Abstract：The expansion of the power communication network and the deployment of smart grids have brought massive amounts of data and calculation pressure to the operation and maintenance center. Edge computing can alleviate the pressure on the grid management platform to process massive amounts of data, reduce computing overhead, and assist operation and maintenance personnel efficiently complete fault diagnosis and maintenance. This paper proposed a power communication network fault diagnosis technical solution based on the edge computing architecture combined with the knowledge graph technology, will focus on the new ecology of edge computing in the power communication network. For improving the traditional rule-based technology and enhancing the reliability and efficiency, the system integrates a variety of intelligent methods to realize fault diagnosis under the edge computing architecture, and realizes timely detection of faults and dispatch maintenance through analysis of equipment alarms and network topology.

Abstract：Energy Internet technology can realize the information fusion of demand side adjustable power load resources, transmission and distribution resources, power generation resources, and play the value benefits of demand side adjustable power load in peak load and frequency regulationof power grid. In this paper, by integrating the advantages and disadvantages of different control modes for demand side resources, a framework and method of decentralized collaborative control within demand side resource cluster and regional grid coordinated control is proposed, which can effectively improve the flexibility and rapidity of adjustable resource response grid frequency regulation.

Abstract：The demand for electric power and the coverage of power communication network has been gradually expanding, which brings the challenges that need to be addressed in the operation and maintenance of the domain. The deployment of edge nodes provides the availability of data collection, information filtering and computational support, which can heavily alleviate the pressure of management. Alarm analysis is a key and difficult problem in operation and maintenance. The traditional alarm analysis first uses rules to merge alarms, so as to reduce the workload of subsequent processing. However, the completeness of rules requires a lot of expert knowledge and human resources investment, and there are limitations. This paper proposed a novel and lightweight algorithm. In this paper, Unsupervised clustering is introduced into the alarm merging process of power communication network edge cloud computing, and the density based clustering method is combined with the existing merging rules. The experimental results show that the effect of alarm merging can be significantly improved by adding unsupervised learning, which is helpful to improve the accuracy and completeness of subsequent defect location.

Abstract：In view of the lack of sufficient computing, storage and communication network resources for computing equipment at the edge of inclement industrial environments, and the requirement for ms-level data processing response, the agile intelligent system named “SWIFT” was introduced from the general architecture, hardware and software composition and key technology. This system has been verified in wind power equipment, which improves the user′s ability to optimize wind turbine operation and maintenance detection, and reduces downtime loss and operation cost. At the same time, it also discussed that the agile intelligent cluster computing technology could be applied in not only intelligent operation and maintenance of single wind turbine，but also the intelligent operation of large-scale wind farm.

Abstract：The industrial internet site has the complexity brought by a large number of heterogeneous devices and networks, as well as the real-time and reliability problems of industrial production. If data analysis and control logic are all implemented in the cloud, it is difficult to meet the network requirements of industrial scenarios. However, edge computing can meet the development needs of the industrial internet in terms of service real-time and reliability. This paper proposes three technical solutions for optical line terminal(OLT) converged edge computing for industrial internet,mainly through the edge computing and OLT business connection, route forwarding and management functions and other aspects of the analysis. Comparing the differences among the three solutions of OLT built-in edge computing with value-added functions, OLT built-in edge computing with general functions, and OLT external edge computing, according to their differences, the scene requirements applicable to different factories are proposed.