A novel machine learning approach for identifying the drivers of domestic electricity users' price responsiveness

Peiyang Guo (), Jacqueline CK Lam and Victor OK Li
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Peiyang Guo: Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong
Jacqueline CK Lam: Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong
Victor OK Li: Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong

No EPRG 1824, Working Papers from Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge

Keywords: Time-based electricity pricing; price responsiveness; high-potential users; variable selection; Time of Use; machine learning (search for similar items in EconPapers)
JEL-codes: C55 Q41 (search for similar items in EconPapers)
Date: 2018-08
New Economics Papers: this item is included in nep-big, nep-cmp, nep-ene and nep-reg
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