1. Description of Work (2011)

The service is entitled “generation of annual energy output (AEO) for decision-support in on-shore wind energy policy planning and private investment” .

Involved partners and contacts: the partner in charge of the development of the product and the service is 3E - Sophie Jacques (sophie.jacques(-at-)3e.eu and Nicolaz Guidon (nicolaz.guidon(-at-)3e.eu)

Prime-user: ESTIA, Lausanne, Switzerland.

 

Expectations of the prime-users:  In the process of building an on-shore wind farm, an accurate assessment of its annual energy output is very important at an early stage. This assessment will lead the decision making of users. Users need an easy-to-access and fast tool for studies for sitting, sizing and return-on-investment on wind farms, and local policies for energy planning and attraction of investors.

Objectives of the service: The service will generate AEO estimation/wind resource estimation for a wind farm project.

Area of interest: Belgium

Exploited GMES downstream services: CORINE Land Cover. They are exploiting the SRTM Digital Elevation Model, which does not belong to GMES. As soon as the TerraSAR DEM (GMES) is available, this will replace SRTM.

Innovation: Wind farm project developers as well as public administrations face the same problem that the data required in order to assess the technical and economical feasibility, impact, and requirements of a wind farm project are scattered across many sources and requires a lot of effort to be collected and processed. There is a strong demand for an integrated service that would offer first-line resource assessment estimation along with implanting constraints for both wind farm project developers and administrations or public authorities that will eventually evaluate the project. The proposed service will meet this demand. The service will use GMES Core Services data and other EO data for the estimation of the AEO for providing an easy and fast access to data sets. AEO is computed using local wind data and using users requirements (number and types of wind mills, length of the wind data time-series…), and other information such as orography, land-use, aerodynamic roughness length… Possibly, administrative constraints (such as distance to buildings, landscape constraints, etc…) or policies (regulation) can be integrated into the service. This capability of combining data of various natures that intervene in decision-making process is the second innovation. A third innovation is to allow the user to get the necessary data in one request and not multiple as currently.