数据驱动的能源互联网建模与仿真关键技术

Key Technologies of Data-driven Energy Interconnection Modeling and Simulation

针对能源互联网面临的多能流运行复杂性、源荷不确定性等日益突出的问题,基于能源生产、传输与消费各环节数据信息,文章设计了一种包含物理层、感知网络层、模型层、算法层、应用层的数据驱动能源互联网建模与仿真框架,并提出能源互联网数据与物理融合统一建模、分布式能源及负荷概率预测、典型运行场景生成以及多能流优化运行等关键技术,最后展望典型应用场景。以数据驱动为核心,为能源互联网建设提供技术支撑。

Aiming at the increasing issues of multi-energy flow complexity and source-load uncertainty of the energy interconnection, based on the data information in all aspects of energy production, transmission and consumption, this paper designs a framework of data-driven energy interconnection modeling and simulation that includes a physical layer, a perception network layer, a model layer, an algorithm layer, and an application layer. And it puts forward key technologies in unified modeling of data and physical integration, distributed energy and load probability prediction, typical running scenario generation, and multi-energy flow optimization operation. Finally, application scenarios are prospected. This paper takes data-driven as the core and provides framework guidance and technical support for the digital transformation of energy interconnection.