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Increasing the adoption of Digital Twin solutions within the built environment for achieving net zero

Increasing the adoption of Digital Twin solutions within the built environment for achieving net zero
在建筑环境中增加数字孪生解决方案的采用,以实现净零排放
批准号:
10045724
负责人:
金额:
$6.24万
依托单位:
依托单位国家:
英国
项目类别:
Grant for R&D
财政年份:
2022
资助国家:
英国
项目状态:
已结题
起止时间:
2022 至 --

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中文摘要
翻译
铜联盟研究所声称,BACS有潜力节省欧洲建筑物总能耗的15-22%。它具有很高的成本效益,效益是成本的九倍。更重要的是对减缓气候变化的贡献。到2035年,减少2.6亿至4.19亿吨二氧化碳将使欧洲的燃料燃烧排放量减少8-13%。UKGBC的终生碳路线图表明,英国建筑环境目前占英国温室气体排放总量的25%。如果将地面交通纳入建筑环境的范围内,英国排放的总份额将增加到42%。新建建筑物的能源效率更高,但到2050年,80%的建筑物已经建成,因此一个主要的优先事项是使我们现有的库存脱碳。因此,我们的解决方案专注于提高现有商业建筑的能源效率。该项目将加速人工智能解决方案在建筑环境中的采用。智能建筑的AI可以使安装的BACS系统和设备更加节能。人工智能经过训练,可以从过去的数据和行为中学习电力、温度等能源需求。根据过去的经验,人工智能可以在需要时预测电力的最佳使用,并可以理解“假设”情景。尽管有这些好处,但小型商业建筑的业主根本没有时间、资源或资金来实施尖端技术。这是因为对于小型项目来说,初始安装的成本和技术要求都很高。我们将通过连接器将我们的Digital Twin AI平台集成到任何传统的BACS系统中,以使建筑更高效,更智能。该解决方案的优势在于,它已经与许多BACS系统集成,并实施AutoML来创建数字孪生,减少了技术技能,从而允许更广泛的部署。通过我们的数字孪生集成平台,可以开发和完善脱碳计划,评估多个选项,模拟结果并实时跟踪进度,以确保您的能效目标如期实现。
英文摘要
The Copper Alliance Institute claims that BACS has the potential of saving 15-22% of the total energy consumption in European buildings. It is highly cost-effective, with benefits being nine times higher than costs. Even more significant are the contributions toward climate change mitigation. A reduction of 260 to 419 million tons of CO2 would reduce Europe's emissions from fuel combustion by 8-13% by 2035\.UKGBC's Whole Life Carbon Roadmap illustrates that the UK Built Environment is currently responsible for 25% of total UK greenhouse gas emissions. If surface transport is included within the scope of the built environment, the total share of UK emissions increases to 42%.Newly constructed buildings are more energy efficient, but 80% of buildings in 2050 have already been built, so a major priority is decarbonising our existing stock. Hence, we focused our solution to increase the energy efficiency in existing commercial buildings.This project will accelerate the adoption of AI solutions within the built environment. AI for Smart Buildings can make installed BACS systems and equipment more energy efficient. AI is trained to learn energy requirements such as electricity, temperature from past data and behaviour. Depending on past experiences, AI can predict the optimum use of power when required and 'what if' scenarios can be understood.Despite the benefits, the owners of small commercial buildings simply don't have the time, resources or capital to implement cutting-edge technologies. This is because the cost and technical requirement for the initial installation are high for small-size projects.We will integrate our Digital Twin AI platform into any traditional BACS system with connectors to make the building more efficient and smarter. Advantages of this solution are that it already integrates with many BACS systems and AutoML is implemented to create the Digital Twin, reducing the technical skills, thus allowing for a wider range of deployments.With our digital twin integrated platform, decarbonization initiatives can be developed and refined, evaluate several options, simulate the outcomes and track progress in real-time to ensure your energy efficiency targets are on track.
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