| Feb. 13, 2024, 4:20 p.m. |
Created
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[{"model": "core.projectfund", "pk": 66700, "fields": {"project": 14951, "organisation": 5, "amount": 161390, "start_date": "2016-03-31", "end_date": "2017-09-30", "raw_data": 182142}}]
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| Jan. 30, 2024, 4:25 p.m. |
Created
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[{"model": "core.projectfund", "pk": 59524, "fields": {"project": 14951, "organisation": 5, "amount": 161390, "start_date": "2016-03-31", "end_date": "2017-09-30", "raw_data": 160579}}]
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| Jan. 2, 2024, 4:16 p.m. |
Created
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[{"model": "core.projectfund", "pk": 52388, "fields": {"project": 14951, "organisation": 5, "amount": 161390, "start_date": "2016-03-31", "end_date": "2017-09-30", "raw_data": 136984}}]
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| Dec. 5, 2023, 4:24 p.m. |
Created
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[{"model": "core.projectfund", "pk": 45133, "fields": {"project": 14951, "organisation": 5, "amount": 161390, "start_date": "2016-03-30", "end_date": "2017-09-29", "raw_data": 108394}}]
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| Nov. 27, 2023, 2:15 p.m. |
Added
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{"external_links": []}
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| Nov. 21, 2023, 4:43 p.m. |
Created
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[{"model": "core.projectfund", "pk": 37857, "fields": {"project": 14951, "organisation": 5, "amount": 161390, "start_date": "2016-03-30", "end_date": "2017-09-29", "raw_data": 77054}}]
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| Nov. 21, 2023, 4:43 p.m. |
Created
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[{"model": "core.projectorganisation", "pk": 113513, "fields": {"project": 14951, "organisation": 13802, "role": "PP_ORG"}}]
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| Nov. 21, 2023, 4:43 p.m. |
Created
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[{"model": "core.projectorganisation", "pk": 113512, "fields": {"project": 14951, "organisation": 13134, "role": "PP_ORG"}}]
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| Nov. 21, 2023, 4:43 p.m. |
Created
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[{"model": "core.projectorganisation", "pk": 113511, "fields": {"project": 14951, "organisation": 11141, "role": "PP_ORG"}}]
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| Nov. 21, 2023, 4:43 p.m. |
Created
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[{"model": "core.projectorganisation", "pk": 113510, "fields": {"project": 14951, "organisation": 11141, "role": "COLLAB_ORG"}}]
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| Nov. 21, 2023, 4:43 p.m. |
Created
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[{"model": "core.projectorganisation", "pk": 113509, "fields": {"project": 14951, "organisation": 11849, "role": "COLLAB_ORG"}}]
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| Nov. 21, 2023, 4:43 p.m. |
Created
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[{"model": "core.projectorganisation", "pk": 113508, "fields": {"project": 14951, "organisation": 10959, "role": "LEAD_ORG"}}]
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| Nov. 21, 2023, 4:43 p.m. |
Created
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[{"model": "core.projectperson", "pk": 71408, "fields": {"project": 14951, "person": 13248, "role": "RESEARCH_COI_PER"}}]
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| Nov. 21, 2023, 4:43 p.m. |
Created
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[{"model": "core.projectperson", "pk": 71407, "fields": {"project": 14951, "person": 19912, "role": "COI_PER"}}]
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| Nov. 21, 2023, 4:43 p.m. |
Created
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[{"model": "core.projectperson", "pk": 71406, "fields": {"project": 14951, "person": 16870, "role": "COI_PER"}}]
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| Nov. 21, 2023, 4:43 p.m. |
Created
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[{"model": "core.projectperson", "pk": 71405, "fields": {"project": 14951, "person": 18230, "role": "PI_PER"}}]
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| Nov. 20, 2023, 2:06 p.m. |
Updated
