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Using economic model predictive control to design sustainable policies for mitigating climate change

Using economic model predictive control to design sustainable policies for mitigating climate change
Using economic model predictive control to design sustainable policies for mitigating climate change
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.
Chu, Bing
555a86a5-0198-4242-8525-3492349d4f0f
Duncan, Stephen
7ffefc44-ffdf-4cd1-aeac-de62671b3f1a
Papachristodoulou, Antonis
e3109556-2fc6-4de8-9324-2601777beab6
Hepburn, Cameron
58a9308b-87c0-48d0-ba98-8970bda7c694
Chu, Bing
555a86a5-0198-4242-8525-3492349d4f0f
Duncan, Stephen
7ffefc44-ffdf-4cd1-aeac-de62671b3f1a
Papachristodoulou, Antonis
e3109556-2fc6-4de8-9324-2601777beab6
Hepburn, Cameron
58a9308b-87c0-48d0-ba98-8970bda7c694

Chu, Bing, Duncan, Stephen, Papachristodoulou, Antonis and Hepburn, Cameron (2012) Using economic model predictive control to design sustainable policies for mitigating climate change. 51st IEEE Conference on Decision and Control, United States. 10 - 13 Dec 2012.

Record type: Conference or Workshop Item (Paper)

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.

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More information

Published date: 10 December 2012
Venue - Dates: 51st IEEE Conference on Decision and Control, United States, 2012-12-10 - 2012-12-13
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 345727
URI: https://eprints.soton.ac.uk/id/eprint/345727
PURE UUID: 802c9f13-9373-4e0c-80ae-b6d70bccd1c4
ORCID for Bing Chu: ORCID iD orcid.org/0000-0002-2711-8717

Catalogue record

Date deposited: 08 Apr 2013 08:32
Last modified: 29 Oct 2019 01:40

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