Emodnet-Arctic

Wind Farm Siting Challenge - Phase II

For Phase II the focus for the Wind Farm Siting Challenge is on reviewing the available datasets and the underlying shared questions of the Checkpoint Projects with the challenges as tools to assess and clarify the points below. It included the identification of:

  • synergies between different monitoring, observation and data collection programmes
  • how well the current data meets the needs of users
  • knowledge gaps
  • views where new technologies will allow for improvements (quicker, more accurate)
  • which temporal and/or spatial resolution of data products are required
  • prioritising the creation of new data and improving the availability and usability of existing data.


Confidence
Confidence in the information available is an important issue. This consists of two different aspects: one statistical and one broader, more subjective aspect with regards to selected datasets and assumptions.

Statistical confidence and confidence limits can be calculated, and included in tables and potentially as additional data layers in (interactive) maps. The wind resource dataset can be utilised in this way as variance and other statistics can be calculated across the available years.
While the bathymetry dataset could also be used in this way, it would require access to the underlying datasets to assess variability in the measurements (e.g. in different locations within a ‘grid cell’).

Statistical measures of confidence could also be applied to the data layer on waves. Copernicus has widened their catalogue so that wave data 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 a product is included in the product ‘Roadmap for Waves’ for a release in April 2018. Statistics on waves, significant heights, extremes etcetera 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 be included is biodiversity as a measure of the environmental intensity of use on which OWT should have minimal impact. For pragmatic reasons biodiversity was based on the MPA-dataset, which was already being collated for the SBC Arctic challenge on Marine Protected Areas in this project. The MPA dataset may show varying confidence levels and initiate questions about the underlying datasets and selection and designation processes. Are the MPA themselves in the right location? Are they of the right size? These questions are beyond the scope of the wind farm siting challenge, but to some extent addressed within the MPA challenge with an analysis on coherence of the MPAs as a network.

Confidence is also important in the activity data layers for shipping and fisheries. For example: how accurate are the available datasets in sufficiently representing the actual activities within the area? To the best of our knowledge the selected datasets represent the best available data that consistently covers the study area. Smaller, more localised but also more detailed datasets could be used, but these would complicate the analysis and may not improve confidence as they involve different collection and processing methodologies. For example, the locations and boundaries are official and precise for shipping lanes, cables, pipelines and oil and gas platforms, and to some extent MPAs. Therefore there is a high level of confidence for these activities.

Marine Spatial Planning
MSP is the main focus of the Wind Farm Siting Challenge according to 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) users of the marine environment.

Due to the scope of the project 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. We will present these new developments and discuss them, mainly to estimate what this would mean if the analysis was repeated.

Wind: Copernicus - the dataset has been updated and now has data for more years (2012 to 2016 have been added). No other developments.

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. This dataset could be an improvement on the global scatterometer based dataset available through Copernicus. However, it is only available as a WMS which, although valuable for visualising, does not allow (re-)use of data in other GIS operations. Contact data for the Norwegian Meteorological Institute is provided so more options may 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 for the potential 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 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 and a research article by Vespe et al. (2016) has also been published. 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. However, the Oil and Gas Platforms dataset available is relevant and it presently covers the full set of Norwegian platforms in both the Norwegian Sea and Barents Sea. 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, also including 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 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 made available, will be redirected towards the MPA challenge where further effort is needed. Similar advices on repeating the challenge were obtained from the Stakeholder Meeting and the Expert Panel Meeting.

A report prepared by a group of Norwegian authorities led by the Norwegian Water Resources and Energy Directorate “Havvind, Forslag til utredningsområder” (NVE, 2010) was 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 SBC Arctic workshop; the Svalbard case (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.