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twinCity -- Physics Informed Digital Twins for Urban Powerplants

twinCity——城市发电厂的物理数字孪生

基本信息

批准号：
10044503
负责人：
金额：
$ 6.37万
依托单位：
DIGILAB SOLUTIONS LTD
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
起止时间：
2022 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=10044503
关键词：
twinCity Physics Informed Digital Twins

项目摘要

Solar energy is a clean renewable energy source, however it comes with significant challenges to deploy at scale. This is because energy production does not always align with energy demand, and excessive energy cannot either be easily fed back into the larger electric grid, or the viability of many energy storage solutions is not clear due to losses at conversion or cost. Solving this challenge is central to meeting UK's commitment to generating all our power renewably by 2035\.In this project digiLab will develop a novel digital pipeline to accurately and efficiently optimize the design of urban powerplants using physics informed digital twins. The solution will use self -learning algorithms to optimal balance, production / demand and storage. The innovative approach provide easy to train and fast deployable solutions not currently available in the market, using bleeding edge methods in so-called "Physics Informed digital twins".Whilst the deployment of urban solar production and intelligent control has broad application across the UK and internationally. In this Fast Start project we will focus on a 30MW solar farm on the roof tops of Marsh Barton Industrial Estate, on the edge of Exeter. UPS is looking to generate sufficient power from local solar to take 150 electric delivery vehicles off grid. The opportunity for the particular case study considered at Marsh Baton is clear. By electrifying 150 vehicles with renewable solar, it is equivalent to the equivalent carbon absorption of 200,000 trees annually. Yet such a solution is not possible without our intelligent control algorithm living beneath.This project paves the way to using smart digital technologies to maximise the economic viability of locally balanced energy solution - a necessary step in our net zero journey.

太阳能是一种清洁的可再生能源，但它在大规模部署方面面临着重大挑战。这是因为能源生产并不总是与能源需求保持一致，过多的能源不能轻易地反馈到更大的电网中，或者由于转换或成本损失，许多储能解决方案的可行性并不明确。解决这一挑战是实现英国到2035年实现所有可再生能源发电的承诺的核心。在该项目中，digiLab将开发一种新型的数字管道，使用物理数字孪生模型准确有效地优化城市发电厂的设计。该解决方案将使用自学习算法来优化平衡、生产/需求和存储。这种创新的方法提供了目前市场上没有的易于培训和快速部署的解决方案，使用所谓的“物理信息数字孪生”中的前沿方法。同时，城市太阳能生产和智能控制的部署在英国和国际上有广泛的应用。在这个快速启动项目中，我们将重点关注位于埃克塞特边缘的Marsh巴顿工业区屋顶上的30兆瓦太阳能发电场。UPS正在寻求从当地太阳能中产生足够的电力，以使150辆电动送货车脱离电网。Marsh Baton所考虑的特定案例研究的机会是显而易见的。通过使用可再生太阳能为150辆汽车充电，相当于每年20万棵树的碳吸收量。然而，如果没有我们的智能控制算法，这样的解决方案是不可能实现的。该项目为使用智能数字技术最大限度地提高本地平衡能源解决方案的经济可行性铺平了道路-这是我们净零旅程的必要一步。