| Feb. 13, 2024, 4:20 p.m. |
Created
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[{"model": "core.projectfund", "pk": 66544, "fields": {"project": 14794, "organisation": 2, "amount": 1511971, "start_date": "2012-10-08", "end_date": "2016-12-16", "raw_data": 185539}}]
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| Jan. 30, 2024, 4:25 p.m. |
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[{"model": "core.projectfund", "pk": 59369, "fields": {"project": 14794, "organisation": 2, "amount": 1511971, "start_date": "2012-10-08", "end_date": "2016-12-16", "raw_data": 165488}}]
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| Jan. 2, 2024, 4:16 p.m. |
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[{"model": "core.projectfund", "pk": 52231, "fields": {"project": 14794, "organisation": 2, "amount": 1511971, "start_date": "2012-10-08", "end_date": "2016-12-16", "raw_data": 140369}}]
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| Dec. 5, 2023, 4:24 p.m. |
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[{"model": "core.projectfund", "pk": 44976, "fields": {"project": 14794, "organisation": 2, "amount": 1511971, "start_date": "2012-10-07", "end_date": "2016-12-16", "raw_data": 116582}}]
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| Nov. 27, 2023, 2:15 p.m. |
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{"external_links": []}
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectfund", "pk": 37700, "fields": {"project": 14794, "organisation": 2, "amount": 1511971, "start_date": "2012-10-07", "end_date": "2016-12-16", "raw_data": 76259}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectorganisation", "pk": 112738, "fields": {"project": 14794, "organisation": 12968, "role": "PP_ORG"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectorganisation", "pk": 112737, "fields": {"project": 14794, "organisation": 14195, "role": "PP_ORG"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectorganisation", "pk": 112736, "fields": {"project": 14794, "organisation": 18673, "role": "PP_ORG"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectorganisation", "pk": 112735, "fields": {"project": 14794, "organisation": 18674, "role": "PP_ORG"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectorganisation", "pk": 112734, "fields": {"project": 14794, "organisation": 17964, "role": "PP_ORG"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectorganisation", "pk": 112733, "fields": {"project": 14794, "organisation": 11845, "role": "PP_ORG"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectorganisation", "pk": 112732, "fields": {"project": 14794, "organisation": 18675, "role": "PP_ORG"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectorganisation", "pk": 112731, "fields": {"project": 14794, "organisation": 18135, "role": "PP_ORG"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectorganisation", "pk": 112730, "fields": {"project": 14794, "organisation": 14385, "role": "LEAD_ORG"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectperson", "pk": 70860, "fields": {"project": 14794, "person": 17351, "role": "COI_PER"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectperson", "pk": 70859, "fields": {"project": 14794, "person": 20586, "role": "COI_PER"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectperson", "pk": 70858, "fields": {"project": 14794, "person": 13025, "role": "COI_PER"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectperson", "pk": 70857, "fields": {"project": 14794, "person": 18938, "role": "COI_PER"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectperson", "pk": 70856, "fields": {"project": 14794, "person": 20587, "role": "COI_PER"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectperson", "pk": 70855, "fields": {"project": 14794, "person": 20588, "role": "COI_PER"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectperson", "pk": 70854, "fields": {"project": 14794, "person": 20589, "role": "COI_PER"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectperson", "pk": 70853, "fields": {"project": 14794, "person": 15010, "role": "COI_PER"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectperson", "pk": 70852, "fields": {"project": 14794, "person": 13244, "role": "COI_PER"}}]
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| Nov. 21, 2023, 4:42 p.m. |
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[{"model": "core.projectperson", "pk": 70851, "fields": {"project": 14794, "person": 13977, "role": "PI_PER"}}]
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| Nov. 20, 2023, 2:06 p.m. |
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{"title": ["", "Energy literacy through an intelligent home energy advisor (ENLITEN)"], "description": ["", "\nThe UK is committed to an 80% reduction in human-created greenhouse gas emissions. As well as financial incentives, carbon reduction will require an increase in "energy literacy", i.e. it will require members of the public to better understand the energy, carbon and financial implications of their behaviours and habits. The ENLITEN project aims to reduce carbon emissions from energy use within buildings by understanding and influencing occupants' habits and behaviours around energy use.\n\nSignificantly reducing energy use within buildings through internal physical controls, such as automatically closing windows, is difficult economically. For example, equipping windows with sensors and motors would cost in the region of £100 per window. Reducing energy use within buildings through external policy controls, such as enforcing times when appliances can and cannot be run, is difficult socially and politically. For example, when California tried to impose a state-wide reduction of 1F in air-conditioning temperature settings, there was public outrage and resistance. Hence, an approach that has more chance - economically, socially and politically - of achieving significant energy reductions is to persuade building occupants to change their energy consuming behaviours.\n\nThere have been many studies of the effect on energy demand of providing building occupants with information on their energy use, founded on the hope that such information will encourage them to reduce their use. The results vary widely, suggesting anything from 0% to 20% reductions. Where reductions are achieved through occupants' behavioural changes, they are often not sustained in the longer term. To achieve significant sustained reductions in energy use by building occupants, we need to avoid simply presenting more information - an approach that has failed in other domains - and focus on providing information that has an effect which lasts beyond any temporary interventions or campaigns.