Adaptive Learning Based Building Load Prediction for Microgrid Economic Dispatch

Rumia Masburah, Rajib Lochan Jana, Ainuddin Khan, Shichao Xu, Shuyue Lan, Soumyajit Dey, Qi Zhu

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

Abstract

Given that building loads consume roughly 40% of the energy produced in developed countries, smart buildings with local renewable resources offer a viable alternative towards achieving a greener future. Building temperature control strategies typically employ detailed physical models which require a significant amount of time, information and finesse. Even then, due to unknown building parameters and related inaccuracies, future power demands by the building loads are difficult to estimate. This creates unique challenges in the domain of microgrid economic power dispatch for satisfying building power demands through efficient control and scheduling of renewable and non-renewable local resources in conjunction with supply from the main grid. In this work, we estimate the real-time uncertainties in building loads using Gaussian Process (GP) learning and establish the effectiveness of run time model correction in the context of microgrid economic dispatch.

Original languageEnglish (US)
Title of host publicationProceedings of the 2021 Design, Automation and Test in Europe, DATE 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages72-75
Number of pages4
ISBN (Electronic)9783981926354
DOIs
StatePublished - Feb 1 2021
Event2021 Design, Automation and Test in Europe Conference and Exhibition, DATE 2021 - Virtual, Online
Duration: Feb 1 2021Feb 5 2021

Publication series

NameProceedings -Design, Automation and Test in Europe, DATE
Volume2021-February
ISSN (Print)1530-1591

Conference

Conference2021 Design, Automation and Test in Europe Conference and Exhibition, DATE 2021
CityVirtual, Online
Period2/1/212/5/21

Keywords

  • Building thermal model
  • Deep Reinforcement Learning
  • Economic Dispatch
  • Gaussian Process Learning
  • Predictive Control

ASJC Scopus subject areas

  • Engineering(all)

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