Leveraging Socioeconomic Information and Deep Learning for Residential Load Pattern Prediction

Wen Jun Tang, Xian Long Lee, Hao Wang, Hong Tzer Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Advanced metering infrastructure systems record a high volume of residential load data, opening up an opportunity for utilities to understand consumer energy consumption behaviors. Existing studies have focused on load profiling and prediction, but neglected the role of socioeconomic characteristics of consumers in their energy consumption behaviors. In this paper, we develop a prediction model using deep neural networks to predict load patterns of consumers based on their socioeconomic information. We analyze load patterns using the K-means clustering method and use an entropy-based feature selection method to select the key socioeconomic characteristics that affect consumers' load patterns. Our prediction method with feature selection achieves a higher prediction accuracy compared with the benchmark schemes, e.g. 80% reduction in the prediction error.

Original languageEnglish
Title of host publicationProceedings of 2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538682180
DOIs
Publication statusPublished - 2019 Sep
Event2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019 - Bucharest, Romania
Duration: 2019 Sep 292019 Oct 2

Publication series

NameProceedings of 2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019

Conference

Conference2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019
CountryRomania
CityBucharest
Period19-09-2919-10-02

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Electrical and Electronic Engineering

Cite this

Tang, W. J., Lee, X. L., Wang, H., & Yang, H. T. (2019). Leveraging Socioeconomic Information and Deep Learning for Residential Load Pattern Prediction. In Proceedings of 2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019 [8905483] (Proceedings of 2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISGTEurope.2019.8905483