Cost-benefit analysis and multi-criteria optimisation for low-carbon heating strategy options

低碳供热策略选择的成本效益分析和多标准优化

• 批准号: 2270149
• 金额: --
• 依托单位: University of Bath
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2270149
• 关键词: Cost; benefit; analysis; multi; criteria

Demands for space and water heating constitute a significant proportion of the total energy demands in the UK and are currently predominantly satisfied through natural gas, which makes the heat sector a large emitter of carbon dioxide and therefore an important sector to decarbonise.There are many alternative low-carbon heating strategy options for the UK. The aim of the project is to evaluate the different strategies using cost-benefit analysis as well as multi-criteria optimisation in order to compare different optimal scenarios under different stakeholder preferences, quantify trade-offs between different strategy options and determine a set of value chains for low-carbon heating that have the greatest potential for deployment in the UK. The 3.5-year PhD project will be carried out as follows:1. In the first year, a comprehensive literature review and high-level cost-benefit analysis will be performed on the main strategy options identified. An exhaustive list of criteria will be identified in order to construct a cost-benefit model for each of the strategy options.The costs and benefits of each heating strategy option with respect to each criterion will be identified from academic literature, government, and by conducting stakeholder surveys. The costs and benefits will be calculated for quantitative criteria and qualitative criteria will be assigned rankings. Sensitivity (or "what-if") analyses will be performed to test the robustness of the cost-benefit model to uncertainties in key parameters. The results will be presented as cost-benefit matrices and radar charts in order to compare all of the strategy options and shortlist 2-3 of the best options that will be examined in detail in the next stage of the PhD.2. In the remaining 2.5 years the 2-3 strategy options will be explored through systems modelling and systematic multi-criteria optimisation approaches.A value chain modelling and optimisation approach will be used to determine the system-wide impacts of implementing the various strategy options.The Value Web Model will be adapted to model the integrated value chains for low-carbon heat. The model will account for the spatial dependence of key parameters. Detailed modelling of the temporal aspects will also be considered. The solution of an optimisation problem using the Value Web Model provides the combination of heating strategy options, where and when they are deployed and what the impacts are.A multi-criteria optimisation will be performed, wherein a series of optimisation runs will be conducted, using combinations of different weightings for the different criteria. This will generate a "Pareto set" of optimal solutions, which encapsulates the trade-off between different strategy options. Specific scenarios extracted from the Pareto sets will be analysed and the most promising value chains for low-carbon heating that have the greatest potential for deployment will be identified. Sensitivity and stochastic analyses will be performed to ensure that the solutions are robust with respect to the uncertainties in the system.

空间和水加热的需求构成了英国总能源需求的很大一部分，目前主要通过天然气来满足，这使得供热部门成为二氧化碳的主要排放者，因此是脱碳的重要部门。英国有许多替代低碳供热战略选择。该项目的目的是使用成本效益分析和多标准优化来评估不同的策略，以比较不同利益相关者偏好下的不同最佳方案，量化不同策略选项之间的权衡，并确定一套在英国部署潜力最大的低碳供暖价值链。3.5年的博士项目将进行如下：1。在第一年，将对确定的主要战略选择进行全面的文献审查和高级别的成本效益分析。将确定一份详尽的标准清单，以便为每个战略选项构建成本效益模型。将从学术文献、政府和利益相关者调查中确定每个供热战略选项相对于每个标准的成本和效益。成本和效益将计算定量标准和定性标准将分配排名。将进行敏感性（或“假设”）分析，以测试成本效益模型对关键参数不确定性的稳健性。结果将以成本效益矩阵和雷达图的形式呈现，以便比较所有的战略选项和最佳选项的短名单2-3，这些选项将在PhD的下一阶段详细研究。在剩下的两年半时间里，将通过系统建模和系统化多标准优化方法探索2-3个战略选项。将使用价值链建模和优化方法来确定实施各种战略选项的全系统影响。将采用价值网模型来模拟低碳供热的综合价值链。该模型将考虑关键参数的空间依赖性。还将考虑时间方面的详细建模。使用价值网模型的优化问题解决方案提供了加热策略选项的组合，这些选项在何时何地部署以及影响如何。将执行多标准优化，其中将使用不同标准的不同权重组合进行一系列优化运行。这将产生一个“帕累托集”的最佳解决方案，其中封装了不同的战略选择之间的权衡。将分析从帕累托集合中提取的具体情景，并将确定最有希望、部署潜力最大的低碳供暖价值链。将进行敏感性和随机分析，以确保解决方案对于系统中的不确定性具有鲁棒性。