Demand profiles and flexibility insights from smart meter data

我们的能源系统需要快速脱碳，以减缓气候变化。建筑存量的能源需求是零碳过渡的重要组成部分;国内部门是冬季高峰期间最大的能源需求。大多数英国脱碳计划的核心是热力和运输的电气化，导致热泵（HP）和电动汽车（EV）充电的电力需求大幅增加。电力需求与供应的匹配对于能源安全和避免停电至关重要，可以通过灵活的发电，存储和需求侧响应（DSR）来实现。随着相对不灵活的低碳发电（风能，光伏，核能）的快速增长，储能和DSR预计将在每小时的时间尺度上平衡电网方面发挥重要作用。然而，DSR的真实的潜力，即响应信号而改变需求，取决于安装的技术、行为、房屋的物理特性和供暖系统。这是不属于特定技术试验的家庭没有很好的特点，因此真正的需求概况和潜力，以适应他们没有很好的定义。这个博士将通过分析智能电表数据，调查数据和能源性能证书（EPC）数据来解决这个令人兴奋的领域，以提供对家庭的需求与HP和EV的见解。通过温度监测，可以更深入地了解供暖的方式和时间，以及更好地了解房屋的热性能。成功的候选人将与国际知名的研究人员合作，不仅得到他们的主管的支持，而且还得到充满活力和熟练的研究团队的支持，他们在该领域进行尖端研究。他们还将加入更广泛的埃尔贝队列，以受益于高质量的培训和支持整个博士学位。该项目旨在分析智能电表数据，上下文调查信息和EPC数据，可能包括基准建模，以调查传统供暖和车辆的家庭需求曲线与HP和EV之间的差异。它将提供对这些技术在不同季节和人口统计中的真实的需求的见解。根据UCL对灵活性评级的研究，将探索根据价格信号（DSR）改变消费的灵活性，其中一个子集参与内部温度监测，以获得更详细的见解。

Rapid decarbonisation of our energy system is required to mitigate climate change. Energy demand from the built stock is an important component of the zero carbon transition; the domestic sector is the largest energy demand during the winter peak. Central to most plans to decarbonise the UK are the electrification of heat and transport, leading to significant increases in electricity demand from heat pumps (HPs) and for charging electric vehicles (EVs).Matching electricity demand with supply is critical for energy security and avoiding power cuts, and may be achieved through flexible generation, storage and demand side response (DSR). With the rapid increase in relatively inflexible low carbon generation (wind, PV, nuclear), storage and DSR are expected to play a major role in balancing the grid on an hourly timescale. However, the real potential for DSR, changing demand in response to a signal, depends on the technologies installed, behaviours, the physical properties of a home and the heating system. This is not well characterised for homes that fall outside specific technology trials and therefore the true demand profiles and potential to adapt them are not well defined.This PhD will address this exciting area by analysing smart meter data, survey data and energy performance certificate (EPC) data to provide insights into the demand from homes with HPs and EVs. Temperature monitoring may also be used to bring deeper insights into how and when heating is used, and to better understand the thermal performance of homes.The successful candidate will work with internationally respected researchers, supported not only by their supervisors but also by the vibrant and skilled research teams undertaking cutting-edge research in this area. They will also join the wider ERBE cohort to benefit from high quality training and support throughout their PhD.This project aims to analyse smart meter data, contextual survey information and EPC data, potentially including benchmark modelling, to investigate the difference between demand profiles for homes with conventional heating and vehicles to those with HPs and EVs. It will provide insights into the real demand from these technologies over different seasons and demographics. The flexibility to change consumption in response to a price signal (DSR) will be explored, building on UCL's research into flexibility ratings, with a sub-set participating in internal temperature monitoring to derive more detailed insight.