Distributional Effects of Dynamic Pricing for Responsive Electricity Demand (DEePRED)

高峰电力需求正成为英国电网日益严重的问题，因为它会导致供需失衡，对系统成本和环境产生负面影响。住宅部门负责约三分之一的总电力需求和高达40%的高峰需求。在需求高峰期间，批发市场的电价可能从不足0.03英镑/千瓦时波动到高达0.29英镑/千瓦时。通过响应电力需求和减少峰值，使用时间关税为系统提供了显著的潜在好处。例如，这可以减少对新一代和网络容量的需求。然而，更多成本反射定价的影响将因消费者而异。特别是那些在用电高峰期用电的人，他们无法改变自己的消费模式，最终可能会付出更多的钱。了解使用时间关税的分配效应对于确保能源账单的可负担性，同时使需求更加灵活至关重要。虽然对燃料贫困与电力消费总量的关系进行了研究，但对动态关税对不同社会人口群体的影响知之甚少。DEePRED将填补这一空白。DEePRED的总体目标是分析使用时间关税的分配影响，以期确定可能通过提供需求灵活性而大大受益或处于不利地位的用户群。该项目将分析来自英国国家统计时间使用调查办公室的10分钟分辨率时间使用活动数据，以期获得不同人群在一天中占据家庭并进行能源相关活动的时间信息。时间使用数据将与温度、日照、家用电器的数量和典型消耗以及住宅类型等参数数据相结合，得出负荷概况。这要归功于活动计划的执行。然后，负载配置数据将用于计算不同消费者群体的消费者账单如何根据程式化的使用时间关税发生变化。

Peak electricity demand is becoming an increasingly significant problem for UK electricity networks as it causes imbalances between demand and supply with negative impacts on system costs and the environment. The residential sector is responsible for about one third of overall electricity demand and up to 40% of peak demand. During peak demand, electricity prices in wholesale markets could fluctuate from less than £0.03/kWh to as much as £0.29/kWh. Time of Use tariffs offer significant potential benefits to the system by enabling responsive electricity demand and reducing peaks. For example, this could reduce the need for new generation and network capacity. However, the impact of more cost-reflective pricing will vary between consumers. In particular, those who consume electricity at more expensive peak periods, and who are unable to change their consumption patterns, could end up paying significantly more. Understanding the distributional effects of Time of Use tariffs becomes vital to ensuring affordability of energy bills, whilst making demand more flexible. Whilst there is research on fuel poverty in relation to aggregate level of consumption of electricity, little is known about the effects of dynamic tariffs on different socio-demographic groups. DEePRED will fill this gap.The overall aim of DEePRED is to analyse the distributional effects of Time of Use tariffs with a view to identify clusters of users which might significantly benefit or be disadvantaged through the provision of demand flexibility. The project will analyse 10-minute resolution time use activity data from the UK Office for National Statistics Time Use Survey with a view to derive information about times of the day in which different groups of people occupy households and carry out energy-related activities. The time use data will be combined with parameter data on temperatures, sunlight, number and typical consumption of household appliances and dwelling types to derive load profiles. This will take place thanks to the implementation of activity schemes. Load profiles data will then be used to calculate how consumer bills may change for different groups of consumers on stylised Time of Use tariffs.