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When large-scale distributed generation (DG) is connected to the grid, the net load of the distribution system fluctuates due to its output characteristics. The system power flow presents a strong random characteristic, which will lead to the phenomenon of reverse power transmission and bidirectional power flow. The traditional scheme of increasing distribution transformer and line reconstruction is difficult to collect data and ensure accuracy, and the calculation workload is large, time-consuming, and labor-intensive. Therefore, in the current situation, priority should be given to the use of distributed energy storage, static var generators, and other plug-and-play devices that are easy to deploy, as well as existing household photovoltaic power generation sources to participate in voltage and line loss management. In this paper, a line loss detection scheme based on distributed photovoltaic access grid is put. In this scheme, a set of joint optimization models of the planning layer and optimization layer is constructed, which takes network topology and line specifications as static parameter input. It also takes a typical photovoltaic-load power generation scenario of intelligent learning mode as dynamic parameter input. Besides, it integrates active and reactive power resources such as distributed energy storage, static var generator, and photovoltaic power system, and integrates the planning layer and operation layer. To synchronously solve the location and capacity scheme of the equipment planning layer and the optimal control strategy of the operation layer, it is helpful to promote a more accurate measurement of electric energy and has an incentive effect on both supply and demand sides to suppress power harmonics and improve the utilization rate of electric energy.
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