TY - GEN
T1 - Energy Yield Prediction of Offshore Wind Farm Clusters at the EERA-DTOC European Project
AU - Cantero, E.
AU - Hasager, Charlotte Bay
AU - Réthoré, Pierre-Elouan
AU - Peña, Alfredo
AU - Hansen, Kasper Hjorth
AU - Badger, Jake
AU - Schepers, J.G.
AU - Faiella, L.M.
AU - Iuga, D.
AU - Giebel, Gregor
AU - Lozano, S.
AU - Sanz, J.
AU - Sieros, G.
AU - Stuart, P.
AU - Young, T.
AU - Palomares, A.
AU - Navarro, J.
N1 - Conference code: 11
PY - 2014
Y1 - 2014
N2 - A new integrated design tool for optimization of offshore wind farm clusters is under development in the European Energy Research Alliance – Design Tools for Offshore wind farm Cluster project (EERA DTOC). The project builds on already established design tools from the project partners and possibly third-party models. Wake models have been benchmarked on the Horns Rev and, currently, on the Lilgrund wind farm test cases. Dedicated experiments from ‘BARD Offshore 1’ wind farm will using scanning lidars will produce new data for the validation of wake models. Furthermore, the project includes power plant interconnection and energy yield models all interrelated with a simplified cost model for the evaluation of layout scenarios. The overall aim is to produce an efficient, easy to use and flexible tool - to facilitate the optimised design of individual and clusters of offshore wind farms. A demonstration phase at the end of the project will assess the value of the integrated design tool with the help of potential end-users from industry.This abstracts summarizes the objectives and preliminary results of work package 3. In order to provide an accurate value of the expected net energy yield, the offshore wind resource assessment process has been reviewed as well as the sources of uncertainty associated to each step. Methodologies for the assessment of offshore gross annual energy production are analyzed based on the Fino 1 test case. Measured data and virtual data from Numerical Weather Prediction models have been used to calculate long term wind speed, wind profile and gross energy.
AB - A new integrated design tool for optimization of offshore wind farm clusters is under development in the European Energy Research Alliance – Design Tools for Offshore wind farm Cluster project (EERA DTOC). The project builds on already established design tools from the project partners and possibly third-party models. Wake models have been benchmarked on the Horns Rev and, currently, on the Lilgrund wind farm test cases. Dedicated experiments from ‘BARD Offshore 1’ wind farm will using scanning lidars will produce new data for the validation of wake models. Furthermore, the project includes power plant interconnection and energy yield models all interrelated with a simplified cost model for the evaluation of layout scenarios. The overall aim is to produce an efficient, easy to use and flexible tool - to facilitate the optimised design of individual and clusters of offshore wind farms. A demonstration phase at the end of the project will assess the value of the integrated design tool with the help of potential end-users from industry.This abstracts summarizes the objectives and preliminary results of work package 3. In order to provide an accurate value of the expected net energy yield, the offshore wind resource assessment process has been reviewed as well as the sources of uncertainty associated to each step. Methodologies for the assessment of offshore gross annual energy production are analyzed based on the Fino 1 test case. Measured data and virtual data from Numerical Weather Prediction models have been used to calculate long term wind speed, wind profile and gross energy.
KW - DTOC European project
KW - Offshore wind resource
KW - Energy yield prediction
KW - Wind resource assessment
KW - uncertainties;
U2 - 10.1016/j.egypro.2014.07.241
DO - 10.1016/j.egypro.2014.07.241
M3 - Conference article
SN - 1876-6102
VL - 53
SP - 324
EP - 341
JO - Energy Procedia
JF - Energy Procedia
T2 - EERA DeepWind 2014 - 11th Deep Sea Offshore Wind R&D Conference
Y2 - 22 January 2014 through 24 January 2014
ER -