Digital Twins for Designing Energy Management Systems for Microgrids: Implementation Example Based on TalTech Campulse Project

Innovative solutions are required to sustain the balance between energy generation and demand to achieve the desired efficiency in the power system and microgrid. With the recent advances in information and communication technologies that provide energy solution services based on big data analytics, machine learning (ML), and IoT technologies, the concept of digital twins (DT) has been introduced as a constructible active model to improve the security and resiliency of the microgrid. The DT is a reliable and economic microgrid technology considering its advantages of virtual real-time simulation, physical-based control, and constant monitoring. Moreover, DTs can predict future performance, energy consumers' behaviour, and a complex system's maintenance. This paper introduces a comprehensive framework for adapting the DT into applying a microgrid that interacts with the control system to ensure its information security and proper operation. Unlike other DT frameworks in the literature, the proposed for the local energy community. The framework was tested on a distributed network system. The implementation test concluded that the TalTech DT system is applicable for developing and validating power system applications.