| The rapid development of smart power grid,ubiquitous power Internet of things and Energy Internet accelerates the exponential growth of edge nodes,which will challenge the centralization-based operation and communication logic in traditional power grid.The increasing data can greatly occupy the system resources during their uploading and calculation processes.However,in the underlying network,a large amount of surplus computing and communication resources can be wasted.Therefore,how to better utilizing these nodes while guaranteeing the cost of deployment can be an urgent problem.As the extension of cloud computing,fog computing can expand kinds of services from the cloud to the edge to provide low-latency network services,efficient data delivery and high resource utilization.Normally,fog computing is considered to be the best way to improve the efficiency while dealing with edge problems.However,different with general-purpose systems,power system has a high requirement of safety and cost,which challenges the application of fog computing.First,the application must built on the current power system monitoring network with more extensive timing collection and rapid response functions.Second,the energy problem in the fog nodes should be considered due to the increase of energy consumption for fog computing and communication.Third,as an unsupported technology,the application should show the better performances with examples to prove its advance.The main contents are presented as follows.1)Propose a fog framework for the system operation.Based on the current infrastructure of power system monitoring network,the framework is design to enhance the utilization of edge resources while satisfying the data collection and transmission requirements.Software defined network is utilized to control and schedule the communication among nodes with fog computing logic.The framework has shorter processing steps which can adapt different event-triggering ways.We also simulate the fog communication logic to prove its lower communication latency.2)Research the energy supply for outdoor nodes in power system monitoring.By analyzing the processing and communication requirements of outdoor nodes in power system,the energy supply strategies have been discussed.Meanwhile,a feasible energy supply approach for the online sensors has been proposed.The approach help separatethe communication and sensing on the overhead line monitoring.With the separation,the maintainance cost of the communication nodes can be decreased.3)Propose a fog computing based network scheduling approach to enhance the operation life of monitoring network.The approach is based on the blind Kriging surrogate model,and operates in the information aggregation nodes.The information aggregation node is defined as the fog node for computing and scheduling.The scheduling approach is based on the monitoring data formed mathematical model,which can be utilized to predict environmental results.The prediction can partly replace the nodes' monitoring operation,hence decrease the system energy consumption.4)Propose an example to prove the performance when utilizing fog computing in power system.A novel scheme for short-circuit diagnosis with high diagnosis accuracy,robust fault tolerance,and shorter time delays has been proposed.The scheme is operated on the proposed fog computing-based framework with the current power system infrastructure.Wide-area backup protection information is processed into targeted knowledge with smaller package sizes and transmitted among the relative fog nodes to establish incidence matrices in each node.Each fog node can calculate its diagnostic value using the matrices for the fault location.The resources of computing and communication are both economized during the process.The performance is validated with the IEEE 118 bus system.The results demonstrate that the scheme can maintain 100% accuracy with any three-error scenarios and provide a shorter latency with high network utilization. |
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