Identification of Distributed Generation from Load data in Power Systems

In modern power systems, distributed energy resources (DER) can ensure grid stability, meet load demand, and better plan and manage grid operations, making its role increasingly significant. Grid operators usually need to plan long-term and short-term grid operations, including load forecasting, power supply, and power distribution. Therefore, existing data management methods often model distributed generation as part of the load to simulate how distributed generation matches the actual load level. The equivalent distributed generators of the 10kV and 35kV outgoing lines of the transmission grid in the given data are currently modeled as loads. Some DERs exhibit load-like characteristics at certain times of the day, while displaying distributed generation characteristics at other times. This makes it challenging to differentiate between distributed generators and loads during scheduling management or equipment management. Therefore, this paper proposes an identification method for distributed generation and load based on graph database technology. The method uses the given real transmission network model data of a province to build a graph model, and performs naming rule verification, topology inspection, plant station power balance verification, and other identification steps in order to identify distributed generation from the existing load data.