Researsh On Reactive Power Optimization Of Energy Internet Supply Side And Routing Communication Strategy

With the excessive exploitation of non-renewable energy sources such as coal,oil and so on,global demand for energy is increasing rapidly and environmental issues are becoming more noticeable,new energy gets more and more attention from various countries.On the other hand,the distribution network structure becomes more complex since different forms of energy into the grid,more and more scenarios of data are appearing in the energy internet,which leads to changes of structures and operation modes of the traditional power system,and the energy internet technology was proposed.How to improve the efficiency and quality of electric power transmission and build a perfect energy network communication network is of great theoretical and practical significance for promoting the development of energy internet and gradually transforming the traditional power grid into the energy internet.Considering different forms of new energy into the grid,the intermittency of distributed energy leads to the fluctuation of power quality of the supply-side of energy internet,this paper focuses on the problems of the power quality of distribution networks and the effective data communication of energy networks under the framework of the energy internet.As a result,an improved particle swarm optimization based on a tuning parameter for the distributed energy distribution network and an improved LEACH routing protocol based on dynamic optimization clustering for energy networks are proposed.The main contents of the research are as follows:(1)Since distributed energy is connected into the grid,the intermittency of distributed energy leads to the fluctuation of power quality of the supply-side of energy internet,this paper analyzes the causes of the instability of power amplitude and high loss in the power supply-side of distribution network,using the capacitive compensator and reactive power output of distributed energy,the mathematical model based on the capacitive compensator and transmission losses is established,at the same time,the objective function and constraint conditions are determined.(2)Based on the mathematical model of the supply-side of the power grid,considering that the particle swarm optimization algorithm is easy to fall into the local optimal value,which affects the reactive power optimization effect of the distribution network,meanwhile,the update of the learning factor affects the particle swarm algorithm to search for the optimal solution in the global scope.Because of this,an adjustable parameter is introduced into the learning factors in this paper and an improved particle swarm optimization algorithm through adjusting update rates of individual learning factors and social learning factors is proposed.In the early stage,the algorithm can enhance the ability to search for the optimal solution globally,reduce the solution domain,and then solve the problem with full effort,thereby improving the resolution accuracy of the traditional particle swarm optimization algorithm.Finally,IEEE-33 node distribution system is given as an example,by using MATLAB soft,to verify that the proposed method can effectively improve the voltage of the distribution network and reduce transmission losses.(3)For the problem of effective data communication in small energy networks,in order to reduce the energy loss of the energy network in the communication process,the topology structure of the small energy network with the energy router,which is the smallest unit,is designed using the hierarchical network structure to provide an accurate energy consumption model for the communication strategy of the energy network.(4)By analyzing the different density of network nodes,the remaining energy of the nodes,the impact of the network range on the load balance,data transmission volume,life cycle and other indicators of the communication network,and considering the influence of network transmission range of the cluster-head selection,a dynamic optimization clustering improved Low Energy Adaptive Clustering Hierarchy(LEACH)protocol based on the range of the network is proposed by dynamically optimizing cluster-head selection probability to increase the data transmission capacity of the energy routing network and balancing the load caused by energy loss in communication transmission.Finally,by comparing with traditional LEACH protocol and energy-efficient routing algorithm(EEPBL),dynamic clustering optimization based on the range of the network precedes the traditional LEACH protocol between data transmission capacity and node life cycle,at the same time,it effectively improves the communication performance of energy routers.