In developing digital twins for power electronics converters and other power system components, selecting an appropriate representation type and level of abstraction is fundamental. The choice of representation should balance fidelity, computational cost, and objectives of the representation. Digital twins are generally given a single, specific representation task; however, various functions can be delegated to the digital twin to support, leaving room for ambiguity in the design of the digital twin. Digital twins can be designed with multi-domain and multi-functional capabilities, allowing them to adapt to diverse system domains and perform a variety of representation tasks. This approach allows the digital twin to be as specialized as the physical asset it serves. This study introduces a framework enabling the development of multi-domain, multi-functional digital twins, adaptable for use in various representation tasks. The framework utilizes a collection of digital images for an accurate depiction of different asset elements, ensuring a detailed yet unified digital twin. The framework is designed to analyze the assigned representation task and select the most suitable digital image for execution. Details on the development of the framework are provided and experimental results validate the effectiveness of the proposed framework.

Detailed design requirements and foundational assumptions for forecasting digital twins in the context of power systems are explored and used in real-time forecasting in this study. Experimental validation of the forecasting methodology is demonstrated via an electro-thermal digital twin of power distribution cables for onboard power systems. The digital twin has the capability to forecast the thermal profile of cables by utilizing sensor measurements from the physical twin. When the predicted temperature reaches specific thresholds, the digital twin informs a decision maker to proactively adjust the power flow within the system to prepare for and avoid upcoming thermal constraints in the cable. This adjustment ensures that the physical cable does not reach specific thermal constraints, thereby enhancing system reliability. This proactive management will be essential to ensuring mission-critical power demand and avoiding load shedding. The concept has been experimentally verified using a three-bus configuration. The developed digital twin is computationally efficient, forecasting only when necessary, and offering an adjustable forecasting time-frame to accommodate a variety of operational scenarios.