Quantitative Evaluation of the Feasibility of Meeting Emission Targets with a Chance Constrained Energy System Model

Abstract

Recently, researchers have incorporated uncertainties into energy system models with stochastic programming-based models. Most studies focused on meeting greenhouse gas (GHG) reduction targets considering various uncertainties. However, meeting targets leads to dramatic cost increases. At the same time, there is a risk to fail to meet the targets if enough uncertainties are not considered. Therefore, it is important to find a balance between cost and risk. In this study, we define the risk as to the feasibility of meeting GHG reduction targets and evaluate the risk by using a chance-constrained model. We apply the model to South Korea and analyze the trade-off between total cost and the risk.