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A Data-Driven Architecture Design of Stream Computing for the Dispatch and Control System of the Power Grid

Physical distribution and logical unification are the crucial features of the future power grid dispatch system, which requires transmitting, processing and storing massive amounts of information. However, the traditional centralized system cannot meet these requirements. Therefore, this paper introduces the big data distribution stream processing technology, and proposes a stream computing framework suitable for the dispatch and control system of the power grid, including task definition, communication queue management, task assignment, task monitoring and task migration. Aiming at solving the problem of poor system extensibility caused by the high coupling of model data and real-time data in current SCADA system, a data decoupling method based on the separation of the dynamic date and static data is proposed, and the task decomposition of real-time data processing is adopted as a case study of the stream computing framework for the dispatch system. The stream computing framework can continuously process the borderless acquired data, and meet the requirements of real-time data distribution storage and interaction for the wide-area dispatch system of the power system.