Integrated, Value-based and Multi-objective wind farm control powered by Artificial Intelligence

For reliable and affordable design and operation of wind power plants 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 ambitious decarbonisation targets, artificial intelligence (AI) and other digitalisation concepts are major accelerators of the energy transition and a key enabler for integrating the processes and prospects of WFC technology into the operation and design of the future energy systems.

To support wind farm owners/operators to make better decisions for system-wide optimised performance, TWAIN’s concept pivots on a full-integration of WFC at five different levels: 1) integration of multi-source and multi-format data of varied nature from wind farms in different life stages; 2) AI-enabled integration of multi-disciplinary processes and phenomena affecting the wind farm operation; 3) integration of multi-objective prospects of WFC to assess the true added value of a certain operation mode; 4) integration of multi-level controllers and scenario analyses in decision support provision for harmonious co-existence of WPPs with their environment and society via optimised operation and design; and 5) integration of wider audience to TWAIN outcomes. TWAIN decision support environment 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 operate a wind farm effective and efficiently. It is oriented to wind power asset management by WF owners/operators, considering as asset the WT and its components within a WF.