Siemens is “teaching” wind turbines how to automatically optimize their operation in line with weather conditions.
The turbines are learning to use sensor data on parameters such as wind speed to make changes to their settings. These changes ensure the turbines can optimally exploit the prevailing conditions. Wind power facilities can’t always generate their maximum electrical output when wind speeds are moderate or low.
Specialists for learning systems at Siemens Corporate Technology (CT) developed the self-optimization software for wind turbines in cooperation with Technische Universität Berlin and IdaLab GmbH in the ALICE project (Autonomous Learning in Complex Environments), which is funded by Germany’s Ministry of Education and Research.
The researchers are presenting the results of their work at the CeBIT trade show (March 10–14) in Hanover. Their solution enables turbines to produce around one percent more electricity annually under moderate wind conditions, while also reducing wear and tear.
The researchers have a demonstration wind turbine unit that uses its own operating data and gradually increases its electrical output. The scientists’ approach combines reinforcement learning techniques with special neural networks.
A neural network is a software algorithm that operates in a way similar to the human brain. For several years now, Siemens CT has been developing neural networks in order to model and predict the behavior of highly complex systems, such as wind farms, gas turbines, factories, or even stock markets.
The software programs learn from historical data, which also enables them to forecast the future behavior of a system. A model can thus be created that predicts the electrical output of a wind turbine under specific weather conditions.
The researchers examined a large amount of very noisy data to identify relevant attributes that would enable the efficiency of a wind turbine to be improved by changing settings such as rotation speed. Patented neural networks were then used to create a so-called reinforcement learning policy from the analysis results.
The system thus learns to change certain wind turbine settings in a manner that ensures the maximum possible amount of electricity is generated in a given situation. After just a few weeks, the system is able to define and store the optimal settings for common weather occurrences.
After an additional extended period of training, it can even regulate electrical output under rare and exceptional weather conditions. The technology was successfully tested at a Spanish wind farm last year.
Ongoing analyses of relevant oper-ating parameters ensure the system can continually improve itself through repetition. The methods used here can be employed in many other fields, which means additional Siemens products can also be taught to optimize their own operation.
Dr. Norbert Aschenbrenner | Siemens InnovationNews
Philippines’ microsatellite captures best-in-class high-resolution images
22.09.2016 | Hokkaido University
OLED microdisplays in data glasses for improved human-machine interaction
22.09.2016 | Fraunhofer-Institut für Organische Elektronik, Elektronenstrahl- und Plasmatechnik FEP
The Fraunhofer Institute for Organic Electronics, Electron Beam and Plasma Technology FEP has been developing various applications for OLED microdisplays based on organic semiconductors. By integrating the capabilities of an image sensor directly into the microdisplay, eye movements can be recorded by the smart glasses and utilized for guidance and control functions, as one example. The new design will be debuted at Augmented World Expo Europe (AWE) in Berlin at Booth B25, October 18th – 19th.
“Augmented-reality” and “wearables” have become terms we encounter almost daily. Both can make daily life a little simpler and provide valuable assistance for...
With the help of artificial intelligence, chemists from the University of Basel in Switzerland have computed the characteristics of about two million crystals made up of four chemical elements. The researchers were able to identify 90 previously unknown thermodynamically stable crystals that can be regarded as new materials. They report on their findings in the scientific journal Physical Review Letters.
Elpasolite is a glassy, transparent, shiny and soft mineral with a cubic crystal structure. First discovered in El Paso County (Colorado, USA), it can also be...
For the first time, Fraunhofer IKTS shows additively manufactured hardmetal tools at WorldPM 2016 in Hamburg. Mechanical, chemical as well as a high heat resistance and extreme hardness are required from tools that are used in mechanical and automotive engineering or in plastics and building materials industry. Researchers at the Fraunhofer Institute for Ceramic Technologies and Systems IKTS in Dresden managed the production of complex hardmetal tools via 3D printing in a quality that are in no way inferior to conventionally produced high-performance tools.
Fraunhofer IKTS counts decades of proven expertise in the development of hardmetals. To date, reliable cutting, drilling, pressing and stamping tools made of...
At AKL’16, the International Laser Technology Congress held in May this year, interest in the topic of process control was greater than expected. Appropriately, the event was also used to launch the Industry Working Group for Process Control in Laser Material Processing. The group provides a forum for representatives from industry and research to initiate pre-competitive projects and discuss issues such as standards, potential cost savings and feasibility.
In the age of industry 4.0, laser technology is firmly established within manufacturing. A wide variety of laser techniques – from USP ablation and additive...
Every three years, the plastics industry gathers at K, the international trade fair for plastics and rubber in Düsseldorf. The Fraunhofer Institute for Laser Technology ILT will also be attending again and presenting many innovative technologies, such as for joining plastics and metals using ultrashort pulse lasers. From October 19 to 26, you can find the Fraunhofer ILT at the joint Fraunhofer booth SC01 in Hall 7.
K is the world’s largest trade fair for the plastics and rubber industry. As in previous years, the organizers are expecting 3,000 exhibitors and more than...
23.09.2016 | Event News
20.09.2016 | Event News
16.09.2016 | Event News
23.09.2016 | Life Sciences
23.09.2016 | Health and Medicine
23.09.2016 | Life Sciences