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Multi-agent simulation of the time-of-use pricing policy in an urban natural gas pipeline network: A case study of Zhengzhou

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  • Li, Lanlan
  • Gong, Chengzhu
  • Wang, Deyun
  • Zhu, Kejun

Abstract

This paper establishes a multi-agent system comprising a government agent, a gas operator agent, and an industrial and commercial users agent. The system simulates the dynamic change process of demands and running states in an UGPN (urban gas pipeline network) and explores the optimal TOU (time-of-use) natural gas price to minimize the peak–valley load difference. The government agent plays a monitoring role of providing the upper and lower limits of natural gas price. The gas operator dynamically sets natural gas price based on user response, within the bounds established by a government authority. Then, the industrial and commercial users modify their consumption according to the price provided by the gas operator. This study considers the case of Zhengzhou, China to simulate the hourly gas-usage behavior of industrial and commercial users under the TOU pricing policy. The results indicate the existence of an optimal peak–valley price difference through which both the gas operator and users can gain benefits. Further, rising peak price also increases the benefits of the end-users, while those of the gas operator decrease; however, at some threshold value, the gas operator benefits from further increases in the peak price.

Suggested Citation

  • Li, Lanlan & Gong, Chengzhu & Wang, Deyun & Zhu, Kejun, 2013. "Multi-agent simulation of the time-of-use pricing policy in an urban natural gas pipeline network: A case study of Zhengzhou," Energy, Elsevier, vol. 52(C), pages 37-43.
  • Handle: RePEc:eee:energy:v:52:y:2013:i:c:p:37-43
    DOI: 10.1016/j.energy.2013.02.002
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    Cited by:

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    4. He, Yongxiu & Liu, Yangyang & Wang, Jianhui & Xia, Tian & Zhao, Yushan, 2014. "Low-carbon-oriented dynamic optimization of residential energy pricing in China," Energy, Elsevier, vol. 66(C), pages 610-623.
    5. Jian Chai & Liqiao Wang, 2020. "Analysis and Design of Interruptible Gas Contract in China under Energy Market Reform," Sustainability, MDPI, vol. 12(2), pages 1-15, January.
    6. Gong, Chengzhu & Tang, Kai & Zhu, Kejun & Hailu, Atakelty, 2016. "An optimal time-of-use pricing for urban gas: A study with a multi-agent evolutionary game-theoretic perspective," Applied Energy, Elsevier, vol. 163(C), pages 283-294.
    7. Li, Lanlan & Gong, Chengzhu & Tian, Shizhong & Jiao, Jianling, 2016. "The peak-shaving efficiency analysis of natural gas time-of-use pricing for residential consumers: Evidence from multi-agent simulation," Energy, Elsevier, vol. 96(C), pages 48-58.
    8. Lin, Boqiang & Chen, Xing, 2018. "Is the implementation of the Increasing Block Electricity Prices policy really effective?--- Evidence based on the analysis of synthetic control method," Energy, Elsevier, vol. 163(C), pages 734-750.

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