基于数据驱动的水电厂数字孪生模型构建与应用

Zengtao Zhao, Dinglin Li, Jun She, Hao Zhang, Yupeng Zhou, Lei Zhao
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引用次数: 1

摘要

水电站数字孪生模型旨在充分利用新型电力系统的海量数据信息,以数字化的方式描述电力系统中的人、事、物及其关系,为水电企业提供有效的海量数据融合和挖掘能力。随着大数据和人工智能技术的发展,数字孪生技术正逐渐成为推动电力行业数字化转型的核心驱动力之一。阐述了水电站数字孪生模型的表示方法,针对电力系统的复杂性和非线性特点,提出了数据驱动的模型构建和应用框架。最后,通过水电厂故障诊断实例验证了本文方法的有效性。
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Construction and Application of Digital Twin Model of Hydropower Plant Based on Data-driven
The digital twin model of hydropower plants is designed to make full use of the massive data information of the new power system, to describe the people, events, things and their relationships in the power system in a digital way, and to provide hydropower companies with effective massive data fusion and mining capabilities. With the development of big data and artificial intelligence technology, digital twin technology is gradually becoming one of the core driving forces to promote the digital transformation of the power industry. The paper expounds the representation method of the digital twin model of hydropower plants, and proposes a data-driven model construction and application framework for the complexity and nonlinear characteristics of the power system. Finally, the effectiveness of the method in this paper is verified by a case of fault diagnosis in hydropower plants.
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