DNVGL.com

Breadcrumbs

Winterwind 2019

A conference that focuses on the challenges of generating wind power in cold climates. Winterwind offers seminars, debates, poster exhibition, networking, social events and technical visits. Parallel with the conference there is a fair.

Contact us:

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

For more information about this event

Contact us
SHARE:
PRINT:
Winterwinds 2016 event

Event Information

  • Where:

    Umeå, Sweden

  • Venue:

    P5, Storgatan 46 A, 903 26

  • When:
    04 February - 06 February 2019
    Add to calendar 2019/02/04 09:00 2019/02/06 16:30 Winterwind 2019 A conference that focuses on the challenges of generating wind power in cold climates. Winterwind offers seminars, debates, poster exhibition, networking, social events and technical visits. Parallel with the conference there is a fair.
    https://www.dnvgl.com/events/winterwind-2019-131779
    This only adds the event to your calendar, please remember to register for this event.
    P5, Storgatan 46 A, 903 26 false YYYY/MM/DD akeGphYOczrmtQTfhmEQ22349
  • Website: http://winterwind.se/

Proud to support
DNV GL is proud to be a KiloWatt sponsor at Winterwind 2019.

We will be located on stand 13.

DNV GL Experts
Our experts will be sharing their expertise during the event:

Presentation:Improving short-term forecasting of turbine icing using machine learning
Presenter: Stefan Söderberg 
Date/time: Tuesday 5 February 2019/13:00
Abstract: DNV GL will present improvements to its icing forecasting model through machine learning and the use of liquid water content forecasts.

In 2015, DNV GL designed a model which estimates icing losses as part of a short-term wind energy forecast, using an ensemble of meteorological condition forecasts to predict the presence of icing conditions. The model uses an adapted Makonnen model to calculate ice load on turbine blades, and a power reduction model to make icing corrections to the forecast energy production. Analysis shows that while the adapted Makonnen model of ice accretion is very accurate, the ability to predict the onset of icing conditions is more challenging. A new model has been developed that takes advantage of the ability of machine learning classification models to find patterns in multivariate data sets, and introduces liquid water content into the ensemble of meteorological forecasts.

The original model was shown to improve forecast accuracy, reducing annual Mean Absolute Percentage Error (MAPE) by up to 1%, and reducing MAPE by up to 5% for icy months. In this new validation, the improved model has been benchmarked against the original using 2 years of SCADA data from 3 wind farms in Sweden. It shows significant improvement in the accuracy of short-term forecasting of turbine icing, and will provide a financial benefit to end-users of icing forecasts used within DNV GL’s wind power forecasting system. DNV GL has also carried out a “market value analysis”, showing the approximate increase in revenue that can be generated by trading the resulting forecasts on the Elspot day-ahead energy market.

Icing has been shown to cause significant power losses for wind turbines in cold climates, such as Scandinavia. Studies have shown that over the course of a year wind farms can lose up to 13% of power due to icing, with monthly losses up to 50%. Individual icing events can lead to full power loss for a wind farm for over a week at a time. Quantitative fore-warning of such events is therefore a necessary requirement in incorporating the generation from these wind farms on the grid system. DNV GL has been providing short-term wind power forecasting services since 2003 globally for TSOs, utilities and asset operators, and currently forecasting for over 50GW of total installed capacity. We have recognised that forecasting icing events accurately is crucial for both AO&M purposes and for energy trading in some regions, and therefore have continuously investigated methods to better capture these events.

Pre-book meetings
To pre-book a meeting or for any further information, please email contact.energy@dnvgl.com.