Designing Sustainable Policies for Greenhouse Gas Emissions
This project uses 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. Concepts from robust control theory are used 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.
This research is supported by EPSRC project EP/H03062X/1.
Related Project Publications
- B. Chu, S. R. Duncan and A. Papachristodoulou. A Model Reduction Method for Large Scale Networks. To appear in Proc. 50th IEEE Conference on Decision and Control and European Control Conference, Orlando, FL, 2011.
- B. Chu, S. R. Duncan and A. Papachristodoulou. A Model for Using Control Theory to Design Sustainable Policies for Greenhouse Gas Emissions. To appear in Proc. IEEE Multiconference on Systems and Control, Denver, CO, 2011.
- B. Chu, S. R. Duncan, A. Papachristodoulou and C. Hepburn. Analysis and Control Design of Sustainable Policies for Greenhouse Gas Emissions. To appear in Proc. International Conference on Sustainable Thermal Energy Management in the Process Industry, Newcastle, UK, 2011.