VALÈNCIA, 29 Oct. — Ceteck, a Valencian company, has partnered with CEU Cardenal Herrera University to develop an AI-based digital twin for cogeneration plants. This innovation allows for improved predictions of energy export capabilities over the following week.
The digital twin integrates production efficiency data from gas and steam turbines with variables such as the plant's energy consumption and external temperature, which significantly impacts the efficiency of sustainable energy production.
Ernesto Bedrina, founder of Ceteck, stated, "We wanted to advance our technology by leveraging research in AI for more accurate predictions. This collaboration has enhanced our digital twin's predictive efficacy, increasing its market value in the energy sector."
To accurately assess the energy output of cogeneration plants, predictions must consider both turbine generation and the plant's energy consumption. Additionally, external temperature plays a crucial role, prompting the inclusion of a proprietary atmospheric installation to improve temperature forecasting.
Juan Pardo Albiach, lead researcher at CEU UCH's ESAI group, emphasized the necessity of machine learning models to analyze vast data volumes for precise energy production predictions. These models must also clarify which variables most influence energy production and plant efficiency.
This collaboration builds on a previous project from 2022 that utilized a digital twin for predictive maintenance of machinery, helping to prevent emergency shutdowns in production. Ceteck specializes in Industry 4.0 software and services aimed at optimizing industrial processes and enhancing environmental sustainability.