\n\nThis may be achieved by encouraging changes to sustainable behaviours that are sustained in the longer term, maximising the savings by each individual while minimising the burden of behavioural change required, and maximising the number of individuals making changes. In order to achieve these goals, we will specifically target long term sustained effects by focusing on changes to the habitual behaviours of building occupants and not just short-term responses to interventions. We will develop an innovative smart system that provides information, recommendations and rewards personalised to each household and associated with novel behaviour-driven energy tariffs. We will maximise accessibility and potential uptake of the system by making the equipment cheap, easily deployable and minimally disruptive to the building fabric.\n\nThe system will be based on a whole building energy model that, uniquely, integrates a thermal model of the building, a model of occupants' habits and requirements and a disaggregated model of energy use in the building. We will use data from a minimal sensor set to develop a unique auto-generated thermal model of the building, and a disaggregated model of energy use. We will use a range of automated and human data collection and analyses to develop an understanding and model of occupants' energy- related attitudes, behaviours and habits. We will bring these models together to inform an interactive in-building tool to help occupants identify and break poor energy habits, form better ones and reduce energy demand and carbon emissions. While fostering changes in the habits of the occupants, we will relate these changes to the broader social and economic context, examining the trade-offs between the value and costs of behavioural change, quantified in terms of reductions in energy cost and carbon footprint for individuals and the energy supply chain. This analysis will allow us to develop novel tariff-based incentives that reward desired behavioural changes.\n\n"], "extra_text": ["", "\n\nPotential Impact:\nWe envisage significant non-academic impacts across a range of issues and actors. Governments worldwide are testing, deploying and mandating the use of smart meters and In-Home Displays (IHDs). The UK government is committed to equipping every home with a smart meter by 2019. The Department of Energy and Climate Change (DECC) estimates a £11.7 billion bill for this mass rollout. However, a number of studies have shown that current IHDs either do not work or deliver savings of less than 5% compared to control. The main reason for this is the difficulty faced by typically non energy-literate occupants in translating information on energy use into energy saving actions. This project directly addresses this issue through its novel iBert home energy advisor which will provide customized actionable prompts (rather than raw energy use) to the occupants on the precise reasons for energy wastage in their home thus setting an outer bound for the extent of savings that can be generated from any IHD based solution. This will be of direct benefit to DECC, EST, Carbon Trust, Cabinet Office Behavioural Insights Team, Ofgem and DCLG.\n\nIt is estimated that 25-30% of all homes in England can be classed as fuel-poor, rising to about 48% in Northern Ireland. However, measuring fuel poverty can be tricky and policies to alleviate it can be problematic. For example, 76% of the Winter Fuel Payment is wasted since all OAPs are eligible for it even though only 24% of them are in fuel poverty. Our project sample groups A & B will consist of a representative sample (25%) of fuel-poor households and physically vulnerable occupants (OAPs, children). Since a mission of the project is to collect co-incident high-resolution energy use and environmental data alongside socio-economic household metrics the project will provide deep insights into the exact causes of fuel poverty in the sample households. This will be of significant benefit to regulators (Ofgem), government (DECC, DCLG, DoH and DEFRA) and fuel poverty groups. \n\nFurther, since social housing provides for the most vulnerable socio-economic groups in society, data on temperatures, occupancy, boiler and thermostat use and overall energy use are required by Local Authorities (LAs), Registered Social Landlords (RSLs) and other providers of social housing to prioritise actions and manage their properties. ENLITEN will collect these data and provide them free of cost in high quality samples to LAs (Exeter, Bath and wider through the Local Government Association) and RSLs (e.g. Somer Community Housing Trust - the largest RSL in the South West). \n\nA key aspect of current energy tariffs is their one-size-fits-all approach. By analysing iBert and household data (income, age, dwelling usage and desires) ENLITEN will deliver a much more granular pricing mechanism, "soft-impact", tariff structure that will help households accelerate those behaviour changes that result in energy savings. The proposed structure will be of direct benefit to suppliers (E-On, Npower etc.), Distribution Network Operators (Npower, Scottish and Southern etc.), regulator (Ofgem) and the Energy and Climate Change Committee (via POST). \n\nInternational reviews of current IHDs and modern programmable thermostats suggest that they are complex and difficult to understand by the average householder. This is due to the scarcity of design guidance on making these devices accessible and inclusive with every manufacturer developing bespoke solutions that have little standardization of control mechanisms, tactility and symbols. We propose the production of a design guide based on the ENLITEN-US experiment (see Pathways to Impact), lab-based experiments, field trials and the expertise of our project partners (BH, SS, NEM, KSA) on these issues. This guidance will be disseminated in the south west via two Low Carbon Business Breakfast events organized by our partner LCSW and nationally and internationally via our partners and the website.\n\n\n"], "status": ["", "Closed"]}
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| Nov. 20, 2023, 2:06 p.m. |
Added
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{"external_links": [58420]}
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| Nov. 20, 2023, 2:06 p.m. |
Created
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[{"model": "core.project", "pk": 14794, "fields": {"owner": null, "is_locked": false, "coped_id": "6e3b3110-9c77-47a4-b81c-40203588d2a2", "title": "", "description": "", "extra_text": "", "status": "", "start": null, "end": null, "raw_data": 76242, "created": "2023-11-20T13:55:43.585Z", "modified": "2023-11-20T13:55:43.585Z", "external_links": []}}]
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