What are the challenges and limitations in using AI for modeling polygeneration digital twins?

One of the major challenges in using AI for modeling polygeneration digital twins is the complex nature of polygeneration systems. These systems involve the simultaneous production of multiple energy carriers, such as electricity, heat, and cooling, through various interconnected processes. Modeling such systems requires a deep understanding of the physical processes and their interactions, which can be difficult to capture accurately using AI algorithms. Additionally, data availability and quality pose limitations for AI modeling. Polygeneration systems often lack comprehensive and high-resolution data, leading to incomplete or biased models. Moreover, the dynamic nature of these systems, with varying operating conditions and changing demands, makes it challenging to develop AI models that can adapt and generalize accurately. Overall, while AI holds great potential for modeling polygeneration digital twins, addressing these challenges and limitations is critical for ensuring reliable and robust applications.

This mind map was published on 26 October 2023 and has been viewed 96 times.