Wind Energy Prospecting
With global energy trends moving steadily towards sustainable solutions, developers are seeking new ways to effectively target potential wind farm sites. Wind prospecting using traditional tools often requires time-consuming preliminary field research in order to locate a suitable site. Our new advanced spatial modelling tools can provide a fresh perspective on these questions. Using sophisticated meso-scale wind speed modelling, advanced terrain analysis, and current land use knowledge, we undertake probabilistic analysis and intelligent spatial modelling of the wind energy potential in a country or region.
For our wind prospecting work to date, Kenex have collaborated with Aurecon, a leading global group of engineers and developers, and Emprendimientos Energeticos y Desarrollos S.A (EEDSA), a Buenos Aires based company of wind energy experts. Aurecon have provided Kenex with mesoscale wind speed data as well as technical expertise on wind farm terrain and design. Kenex expertise in spatial data analysis and modelling is used to apply this knowledge to predictive targeting for ideal wind farm sites in any kind of terrain and environment. The recent business partnership with EEDSA has enabled Kenex to adapt their wind prospecting system for the Latin American market requirements, leading the way to new and exciting projects in the region.
Our prospecting system uses spatial modelling techniques that combine wind speed and direction data, advanced terrain analysis, and land use variables to define the extent of potential wind farms at regional and country-wide scales. Our models can quickly and cost effectively target and rank new wind farm opportunities and define the potential extent of an individual wind farm. It allows for easy approximation of the number of turbines that the wind farm can hold, can be a guide for turbine and monitoring mast placement, and can be used to identify the land owners that need to be approached early on in the development process.
This is the most comprehensive spatial modelling method being used for wind energy prospecting.
Wind prospecting targets over the Manawatu Gorge, NZ. The model results are validated by existing turbines at wind farms on both sides of the gorge
We use Fuzzy Logic,a modelling method used to combine spatial data using expert knowledge. With this method predictive variables are weighted and statistically combined so that every variable has its relevant influence on the model output. This provides a much more integrated result than just overlaying variables from the initial data, i.e. the wind speed grid. The fuzzy logic technique requires the creation of classified grids (predictive maps) for each variable. Each grid class is weighted using a fuzzy membership function (a value between 0 and 1), which expresses the degree of importance of the various map layers as predictors for wind farm locations. The predictive maps are combined using a combination of the fuzzy functions (AND, OR, SUM, product and gamma), to produce a final map that highlights potential wind farm locations and takes into account all of the input variables.
Our prospecting system has been used by Genesis Energyy in New Zealand to locate new sites for wind farm development and determine possible turbine layouts at current prospects. State-wide modelling for new projects throughout several states in Australia is being considered by several parties. More details about these projects can be found in our New Zealand and Australia wind energy pages.
The most exciting phase of wind prospecting for Kenex is the development of new business opportunities in the Argentinian renewable energy market. This has been a key project for Kenex during the past two years, enabld by our rapidly growing business relationship with EEDSA. More information about these new projects can be found in our Argentina wind energy page.