History of changes to: Wind-AI: Wind Turbine Performance modelling utilising Deep Learning with LIDAR Validation
Date Action Change(s) User
Nov. 27, 2023, 2:12 p.m. Added 35 {"external_links": []}
Nov. 20, 2023, 2:02 p.m. Added 35 {"external_links": []}
Nov. 13, 2023, 1:33 p.m. Added 35 {"external_links": []}
Nov. 6, 2023, 1:30 p.m. Added 35 {"external_links": []}
Aug. 14, 2023, 1:30 p.m. Added 35 {"external_links": []}
Aug. 7, 2023, 1:31 p.m. Added 35 {"external_links": []}
July 31, 2023, 1:33 p.m. Added 35 {"external_links": []}
July 24, 2023, 1:35 p.m. Added 35 {"external_links": []}
July 17, 2023, 1:33 p.m. Added 35 {"external_links": []}
July 10, 2023, 1:25 p.m. Added 35 {"external_links": []}
July 3, 2023, 1:26 p.m. Added 35 {"external_links": []}
June 26, 2023, 1:25 p.m. Added 35 {"external_links": []}
June 19, 2023, 1:26 p.m. Added 35 {"external_links": []}
June 12, 2023, 1:29 p.m. Added 35 {"external_links": []}
June 5, 2023, 1:32 p.m. Added 35 {"external_links": []}
May 29, 2023, 1:27 p.m. Added 35 {"external_links": []}
May 22, 2023, 1:28 p.m. Added 35 {"external_links": []}
May 15, 2023, 1:30 p.m. Added 35 {"external_links": []}
May 8, 2023, 1:36 p.m. Added 35 {"external_links": []}
May 1, 2023, 1:27 p.m. Added 35 {"external_links": []}
April 24, 2023, 1:34 p.m. Added 35 {"external_links": []}
April 17, 2023, 1:29 p.m. Added 35 {"external_links": []}
April 10, 2023, 1:24 p.m. Added 35 {"external_links": []}
April 3, 2023, 1:26 p.m. Added 35 {"external_links": []}
Jan. 28, 2023, 11:08 a.m. Created 43 [{"model": "core.projectfund", "pk": 24637, "fields": {"project": 1824, "organisation": 4, "amount": 322166, "start_date": "2020-03-31", "end_date": "2021-06-29", "raw_data": 38811}}]
Jan. 28, 2023, 11:08 a.m. Created 40 [{"model": "core.projectperson", "pk": 53810, "fields": {"project": 1824, "person": 11539, "role": "PM_PER"}}]
Jan. 28, 2023, 10:51 a.m. Updated 35 {"status": ["Active", "Closed"]}
Jan. 28, 2023, 10:51 a.m. Added 35 {"external_links": []}
April 11, 2022, 3:45 a.m. Created 43 [{"model": "core.projectfund", "pk": 16740, "fields": {"project": 1824, "organisation": 4, "amount": 322166, "start_date": "2020-03-31", "end_date": "2021-06-29", "raw_data": 7809}}]
April 11, 2022, 3:45 a.m. Created 41 [{"model": "core.projectorganisation", "pk": 63070, "fields": {"project": 1824, "organisation": 1624, "role": "PARTICIPANT_ORG"}}]
April 11, 2022, 3:45 a.m. Created 41 [{"model": "core.projectorganisation", "pk": 63069, "fields": {"project": 1824, "organisation": 1180, "role": "PARTICIPANT_ORG"}}]
April 11, 2022, 3:45 a.m. Created 41 [{"model": "core.projectorganisation", "pk": 63068, "fields": {"project": 1824, "organisation": 812, "role": "PARTICIPANT_ORG"}}]
April 11, 2022, 3:45 a.m. Created 41 [{"model": "core.projectorganisation", "pk": 63067, "fields": {"project": 1824, "organisation": 1624, "role": "LEAD_ORG"}}]
April 11, 2022, 3:45 a.m. Created 40 [{"model": "core.projectperson", "pk": 38973, "fields": {"project": 1824, "person": 1864, "role": "PM_PER"}}]
April 11, 2022, 1:47 a.m. Updated 35 {"title": ["", "Wind-AI: Wind Turbine Performance modelling utilising Deep Learning with LIDAR Validation"], "description": ["", "\nThe UK has significant wind power resources and leads the world in offshore wind power generation. In 2018 the wind industry provided 17% (57.1 TWh) of the UK electricity supply \\[UK Energy Statistics, 2018\\] and is forecast to increase substantially over the coming decade \\[National Grid FES\\]. In order to ensure renewable energy can be deployed effectively to combat climate change and to ensure costs to consumers remain low the industry must continue to develop new technologies and operate more efficiently.\n\nCurrently wind turbines can incur significant hidden losses and must routinely be tested for performance loss. This reduces the amount of power they can generate and increases the costs of operation.\n\nThis project will develop a unique method for accurately predicting wind turbine output and hence enable the monitoring of performance losses for every wind turbine at a farm without the need to regularly perform performance testing. An accurate online performance monitoring technology would allow wind turbine operators to reduce the risk of structural blade failure and other common component failure (such as yaw or pitch actuation).\n\nThe project will provide robust evidence to the industry that validates the technology as a credible monitoring technology for the optimisation of site yield and reduction in periodic maintenance; reducing costs and increasing asset production. The technology will enhance the UK's position as leader in effective management and optimisation of wind assets, reducing the cost of energy for consumers and lowering the Levelised Cost of Energy (LCOE) by up to 2.7% (based on ORE Catapult modelling).\n\nThis project will provide the basis for a UK technology to be exported to the global wind industry, creating skilled jobs, and supporting further deployment and utilisation of wind farms to help combat climate change.\n\n"], "extra_text": ["", "\n\n\n\n"], "status": ["", "Active"]}
April 11, 2022, 1:47 a.m. Added 35 {"external_links": [6588]}
April 11, 2022, 1:47 a.m. Created 35 [{"model": "core.project", "pk": 1824, "fields": {"owner": null, "is_locked": false, "coped_id": "14d101b5-1097-4c70-9694-3dd27c4c910f", "title": "", "description": "", "extra_text": "", "status": "", "start": null, "end": null, "raw_data": 7792, "created": "2022-04-11T01:32:36.013Z", "modified": "2022-04-11T01:32:36.013Z", "external_links": []}}]