The Project

In order to reach decarbonisation targets of the European Commission, the European Union will need 451 GW of wind power capacity by 2030, up from 190 GW today. By 2050, wind power plants are projected to produce around 3500 TWh per year (2300 TWh onshore, 1200 TWh offshore) in Europe.

For reliable and affordable design and operation of WPPs that also consider system-level stability and security as well as the surrounding natural and social environment, coordinated wind farm control (WFC) and asset management solutions play an important role.

Additionally, given the urgency of growth implied by these ambitious targets, AI, and other digitalisation concepts are essential accelerators of the energy transition and key enablers for integrating the processes and prospects of WFC technology into the operation and design of the future energy systems.

Meanwhile, business-planning and decision-making by operators face higher volatility and risks in an interconnected energy grid, where geopolitics, wild market swings, changing regulatory regimes, social acceptance, environmental parameters, and climate change play an increasingly important role. For wind power plants with a lifetime of 20+ years, changes may occur at all levels of surrounding conditions for operation.

This includes meteorological and electricity/energy market conditions, grid development, changes in wildlife activities, regulation and policies (grid requirements, environmental, noise-related, etc.), new neighbouring, or supply chain disruptions. In such a complex context, the capability to account for alternative futures and the flexibility to actively change wind farm operation through wind farm control, accordingly, become crucial features for resilient and adaptive green energy production.

However, the existing tools lack the holistic approach capturing all these processes to represent the interplay among the effects of the respective control actions. The current WFC architectures are not capable of assessing the integrated economic, social, and environmental implications of the control actions. Hence, we introduce TWAIN.

The final product of TWAIN is a decision support environment, which is a digital environment architected for multi-source data integration and optimised computing, which contains a set of toolboxes with the critical analytical steps to define and assess an effective and efficient WF operation. It is oriented to wind power asset management by WF owners/operators, considering as assets the WT and its components within a WF.

Specifically, TWAIN will be focused on:

Creating an open-source data management toolbox including containerised experimental and numerical data.

Establishing AI-driven WFC-oriented tools for multi-objective WFC by digitalising the existing models, building new ones and incorporating them into model ensembles.

Assessing the holistic socio-economic and environmental impact of WF operation modes, reinforced by experiments and experience in the field.

Developing a secure-by-design, open-source TWAIN integrated WF controller and decision support environment for wind power asset management.