Author/Authors :
Fan,Shixiong Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology - China Electric Power Research Institute, Haidian District, China , Liu, Xingwei Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology - China Electric Power Research Institute, Haidian District, China , Chen,Ying School of Computer Science and Engineering - Central South University, China , Liao, Zhifang School of Computer Science and Engineering - Central South University, China , Zhao, Yiqi School of Computer Science and Engineering - Central South University, China , Luo, Huimin School of Computer Science and Engineering - Central South University, China , Fan, Haiwei State Grid Fujian Electric Power Co., Ltd., China
Abstract :
Knowledge graph is a kind of semantic network for information retrieval. How to construct a knowledge graph that can serve the power system based on the behavior data of dispatchers is a hot research topic in the area of electric power artificial intelligence. In this paper, we propose a method to construct the dispatch knowledge graph for the power grid. By leveraging on dispatch data from the power domain, this method first extracts entities and then identifies dispatching behavior relationship patterns. More specifically, the method includes three steps. First, we construct a corpus of power dispatching behaviors by semi-automated labeling. and then, we propose a model, called the BiLSTM-CRF model, to extract entities and identify the dispatching behavior relationship patterns. Finally, we construct a knowledge graph of power dispatching data. The knowledge graph provides an underlying knowledge model for automated power dispatching and related services and helps dispatchers perform better power dispatch knowledge retrieval and other operations during the dispatch process.
