Abstract
The electricity market has been significantly changing in the last decade. The deployment of smart meters is enabling the logging of huge amounts of data relating to the operations of utilities with the potential of being translated into knowledge on consumers and enable personalized energy efficiency programs. This paper proposes an approach for mining characteristics of a residential consumers (income, education and having children) from high-resolution smart meter data using transparent fuzzy models. The system consists in: (1) extraction of comprehensive consumption features from smart meter data, (2) use of fuzzy models in order to estimate the characteristics of consumers, and (3) knowledge extraction from the fuzzy models rules. Accurate estimates of consumer income and education level were not achieved (60 % accuracy), for the presence of children accuracies of over 70 % were achieved. Performance is comparable to the state of the art with the addition of model interpretability and transparency.
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Acknowledgments
This work was supported by FCT through IDMEC, under Project SusCity: Urban data driven models for creative and resourceful urban transitions, MITP-TB/CS/0026/2013. The work of J.L. Viegas was supported by the PhD in Industry Scholarship SFRH/BDE/95414/2013 from FCT and Novabase. S.M. Vieira acknowledges support by Program Investigador FCT (IF/00833/2014) from FCT, co-funded by the European Social Fund (ESF) through the Operational Program Human Potential (POPH). Acknowledgement to FCT, through IDMEC, under LAETA, project UID/EMS/50022/2013.
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Viegas, J.L., Vieira, S.M., Sousa, J.M.C. (2016). Mining Consumer Characteristics from Smart Metering Data through Fuzzy Modelling. In: Carvalho, J., Lesot, MJ., Kaymak, U., Vieira, S., Bouchon-Meunier, B., Yager, R. (eds) Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2016. Communications in Computer and Information Science, vol 610. Springer, Cham. https://doi.org/10.1007/978-3-319-40596-4_47
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DOI: https://doi.org/10.1007/978-3-319-40596-4_47
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