A Digital Twin framework in Microgrids including Renewable Generation and Energy Storage

Project Details


A Digital Twin (DT) is a virtual model designed to accurately reflect a physical object. The object being studied is outfitted with various sensors related to vital areas of functionality. These sensors continuously collect data from different aspects of the physical object, such as output energy, temperature, operating conditions, and so on. This data is then relayed to a processing system and applied to the digital copy in real-time. Due to the increased usage of the DT technique, it shows that it has significant potential for systems operation management. Having an accurate estimation of the current state of the system and its future behavior are the most important DT purposes to deliver essential information about the systems for operation management and degradation monitoring, which can be used to perform timely maintenance or adapt operational strategies to extend its service life. DT could be a new solution for MGs challenges. So, more investigation on the DT modeling in MGs is needed.
From the above demands, this Ph.D. project aims to design an advanced DT framework for MGs including renewable energy sources (RESs) and energy storage systems (ESSs). Mathematical models for RESs and ESSs will be developed, and MG DT will be designed using advanced artificial intelligence (AI) techniques. Several DT-based algorithms to improve operational management and predictive maintenance of RESs and ESSs in MGs will be proposed.

Funding: Self-funded
Effective start/end date01/08/202131/07/2024


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.