4.7 Article

Design and operation of park-level integrated energy systems in various climate zones in China

Journal

SUSTAINABLE CITIES AND SOCIETY
Volume 96, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.scs.2023.104705

Keywords

Energy system; Optimization; Climate; Energy demand; Operation

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This paper presents the park-level integrated energy systems (PIESs) in different climate zones of China and proposes a two-stage optimal approach for modeling and optimizing the operation strategies. The results show that PIES-1 in Dalian has the lowest total cost and carbon dioxide emissions.
Park-level integrated energy systems (PIESs) have a unique role in developing communities' energy infrastruc-ture in more economical and sustainable ways. The design and operation of a PIES depend on the energy demand of buildings, which could be significantly affected by climate change. This paper presented the PIES in China's different climate zones (Harbin, Dalian, Changsha, and Haikou). The PIES integrating natural gas, solar and geothermal energy simultaneously produces electric, heating and cooling loads. A two-stage optimal approach was proposed in this paper to model the PIES mathematically. In the first stage, the worst-case scenario was obtained by the confidence interval combination method to optimize the minimum total cost. In the second stage, the operation strategies of following electric loads and following thermal loads were used to optimize the operation cost. The results revealed that the annual total cost of the PIES presented a v-shaped cost curve with the power generation unit (PGU) capacity from 400 kW to 2000 kW. PIES-1, located in Dalian, had the lowest total cost of $0.71 million. The carbon dioxide emissions had the same trend. When the PGU's capacity reached the optimum (1000 kW), the PGU's utilization rate was between 50% and 60% in all scenarios. From Harbin to Haikou, the operation cost gap between PIES-1 and PIES-2 narrowed from $0.18 million to $0.01 million. Moreover, PIES-1, located in Harbin, had the lowest CO2 emissions.

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