{"help": "https://data.gov.au/data/api/3/action/help_show?name=package_show", "success": true, "result": {"archived": false, "author_email": null, "contact_point": "clientservices@ga.gov.au", "creator_user_id": "c2fbbe4a-4ba0-4945-808b-67454605a4cf", "duplicate_score": 2, "geospatial_topic": [], "id": "38eb0993-9e1e-4308-a99c-91c02d5f001c", "isopen": false, "language": "eng", "license_id": "notspecified", "license_title": "notspecified", "maintainer": null, "maintainer_email": null, "metadata_created": "2026-01-08T12:54:19.611691", "metadata_modified": "2026-01-08T12:54:19.611698", "name": "renewable-energy-capacity-factor-maps-wcs", "notes": "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.\n\nSolar Photovoltaic capacity factor map\nThe 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).\n\nConcentrated Solar Power capacity factor map\nThe 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).\n\nWind (150 m hub height) capacity factor map\nThe 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).\n\nHybrid Wind and Solar capacity factor maps\nNine 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.) For all maps the minimum capacity factor is <25% and the maximum is 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).\n\nDisclaimer\nThe 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. 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