Photovoltaic-storage-charging Intergrated Station And Its Reasearch On Energy Scheduling Optimization

In order to deal with the energy crisis and environmental pollution,and in response to the "two-carbon" economy,countries around the world are committed to studying the application of new energy in the field of transportation,which promotes the development of electric vehicle related fields,and promotes the research and construction of charging facilities.In order to solve the problem that electric vehicle charging stations have a single form of energy and are difficult to cope with large-scale electric vehicle charging load,photovoltaic power generation system and energy storage system are combined to form a flexible photovoltaic-storage-charging integrated station.While meeting the charging demand of electric vehicles,photovoltaic local consumption is realized and the dependence on traditional energy is reduced.In order to achieve the above goals,it is necessary to carry out reasonable analysis and research on its system and energy scheduling strategy.This paper analyzes the system structure and characteristics of the photovoltaic-storage-charging integrated station,and introduces the building form and the overall structure of the charging station.Then,the electrical system structure is analyzed from the overall structure,subsystem structure and system framework,and the DC coupling system is determined as the framework scheme.Nextly,a communication system structure using fiber channel and CAN bus is proposed and its operation process is analyzed.Finally,the characteristics of photovoltaic power generation system and energy storage system are described respectively to lay a foundation for the realization of energy scheduling optimization.To ensure the normal operation of the integrated optical storage and charging station,the charging load of electric vehicles is analyzed and modeled.Firstly,the related theories of EV are introduced from the types,charging modes,charging strategies and charging process of on-board battery.Then,the travel characteristics of EV users were analyzed from the road model,travel chain,travel path planning,charging behavior and travel time characteristics.Based on the above information,the spatial-temporal distribution model of EV charging load was established using Monte Carlo sampling method.Finally,a numerical example was introduced to verify the feasibility of the model.To meet the charging demand of electric vehicles and improve the overall operating efficiency of charging stations,the energy scheduling strategy is analyzed from the aspect of active power scheduling.Firstly,the energy flow strategy considering electric energy complementarity and peak-valley price is analyzed.On this basis,in order to improve the economic benefits of charging stations and reduce their impact on the power grid,the charging and discharging power of the energy storage system is used as the control variable,and the active power scheduling optimization model is established with the minimum daily operation cost of charging stations and the minimum fluctuation of the switching power of the public grid as the target.A multi-strategy improved driving training optimization algorithm is proposed as the solution method.Finally,an example is introduced for simulation analysis.The results show that the model and the improved algorithm can not only improve the economic benefits of charging stations,but also reduce the impact on the public power grid,which is feasible.In order to further reduce the influence of the purchasing and selling behaviors of the optical storage-charging station on the power grid system,this paper adds the energy scheduling strategy from the aspect of reactive power scheduling.Firstly,the IEEE 33 node system is introduced as an example to analyze the negative effects of grid-connected charging stations on the system.Then,the reactive power output of reactive compensation equipment of charging station is selected as the control variable,and the reactive power scheduling optimization model is established with the minimum active power loss and minimum node voltage deviation as the target.Finally,combined with the above node system,the improved algorithm proposed above is used to solve the reactive power scheduling optimization model.The results show that the model and the improved algorithm can effectively reduce the network loss and raise the node voltage,improve the operational stability of the power system connected to the integrated optical storage and charging station,and verify the feasibility.Therefore,active power scheduling optimization and reactive power scheduling optimization are integrated to provide a reference scheme for solving the energy scheduling optimization problem of an integrated optical storage and charging station.