complex and changeable structure of the microgrid system and the variety of micro-sources and loads in the system,the mathematical model of the microgrid system is difficult to obtain and the method of tuning the controller parameters through the model becomes time-consuming and labor-intensive.Model-free adaptive control(MFAC)is a new kind of data-driven control method.During the control process,there is no need to understand the internal structure and model parameter information of the controlled system.It achieves effective control of the system by establishing the equivalent dynamic data model of the system through the real-time input and output data.Therefore,this paper proposes to apply MFAC to the microgrid to achieve secondary frequency control,and proposes an improved MFAC scheme based on radial basis function(RBF)neural networks to solve the problems that MFAC controller still needs to be designed offline before application and cannot achieve the online self-tuning of controller parameters during application.Online self-tuning of controller parameters and adaptive control of microgrid frequency are realized.The main research contents of this paper are:First,the inverter control strategies for establishing microgrid frequency is introduced.In order to solve the problem of frequency steady-state error caused by the primary control strategy,the realization principle of the secondary frequency control of the microgrid is introduced in detail.Then the basic concept and theoretical basis of model-free adaptive control are introduced.Based on the dynamic linearization method,the overall control scheme of model-free adaptive control is designed,and its stability and convergence are proved.Secondly,the model-free adaptive controller based on the secondary frequency control is designed,the control scheme of the secondary frequency control is given,and the specific process of the model-free adaptive control to realize the secondary frequency control of the microgrid is introduced.A microgrid simulation platform was built based on Matlab/Simulink,and a set of load step disturbance experiments verified that the proposed method can still maintain the frequency at the reference value under the condition of continuous load fluctuations.Finally,the basic concepts and implementation principles of artificial neural networks and RBF neural networks are introduced,based on which an online self-tuning algorithm of model-free adaptive controller parameters is presented,the specific design ideas of the algorithm and The formula derivation process are given.The proposed RBF-MFAC method is applied to the microgrid,and the specific process of the proposed method to realize the secondary frequency control is designed.Finally,two sets of simulations with unknown optimal parameters of the proposed controller and a sudden change in the system structure are carried out,and the proposed controller is compared with the PI controller when the microgrid structure changes suddenly to verify the effectiveness of the proposed method.