Using Control Theory to Design Sustainable Policies for Greenhouse Gas Emissions in the Presence of Model Uncertainty

在存在模型不确定性的情况下利用控制理论设计温室气体排放的可持续政策

• 批准号: EP/H03062X/1
• 负责人: Stephen Duncan
• 金额: $ 30.78万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2010
• 资助国家: 英国
• 起止时间: 2010 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FH03062X%2F1
• 关键词: Using; Control; Theory; Design; Sustainable

This project will apply concepts from modern robust control theory to develop algorithms for determining the optimal policy that both achieves sustainable levels of emissions of CO2 (and other greenhouse gases) and minimises the impact on the economy, but also explicitly addresses the high levels of uncertainty associated with predictions of future emissions. The aim of the optimal policy is to adjust factors such as the mix of energy generation methods and policies for reducing emissions from housing, industry and transport, in order to achieve a rate of emissions that will allow the UK to achieve its emissions targets while maximising economic growth as measured by discounted GDP. A key difficulty in determining the optimal policy is handling the uncertainty associated with the effect that the policy changes will have on the rate at which is CO2 emitted. One of the main conclusions of the Stern Review is that policies for stabilisation of CO2 emissions have to be implemented immediately and it is not possible to delay decisions until models with less uncertainty become available. If this conclusion is accepted (and indeed even if it is not) model uncertainty has to be incorporated as an integral part of the design of these policies. Currently, economists are unable to find optimal policies in the presence of uncertainty and most existing economic models address model uncertainty by running repeated what if scenarios to predict the outcome for a range of parameter values. This project will use concepts from robust control theory to develop tools for incorporating uncertainty directly into the design of the optimal emissions policy; the tools can then be applied to other existing models. Including uncertainty within the design quantifies the risk associated with the emissions policy, which allows policy makers and emitters of CO2 to incorporate risk within their strategic plans. The tools will be implemented on the ECCO (Evolution of Capital Creation Options) model that describes the dynamic evolution of CO2 levels emitted by UK economy. Unlike many other economic models, this model is based on the physical principles of mass and energy balances, which are used to derive economic measures.

该项目将应用现代稳健控制理论的概念来开发算法，以确定既能实现可持续的二氧化碳（和其他温室气体）排放水平，又能最大限度地减少对经济的影响的最优政策，同时还能明确解决与未来排放预测相关的高度不确定性。最优政策的目的是调整诸如能源生产方法和减少住房，工业和运输排放的政策的组合等因素，以实现排放率，使英国能够实现其排放目标，同时最大限度地实现经济增长（以贴现GDP衡量）。确定最优政策的一个关键困难是处理与政策变化将对二氧化碳排放率产生的影响有关的不确定性。《斯特恩评估报告》的一个主要结论是，必须立即实施稳定二氧化碳排放的政策，不可能在获得不确定性较小的模型之前推迟决策。如果这个结论被接受（事实上，即使它不被接受），模型的不确定性必须作为这些政策设计的一个组成部分被纳入。目前，经济学家无法在存在不确定性的情况下找到最优政策，大多数现有的经济模型通过运行重复的假设情景来预测一系列参数值的结果来解决模型的不确定性。该项目将使用鲁棒控制理论的概念来开发工具，将不确定性直接纳入最佳排放政策的设计；然后可以将这些工具应用于其他现有模型。在设计中包含不确定性可以量化与排放政策相关的风险，从而允许政策制定者和二氧化碳排放者将风险纳入其战略计划。这些工具将在ECCO（资本创造选择的演变）模型上实施，该模型描述了英国经济排放的二氧化碳水平的动态演变。与许多其他经济模型不同，该模型基于质量和能量平衡的物理原理，这些原理用于推导经济度量。

项目成果

Generalised absolute stability and sum of squares

广义绝对稳定性和平方和

• DOI: 10.1016/j.automatica.2013.01.006
• 发表时间: 2013
• 期刊: Automatica
• 影响因子: 6.4
• 作者: Hancock E

Algorithmic Construction of Lyapunov Functions for Power System Stability Analysis

• DOI: 10.1109/tcsi.2013.2246233
• 发表时间: 2013-09-01
• 期刊: IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
• 影响因子: 5.1
• 作者: Anghel, Marian;Milano, Federico;Papachristodoulou, Antonis
• 通讯作者: Papachristodoulou, Antonis