Windey is one of the earliest wind turbine manufacturers in China and a pioneer and innovator in China’s Chinese wind energy industry. With the mission of “Green power to human, blue sky to nature”, Windey is becoming a leader in the Chinese wind power industry, building a national wind power brand, and providing customers with high-quality products and technical services.
With global ambition, Windey European Wind Power Research Center was created at the heart of Bristol city in 2019. Windey is looking forward to building partnerships with local universities and research institutes to develop these technologies which will benefit the renewable energy industry and reduce the cost of wind power generation.
Our Story
Windey has been manufacturing and operating wind turbines for more than 20 years and has over 6000 turbines operating worldwide. Our turbine products range from 1.5 MW to 5 MW for various wind and terrain conditions. With our 20 years of design experience, we can provide customized production for challenging climate conditions such as typhoon, low wind speed, low temperature, high altitude and offshore, etc.
In 2019, Windey listed its Initial Public Offering of class A shares on the Shenzhen Stock Exchange. The capital raised from stock market helped Windey to strengthen its research and development and become a wind turbine owner and operator. Windey is extending its business from wind turbine manufacturing to wind farm operation and maintenance.
Bristol is one of the top technology hubs in the UK. Windey European wind power research center was founded here in 2019 to attract talent to develop state-of-the-art wind turbine technologies through innovation. We have expertise in software and the wind energy industry, so we are trying to bring technology from the software industry to make our wind turbines better, safer and smarter.
We are working on some exciting projects to reduce the cost of energy and make green energy affordable to everyone.
High performance computing
Modern turbines are getting bigger and smarter, so higher fidelity simulation models are required. This will increase the computation requirements significantly. To address this demand, we have built infrastructure for a distributed computing network to run hundreds of simulations in parallel to speed up the design iterations. The infrastructure is flexible and can be deployed on both private or public cloud infrastructure.
Advanced real-time analysis and fault detection
The potential data output from a wind turbine requires high-bandwidth comms and hardware to digest and analyze. By allowing each turbine to perform some of the heavyweight analysis itself, there is scope to reduce the required bandwidth and off-board processing requirements and server roundtrips, allowing the turbine controller to make direct use of its high frequency data, e.g. by implementing on-board digital signal.
Lidar assisted control
As it is widely used in self-driving cars, we use Lidar (Light Detection and Ranging) to improve the performance of our turbines. Compared to traditional close loop control, Lidar assisted control has visibility of the incoming wind speed. This enables engineers to build sophisticated algorithms in the controller to work out how the wind speed is evolving and let the turbine react in advance. This will allow turbines to be built bigger and lighter which can harvest more energy from the wind at a lower cost.
Digital Twin
At our research center, we use aeroelasticity simulations together with big data and AI to build a “digital twin” of a wind turbine which lives in the cloud. The digital twin platform gives us insight into our physical wind turbines and allows us to monitor and optimize their performance. Turbine fault data can be used to train machine learning models and the digital twin platform will be used to predict turbine faults in advance to reduce downtime and boost energy production.
Wind farm control
In a wind farm, upstream wind turbines extract energy from the wind flow so as to have a blocking effect on downstream turbines. Because of this blocking effect, turbines may not produce as much energy as anticipated. Instead of allowing each turbine to operate individually, a wind farm control algorithm can allow turbines to ‘talk to each other’ and adjust setpoints in a coordinated way to boost overall energy production of the wind farm.
