Wind Farm Siting Challenge - Phase II

For Phase II the focus for the Wind Farm Siting Challenge has been placed on reviewing the available datasets and the underlying shared questions of the Checkpoint Projects.

  • Synergies between different monitoring, observation and data collection programmes
  • Identification of how well the current data meets the needs of users
  • Identification of gaps
  • View of where new technologies will allow for improvements (quicker, more accurate)
  • Required temporal and/or spatial resolution of data products
  • Prioritising the creation of new data and improving the availability and usability of existing data.

With the challenges as tools to assess and clarify the questions listed above.

Confidence is one of the issue that is discussed. This has a two different aspects: one statistical and one broader, subjective on selected datasets and assumptions.

Statistical uncertainty or its reverse confidence and confidence limits can be calculated, and included in tables and if needs be as additional data layers in (interactive) maps. The main dataset that lends itself to this is the wind resource. Variance and other statistics can be calculated across the available years.

Possibly much the same can be applied to the bathymetry dataset, although that would imply the need to have access to the underlying datasets to assess variability in the measurements (e.g. in different locations within a ‘grid cell’).

A third and new datasets for which statistical measures of confidence could be useful would be waves. Copernicus has widened their catalogue and a wave data also covering (most of) the study area of the Wind Farm Siting Challenge is now available. However the current service release offers real time modelled wave data and in-situ observations.  For the purpose of this challenge a reprocessed product giving e.g. monthly means calculated across several would be more useful. Such product is included in the product roadmap for waves for a release in April 2018. Statistics on waves, significant heights, extremes etc. are useful when calculating the required strengths of engineered constructions such as foundations for fixed OWT and moorings as wells as bodies for floating OWT.

The fourth data layer where confidence could come in to play is the biodiversity, that renewable energy generation should not endanger (no more than fossil fuels, anyway). It is one of the ‘other uses’ that: ‘need to respect and work with many existing activities’. For pragmatic reasons a choice was made to base this on the MPA-dataset – which was already being collated for another challenge of the project. Confidence and questions around the MPA dataset may arise from the underlying datasets and selection and designation processes. Are the MPA themselves in the right location and of the right size? These questions are beyond the scope of the wind farm siting challenge, but to some extent are addressed within the MPA challenge. There an analysis on coherence of the MPA’s as a network is included.

Confidence also come to play with the activity data layers: Shipping and Fisheries. Are the available datasets sufficiently representing the actual activities within the area etc. To the best of our knowledge the selected datasets represent the best available data that covers the study area in a consistent manner. Smaller more localised but also more detailed datasets could be used instead, but would complicate the analysis and may not improve confidence as they different collection methods and processing methodologies introduce new problems as well.

For e.g. shipping lanes, cables, pipelines and oil+gas platforms – and to some extent MPAs- there is little uncertainty about the geographical datasets and conversely high confidence. The locations and boundaries are official and precise.

Marine Spatial Planning
MSP has been taken by the project team to be the main aim of the Wind Farm Siting Challenge. This is in line with the questions posed for the challenge in the tender document. As such the focus has been to find areas that are best suited for developing offshore wind farms while at the same time respecting the presence and needs of several other (competing) uses of the marine environment.

As such we have not attempted to gauge the cost of constructing the wind farms, the amount of kWh produced annually, nor what changes to design parameters such as hub height, blade length would make e.g. with respect to vertical wind profiles.

New and improved datasets
Since our initial assessment (Phase I) some of the datasets have been improved and a few new ones have come to our attention. These we will present and discuss, mainly to estimate what their impact would have been on a complete redo of the analysis.

Wind: Copernicus: The dataset has been updated and currently has data for more years, from 2012 to 2016 has been added according to the documentation. No other improvements.

Wind: A search was made for an alternative wind resource dataset and an annual mean wind speed dataset (at 10 m. height) was identified. The horizontal resolution is stated as 12 km for sea areas. So this could be an improvement over the global scatterometer based dataset available through Copernicus. However it is only available as a WMS, which although valuable for visualising do not allow (re-)use of data in other GIS. Contact data for the Norwegian Meteorological Institute is provided so more options can be available on request. Related datasets are available for ice concentration and wave height (significant) from the same source.

wind speed WMS Norwegian Meteorologish institutt
Figure 1: Zoomed view of annual mean wind speed from WMS by the Norwegian Meteorologish institutt served by GeoNorge as part of NorgesKart.

