Online Model-based Functional Clustering and Functional Deep Learning for Load Forecasting Using Smart Meter Data

Shuang Dai, Fanlin Meng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Smart meter data analysis is essential for balancing energy consumption and minimizing power outages. However, high-resolution smart meter readings pose challenges to data analysis due to their high volume and dimensions. We propose Online-FDA, an online functional load demand analysis and forecasting framework that incorporates real-time smart meter readings with adaptive clustering to identify daily patterns in functional load consumption and predict daily load demands. This framework utilizes a model-based functional clustering approach assisted by the intra-day load consumption attributes to analyze real-time smart meter data. Moreover, the Online-FDA augments the clusters with a state-of-the-art functional deep neural network that utilizes the training-testing-updating strategy to adaptively learns from real-time smart meter data. Experimental results with real-world smart meter data showed that the proposed Online-FDA is superior to other benchmark algorithms for capturing time-varying variations in load demand, which are essential to the real-time control of electricity grids and the planning of power systems.

Original languageEnglish
Title of host publicationSEST 2022 - 5th International Conference on Smart Energy Systems and Technologies
PublisherIEEE
ISBN (Electronic)9781665405577
DOIs
Publication statusPublished - 2022
Event5th International Conference on Smart Energy Systems and Technologies, SEST 2022 - Eindhoven, Netherlands
Duration: 5 Sept 20227 Sept 2022

Publication series

NameSEST 2022 - 5th International Conference on Smart Energy Systems and Technologies

Conference

Conference5th International Conference on Smart Energy Systems and Technologies, SEST 2022
Country/TerritoryNetherlands
CityEindhoven
Period5/09/227/09/22

Keywords

  • functional clustering
  • Functional data analysis
  • functional deep learning
  • online load forecasting
  • smart meters

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