Geoscience Australia and Monash University have produced a series of renewable energy capacity factor maps of Australia. Solar photovoltaic, concentrated solar power, wind (150 m hub height) and hybrid wind and solar capacity factor maps are included in this web service. Solar Photovoltaic capacity factor map The minimum capacity factor is <10% and the maximum is 25%. The map is derived from Bureau of Meteorology (2020) data. The scientific colour map is sourced from Crameri (2018). Concentrated Solar Power capacity factor map The minimum capacity factor is 52% and the maximum is 62%. The map is derived from Bureau of Meteorology (2020) data. Minimum exposure cut-off values used are from International Renewable Energy Agency (2012) and Wang (2019). The scientific colour map is sourced from Crameri (2018). Wind (150 m hub height) capacity factor map The minimum capacity factor is <15% and the maximum is 42%. The map is derived from Global Modeling and Assimilation Office (2015) and DNV GL (2016) data. The scientific colour map is sourced from Crameri (2018). Hybrid Wind and Solar capacity factor maps Nine hybrid wind and solar maps are available, divided into 10% intervals of wind to solar ratio (eg. (wind 40% : solar 60%), (wind 50% : solar 50%), (wind 60% : solar 40%) etc.). The maps show the capacity factor available for electrolysis. Wind and solar plants might be oversized to increase the overall running time of the hydrogen plant allowing the investor to reduce electrolyser capital expenditures for the same amount of output. Calculations also include curtailment (or capping) of excess electricity when more electricity is generated than required to operate the electrolyser. The minimum and maximum capacity factors vary relative to a map’s specified wind to solar ratio. A wind to solar ratio of 50:50 produces the highest available capacity factor of 64%. The maps are derived from Global Modeling and Assimilation Office (2015), DNV GL (2016) and Bureau of Meteorology (2020) data. The scientific colour map is sourced from Crameri (2018). Disclaimer The capacity factor maps are derived from modelling output and not all locations are validated. Geoscience Australia does not guarantee the accuracy of the maps, data, and visualizations presented, and accepts no responsibility for any consequence of their use. Capacity factor values shown in the maps should not be relied upon in an absolute sense when making a commercial decision. Rather they should be strictly interpreted as indicative. Users are urged to exercise caution when using the information and data contained. If you have found an error in this dataset, please let us know by contacting clientservices@ga.gov.au.

Geoscience Australia and Monash University have produced a series of renewable energy capacity factor maps of Australia. Solar photovoltaic, concentrated solar power, wind (150 m hub height) and hybrid wind and solar capacity factor maps are included in this web service. Solar Photovoltaic capacity factor map The minimum capacity factor is <10% and the maximum is 25%. The map is derived from Bureau of Meteorology (2020) data. The scientific colour map is sourced from Crameri (2018). Concentrated Solar Power capacity factor map The minimum capacity factor is 52% and the maximum is 62%. The map is derived from Bureau of Meteorology (2020) data. Minimum exposure cut-off values used are from International Renewable Energy Agency (2012) and Wang (2019). The scientific colour map is sourced from Crameri (2018). Wind (150 m hub height) capacity factor map The minimum capacity factor is <15% and the maximum is 42%. The map is derived from Global Modeling and Assimilation Office (2015) and DNV GL (2016) data. The scientific colour map is sourced from Crameri (2018). Hybrid Wind and Solar capacity factor maps Nine hybrid wind and solar maps are available, divided into 10% intervals of wind to solar ratio (eg. (wind 40% : solar 60%), (wind 50% : solar 50%), (wind 60% : solar 40%) etc.). The maps show the capacity factor available for electrolysis. Wind and solar plants might be oversized to increase the overall running time of the hydrogen plant allowing the investor to reduce electrolyser capital expenditures for the same amount of output. Calculations also include curtailment (or capping) of excess electricity when more electricity is generated than required to operate the electrolyser. The minimum and maximum capacity factors vary relative to a map’s specified wind to solar ratio. A wind to solar ratio of 50:50 produces the highest available capacity factor of 64%. The maps are derived from Global Modeling and Assimilation Office (2015), DNV GL (2016) and Bureau of Meteorology (2020) data. The scientific colour map is sourced from Crameri (2018). Disclaimer The capacity factor maps are derived from modelling output and not all locations are validated. Geoscience Australia does not guarantee the accuracy of the maps, data, and visualizations presented, and accepts no responsibility for any consequence of their use. Capacity factor values shown in the maps should not be relied upon in an absolute sense when making a commercial decision. Rather they should be strictly interpreted as indicative. Users are urged to exercise caution when using the information and data contained. If you have found an error in this dataset, please let us know by contacting clientservices@ga.gov.au.

