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From numerical model to computational intelligence: The digital transition of urban energy system
Abstract
With the development of digital technologies, especially big data analytics, digital innovations are taking root in various industries, including energy sector. Particularly, urban energy system is also experiencing digital transition; such digital transition not only offers new business models commercially, but also brings new research problems scientifically. The new capabilities enabled by these digital technologies are reshaping the generation, transmission, consumption and storage sections in the urban energy system, sequentially the traditional way of how urban energy system is designed and operated should be reexamined. Starting from here, there have been many studies regarding how various digital technologies can be applied all along the urban energy system value chain; these studies range from individuals’ energy consumption pattern characterization by using customer behavior data in smart home, to complex data-driven planning of regional scale energy system. More specifically, numerous computational models have been proposed by the scientific community to mimic the dynamics of various components at various levels in the urban energy system. However, the potential benefits of applying these numerical models are somehow underestimated; we believe there are still several gaps from numerical modeling to computational intelligence which need to be bridged. In such a context, in this paper we strive to present a systematic review on the status of urban energy system related digital innovations as well as prospective outlook on the future application of such digital technologies. Through the study of this paper, we hope to identify several key points where digitalization should be prioritized in urban energy system, picture a roadmap towards future digital technology enabled intelligent urban energy system, and finally points out the research gaps that need to be fulfilled over there.