A resilient high-speed Digital Twin for critical energy infrastructure applications.

英国的配电网络正在经历自近一个世纪前电网形成以来最大的变化。直到十多年前，电网电力还由几个大型发电站生产，并且大部分是单向分配的。今天，主要是在到2050年实现温室气体净零排放的全球目标的推动下，我们已经看到可再生能源发电量达到创纪录的水平。电动汽车的快速普及以及人们希望摆脱天然气用于建筑供暖的愿望，将对我们当地的电力分配提出挑战，超出现有基础设施所能支持的范围。随着能源价格持续上涨，我们看到当地可再生能源发电和储能的激增，因为资产所有者可以获得实时能源市场定价和出口担保。在Vividgrd，我们正在开发数字孪生技术，以支持能源系统管理人员，业主和能源社区了解和运营他们的能源资产。我们帮助他们最大限度地提高其资产的运营和经济价值，同时帮助稳定当地分销网络。我们的运营平台提供持续的全系统能源监控，将数据解读为洞察力，可用于围绕资产采购做出合格的决策，以实现最大价值。除此之外，它还可以提供现场管理，根据当前的市场状况，季节变化和持续的实时学习来做出最佳能源资产利用的决策。由于能源需求经常变化，我们的系统不断寻找机会，以最大限度地提高现场性能或回报，并将提出合格的升级建议。

The UK's power distribution networks are undergoing their biggest change since the formation of the electricity grid almost a century ago. Until just over a decade ago, the grid power was produced by a few large-scale power stations and distributed mostly one-way. Today, driven primarily by global goals to achieve net-zero greenhouse gas emissions by 2050, we have seen record levels of renewable energy generation added to our grid. The rapid uptake of electric vehicles and the desire to move away from natural gas for building heating is set to challenge our local power distribution beyond the limits that the existing infrastructure can support. As energy prices continue to increase, we see a surge in local renewable power generation and energy storage as asset owners are given access to real-time energy market pricing and export guarantees.At Vividgrd, we are developing Digital Twin technology to support energy system managers, property owners and energy communities to understand and operate their energy assets. We help them maximise both the operational and economic value of their assets while helping to stabilise the local distribution network. Our operating platform provides continuous whole-system energy monitoring, interpreting data into insights which can be used to make qualified decisions around asset procurement for maximum value. In addition to this, it can provide site management, making decisions on optimal energy asset utilisation based on current market conditions, seasonal variation and continuous real-time learning. As energy requirements often change, our system continuously looks for opportunities to maximise site performance or return and will make qualified upgrade recommendations.