Australia Wind and Grid Prospecting
Wind farm development in Australia is a part of the renewable energy mix with more than 50 wind farms operating oin the country and generating more than the 20% of total renewable energy supply. Nevertheless there is still significant potential for further investments. Due to the nature of the industry it is important for the best sites to be identified and given priority for development in order to get the best return for investment and the most energy out of this renewable resource.
As a first step to finding ideal wind farm sites in Australia, Kenex has developed preliminary wind prospecting models for several areas, including regions in Queensland, New South Wales and Victoria. The models used the Fuzzy Logic modelling technique successfully applied in wind prospecting in New Zealand. However, they differ greatly from the New Zealand models in scale, spatial variables chosen, and weighting of each variable, due to the considerably different terrain and cultural considerations in Australia. While still using the principal spatial variables that influence wind farm siting (e.g. wind speed, slope, and land use), we have realised that in countries like Australia, where the topography is not as an influential factor for building a wind farm, other parameters become determinant for the success of a project and therefore need to be considered in an prospecting model.
The principal parameter in making a wind project economic in Australia is gaining a good connection with the transmission grid. For this reason Kenex, with the help of Aurecon experts, have developed a transmission grid model and integrated it in our wind prospecting system.
Kenex has developed a preliminary transmission grid model in Victoria and New South Wales. The main challenge of this task has been creating a GIS database of transmission lines, substation, generators and loads from the available data. We have compiled a highly accurate East Australia transmission network database using information from the Australia Energy Market Operator (AEMO ) and verifying almost each line and station location using aerial photos.
Identifying powerstations on Google Earth
The second step has been identifying which spatial parameters are important for gaining a good connection. With the help of grid connection experts, we created new predictive maps based on proximity, density and marginal loss factor - a parameter representing the increase or decrease in energy loss that that would occur in response to an incremental change in generation output or load demand - of transmission lines and stations.
The three maps have then been weighted and combined into a single fuzzy logic model and the results have been used to rank the existing wind and terrain targets in order to prioritise the areas which are most advantageous to be connecting to the transmission grid.
Ranking the terrain and wind targets using the grid model
The transmission grid model has proved to be a successful addition to the wind prospecting system, improving the efficacy of Kenex wind modelling and its capacity of adapting to terrain, social and energy constraints of different countries.
That allows us to successfully apply it anywhere in the world, especially where we can collaborate with local wind experts who know the requirements of the country energy market, as proved also with our Argentina wind projects.