Energy Security Versus Fuel Poverty: Protecting Vulnerable Households During an Energy Crisis

我的博士学位旨在分析英国目前在燃料贫困和能源安全方面的经验，最终目的是提出地方和国家政策建议，以补救最严重的燃料贫困情况。在文献中，普遍认为家庭收入、家庭构成、建筑效率和能源价格是影响燃料贫困风险的主要因素；然而，目前在英国采用的低收入低能效(LILEE)对燃料贫困的定义与这套标准相矛盾，并将(潜在)不必要的关注置于能源性能证书(EPC)评级上。我对博士的第一项研究题为对低收入低能效(LILEE)方法衡量燃料贫困的经验批判，表明英格兰目前的燃料贫困指标(LILEE)严重低估了地面燃料贫困的真实比率(预印本见http://dx.doi.org/10.2139/ssrn.4583384)。这些发现是对诺丁汉和伦敦燃料贫困的两个阶段分析的结果：第一阶段涉及根据Lilee度量的有缺陷的标准从燃料贫困统计中遗漏的经济脆弱家庭的估计；而第二阶段分析在伦敦收集的调查数据，显示能源不安全(指家庭自我报告的能力/无能力负担足够的能源)比2022年冬季伦敦的Lilee燃料贫困率高出约145%。根据第一项研究的结果，我的博士学位剩余部分的研究问题如下：研究问题I：在英国引入新的/修订的燃料贫困指标的可行性如何？研究问题II：不同类型的健康问题或残疾如何影响燃料贫困/能源安全的风险？研究问题III：能否开发一种后自组织机器学习(ML)方法来增强离散结果建模框架中异质变量的可解释性和理解性？在这一点上，最主要的焦点将集中在英国新的或修订的燃料贫困指标的设计、可行性和建议(根据RQI)。这项研究的结果可以用来显示Lilee低估的程度，以及改善对真正燃料匮乏(即能源不安全)家庭的识别。在提出新的衡量标准后，将探索政治影响路线，以期塑造未来衡量英格兰燃料贫困的方法。

My PhD aims to analyse current experiences of fuel poverty and energy security in the UK, with the ultimate aim of generating local and national policy recommendations to remedy the most severe cases of fuel poverty. In the literature, there is a general consensus that household income, household composition, building efficiency and energy prices are the main contributing factors affecting fuel poverty risk; however, the Low Income Low Energy Efficiency (LILEE) definition of fuel poverty, which is currently adopted in England, contradicts this set of criteria, and places a (potentially) unwarranted level of focus on Energy Performance Certificate (EPC) ratings instead.The first study of my PhD, entitled An Empirical Critique of the Low Income Low Energy Efficiency (LILEE) Approach to Measuring Fuel Poverty, showed that the current fuel poverty metric in England (LILEE) significantly underestimates the true rate of on-the-ground fuel poverty (see http://dx.doi.org/10.2139/ssrn.4583384 for preprint). These findings are the result of a two-stage analysis of fuel poverty in Nottingham and London: stage 1 involved the estimation of financially vulnerable households omitted from fuel poverty statistics according to the flawed criteria of the LILEE metric; while stage 2 analysed survey data collected in London to show that energy insecurity (which refers to a household's self-reported ability/inability to afford sufficient energy) was around 145% higher than the LILEE fuel poverty rate for London in winter 2022. Given the findings of the first study, the research questions for the remainder of my PhD are as follows:Research Question I: How feasible is the introduction of a new/amended fuel poverty metric in England?Research Question II: How do different types of health problems or disabilities affect risk of fuel poverty/energy security?Research Question III: Can a post-hoc machine learning (ML) method be developed to enhance the interpretability and understanding of heterogenous variables in discrete outcome modelling frameworks?At this point, most focus will be afforded to the design, feasibility and proposal of a new or amended fuel poverty metric in England (as per RQI). The findings of this study can be used to show the degree of LILEE's underestimation, as well as improving the identification of truly fuel poor (i.e., energy insecure) households. Following the proposal of a new metric, political impact routes will be explored, with a view to shaping the future approach to measuring fuel poverty in England.