IFS and Dezineforce participate on All Energy 2009 Conference and Exhibition - May 2009
Great demand for renewable sources of electric energy exist, where wind power is (one of) the largest contributors. Power output from a wind farm depends on wind availability (intermittency in strength and wind direction) and local topology. Beside that the installation of wind farm(s) is capital intensive. In such environment, accurate prediction of wind farm power output is crucial for planning installation capacity and to provide return on the investment.
Intelligent Fluid Solutions developed a CFD based modelling methodology that is able to predict wind farm power output for different wind and topology conditions, and wind farm configurations. Blade element model was implemented in a commercial CFD package to simulate operation of wind turbines in a wind farm environment. Using statistical algorithms provided by Dezineforce, an optimal wind farm configuration can be determined. Present work shows a case study for a representative on-shore wind farm, where the developed methodology was used to find an optimal wind farm arrangement, which gives maximum power output for given investment costs.
To find maximum power output for given investment costs, Computational Fluid Dynamics (CFD) calculations of the different wind farm arrangements were performed and total power calculated as a sum of power output from each turbine. The investment costs were divided into fixed costs (construction, grid connection, development etc.) and variable costs (proportional to the number of installed turbines)
For a set area and staggered layout, the number of turbines in each row (ny) and the number of rows (nx) were varied. Advanced design search and optimisation techniques were used to search for an optimal wind farm configuration. This approach cost effectively assessed the range of design options available. Additional variables can be considered, e.g. wind speed, direction, geographical site etc.
The analysis shows that the same number of turbines in different layouts can result in significantly different yield. With alternate offset rows, wide, shallow wind farms are most profitable. The use of computational simulation methods and advanced optimisation tools can result in significant performance improvements. In future, we would like to analyse
- different wind angles and speeds for full wind rose
- alternative staggering
- assessment of specific geographical topologies
- allowance for local geographical features
- more complex investment models
