Research On Resource Management Algorithm With The Requirements Of Smart Grid Communication

In recent years,the traditional power network relies on the burning of fossil fuels to obtain electric energy,which has caused a great deal of pollution,and the control policy of power limitation and energy consumption has been introduced,which has prompted the traditional power network to transform into a more intelligent power network and evolve into a new generation of"Smart Grid(SG)".In addition,the development of the fifth generation of mobile communication technology(5G)provides strong support for smart grid.There are three types of services in smart grid,including control services,information collection services and mobile application services,which have some similar characteristics with the three typical scenarios of 5G.The combination of smart grid and 5G makes the intelligent scale of power grid gradually expand,and the types of services become various,for example,the services of distribution automation and precise load control,which belong to the control services,the services of electricity information collection,power transmission and transformation status monitoring,which belong to the information collection services,and the services of transmission,distribution and transformer machine inspection and mobile operation,which belong to the mobile application information collection.On this basis,combined with the call for increasing energy conservation and emission reduction,this thesis focuses on the energy efficiency of power users in community smart grid,and tries its best to improve the energy efficiency of power equipment.However,due to the limitations of mixed cellular users on throughput and other indicators and wireless resources such as power consumption and channels,how to allocate resources reasonably to meet the performance indicators of power users and ordinary users is facing many challenges.With the rapid development of smart grid,there are more and more types of grid devices,which makes it necessary to transmit a large amount of data with strict requirements on error rate in smart grid.At the same time,it is also necessary to save energy and reduce emissions,advocate the transformation of energy structure,and vigorously develop distributed renewable energy in community smart grid.Based on this,facing the characteristics of limited resources,diversified services and strict reliability requirements of control services in smart grid,this thesis uses finite length coding to improve the reliability of control services,and optimizes the throughput of single-service and multi-service smart grid scenarios,and then studies the energy efficiency of mixed scenarios of power users and cellular users in community smart grid,and designs a variety of new information transmission architectures and resource management algorithms.The main work of this thesis is as follows:First of all,the wireless access network congestion and highly reliable communication problems caused by the need to transmit a large amount of delay-sensitive data in smart grid are addressed.Based on the finite length coding theory,this thesis designs a heterogeneous cellular network uplink information communication system.Under this system model,a resource management algorithm is proposed to jointly optimize the channel allocation and power allocation,with the objective function of maximizing the system throughput,and finally the system throughput is optimized.In addition,this thesis introduces the concept of virtual devices into the sub-problem of channel allocation,which reduces the complexity of the problem.On this basis,the optimized transmission power is obtained through the iterative algorithm based on Taylor expansion linear approximation method.Next,the channel allocation matrix is obtained by using convex optimization algorithm and relaxation method,and then the two subproblems are combined to obtain the maximum system throughput.Finally,the numerical simulation of the proposed resource management algorithm verifies the effectiveness of the algorithm.Compared with other schemes,it is proved that this scheme can significantly improve the throughput of the system.Next,in order to solve the problem of service diversity caused by the rapid increase of types and numbers of terminal devices in smart grid,this thesis designs a communication architecture of uplink information transmission in smart grid scene where multiple services coexist.Under this framework,a resource management algorithm combining three types of service priorities,channel allocation and power control is proposed to maximize the system throughput.In order to solve this mixed integer nonlinear programming problem,this thesis deals with channel allocation problem,power control problem and three kinds of service priority problems separately.The exchange operation and Lagrange dual decomposition method are used to solve another problem under the condition of fixing one problem,and then the maximum system throughput is obtained through iterative convergence.Finally,numerical simulation of the resource management algorithm is carried out in this thesis,and the simulation results show that the proposed algorithm is effective and can significantly improve the system throughput.Finally,aiming at the problems of large devices energy consumption,power limitation,energy saving and emission reduction in the current smart grid,this thesis proposes a communication architecture of community smart grid information transmission based on the mixed model of power users and ordinary cellular users,and under this architecture,a resource management algorithm of maximizing system energy efficiency that jointly optimizes the matching relationship between power users and cellular users and power control of power users is proposed.Iterate through the exchange operation,Dienkelbach and other methods until convergence.Then,the maximum system energy efficiency was obtained.Finally,the simulation results verify the effectiveness and convergence of the proposed resource management algorithm,and the performance gain of the proposed algorithm compared with other schemes can significantly improve the energy efficiency of the system.