Delivering Energy Flexible Built Environments through digital twins

问题或挑战2019年第三季度，英国可再生能源发电量首次超过化石燃料发电量。这种受欢迎的转变的可持续性和弹性要求将所谓的能源灵活性纳入国家能源系统。到目前为止，从供应方管理的能源灵活性是使发电厂的电力生产同步以满足需求的能力。通过更大程度的电气化来脱碳供热和运输的紧迫性，以及管理可再生能源供应的间歇性，将不可避免地增加电网的压力。因此，迫切需要新的和熟练的能源需求同步机制，以适应电力供应的变化。MRES/PHD项目目标该项目将建立在数字配对的最新进展基础上，并开发新的模拟能力，以便能够熟练地在地区范围内对建筑物进行需求侧管理。它将研究可以量化建筑物的能源灵活性的方法，以及它们对未来冲击和变化的弹性，并对不确定性进行量化。PHD项目描述通过热和电池存储，或通过对建筑物内活动和过程的时间管理，可以实现需求的灵活性。然而，只有在地区范围内才能充分发挥潜力，在地区范围内，可以动态和集体地跟踪和管理来自多个建筑的各种活动和流程的需求。这带来了挑战，其中(A)能源需求必须按活动分类，并在空间和时间上分配(B)建筑物中的能源消耗活动和过程必须量化为依赖时间的灵活性指数，(C)必须测试主动需求-响应和控制的模型，其中包括短期预测。MRES部分-对结合使用能源监测和建筑物模拟建模的最先进的文献回顾-对一小部分大学建筑的概念验证研究，制定了方法的一到两个组成部分

Problem or ChallengeIn the third quarter of 2019, the UK generated more electricity from renewables than from fossil fuels for the first time. The sustenance and resilience of this welcome shift necessitates building in so-called energy flexibility into the national energy system. Hitherto managed from the supply side, energy flexibility is the ability to synchronise the production of electricity from power plants to match demand. The urgency of decarbonising heat and transport through greater degrees of electrification, along with managing the intermittent nature of supply from renewables will inevitably increase the pressure on the grid. Therefore,there is a pressing need for new and adept mechanisms of synchronising energy demand to adapt to variations in electricity provision.MRes/PhD project objectivesThis project will build upon recent advancements in digital twinning and develop novel simulation capabilities that enable adept demand-side management of buildings at district scales. It will investigate methods that can quantify energy flexibility of buildings, and their resilience to future shocks and changes with quantification of uncertainties.PhD project descriptionFlexibility in demand can be achieved through thermal and battery storage, or through time management of activities and processes within buildings. However, the full potential can only be accrued at district-scales where demand from various activities and processes across multiple buildings can be tracked and managed dynamically and collectively. This poses challenges, whereby (a) energy demand must be disaggregated by activities, and allocated spatially and temporally (b) energy consuming activities and processes in buildings must be quantified as a time-dependent flexibility index, (c) models of active demand-response andcontrol must be tested, which includes short term forecasting.MRes component- A thorough literature review of the state-of-the-art in the combined use of energy monitoring and simulation modelling of buildings- A proof-of-concept study of a small set of university buildings, which develops one or two components of the methodology