Review of Digital Twins–enabled applications for demand response

Authors:
Publisher website
Google Scholar
Abstract
Digital Twins (DT), as one of the emerging trends in digitalisation, have attracted a large amount of research in the past few years due to its ability to provide more accurate models and better predictions for various energy-related applications. In the context of demand response (DR), the real-time bidirectional communication characteristic of DT allows for functions such as real-time energy forecast and decision-making aid, which provided high potential in DR applications due to the nature of DR being highly time-sensitive. The objective of this paper is to explore the concept and application of DT in the domain of DR, as there are currently limited numbers of review on this topic. It was identified that most work in this area shows promising results but is still exploratory. The main application of DT in the domain of DR is using DT as an enabling tool by leveraging the real-time and data processing function of DT for monitoring and decision-making, and providing a medium for better visualisation. Future studies can experiment with applying DT frameworks to larger case studies and apply more elaborate DT with higher maturity levels.

This publication has 29 references indexed in Scilit: