Abstract
A novel co-simulation framework was developed and demonstrated through virtual power plant (VPP) simulations that include hundreds of unique building models randomly populated into a modified IEEE 123-bus feeder system. The framework employs ultra-fast models for heating, ventilation, and air-conditioning (HVAC) systems as well as building thermal envelopes that are satisfactorily accurate for both electric power and indoor temperature. The approach circumvents generic control time limits typically in conventional implementations by enabling occupant thermal comfort monitoring. The HVAC and building models contain parameters by which they are characterized as generalized energy storage (GES) systems based on Energy Star definitions. This enables their compatibility with the Consumer Technology Association (CTA) 2045 standard control commands and event types. Example CTA-2045 “shed” events are illustrated to exemplify this feature and to analyze power distribution system effects in terms of power flow and voltages.
| Original language | English |
|---|---|
| Title of host publication | 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022 |
| ISBN (Electronic) | 9781728193878 |
| DOIs | |
| State | Published - 2022 |
| Event | 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022 - Detroit, United States Duration: Oct 9 2022 → Oct 13 2022 |
Publication series
| Name | 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022 |
|---|
Conference
| Conference | 2022 IEEE Energy Conversion Congress and Exposition, ECCE 2022 |
|---|---|
| Country/Territory | United States |
| City | Detroit |
| Period | 10/9/22 → 10/13/22 |
Bibliographical note
Publisher Copyright:© 2022 IEEE.
Funding
The support of the Department of Energy (DOE) through the project DEEE0009021 led by the Electric Power Research Institute (EPRI) is gratefully acknowledged. The support received by Mr. Evan S. Jones through a Department of Education (DoEd) GAANN Fellowship and by Miss Rosemary E. Alden through an NSF Graduate Research Fellowship (NSF) under Grant No. 1839289 is also gratefully acknowledged. Any opinions, findings, and conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of DOE, DoEd, and NSF. ∗Huangjie Gong and Abdullah Al Hadi have been with the SPARK Lab at the University of Kentucky and are now with ABB Corporate Research Center, Raleigh, NC, USA and Enginuity Power Systems, Clinton Twp, MI, USA, respectively. The support of the Department of Energy (DOE) through the project DEEE0009021 led by the Electric Power Research Institute (EPRI) is gratefully acknowledged. The support received by Mr. Evan S. Jones through a Department of Education (DoEd) GAANN Fellowship and by Miss Rosemary E. Alden through an NSF Graduate Research Fellowship (NSF) under Grant No. 1839289 is also gratefully acknowledged. Any opinions, findings, and conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of DOE, DoEd, and NSF.
| Funders | Funder number |
|---|---|
| Enginuity Power Systems, Clinton Twp | |
| National Science Foundation (NSF) | 1839289 |
| Michigan State University-U.S. Department of Energy (MSU-DOE) Plant Research Laboratory | DEEE0009021 |
| U.S. Department of Education, OSERS | |
| Electric Power Research Institute |
Keywords
- Building Energy Model
- CTA-2045
- Generalized Energy Storage (GES)
- HVAC
- OpenDSS
- co-simulation
- machine learning
- power distribution system
- smart grid
- smart home
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
