Exploiting geospatial shifting flexibility of building energy use for urban multi-energy system operation

Pengxiang Liu, Zhi Wu, Zijun Zhang, Wei Gu, Qirun Sun and Haifeng Qiu

Energy, 2024, vol. 313, issue C

Abstract: As one of the major energy consumers and greenhouse gas emitters, cities are at the center of global energy transition. For city managers, the energy consumption in the building sector is an important flexibility resource that can be utilized to improve the operation of urban multi-energy systems. Although demand response strategies have been widely studied for the temporal shifting of building energy use, the potential of spatial shifting flexibility is still lack of exploration. To this end, this paper proposes a novel approach to estimate and utilize the geospatial load shifting flexibility at the city scale. At the estimation stage, a methods is developed to calculate urban building energy consumption using publicly available databases and simulation tools, and the spatial distribution of supply side (energy infrastructures) and demand side (buildings) is analyzed through geographical information system. In the utilization part, a novel optimal energy flow model is proposed, where the geospatial shifting of load demand among different energy suppliers is achieved by topology reconstruction and equipment switching. To demonstrate the effectiveness and superiority of the proposed method, a real-world case study is conducted. The results show that the proposed approach can effectively exploit the spatial shifting flexibility of load demand, and the operation indicators of urban multi-energy systems such as total operating cost and maximum available capacity have also been improved.

Keywords: Multi-energy system; Building; Geographical information system; Optimization; Machine learning (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:313:y:2024:i:c:s0360544224037861

DOI: 10.1016/j.energy.2024.134008

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