Impact of extreme weather on the reliability of building distributed energy systems–A case study in three cities in China

Huizhen Han, Yongkai Ge, Qingrui Wang, Xi Chen, Qing Yang, Luning Tian and Xiaowei Chen

Renewable and Sustainable Energy Reviews, 2025, vol. 212, issue C

Abstract: A building distributed energy system is an efficient low-carbon energy supply option. As extreme weather events become more frequent, clarifying the ability of distributed energy systems to withstand extreme weather is fundamental to assessing their potential for future applications. However, the impact of extreme weather on the reliability of distributed energy systems is unclear. To fill this gap, a method based on mixed-integer linear programming is proposed to quantitatively assess the impact of extreme weather on the reliability of distributed energy systems. The effects of system location, operating scenarios, and operating strategies on system reliability under extreme weather are explored. Taking three Chinese cities that had heat waves as examples, the results show that only the reliability of the system in Tianjin is affected by the operation strategy. The electricity supply reliability of the system with grid-connected operation is 100 %, but the system cooling supply reliability may decrease by up to 5 %. When the system operates in islanded mode, heat waves have a greater impact on the reliability of the system located in the south than that in the north. The level of power supply incidents caused by system-reduced reliability in Chongqing, Wenzhou, and Tianjin is classified as major-normal, special major-normal, and major/large-short. The minimum cooling supply factor is 80 %, 94 %, and 100 %. The longer the heat wave lasts, the less reliable the system is. This study provides a theoretical foundation for improving the resilience of distributed energy systems to extreme weather.

Keywords: Extreme weather events; Heat wave events; Distributed energy systems with near-zero carbon emissions; System capacity and operation optimization; Electricity/cooling/heating supply reliability (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.rser.2025.115374

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