Study On Voltage Fluctuation Analysis And Overvoltage Control Method Of Rural Network Caused By Photovoltaic Access

Due to the weak structure of the rural distribution network,etc,the access of photovoltaic to the rural distribution network will bring danger to the safe and stable operation of the network.When the photovoltaic with high permeability is connected to the rural power network,it will have a certain influence on the size and direction of the original power flow in the network.and will exceed the voltage’s limit when it is serious,which will have a serious impact on the safe and stable operation of the distribution line.In order to solve the overvoltage phenomenon and ensure the good voltage quality in the rural distribution network,this thesis presents a comprehensive active and reactive power control method based on voltage sensitivity and the predictive model of active power’s reduction.The proposed control method is verified and analyzed by MATLAB.The main work of this thesis is as follows:(1)The characteristics of rural distribution network are simply analyzed.According to the characteristics,the variation of line node voltage is analyzed when the photovoltaic system is not connected,the single photovoltaic system is connected and the multiple photovoltaic system is connected.The above three situations are simulated and analyzed.Through the simulation results,the factors affecting overvoltage and the law of overvoltage are analyzed to provide a basis for solving the overvoltage problem.(2)In view of the overvoltage problem caused by the high permeability photovoltaic power system connecting to the rural distribution network,this thesis proposes a comprehensive active and reactive power control strategy.Firstly,according to the voltage sensitivity formula,the relationship between voltage and active power or reactive power is deduced and analyzed,and a rural distribution network voltage relationship model about active power and reactive power is established,which provides a theoretical basis for the proposed control strategy.Then,according to the relationship between the reactive capacity and the active power output of the inverters,a comprehensive active and reactive power control strategy is proposed in this thesis.The overvoltage is adjusted by switching between reactive power compensation and active power reduction.Finally,three scenarios are used to simulate and verify the proposed overvoltage control method for active and reactive power comprehensive control.(3)In view of the frequent switching problems in the process of reactive compensation and active power reduction in the proposed active and reactive power comprehensive control overvoltage method,this thesis further establishes a power reduction prediction model based on BP neural network.Firstly,the factors affecting the output of photovoltaic power generation and the principle of photovoltaic power prediction are analyzed,which provides a theoretical basis for the establishment of power reduction prediction model in this thesis.Then,a power reduction prediction model based on BP neural network is established,and three prediction model evaluation methods are used to evaluate the prediction model established in this thesis.The evaluation results show that the prediction model established in this thesis is accurate.Finally,aiming at the validity of the overvoltage control method based on power reduction prediction model for active and reactive power comprehensive control,the simulation of overvoltage in undisturbed and disturbed scenarios is carried out respectively,and compared with the traditional voltage regulation control method.The simulation results show that the proposed control method based on power reduction prediction model for active and reactive power comprehensive control overvoltage can effectively solve the phenomenon of overvoltage,and compared with the traditional voltage regulation method,the proposed control method can more effectively regulate the overvoltage and simultaneously reduce the network loss,which can guarantee the economy and stability of network system operation.