Turbit Receives IBB Pro FIT Grant for Turbit Assistant Development

Turbit Systems GmbH has been awarded funding through the Investitionsbank Berlin's Pro FIT program for the research and development of "Copilot" (Turbit Assistant), an AI chat assistant designed for wind energy operators. The project focuses on developing AI-based algorithms that can analyze, process, and interpret various text-based and numerical data types from wind farm operations.

Research Project Overview

The Pro FIT-funded project, titled "Copilot - Entwicklung eines Chatassistenten für Betreiber von Windenergieanlagen" (Copilot - Development of a Chat Assistant for Wind Energy Operators), addresses the growing complexity of condition-based maintenance in wind farms due to massive data volumes generated by monitoring and maintenance activities.

Currently, there are no automated analyses available for documents in the wind energy sector. The project aims to develop AI models and systems that can correctly reproduce user queries through appropriate communication systems (text and speech), similar to a chat assistant, while being specifically trained on wind energy domain knowledge.

"We're grateful to Investitionsbank Berlin for recognizing the potential of this technology to advance the energy transition. This funding enables us to pursue relevant research that will fundamentally improve how wind farm operators interact with their data and make critical operational decisions." - Michael Tegtmeier, Turbit’s CEO

Technical Development Approach

Since the project's launch on July 1st, 2024, Turbit’s development team has made significant progress in implementing core AI technologies. Early versions of the Turbit Assistant are already being tested and utilized in operational environments, providing valuable real-world validation of the research approach.

Turbit Assistant utilizes several advanced technologies working in concert:

Natural Language Understanding (NLU) enables operators to communicate with the system using everyday language, asking questions about their wind farm operations in the same way they would consult a technical expert.

Retrieval Augmented Generation (RAG) with Large Language Models allows the system to access and synthesize information from vast databases of wind farm documentation, combining general AI capabilities with specific industry knowledge.

Vector Database Architecture stores all wind park information as homogeneous wind turbine data, making it possible to query across different data types and sources seamlessly.

Multi-Data Processing capabilities handle numerical machine data, text documents, and image data, providing comprehensive analysis rather than siloed insights.

The initial research phase focuses on developing capabilities for specific text-based data types, particularly oil condition reports and analyses. Following project completion, additional text-based data including maintenance protocols and operational reports will be integrated through experimental development.

Addressing Industry Challenges

The project targets a critical issue in modern wind energy operations: wind turbines are subject to extreme environmental conditions, leading to significant irregular operational loads. Larger modern turbines (6+ MW) experience greater stresses and lead to higher component failure rates and complex degradation processes that are not fully covered by Original Equipment Manufacturer (OEM) full-service contracts.

The Turbit Assistant technology aims to bridge the gap between users, technicians, or operators and the vast amounts of data, reports, and maintenance protocols from individual wind turbines and wind farms.

Research Methodology

The development process includes comprehensive research activities:

• Dialog management studies to ensure effective communication for operations teams, service teams, and insurance companies

• User Interface/User Experience design for intuitive operator interaction

• Real-time data testing and validation with actual operational data

• Continuous user feedback collection to optimize system performance

• Safety-critical query protocols for high-stakes operational scenarios

Industry Impact and Innovation

The research aims to create new operational standards in wind energy by providing expert-level insights with the quality of specialized technical operations management. This democratization of knowledge makes specialized wind energy expertise accessible regardless of users' technical backgrounds, helping to resolve conflicts of interest and inefficiencies between OEMs and operators.

As the wind energy industry continues scaling toward 100% renewable energy goals, tools like Turbit Assistant become essential infrastructure. The ability to quickly interpret complex operational data, identify potential issues before they become critical, and optimize maintenance strategies based on comprehensive data analysis will be fundamental to achieving reliable, cost-effective wind energy operations.

About the Project Partners

Turbit Systems GmbH provides AI-driven monitoring solutions for the wind energy industry. The company has established strategic partnerships with VSB Gruppe, EnergieKontor AG, AREAM Group SE, and SAB WindTeam GmbH.

About Pro FIT: The Pro FIT program by Investitionsbank Berlin supports innovative research and development projects that strengthen Berlin's position as a technology and innovation hub.