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{"title": ["", "Storm Risk Assessment of Interdependent Infrastructure Networks"], "description": ["", "\nElectricity infrastructure provides a vital services to consumers. Across the UK there are thousands of miles of overhead lines and other assets that are vulnerable to a number of environmental risks. Wind risks have caused more disruptions to power supplies in the UK than any other environmental risks. Despite their importance, the future risks associated with windstorm disruption are currently highly uncertain as the coarse spatial resolution of climate models makes them unable to properly represent wind storm processes.\n\nSTRAIN will address two challenges for infrastructure operators and stakeholders who are urgently seeking to understand and mitigate wind related risks in their pursuit to deliver more reliable services:\n\n(i) Build upon state-of-the-art modelling and analysis capabilities to assess the vulnerability of electricity networks and their engineering assets to high winds. This will consider the impact of different extreme wind events, over different parts of the electricity network, the households and businesses connected, and also apply a model representing infrastructure inter-connections to understand the potential impact on other infrastructures that require electricity such as road, rail and water systems.\n\n(ii) Climate models provide very uncertain wind projections, yet infrastructure operators require an understanding of future climate change to develop long term asset management strategies. To provide the necessary information we shall work with the Met Office and benefit from new high resolution simulations of future wind climate using a 1.5km climate model. These simulations have proven capable of representing convective storm processes, that drive many storms across the UK, and have already proven that they better capture extreme rainfall events.\n\nThese methods will be applied to a case study of an electricity distribution network. These are more vulnerable to windstorms than the high voltage national transmission network.\n\nSTRAIN will therefore, by synthesising and translating cutting-edge research, provide electricity distribution network operators with a significantly improved understanding of wind risks both now and in the longer term. This will improve the reliability of electricity supply to UK consumers including other infrastructure providers reliant on electricity distribution networks, and reduce costs by enabling more effective allocation of investments in adaptation and asset management. Furthermore, it will help other infrastructure service providers better understand the impacts of electricity disruption on their own systems, and plan accordingly. The improved understanding of future extreme wind storms will provide benefits across an even wider group of infrastructure and built environment stakeholders.\n\n"], "extra_text": ["", "\n\nPotential Impact:\nA reliable supply of electricity is fundamental to the UK and global economy, and to the health and wellbeing of citizens. In the UK, windstorms pose the most significant threat to electricity distribution, yet long term changes in wind are one of the most uncertain climate model outputs posing challenges for long term planning and asset management. \n\nAssessment of these risks is complicated by a complex infrastructure: half a million miles or so of cable across the UK, and many other assets such as substations and transformers, that deliver this service. For example - case study partners, Northern Powergrid, serve 3.8m customers, manage an enormous infrastructure asset base, including 91,000 miles overhead lines and cables and 31,000 substations, that sprawls across an area of 25,000km2.\n\nFuture investment in the electricity sector will be significant - the 2014 National Infrastructure Plan identified £38bn investment in electricity transmission and distribution by 2020-21. Electricity is fundamental to the continued operation of other infrastructures (including transport, water and ICT), and globally some $40trillion (over 3% gross world product) is forecast by the World Bank to be invested in infrastructure over the next twenty years. \n\nThe most significant initial impact on the electricity sector will be in the Norther Powergrid (NPG) region as they are our case study partners. Their 3.8m customers will therefore be the first to benefit from their electricity provider exploiting the latest science and understanding of wind related risks to enhance the resilience of their system. However, we will work with NPG and our other partners that include infrastructure providers and engineering consultancies, to disseminate and promote wider uptake and impact of the STRAIN modelling capabilities to reduce environmental risks to infrastructure systems and to allow UK consultancies to extend their reach.\n\nThe better understanding of wind risks to electricity networks, and the utility of this analysis to enhance energy resilience and reduce asset management costs through better-targeted interventions, that STRAIN will provide will therefore have huge economic and social benefits.\n\n\n"], "status": ["", "Closed"]}
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| Nov. 20, 2023, 2:06 p.m. |
Added
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{"external_links": [59040]}
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| Nov. 20, 2023, 2:06 p.m. |
Created
35
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[{"model": "core.project", "pk": 14951, "fields": {"owner": null, "is_locked": false, "coped_id": "8ed85185-9c47-40cd-9e3e-159c039a7c04", "title": "", "description": "", "extra_text": "", "status": "", "start": null, "end": null, "raw_data": 77037, "created": "2023-11-20T13:56:24.420Z", "modified": "2023-11-20T13:56:24.420Z", "external_links": []}}]
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