Research On Regulation Technology Of Photovoltaic And Energy Storage System Based On Demand Response

In recent years,photovoltaic and other clean energy in our country is developing rapidly,and the capacity of access to the power grid has also been increasing.In order to meet the power quality requirements of the power grid such as safety and stability,economic operation,and power supply reliability,to avoid the intermittent and uncertainty of renewable energy output from causing serious impact on the power grid,a large number of wind and light abandonment phenomena often occur.At the same time,as environmental pollution has led to increasingly severe climate warming,persistent high temperatures have appeared in some areas,which has led to the rapid increase in the number of temperature-controlled loads,resulting in the seasonal peak pressure of the grid,and the gap between peaks and valleys has become increasingly prominent.Therefore,this thesis proposes to use the energy storage characteristics of the battery and the temperature control load to store energy,and at the same time to convert the photovoltaic clean energy with uncertainty into demand response resources,so that the three can work together to participate in the demand response,so as to realize the full consumption of photovoltaic and alleviate the peak pressure of the power grid.The specific work of this thesis is as follows:(1)In this thesis,the equivalent thermal parameter model of temperature control load,the dynamic model of cluster temperature control load and its virtual energy storage model are firstly established,and the virtual energy storage model is simulated and verified.The results prove the effectiveness of the model.In addition,the Monte Carlo simulation method is used to simulate the virtual energy storage characteristics of the temperature-controlled load.Based on the simulation results,the maximum virtual energy storage capacity that can be reached when the temperature-controlled load setting value is changed is calculated.In addition,this chapter also establishes the output power models of photovoltaics and batteries to support the control of power balance in the system and participation in demand response.(2)The thermal inertia in the space of temperature control load is not considered in most of the current temperature control load control models.In this thesis,a temperature control load state space model with thermal inertia is proposed,and the corresponding temperature compensation mechanism is proposed.In order to fully consider the satisfaction of users of temperature control load,this thesis conducts secondary clustering of temperature control load group and establishes a dynamic model based on secondary clustering.Using monte carlo simulation method to simulate large-scale cluster dynamic response temperature load will cause the dimension disaster,so in this thesis,using the control of the temperature field model instead of the time domain cluster temperature control model to control the temperature,ultimately through differencing to control the temperature of the continuous domain model can be converted to temperature control of the cluster of load model.(3)First of all,a real-time power balance control strategy for cluster photovoltaic and energy storage systems in the area is proposed,which achieves the "spontaneous and self-use"power balance goal in the area and the full consumption of photovoltaic power generation.In this scenario,clean energy can be avoided.It can also make full use of the energy storage characteristics of temperature-controlled loads.The other scenario is to use the cluster photovoltaic and energy storage systems in the area to participate in demand response to ensure the quality of the power grid and improve the economy of the grid.In this scenario,a typical CSO optimization algorithm is used to minimize the running cost as the objective function and to participate in The demand response error is a penalty term.Constrained by the power balance of each device and its own operating conditions,the power provided by the cluster photovoltaic and energy storage system in the region to participate in demand response is optimized.Finally,a simulation analysis is performed.