DNVGL.com

Vind 2019

Winterwinds 2016 event

Swedish wind power production is likely to double by 2030 and this event will discuss how this increase can be achieved in a smart and sustainable way, socially, ecologically and economically.

Proud to support
DNV GL is proud to be a exhibiting at Vind 2019 and will be located on stand 33.

Presenting expertise
DNV GL's experts will be sharing their knowledge and experience at this event:

Date/time: Wednesday 23rd October/13:45
Presenter: Jan Näs, Senior Engineer, Renewable Energy Analytics, DNV GL
Presenter title: Identification of sub-optimal performance using machine learning techniques
Presentation abstract: Understanding wind turbine performance status improves operations, maintenance and the assessment of future energy production. Until now the status labeling of historical SCADA data have been performed manually. What if machine learning methods can be used for generalization of the model across wind farms with different manufacturing properties and geographical location?

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To pre-book a meeting or for any further information, please contact us.

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Chris Gowen
Chris Gowen

Marketing Communication Advisor - UK, Ireland, Scandinavia, Africa and Middle East

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Où :

Stockholm, Sweden

Münchenbryggeriet

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Quand :

23 octobre - 24 octobre 2019

Add to calendar 2019/10/23 09:00 2019/10/24 16:30 Vind 2019 Swedish wind power production is likely to double by 2030 and this event will discuss how this increase can be achieved in a smart and sustainable way, socially, ecologically and economically.
https://www.dnvgl.fr/events/vind-2019-156915
This only adds the event to your calendar, please remember to register for this event.
Münchenbryggeriet false YYYY/MM/DD akeGphYOczrmtQTfhmEQ22349

Site Internet :

https://windsweden.com/

Proud to support
DNV GL is proud to be a exhibiting at Vind 2019 and will be located on stand 33.

Presenting expertise
DNV GL's experts will be sharing their knowledge and experience at this event:

Date/time: Wednesday 23rd October/13:45
Presenter: Jan Näs, Senior Engineer, Renewable Energy Analytics, DNV GL
Presenter title: Identification of sub-optimal performance using machine learning techniques
Presentation abstract: Understanding wind turbine performance status improves operations, maintenance and the assessment of future energy production. Until now the status labeling of historical SCADA data have been performed manually. What if machine learning methods can be used for generalization of the model across wind farms with different manufacturing properties and geographical location?

Pre-book meetings
To pre-book a meeting or for any further information, please contact us.