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Privacy-Preserving Distributed Clustering for Electrical Load Profiling
[article]
2020
arXiv
pre-print
Electrical load profiling supports retailers and distribution network operators in having a better understanding of the consumption behavior of consumers. However, traditional clustering methods for load profiling are centralized and require access to all the smart meter data, thus causing privacy issues for consumers and retailers. To tackle this issue, we propose a privacy-preserving distributed clustering framework for load profiling by developing a privacy-preserving accelerated average
arXiv:2002.12769v1
fatcat:34yr53nrfvdylgfgn2ao5clpgy