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A fair grid connection cost-sharing model for electricity based on the random forest machine learning method

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  • Xie, Li
  • Kong, Chun

Abstract

Developing countries should clarify the dedicated grid connection cost-sharing model when reforming electricity user price policy, which could be learned from developed countries’ experiences. We use the random forest method and monthly data from several developed countries or regions, including the United States and the United Kingdom in 2018–2020, to identify key features that influence decision-makers in choosing dedicated grid connection cost-sharing models and simulate the connection cost-sharing models suitable for various regions of China using provincial data. It provides experience and enlightenment for China and other developing countries to implement the connection price policy reform.

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  • Xie, Li & Kong, Chun, 2024. "A fair grid connection cost-sharing model for electricity based on the random forest machine learning method," Utilities Policy, Elsevier, vol. 90(C).
    • Handle: RePEc:eee:juipol:v:90:y:2024:i:c:s0957178724001000
    DOI: 10.1016/j.jup.2024.101807
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