{"help": "https://data.gov.au/data/api/3/action/help_show?name=package_show", "success": true, "result": {"archived": false, "author": "", "author_email": null, "contact_point": "unknown", "creator_user_id": "c2fbbe4a-4ba0-4945-808b-67454605a4cf", "duplicate_score": 2, "geospatial_topic": [], "id": "4827b1ae-ef8f-4566-be35-bf49774b47be", "isopen": false, "license_id": "CC-BY-4.0", "license_title": "CC-BY-4.0", "maintainer": "", "maintainer_email": "", "metadata_created": "2025-11-15T11:59:04.863743", "metadata_modified": "2026-01-10T07:40:00.419270", "name": "solar_irradiance_monthly_cumulative_kbf", "notes": "This dataset quantifies cumulative monthly solar irradiance totals for building footprints in Kalgoorlie-Boulder, providing monthly and annual energy budgets essential for photovoltaic system sizing and economic analysis.\n\nDerived from hourly simulations aggregated to monthly totals, the dataset delivers cumulative irradiance values (W/m\u00b2) for each of 12 months plus annual totals across approximately 16,000 buildings. This format directly supports PV system performance modelling, return-on-investment calculations, and comparative analysis of seasonal energy availability across different urban areas.\n\nThe data combines Microsoft Bing 2D building geometries with validated climate datasets and Radiance-based solar simulation. Monthly cumulation allows users to assess seasonal energy production patterns, identify optimal installation timeframes, and estimate annual yield without managing high-temporal-resolution data files.\n\nKey applications include renewable energy target setting for local government, preliminary system sizing for commercial solar installations, and academic research into urban energy self-sufficiency potential. Energy utilities and planners can use monthly totals to model distributed generation contributions to grid supply across different seasons.\n\nValues assume flat rooftop surfaces without accounting for actual roof pitch, azimuth, or shading effects. Users requiring panel-specific calculations should apply the irradiance values to their chosen panel specifications using standard photovoltaic performance models. For sub-monthly temporal dynamics, see the hourly potential dataset.\n\nComprehensive technical documentation, including data dictionary, usage examples, and processing methodology, is available in <a href=\"https://resources.aurin.org.au/ckan/resources/DataSet-Information.pdf\">here</a>; software stack details and calculation workflows are documented in <a href=\"https://resources.aurin.org.au/ckan/resources/Software_Stack.pdf\">here</a>.", "num_resources": 1, "num_tags": 5, "organization": {"id": "b0429d6f-82d8-4c5f-9325-37b64b9b1c48", "name": "school-of-electrical-engineering-computing-and-mathematical-sciences-curtin-university-australian-ur", "title": "School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University", "type": "organization", "description": "Our school brings together Curtin\u2019s core capabilities across electrical engineering, computing, physics and mathematics, to better understand and advance our data-driven world. We have built substantial knowledge in machine learning, cyber security, statistics and optimisation, digital transformation, radio astronomy, the Internet of Things, signal processing, embedded systems, renewable and power engineering. The school offers a range of undergraduate and postgraduate courses across these areas, which give students the skills they need to tackle the challenges of the future. The school attracts millions of dollars of research income each year, the majority of which is from industry, reflecting the focus of the school on demand driven research. The school is home to some of the largest institutes and centres at Curtin.", "image_url": "", "created": "2025-11-15T22:58:53.507896", "is_organization": true, "approval_status": "approved", "state": "active"}, "original_harvest_source": {"site_url": "https://data.aurin.org.au/", "href": "https://data.aurin.org.au/dataset/solar_irradiance_monthly_cumulative_kbf", "title": "Australian Urban Research Infrastructure Network"}, "original_name": "solar_irradiance_monthly_cumulative_kbf", "owner_org": "b0429d6f-82d8-4c5f-9325-37b64b9b1c48", "private": false, "promotion_level": "0", "remote_last_updated": "2025-12-23T05:43:28.908920", "spatial": "{\"type\": \"Polygon\", \"coordinates\": [[[121.42359807500652, -30.803203268101967], [121.53928549242828, -30.803203268101967], [121.53928549242828, -30.71136853194179], [121.42359807500652, -30.71136853194179], [121.42359807500652, -30.803203268101967]]]}", "spatial_coverage": "{\"type\": \"Polygon\", \"coordinates\": [[[121.42359807500652, -30.803203268101967], [121.53928549242828, -30.803203268101967], [121.53928549242828, -30.71136853194179], [121.42359807500652, -30.71136853194179], [121.42359807500652, -30.803203268101967]]]}", "state": "active", "temporal_coverage_from": "2025-10-16 06:57:12.726543", "title": "Kalgoorlie-Boulder Photo-Voltaic (PV) Potential Maps: Monthly Cumulative Irradiance Values", "type": "dataset", "unpublished": false, "url": "", "version": "", "extras": [{"key": "harvest_object_id", "value": "4b81b1df-1963-46a1-91a8-9c0230a5c353"}, {"key": "harvest_source_id", "value": "3b753826-54f7-43e3-8246-4b09aaee723f"}, {"key": "harvest_source_title", "value": "Australian Urban Research Infrastructure Network"}], "resources": [{"cache_last_updated": null, "cache_url": null, "created": "2025-10-16T06:57:12.729536", "datastore_active": false, "datastore_contains_all_records_of_source_file": false, "description": "Download this dataset via the AURIN Download Manager", "format": "HTML", "hash": "", "id": "e71f4264-3e54-4f64-b2ec-9f1dafa4a64f", "last_modified": null, "metadata_modified": "2026-01-10T07:40:00.426780", "mimetype": null, "mimetype_inner": null, "name": "AURIN Download Manager", "package_id": "4827b1ae-ef8f-4566-be35-bf49774b47be", "position": 0, "resource_type": "file", "size": null, "state": "active", "url": "https://adp-access.aurin.org.au/dataset/solar_irradiance_monthly_cumulative_kbf", "url_type": null, "zip_extract": false}], "tags": [{"display_name": "PV Potential", "id": "3fc5ffe2-14f8-4d48-93cf-8d0f243a44fa", "name": "PV Potential", "state": "active", "vocabulary_id": null}, {"display_name": "PV Rooftops", "id": "2612481d-6d17-4a49-b711-743a47df5eaa", "name": "PV Rooftops", "state": "active", "vocabulary_id": null}, {"display_name": "Photo-Voltaic", "id": "10b08dc0-473f-4a27-ae96-a73848a59109", "name": "Photo-Voltaic", "state": "active", "vocabulary_id": null}, {"display_name": "Solar Irradiance Estimation", "id": "b492f980-23aa-4324-bf8a-d8a622d2837a", "name": "Solar Irradiance Estimation", "state": "active", "vocabulary_id": null}, {"display_name": "Urban Rooftop Aggregation", "id": "938017db-5128-4f59-b7a0-30218ff142a2", "name": "Urban Rooftop Aggregation", "state": "active", "vocabulary_id": null}], "groups": [], "relationships_as_subject": [], "relationships_as_object": []}}