High-proportion Household Photovoltaic Grid-connected Voltage Control Based On Source-load Interaction

With the rapid development of the energy industry and the urgent requirement of low-carbon transformation,the cost of household photovoltaic and electric vehicles is decreasing day by day,and it is more and more commonly connected to the power grid.However,due to the intermittent and fluctuating characteristics of photovoltaic power generation and the randomness of high-power energy consumption of electric vehicles,a high proportion of new generation / energy consumption equipment connected to the grid will aggravate the problem of grid voltage overrun and many other risks.In order to solve the problem of grid connected power consumption of household photovoltaic system and improve the consumption capacity of distribution network for household photovoltaic system,the management of grid connected photovoltaic system has been widely concerned by scholars at home and abroad.However,most of the existing studies start from increasing energy storage or reducing photovoltaic active power output.The former costs more,while the latter causes a waste of clean energy.In this paper,from the perspective of source load interaction,by means of regulating and controlling the schedulable load such as electric vehicles and intelligent load,the two aspects of source load interaction energy management based on schedulable load and source load interaction voltage stabilizing control method based on intelligent load are analyzed respectively.Firstly,the model of household micro grid with smart load is built,and the dynamic models of single-phase phase-locked loop,photovoltaic grid side PWM converter and ES are established.The control strategy of household photovoltaic grid connected system and smart load in household micro grid is analyzed,and the voltage stabilizing control method of smart load based on active power control is proposed.In order to effectively improve the dynamic control performance of the system and the dynamic response speed of the front and back stages of the photovoltaic grid connected system,the original photovoltaic control system is improved.Based on the traditional voltage and current double closed-loop,the grid disturbance voltage term and voltage drop term are introduced for feedforward compensation,and the power and voltage feedforward double closed-loop control strategy is proposed.Secondly,the user source load interactive energy management method based on schedulable load is studied.Based on the day ahead forecast value,the comfort evaluation index is established,and the fuzzy membership function based on price sensitivity is proposed,so that the comfort related load can dynamically change its demand response strength according to the different electricity prices,and reduce the user’s electricity expenditure while ensuring the user’s satisfaction.The proposed strategy is optimized by using the mixed integer linear programming algorithm to realize the optimization Finally,an example is given to verify the effectiveness of the proposed method.Finally,aiming at the voltage fluctuation and cross-border problems caused by household photovoltaic grid connection.The impedance line model of user access distribution network is established,and the voltage characteristics of user nodes are analyzed.In order to improve the dynamic performance of the system,Jaya algorithm is used to optimize the multi PI parameters of the controller according to the time multiplied absolute error integral criterion.The simulation results show that the system has good robustness in different operating states.Aiming at the problem of feeder voltage deviation in distribution network,a two-layer coordinated control method of photovoltaic reactive power and intelligent load active power is adopted,and a multi intelligent load cooperative control strategy is proposed,which uses intelligent load to accurately change the active power of user nodes.Finally,the simulation results show that the two-layer coordinated control method based on photovoltaic reactive power and intelligent load active power,as well as the effectiveness of multi intelligent load coordinated control.