Definition of core power grid business based on intelligent mapping and dynamic assessment

As the size and complexity of power systems continue to grow, issues related to a lack of clarity in the core power grid business, extreme data silos, and challenges in the quantification of business relevance are pressing urgent issues. To resolve this, in this paper, a framework for defining the core power grid business is built on an Intelligent Knowledge Graph (IKG) and a Dynamic Evaluation Model (DEM). The first is that, based on multi-source heterogeneous data fusion and entity relationship extraction, an intelligent graph of power grid business, such as business nodes, process nodes, and resource nodes, is constructed to attain a structured articulation of all-encompassing business knowledge. Second, there is a dynamic evaluation model constructed based on a three-dimensional index system of Key Business Index (KBI), Relevance Degree (RD), and Timeliness Factor (TF) to quantitatively analyze core businesses. Third, the dynamically calculated node influence by means of a multi-layer graph neural network (GNN) is developed to create an automatic identification mechanism of core power grid businesses. The experiments demonstrate that on the business dataset of the national-level power grid demonstration zone, the core business identification of this method is 94.1, and the mean processing time was 305 to 346 ms, which proves the effectiveness and scalability of the proposed method. The outcomes of the research also offer a scientific explanation, as well as a technical justification of the optimization of the business processes of the power grid, intelligent scheduling, and electronic operation.