In order to make the modern power system more intelligent, various data acquisition equipment and information management systems are required, such as smart meters, remote terminal units (RTU), phasor measurement units(PMU), power distribution management systems(DMS), and energy management systems(EMS), customer management system(CMS), power generation management system(GMS) have been widely installed. These systems create large amounts of data, which is the main source of smart grid big data. Researching advanced data analysis technology is the most urgent task for the development of smart grid. It can make the best decision for the control and operation of the grid, and can improve the flexibility, safety, reliability and efficiency of the power system. This article analyses the cause of smart grid big data and the importance of data analysis, and discusses the development trend of big data technology. Selectively analysed the source and type of smart grid big data, summarized the characteristics of smart grid big data, gave various application scenarios, and introduced the smart grid big data analysis platform and the functions being developed.
Distribution network plays the role of distributing electric energy in the power system, whether it can run normally relates to people’s production and life. In recent years, frequent natural disasters have caused large-scale failures of distribution networks, resulting in the interruption of a large number of load power supply, which has a huge impact on people’s lives and post-disaster recovery work. Therefore, it is very important to formulate scientific and efficient emergency repair strategies. This paper will study the power supply recovery and multi-fault rush repair of distribution network respectively from the two aspects of load grade and the economy of power grid operation, establish mathematical model, and use particle swarm optimization algorithm to solve, so as to provide a more efficient emergency plan for power supply recovery after disaster.
With the increasing frequency of extreme weather caused by energy problems, the number of large-scale power outages caused by natural disasters is increasing, which brings greater challenges to the problem of system failure recovery. In recent years, the influx of controllable loads such as demand-side resources such as electric vehicles and energy storage equipment into the electricity market has further enriched the resources and means available for grid fault recovery. Therefore, considering the active participation of power users in the fault recovery of the distribution network, this paper establishes a controllable load model, and at the same time uses the power generation ratio to assess the direct loss of the lost power users, and then assess its importance. In the final solution, the active distribution network recovery power supply strategy with controlled load participation can be solved. Simulation analysis of IEEE33 node system shows that the proposed strategy established can make full use of the user-side demand response resources to prioritize the recovery of important loads, reduce the loss caused by power loss, and improve the recovery efficiency of the distribution network.
Urban distribution network planning is the key technology of smart distribution network. The survey method is used to summarize the economic evaluation, load forecasting, and power grid planning of urban power grids. On this basis, the corresponding methods and solutions to the problem are proposed, including: improving the professional literacy of relevant technical practitioners, establishing and improving a smart distribution network supervision mechanism, and strengthening relevant maintenance of smart distribution network equipment. Optimize planning quality. Enable power companies to fully meet the development needs of modern society, better ensure the safety of power grid projects, and effectively plan urban power grids.
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