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Thursday, 13 March 2014
11:15 - 12:45 Forecasting: Maximizing grid deliverability and leading your business processes to profitability
Resource Assessment  

Room: Tramuntana
Session description

The growth of wind energy is increasingly impacting upon and limited by the grid infrastructure of many countries. Accurate short-term forecasting of wind power can help to maintain the growth of the sector. System operators are able to avoid many balancing issues if accurate production forecasts are available. Deviation charges of wind farm owners could be greatly reduced using new techniques. Accurate forecasts can also bring significant benefits when planning turbine maintenance, especially offshore.

Learning objectives

Delegates will learn about topics including:

  • Economic impact of forecast accuracy
  • Making wind a firm resource: the role of forecasting
  • Using forecasting models to schedule maintenance activities
  • Dealing with the real world: best practices for including extreme conditions into the forecast models
  • Forecasting challenges for 2014-2020, quick-to-market tools and R&D
Lead Session Chair:
Miguel Ezpeleta, Acciona Energia, Spain
Jeremy Parkes
DNV GL, , United Kingdom

Presenter's biography

Biographies are supplied directly by presenters at EWEA 2014 and are published here unedited

Jeremy Parkes has a Masters Degree in Aeronautical Engineering, and is a chartered engineer with the Royal Aeronautical Society. Before joining GL Garrad Hassan in 2003, he worked as a Senior Aerodynamicist for Rolls-Royce. At GL Garrad Hassan Jeremy worked as “Global Head of Forecasting”, where he was responsible for managing the company’s short term forecasting services. Now in the merged DNV GL Group Jeremy is Head of Asset Operation & Management for renewables projects, leading the technical development and coordination of DNV GL’s activities to help customers maximise the value of renewables.


As the penetration of wind energy continues to increase around the world, its potential impact on the efficient and effective management of electrical grids is becoming increasingly evident. The challenge for the grid operator to integrate wind energy, or for the energy trader to maximise the market value of the energy, relies not only on having accurate forecasts, but also on that information being presented and incorporated effectively into their systems.

This presentation focuses on how the information available from state-of-the-art forecasting models is adapted to business processes, in particular wind power trading. In addition to a central best estimate of wind production, further information, such as reliable probabilistic forecasts, ramp warnings and extreme weather alerts, allow the end user to make informed decisions about wind power trading or generation scheduling.

The presentation will touch on how the models are adapted to produce additional information and how this information is presented, as well as showing more details of the potential trading benefits of using highly accurate forecasts combined with forecast meta data. The importance of adapting forecasting models with appropriately processed and cleaned wind farm data is also highlighted.

The results are based on DNV GL’s forecasting services for both individual and portfolios of wind farms, in a range of countries around the world. The outcome of the investigation demonstrates that adapting forecast models to business processes helps traders maximise the value of wind power, which ultimately helps wind to be more effectively and efficiently integrated into the grid.