Research On Economic Benefit Optimization Scheduling Model Of Family Photovoltaic Systems

As the Energy Internet develops,China has made a great breakthrough in photovoltaic power generation technology and energy storage technology,and the cost is declining.Due to the strong support of the national policy and high subsidies provided for photovoltaic users by the government,more and more families have installed photovoltaic system.Therefore,the optimal scheduling problem of family photovoltaic system is a very significant research topic.However,for these users,further study is still needed to research how to make their installed photovoltaic power generation system to maximize the user's revenue.Aiming at the shortcomings of traditional PV dispatching strategy,this paper proposes a new economic benefit optimization scheduling model of the family photovoltaic system.Firstly,through the analysis of the current domestic and foreign research status of photovoltaic power generation,this paper finds out the problems and deficiencies in the traditional photovoltaic power generation system,and points out the necessity of the proposed model.In order to provide a better judgment basis for the optimal scheduling,this paper analyzes the working principle of the family photovoltaic system,and establishes the active power output model of the PV array and the charging and discharging power model of the energy storage device.The simulation work of the model is completed according to the future weather forecast,which provides the judgment basis for the subsequent optimization scheduling model.Secondly,in order to realize the maximum benefit of the household photovoltaic system and optimize the electricity structure,this paper proposes a new economic benefit optimization scheduling model of the household photovoltaic power generation system with consideration of various factors.The allocation proportion of grid-connected power in the surplus power and the allocation proportion of purchase power in the lacking power are the optimization variable.The objective function is to maximize user revenue.Under the policy of time-of-use tariff,the model can get the optimal scheduling instruction to maximize the user's revenue.We choose particle swarm optimization algorithm(PSO)to solve the optimization model.Then,a specific study case is given to verify the rationality and advantage of the proposed model.By comparing with the simulation results of the traditional scheduling model,the good scheduling effect of the proposed model is highlighted.The model can improve the user's benefit and optimize the user's electric structure.For the power grid,the model plays a good role in peak shaving to ease the peak power supply pressure.Since the weather is uncertain,the optimal scheduling strategy can't be immutable.In order to consider the uncertainty factors such as weather,this paper proposes two methods to improve the optimization scheduling model.Affected by weather factors,the amount of energy stored in the energy storage device at the end of the day will greatly affect the scheduling effect of the next day.So it is very important to set up the constraint conditions of the energy storage device at the end of the day.In order to solve the above problems,this paper puts forward two methods to improve the model,which is the direct method and the method of evaluating the value of energy storage.The improved model can reasonably constitute the best constraint condition of the energy storage device at the end of the day to make adequate preparations for the next scheduling,fully responding to the influence of the uncertainty of weather factors.Meanwhile,it can ensure to achieve the best overall economic benefits of the system in the whole scheduling cycle.Finally,the proposed optimal scheduling model is simulated.The correctness and effectiveness of the proposed scheme are verified by comparing the scheduling results and economic benefits of each scheme.