We introduce a novel framework to approximate the aggregate frequency dynamics of coherent generators. By leveraging recent results on concentration tightly connected networks, and weighted balanced truncation, hierarchy reduced-order models is developed. This provides increasing accuracy in approximation system response, outperforming existing aggregation techniques.

Abstract The concept of “hybrid twin” (HT) has recently received a growing interest thanks to the availability powerful machine learning techniques. This twin combines physics-based models within model order reduction framework—to obtain real-time feedback rates—and data science. Thus, main idea HT is develop on-the-fly data-driven correct possible deviations between measurements and prediction...

Within model-based approaches to structural health monitoring (SHM), numerical simulations must be tailored continuously adapt the degradation processes and possibly changing environment. This model update stage of analysis brings two competing requirements: accuracy model, with a more detailed description phenomena required where damage is supposed take place; efficiency reduce overall computa...