课题基金 / 基金详情

Energy-focused geospatial system using multi-sectoral data to deliver net zero

Energy-focused geospatial system using multi-sectoral data to deliver net zero
以能源为中心的地理空间系统,利用多部门数据实现净零排放
批准号:
98797
负责人:
金额:
$18.5万
依托单位:
依托单位国家:
英国
项目类别:
Small Business Research Initiative
财政年份:
2021
资助国家:
英国
项目状态:
已结题
起止时间:
2021 至 --

项目摘要

项目成果

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
The UK is the first major world economy to pledge net zero carbon emissions by 2050\. The achievement of this goal will require transformations in a number of sectors. To this end, sectors such as transport and urban planning, have embarked upon a nimble, focused and data-driven approach in addressing their challenges. The energy sector can undertake a similar approach, taking data from the energy sector and additional sectors , such as transport, to deliver targeted solutions at the local level.We intend to use geospatial data, which combines location information with attribute and often temporal information, can contribute to the evolution of the distributed energy paradigm.The ability to analyze sparse or incomplete data with respect to, for example smart meters, electric vehicle (EV) uptake, EV charging type, locations and user profile, has a range of implications that are difficult to model with conventional approaches.We propose the creation of an energy-focused geospatial system that will enable the user to visualise overlays of multivariate spatially and temporally varying data, model and predict trends and correlations, infer across areas of sparse data collection, and model the effects of changes on the system such as varying supply, demand or infrastructure. It will further allow for the simulation and testing of different strategies, for example, alternative charging point placement.We will address these challenges using our world-class expertise in Bayesian optimization and scalable Gaussian Process (GP) models. Using GPs will significantly improve the accuracy of AI models, over existing AI based tools. The successful application of this approach will enable the local energy sector to be more quantitative and targeted in its planning and prioritising of resources.The successful transition to net zero local energy systems requires not only cross-sectoral data, advanced geospatial and machine learning models and techniques, but also, crucially extensive collaboration with a broad set of stakeholders to properly understand their needs.We have already taken some initial steps in this process. For example, with respect to the EVs, we are in dialogue with a local council who are currently looking for immediate support with respect to the analysis of EV charger types, optimised roll-out of EV charging points and the implications for the capacity of local energy networks.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
国内基金
海外基金
高致病性2型猪链球菌Sao-M蛋白Epitope-focused新型疫苗的研究
  • 批准号:
    81701635
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    20.0万元
  • 批准年份:
    2017
  • 负责人:
    王晶
  • 依托单位:
基于本体的Deep Web搜索技术
  • 批准号:
    60973040
  • 项目类别:
    面上项目
  • 资助金额:
    29.0万元
  • 批准年份:
    2009
  • 负责人:
    左万利
  • 依托单位: