Study and Grouping of Suburban Consumers Energy Behavioural Demand Using Smart Meter Information

Authors

  • Sathyanarayanan. P  Assistant Professor, Department of EEE, Narasu's Sarathy Institute of Technology, Tamil Nadu, India
  • Jayapiriya. A  Student, Department of EEE, Narasu's Sarathy Institute of Technology, Tamil Nadu, India
  • Nanthini. K  Student, Department of EEE, Narasu's Sarathy Institute of Technology, Tamil Nadu, India
  • Revathi  Student, Department of EEE, Narasu's Sarathy Institute of Technology, Tamil Nadu, India
  • Gowri V  Student, Department of EEE, Narasu's Sarathy Institute of Technology, Tamil Nadu, India

Keywords:

Data Mining; Users’ Behaviors; Smart Metering; Smart Home; Energy Usage Patterns

Abstract

The main goal of this research is to discover the structure of home appliances usage patterns, hence providing more intelligence in smart metering systems by taking into account the usage of selected home appliances and the time of their usage. In particular, we present and apply a set of unsupervised machine learning techniques to reveal specific usage patterns observed at an individual household. The work delivers the solutions applicable in smart metring systems that might: (1) contribute to higher energy awareness; (2) support accurate usage forecasting; and (3) provide the input for demand response systems in homes with timely energy saving recommendations for users. The results provided in this paper show that determining household characteristics from smart meter data is feasible and allows for quickly grasping general trends in data.

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International Journal of Scientific Research in Science and Technology

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Published

2021-04-10

Issue

Volume 9, Issue 1, March-April-2021

Section

Research Articles

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Copyright (c) IJSRST

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Sathyanarayanan. P, Jayapiriya. A, Nanthini. K, Revathi, Gowri V, " Study and Grouping of Suburban Consumers Energy Behavioural Demand Using Smart Meter Information , International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 9, Issue 1, pp.1009-1016, March-April-2021.