Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Digital Twin of Microgrid for Predictive Power Control to Building

Hao Jiang
,
Rudy Tjandra
,
Chew Beng Soh
* ORCID logo ,
Shuyu Cao
ORCID logo ,
Donny Cheng Lock Soh
,
Kuan Tak Tan
ORCID logo ,
King Jet Tseng
ORCID logo ,
Sivaneasan B. Krishnan
ORCID logo
Version 1 : Received: 5 December 2023 / Approved: 6 December 2023 / Online: 6 December 2023 (05:43:41 CET)

A peer-reviewed article of this Preprint also exists.

Jiang, H.; Tjandra, R.; Soh, C.B.; Cao, S.; Soh, D.C.L.; Tan, K.T.; Tseng, K.J.; Krishnan, S.B. Digital Twin of Microgrid for Predictive Power Control to Buildings. Sustainability 2024, 16, 482. Jiang, H.; Tjandra, R.; Soh, C.B.; Cao, S.; Soh, D.C.L.; Tan, K.T.; Tseng, K.J.; Krishnan, S.B. Digital Twin of Microgrid for Predictive Power Control to Buildings. Sustainability 2024, 16, 482.

Abstract

The increased focus on sustainability in response to climate changes has given rise to many new initiatives to meet the rise in building load demand. The concept of distributed energy resources (DER) and optimal control of supply to meet power demands in buildings have resulted in growing interest to adopt microgrids for a precinct or a university campus. In this paper, a model for an actual physical microgrid has been constructed in OPAL-RT for real-time simulation studies. The load demands for SIT@NYP campus and its weather data are collected to serve as input to run on the digital twin model of DERs of the microgrid. The dynamic response of the microgrid model in response to fluctuations in power generation due to intermittent solar PV generation and load demands are examined via real-time simulation studies and compared with the response of the physical assets. It is observed that the simulation results match closely to the performance of the actual physical asset. As such, the developed microgrid model offers plug-and-play capability which will allow power providers to better plan for on-site deployment of renewable energy sources and energy storage to match the expected building energy demand.

Keywords

Matlab/Simulink; load demands; microgrid; DER, OPAL-RT; digital twin; energy optimization; Gurobi; sustainable building

Subject

Engineering, Energy and Fuel Technology

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Download PDF

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Metrics 0
Get PDF Cite Share 0
Bookmark BibSonomy Mendeley Reddit Delicious
×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.