Digital Twin for HVAC Load and Energy Storage based on a Hybrid ML Model with CTA-2045 Controls Capability

Rosemary E. Alden, Evan S. Jones, Steven B. Poore, Huangjie Gong, Abdullah Al Hadi, Dan M. Ionel

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

4 Scopus citations

Abstract

Building modeling, specifically heating, ventilation, and air conditioning (HVAC) load and equivalent energy storage calculations, represent a key focus for decarbonization of buildings and smart grid controls. Widely used white box models, due to their complexity, are too computationally intensive to be employed in high resolution distributed energy resources (DER) platforms without simulation time delays. In this paper, an ultra-fast one-minute resolution Hybrid Machine Learning Model (HMLM) is proposed as part of a novel procedure to replicate white box models as an alternative to wide spread experimental big data collection. Synthetic output data from experimentally calibrated EnergyPlus models for three existing smart homes managed by the Tennessee Valley Authority is used. The HMLM employs combined k-means clustering and multiple linear regression (MLR) models to predict minutely HVAC power with satisfactory nRMSE error of less than 10% across an entire year test set. An approach is provided to characterize HVAC systems through the newly proposed hybrid model as a generalized storage (GES) device suitable for DER control and event types in accordance with the Communication Technology Association (CTA) 2045 standard and Energy Star metrics such as “energy take”, currently developed by industry, to unify household appliance controls.

Original languageEnglish
Title of host publication2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
ISBN (Electronic)9781728193878
DOIs
StatePublished - 2022
Event2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022 - Detroit, United States
Duration: Oct 9 2022Oct 13 2022

Publication series

Name2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022

Conference

Conference2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022
Country/TerritoryUnited States
CityDetroit
Period10/9/2210/13/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

  • ANSI/CTA-2045-B
  • Battery Energy Storage System (BESS)
  • Demand Response (DR)
  • Energy Star
  • Energy Storage
  • Energy Take
  • Heating Ventilation and Air Conditioning (HVAC)
  • Home Energy Management (HEM)
  • machine learning
  • smart grid
  • smart homes

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Safety, Risk, Reliability and Quality
  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment
  • Control and Optimization

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