Waves: new from Copernicus

  • Can be used as engineering information. E.g. to avoid for OWE development areas with an extreme and thus costly wave climate.
  • By avoiding these areas for OWE development, they are also left available to development of wave energy as a renewable energy source. However wave energy may also be better off with not the most extreme wave locations, but with a fairly mild and predictable and harvestable wave resource.
  • Starting with the service release of April 2017, the available data includes real time in-situ observations and real time models. For the purpose of the Wind Farm Siting Challenge a reprocessed dataset e.g. a wave climatology with monthly means, extremes, etc. would be more suitable. In the product roadmap such information may become available as part of the release that is planned for April next year (2018).

Fisheries: JRC – MFA
The EU-JRC has reported an interesting development regarding the use of AIS to map fishing activity. The ‘Mapping Fishing Activitiy’ or MFA tool is presented within their EU Science Hub, more specifically as part of the BlueHub. A research article by Vespe et al. (2016) has been published as well. The WebGIS tool delivers the results as a WMS, as shown in Figure 2. An email address is offered, to contact for download access.

Bluehub webgis MFA results
Figure 2 BlueHub WebGIS showing the MFA results (blue colours, contrasting edge) and data coverage (red colours).

Vespe, M., Gibin, M., Alessandrini, A., Natale, F., Osio, G. C., Vespe, M., … Osio, G. C. (2016). Mapping EU fishing activities using ship tracking data Mapping EU fi shing activities using ship tracking data. Journal of Maps, 5647(April 2017). http://doi.org/10.1080/17445647.2016.1195299

Oil and Gas Platforms: EMODnet Human Activities portal
The Human Activities portal from EMODnet has seen considerable improvement over the last year. However as the study area for the Arctic Wind Farm Siting Challenge is mostly outside the focal area of the portal many datasets are not relevant. The Oil and Gas Platforms is an exception to this and it presently does cover the full set of Norwegian platforms in both the Norwegian and Barents Seas. It is now a viable alternative to the authoritative data available from the Norwegian Petroleum Directorate, as used in Phase I.

Bathymetry: EMODnet Bathymetry portal
The Bathymetry portal from EMODnet has updated data that is of some relevance to the Wind Farm Siting Challenge. The geographic cover has been widened so that the Norwegian and Barents Sea, including also the Murmans Rise in the Russian part. This dataset offers improved horizontal resolution 1/8 * 1/8 minutes, where the GEBCO2014 bathymetry used in Phase I has ½ * ½ minutes.

FINAL Assessment Wind Farm Challenge, Phase II

Despite the availability of a few of improved datasets, the project team felt that a complete re-analysis of this challenges was not warranted. The main dataset on wind resource is mostly unchanged and the outcome would be only a minor revision. The resources that are freed up, will be redirected towards the MPA challenge where further effort is needed. Similar comments on repeating the challenge were obtained from the Steering Group Meeting and the Expert Panel Meeting.

A report prepared by group of Norwegian authorities led by the Norwegian Water Resources and Energy Directorate “Havvind, Forslag til utredningsområder” (NVE, 2010) has been identified. The 15 areas that have been studied there, are roughly located in the same areas as our results. Though mostly closer to shore.

An on-going project that may provide helpful information for a.o. Windfarm Siting is NOVASARC, Nordic Project On Vulnerable Marine Ecosystems And Anthropogenic Activities In Arctic and Sub-Arctic Waters (http://novasarc.hafogvatn.is/ ). A suggestion for an interesting and different approach was received from one of the experts following the Svalbard Case Study Workshop (June 2017) for ConSite, a consensus-based siting tool aiming to make the process of siting a new development more democratic, verifiable and cost-effective (http://www.nina.no/consite).

NVE. (2010). Havvind, Forslag til utredningsområder. Oslo. Retrieved from https://www.regjeringen.no/globalassets/upload/oed/rapporter/havvind_ver02.pdf?id=2181946

Total hours spent on Phase II of the Wind Farm Siting Challenge: 16.