Distributed Cloud Data Center Placement Optimization And Cloud-edge Resource Allocation Strategies For Power Internet Of Things

The development of power grid and integrated energy has expanded power business and spawned new power business formats,requiring the power automation system to have stronger business support capability.Under this background,the theory and application of Power Internet of Things(PIo T)have become research hotspots in the current field of power system.In order to optimize the construction,device placement and operating performance of PIo T,and improve the power business support capability of PIo T,this paper takes the PIo T Monitoring Business(PIo TMB)as an example to consider the power business,and proposes the distributed cloud data center placement optimization strategy and the cloud-edge resource allocation strategy for PIo T,including the optimization problem models and problem-solving methods.Furthermore,simulation analysis is carried out by setting cases,which proves the effectiveness of the proposed strategies.The main research of this paper includes:(1)The cloud-pipe-edge-terminal PIo T architecture is analyzed and the layers and devices in the architecture are illustrated.The specific implementation methods of some key technologies are studied,including device virtualization method based on virtual machine and container,and cloud data center placement method based on substation.Furthermore,the PIo T overall architecture and architecture characteristics are summarized and analyzed.(2)Based on the analysis of PIo TMB,the cloud-edge collaboration mechanism for PIo TMB processing is proposed.The typical PIo TMB and important PIo TMB characteristics are analyzed;the qualitative classification of PIo TMB is studied according to PIo TMB characteristics and the basic PIo TMB model is proposed.The cloud-edge collaborations in the process of PIo TMB are analyzed and cloud-edge collaboration methods are explained.The overall implementation of cloud-edge collaboration is analyzed and the cloud-edge resource allocation is emphasized.(3)A distributed cloud data center placement optimization strategy is proposed.Considering PIo TMB characteristics,taking the proposed PIo T architecture as the main constraint,the optimization problem model is built with the economy performance of cloud data center construction,communication network construction and cloud data center operation as the objective function.The optimization problem model is linearized and the problemsolving method is proposed.Case study results prove the effectiveness of the proposed optimization problem model and the problem-solving method,and prove that the proposed distributed cloud data center placement optimization strategy can decrease the construction and operation costs of distributed cloud data centers.(4)A resource allocation strategy based on cloud-edge collaboration is proposed.Considering the characteristics of PIo TMB and Power Monitoring Data(PMD),taking the security of PIo TMB and PMD and the real time requirement of PIo TMB as constraints,the cloud-edge resource allocation problem model is built with the total communication workload in PIo TMB processing as the objective function.The resource allocation problem model is linearized and the problem-solving method is proposed.Case study results prove the effectiveness of the proposed problem model and problem-solving method,and prove that the proposed cloud-edge resource allocation strategy can decrease communication workload on the basis of ensuring security and real-time requirement,so as to improve the PIo TMB support capability of PIoT.