Monash University under commission of Geoscience Australia produced an offshore wind capacity factor map assessed at a 150m hub height applying the Bureau of Meteorology 10 year (2009-2018) “Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia” (BARRA) hindcast model. The wind capacity factor has been calculated using the bounding curve of all scaled power curves for wind turbines available within the Open Energy Platform as of 2021. Average wind capacity factor values were also calculated for the Vestas V126 3.45MW and the GE V130 3.2MW wind turbines and are available in this web map service.

Monash University under commission of Geoscience Australia produced an offshore wind capacity factor map assessed at a 150m hub height applying the Bureau of Meteorology 10 year (2009-2018) “Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia” (BARRA) hindcast model. The wind capacity factor has been calculated using the bounding curve of all scaled power curves for wind turbines available within the Open Energy Platform as of 2021. Average wind capacity factor values were also calculated for the Vestas V126 3.45MW and the GE V130 3.2MW wind turbines and are available in this web map service.

<div>Steelmaking value chains are economically important to Australia, but the need to decarbonize traditional steel-making processes could disrupt existing supply lines. Hydrogen-based iron and steel production offers one pathway for reducing the carbon intensity of steel. Here, we present maps assessing the costs of hydrogen-based direct reduction of iron oxides (to produce hot briquetted iron), optionally coupled with steelmaking in an electric arc furnace (i.e. the H2-DRI-EAF value chain). Developed as part of the Exploring for the Future program and in collaboration with Monash University, these models build off the functionality of the Green Steel Economic Fairways Mapper (beta release), with additional enhancements to the modelling algorithm to reflect constant furnace operation, the incorporation of costings to transport the produced hot briquetted iron or steel to domestic ports, and the optimisation of facility capacities. The capacity of facilities (including solar and wind generation, proton exchange membrane [PEM] electolysis, battery storage, and hydrogen storage tanks) are determined by the 1 Mtpa production target and the local availability of renewable energy resources, as modelled according to 2019 data sourced from the Renewables.Ninja (https://www.renewables.ninja/; Pfenninger & Staffell, 2016; Staffell & Pfenninger, 2016). The high-resolution (approximately 5.5 km pixels) maps reflect our preferred technology cost assumptions (see Wang et al., 2023) for the year 2025. Iron concentrate feedstocks are assumed to cost AU$150 per tonne, reflecting approximate costs for 65 % Fe pellets as derived from magnetite ores. Conversions to USD assume US$1.00 = AU$0.73.</div><div><br></div><div>Geoscience Australia's Exploring for the Future program provides precompetitive information to inform decision-making by government, community and industry on the sustainable development of Australia's mineral, energy and groundwater resources. By gathering, analysing and interpreting new and existing precompetitive geoscience data and knowledge, we are building a national picture of Australia's geology and resource potential. This leads to a strong economy, resilient society and sustainable environment for the benefit of all Australians. This includes supporting Australia's transition to a low emissions economy, strong resources and agriculture sectors, and economic opportunities and social benefits for Australia's regional and remote communities. The Exploring for the Future program, which commenced in 2016, is an eight year, $225m investment by the Australian Government.</div>

Monash University under commission of Geoscience Australia produced an offshore wind capacity factor map assessed at a 150m hub height applying the Bureau of Meteorology 10 year (2009-2018) BARRA hindcast model. The wind capacity factor has been calculated using the bounding curve of all scaled power curves for wind turbines available within the Open Energy Platform as of 2021. Average wind capacity factor values were also calculated for the Vestas V126 3.45MW and the GE V130 3.2MW wind turbines.