Stochastic and Robust Modelling of Mitigation and Adaptation Policies Applied to Regional Systems
Andrey, Christopher
Stochastic and Robust Modelling of Mitigation and Adaptation Policies Applied to Regional Systems - 2015.
67
This article presents the long-term techno-economic prospective model ETEM-AR that aims to help decision-makers to analyze the future of the energy mix and energy use at a regional level in the context of climate change. The model incorporates a description of the two potential paths one may choose to follow when confronting the impacts of climate change : mitigation and adaptation, together with the corresponding technologies. The inherent uncertainties in the evaluation of the importance of climate change and of its consequences on the energy sector are treated via stochastic programming and robust optimization. À set of contrasted scenarios is used to describe the possible future consequences of climate change on key parameters of the energy system, such as the reduction of the efficiency of some of the technologies. By comparing the results emerging from the stochastic analysis performed with these scenarios with the analysis of deterministic scenarios, one can understand the necessity, or the absence of it, of investing in certain adaptation technologies prior to the unfolding of the considered uncertainties. The robust optimization techniques are used to ensure the optimal strategy remains a good strategy if some parameters vary in a given interval. The main effect of using a robust analysis is the emergence of a diversification of the technology choices. The model, ETEM-AR, is illustrated here through its application to the French region of Midi-Pyrénées.
Stochastic and Robust Modelling of Mitigation and Adaptation Policies Applied to Regional Systems - 2015.
67
This article presents the long-term techno-economic prospective model ETEM-AR that aims to help decision-makers to analyze the future of the energy mix and energy use at a regional level in the context of climate change. The model incorporates a description of the two potential paths one may choose to follow when confronting the impacts of climate change : mitigation and adaptation, together with the corresponding technologies. The inherent uncertainties in the evaluation of the importance of climate change and of its consequences on the energy sector are treated via stochastic programming and robust optimization. À set of contrasted scenarios is used to describe the possible future consequences of climate change on key parameters of the energy system, such as the reduction of the efficiency of some of the technologies. By comparing the results emerging from the stochastic analysis performed with these scenarios with the analysis of deterministic scenarios, one can understand the necessity, or the absence of it, of investing in certain adaptation technologies prior to the unfolding of the considered uncertainties. The robust optimization techniques are used to ensure the optimal strategy remains a good strategy if some parameters vary in a given interval. The main effect of using a robust analysis is the emergence of a diversification of the technology choices. The model, ETEM-AR, is illustrated here through its application to the French region of Midi-Pyrénées.
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