Using economic Model Predictive Control to design sustainable policies for mitigating climate change

Abstract

Reducing greenhouse gas emissions is now an important and pressing matter. Systems control theory, and in particular feedback control, can contribute to the design of policies that achieve sustainable levels of emissions of CO2 (and other greenhouse gases) while minimizing the impact on the economy, and at the same time explicitly addressing the high levels of uncertainty associated with predictions of future emissions. In this paper, preliminary results are described for an approach where economic Model Predictive Control (MPC) is applied to a Regional dynamic Integrated model of Climate and the Economy (RICE model) as a test bed to design savings rates and global carbon tax for greenhouse gas emissions. Using feedback control, the policies are updated on the basis of the observed emissions, rather than on the predicted level of emissions. The basic structure and principle of the RICE model is firstly introduced and some key equations are described. The idea of introducing feedback control is then explained and economic MPC is applied to design policies for CO2 emissions. Simulation results are presented to demonstrate the effectiveness of the proposed method for two different scenarios. Feedback control design provides a degree of robustness against disturbances and model uncertainties, which is illustrated through a simulation study with two particular types of uncertainties. The results obtained in this paper illustrate the strength of the proposed design approach and form the basis for future research on using systems control theory to design optimal sustainable policies.