Research on Key Technology of Digital Twin and Its Application in Integrated Energy System

Qi Zhao, Sheng Chen, Xinying Wang, Jie Tian, Rixiao Zhao, Jun Yang
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Abstract

Integrated Energy System (IES) can effectively improve energy utilization efficiency through multi-energy coupling. However, the mechanism is unclear and the randomness of the system is strong, which is difficult for system modeling and operation optimization. Digital twin (DT) can built the twin model in digital space that change synchronously with the physical object, and carry out behavior prediction and intelligent decision-making, which is an effective way to solve the above problems of IES. Focusing on DT, this paper firstly analyzes the development mode of DT system, including symbiosis, evolution and optimization, and puts forward key technology on fusion modeling, neural network optimization and intelligent decision making. Secondly, from the view of source, network, load and storage, this paper deeply summarizes and refines the current methods of the DT model building in IES. Finally, the symbiosis framework of DT model building in IES is proposed, which enables the accurate description and mapping of the system characteristic, and provides accurate model support for the operation optimization in IES.
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数字孪生关键技术及其在综合能源系统中的应用研究
综合能源系统可以通过多能耦合有效地提高能源利用效率。但其机理不明确,系统随机性强,给系统建模和运行优化带来困难。数字孪生(DT)可以在数字空间中建立与物理对象同步变化的孪生模型,并进行行为预测和智能决策,是解决上述IES问题的有效途径。以DT为重点,首先分析了DT系统的发展模式,包括共生、进化和优化,提出了融合建模、神经网络优化和智能决策等关键技术。其次,从源、网络、负载和存储的角度,对目前IES中DT模型的构建方法进行了深入的总结和提炼。最后,提出了在IES中建立DT模型的共生框架,实现了对系统特性的准确描述和映射,为IES中的运行优化提供了准确的模型支持。
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