RCUK Innovation Fellowship in UK Housing Stock Decarbonisation

英国已经开发了几个模型来预测英国住房存量的能源和相关碳排放。根据采用这些翻新方案的不同情况，这些指标被用来预测替代翻新方案(例如，隔热墙和屋顶、通风、安装更高效的供暖系统)所产生的能源消耗和碳排放的减少。现有的模型都不能预测翻修备选方案的采用情况，以应对旨在刺激这些方案的具体政策措施。这些措施的例子包括建筑法规、财政补贴、税收减免和教育活动。为了解决这一不足，我们将开发一个新的原型社会模拟平台，该平台将模拟家庭投资于减少能源改造方案和/或改变其能源使用行为的可能性，以回应政策措施。该平台将与新的动态住房存量能源模型相结合，使我们能够预测家庭脱碳决定对全国的影响。这个结合了物理和社会模拟的平台将被部署在英国，以评估替代住房脱碳政策措施的有效性。为了使我们能够设计和校准社交模拟平台，我们还将设计和进行一项试点的英国房主社交调查。这将与现有的二级数据集相辅相成，以表征家庭原型及其属性(以补充现有住房)。

Several models have been developed in the UK to predict the energy and associated carbon emissions of the UK housing stock. These have been used to predict the reductions in energy use and carbon emissions arising from alternative renovation options (e.g. insulating walls and roofs, draught stripping, fitting more efficient heating systems), based on different scenarios in terms of the adoption of these renovation options. None of the existing models is able to predict the adoption of renovation options in response to specific policy measures that are designed to stimulate them. Examples of these include building regulations, financial subsidies, taxation relief and educational campaigns. To address this shortfall, we will develop a new prototype social simulation platform that will model the likelihood that households will invest in energy reducing renovation options and / or change their energy using behaviours, in response to policy measures. This platform will be coupled with a new dynamic housing stock energy model, enabling us to predict the nationwide impacts of households' decarbonisation decisions.This combined physical and social simulation platform will be deployed in the UK to evaluate the effectiveness of alternative housing decarbonisation policy measures. To enable us to design and calibrate the social simulation platform, we will also design and conduct a pilot UK homeowners' social survey. This will be complemented with existing secondary datasets, to characterise household (to complement existing housing) archetypes and their attributes.