Research On Optimization Strategy Of Charging Scheduling Network Based On Graph

With the occurrence and proliferation of the interconnection of all things,we are facing a broader and deeper mass of terminal information.How to better analyze and process this data and transform it into a catalyst for economic and social development is the challenge and opportunity brought to us by the era of big data.Graph databases and graph algorithms that use nodes and edges to express data models have entered the vision of academia and industry.Smart grid is one of the results of the development of the industrial Internet.New energy vehicles can be regarded as a mobile node in the smart grid.Combining emerging technologies and traditional industrial systems,the future development goal of the electric vehicle industry will be to strive to create safe driving and convenient charging.,Intelligent vehicles with sufficient battery life,strong environmental adaptability,high degree of informationization,and clean and pollutionfree.However,due to the constraints of battery capacity,new energy electric vehicles need to regularly go to charging facilities to replenish electrical energy.By rationally planning the location of electric vehicle charging stations,ensuring the utilization rate of charging stations and optimizing the charging cost of vehicles,it is conducive to load balancing of power stations,optimal use of energy,alleviation of urban congestion,and optimal life management of electric vehicles.Based on this,in the edge computing environment,this paper combines graph computing and topological potential to study the graph division of terminal networks.At the same time,it proposes a graph model-based charging recommendation strategy and optimization for the charging scheduling network.By optimizing the charging scheduling strategy,reasonably planning the charging route,and personalizing the recommendation of charging stations according to the different needs of users,not only can meet the needs of electric vehicle users for timely and efficient charging,shorten the waiting time for vehicle charging,but also help realize the load balance of charging stations,To ensure the safe and orderly operation of the power grid.The research content mainly includes the following aspects:(1)Research on the construction of graph data model: for the terminal data network graph model,combined with network characteristics,study the graph network node set and graph network edge set composed of the most effective nodes,and construct a reasonable and efficient graph data model to improve the graph algorithm Efficiency,reduce network resource expenditure.Establish specifications for the design of the charging dispatch network diagram model later.(2)Research on terminal graph division based on topological potential: This research will introduce the concept of topological potential.By calculating the topological potential value of each point in the terminal network graph model,effective information such as key nodes in the graph can be obtained,thereby providing the terminal data network Provide the basis for the research of graph partitioning algorithm.(3)Research on the charging recommendation strategy of edge computing based on graph model: establish a graph model of charging dispatch network,a single electric vehicle model,and a traffic road network model,combined with topological potential,on the basis of graph division of the charging dispatch network,According to the actual travel needs of users,the edge side recommends strategies with different focuses and optimizes them.The proposed algorithm is verified under the actual charging pile edge computing system.