{"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": "a52cddc8-870d-4df6-b8f7-4906ab09605c", "isopen": false, "license_id": "CC-BY-4.0", "license_title": "CC-BY-4.0", "maintainer": "", "maintainer_email": "", "metadata_created": "2025-11-15T11:59:24.308565", "metadata_modified": "2026-01-10T07:40:11.395684", "name": "solar_pv_potential_footprint_daily_average", "notes": "This dataset translates solar irradiance into estimated daily photovoltaic energy output (kWh) for individual buildings, incorporating panel characteristics and temperature efficiency losses to deliver actionable generation estimates.\n\nCovering approximately 16,000 footprints, the dataset provides monthly daily average PV potential values that account for panel efficiency (27%), temperature coefficient (-0.5%/\u00b0C), and optimal panel layout within each rooftop geometry. These values represent realistic generation expectations from standard mid-performance panels (0.96 x 1.64m, 300W), enabling direct comparison of building-level solar capacity across the urban area.\n\nThe dataset was created to bridge the gap between raw irradiance data and practical energy planning. By incorporating panel specifications and calculating maximum feasible panel counts per rooftop (accounting for edge setbacks and spacing), it delivers estimates directly usable for installation feasibility studies and energy self-sufficiency analysis.\n\nTarget users include building owners evaluating solar investment opportunities, property developers assessing renewable energy contributions, and municipal planners setting district-level clean energy targets. The daily average format provides accessible seasonal generation patterns without requiring specialised photovoltaic modelling software.\n\nEstimates assume flat-mounted panels in optimal orientation and do not account for actual roof pitch, shading, or site-specific installation constraints. For hourly generation profiles needed for grid integration studies or battery sizing, reference the hourly PV potential dataset. For customised panel specifications, apply your parameters to the irradiance datasets.\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_pv_potential_footprint_daily_average", "title": "Australian Urban Research Infrastructure Network"}, "original_name": "solar_pv_potential_footprint_daily_average", "owner_org": "b0429d6f-82d8-4c5f-9325-37b64b9b1c48", "private": false, "promotion_level": "0", "remote_last_updated": "2025-12-23T05:42:49.303049", "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 06:57:13.559326", "title": "Kalgoorlie-Boulder Photo-Voltaic (PV) Potential Maps: Daily Average Potential Values", "type": "dataset", "unpublished": false, "url": "", "version": "", "extras": [{"key": "harvest_object_id", "value": "68760a9f-0428-48de-b7f8-8e63c91794de"}, {"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": "2025-10-16T06:57:13.632990", "datastore_active": false, "datastore_contains_all_records_of_source_file": false, "description": "Download this dataset via the AURIN Download Manager", "format": "HTML", "hash": "", "id": "9f65cd84-a30a-4fd8-8eda-6af18b794628", "last_modified": null, "metadata_modified": "2026-01-10T07:40:11.403620", "mimetype": null, "mimetype_inner": null, "name": "AURIN Download Manager", "package_id": "a52cddc8-870d-4df6-b8f7-4906ab09605c", "position": 0, "resource_type": "file", "size": null, "state": "active", "url": "https://adp-access.aurin.org.au/dataset/solar_pv_potential_footprint_daily_average", "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": []}}