Leveraging Socioeconomic Information and Deep Learning for Residential Load Pattern Prediction

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

研究成果: Conference contribution

摘要

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.

原文English
主出版物標題Proceedings of 2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781538682180
DOIs
出版狀態Published - 2019 九月
事件2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019 - Bucharest, Romania
持續時間: 2019 九月 292019 十月 2

出版系列

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

Conference

Conference2019 IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2019
國家Romania
城市Bucharest
期間19-09-2919-10-02

    指紋

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

引用此

Tang, W. J., Lee, X. L., Wang, H., & Yang, H. T. (2019). Leveraging Socioeconomic Information and Deep Learning for Residential Load Pattern Prediction. 於 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