Smart Grid improves the electricity grid infrastructure by introducing new powerful communication system between consumer and supplier. Implementation of smart meters increases the availability of detail level of consumer electricity load profile data. To improve and efficient planning and development of this new power system, a primary challenge is to analyze the electricity consumption data. To analyze the energy consumption or achieve our objective we choose the best analytic process is data mining techniques including exploratory data analysis and preprocessing, frequent patterns mining and associations, classification/characterization,clustering and outlier deduction. In this paper, we use these techniques and apply on two different public available datasets. Explain and evaluate which techniques is use full for the better understanding of electricity load profile consumption data.

Households electricity consumption analysis with data mining techniques

BUCCELLA, CONCETTINA;CECATI, Carlo
2016-01-01

Abstract

Smart Grid improves the electricity grid infrastructure by introducing new powerful communication system between consumer and supplier. Implementation of smart meters increases the availability of detail level of consumer electricity load profile data. To improve and efficient planning and development of this new power system, a primary challenge is to analyze the electricity consumption data. To analyze the energy consumption or achieve our objective we choose the best analytic process is data mining techniques including exploratory data analysis and preprocessing, frequent patterns mining and associations, classification/characterization,clustering and outlier deduction. In this paper, we use these techniques and apply on two different public available datasets. Explain and evaluate which techniques is use full for the better understanding of electricity load profile consumption data.
9781509034741
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/111014
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