TY - JOUR
T1 - Investigation of offshore wind farm layouts regarding wake effects and cable topology
AU - Wade, Bryce
AU - Pereira, Ricardo
AU - Wade, Cameron
PY - 2019/5/21
Y1 - 2019/5/21
N2 - Offshore wind energy is emerging as a large contributor to installed renewable energy capacity. In order to continue the momentum of its development, the offshore wind industry is looking to continually lower the levelized cost of electricity (LCOE). One area being explored in an effort to lower the LCOE of offshore wind generation is the optimization of the wind farm layout. Many of the offshore wind farm layout designs that exist today are structured in a rectilinear form where turbines are spaced evenly along columns and rows. This research explores the economic advantages of removing rectilinear constraints and optimizing the positions of the individual turbines within an offshore wind farm. At the core of achieving the research objective was the development of a model that is capable of simulating an existing offshore wind farm by converting representative wind farm data into an LCOE. The positions of the turbines within the wind farm can be modified using an optimization framework with the intent to minimize the LCOE. The model comprised of the Jensen Wake Model, a hybrid cable layout heuristic and a cost scaling model. The wind farm layout was optimized using a genetic algorithm. The cost estimation model and optimization framework were applied into two case studies to analyze the results of the wind farm layout optimization of two wind farms, Horns Rev and Borssele. In both case studies the optimized layouts provided higher AEP, shorter intra-array collection cable lengths and ultimately a lower LCOE than the baseline rectilinear layouts.
AB - Offshore wind energy is emerging as a large contributor to installed renewable energy capacity. In order to continue the momentum of its development, the offshore wind industry is looking to continually lower the levelized cost of electricity (LCOE). One area being explored in an effort to lower the LCOE of offshore wind generation is the optimization of the wind farm layout. Many of the offshore wind farm layout designs that exist today are structured in a rectilinear form where turbines are spaced evenly along columns and rows. This research explores the economic advantages of removing rectilinear constraints and optimizing the positions of the individual turbines within an offshore wind farm. At the core of achieving the research objective was the development of a model that is capable of simulating an existing offshore wind farm by converting representative wind farm data into an LCOE. The positions of the turbines within the wind farm can be modified using an optimization framework with the intent to minimize the LCOE. The model comprised of the Jensen Wake Model, a hybrid cable layout heuristic and a cost scaling model. The wind farm layout was optimized using a genetic algorithm. The cost estimation model and optimization framework were applied into two case studies to analyze the results of the wind farm layout optimization of two wind farms, Horns Rev and Borssele. In both case studies the optimized layouts provided higher AEP, shorter intra-array collection cable lengths and ultimately a lower LCOE than the baseline rectilinear layouts.
UR - http://www.scopus.com/inward/record.url?scp=85066430471&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1222/1/012007
DO - 10.1088/1742-6596/1222/1/012007
M3 - Conference article
AN - SCOPUS:85066430471
SN - 1742-6588
VL - 1222
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012007
T2 - WindEurope Conference and Exhibition 2019
Y2 - 2 April 2019 through 4 April 2019
ER -