Universal, open-source and cybersecure Digital Twin to provide investors in onshore wind farms valuable insights about current operations and future investments.

TWINVEST intends to create the foundations of a universal, open-source and cybersecure Digital Twin to provide investors in onshore wind farms valuable insights about current operations and future investments.

Guide investment decisions in wind energy is a complex as it involves various factors to monitor or assess such as energy production, maintenance, investment framework and characteristics of the wind farm.

In order to tackle those different factors, a team of 14 partners have united to create a Digital Twin that seamlessly integrates and considers all these factors.

This Digital Twin will have different platforms: i) Framework investment conditions platform focuses on energy storage, energy demand and pricing dynamics, regulatory mechanisms, and the essential grid requisites for ancillary services; ii) Component to Farm platform, focused on different components used for the turbines nominal energy production CAPEX estimation of the investment; iii)Environment and Earth platform’s objective is to assess the impact of weather and wind dynamics, culminating in the provision of real-time energy production projections; and iv) Maintenance and risks platform aiming to optimize OPEX by leveraging predictive methodologies to anticipate potential system failures.The project duration will be 42 months and it will be structured in 3 stages: Stage 1: Platform and model development where the research partners will develop, train and explore different AI models that allows the investor to forecast and monitor essential factors in a wind farm Stage 2 (M6-M42): Digital Twin Integration, where the different mentioned platforms will be integrated ensuring the interoperability among all models; and Stage 3 (M25-M42): Individual Platforms and Digital Twin validation, where the TWINVEST Digital Twin will be validated with real wind energy farms from the industry and will be used to conduct feasibility studies on investment plans coming from industry to show its capabilities.