Design of Multi-source Message Big Data Platform for Power Grid Dispatching Based on Improved Ontology Aggregation

Abstract

Power grid dispatching decision is a process of making full use of the data of each system in the power grid and comprehensively analyzing the power grid operation state. However, in the current grid dispatching system, the data needed for dispatching decision is stored in different systems, which has the characteristics of decentralized, multi-source and heterogeneous. Existing data architectures are difficult to break down the data barriers between different systems, so they cannot efficiently retrieve the required dispatching data. To meet the needs of integration and aggregation of power grid multi-source heterogeneous dispatching messages, a big data platform for power grid multi-source dispatching messages based on improved ontology aggregation is proposed. The platform is based on Map/Reduce architecture, and the improved ontology clustering method is used to enhance the query and reasoning ability of the platform scheduling data, so as to realize the efficient integration and aggregation of multi-source messages in power grid dispatching.