Development of an inexact risk-aversion optimization model for regional carbon constrained electricity system planning under uncertainty

Since carbon dioxide (CO2) emission reduction gains global concerns, power industry is one of the main sources of CO2 emission. Thus, carbon cap and trade scheme and the application of carbon capture and storage have been employed to mitigate CO2 emission. In consideration of these technologies and constraints, an inexact risk-aversion model based on interval two-stage stochastic programming (ITSP) and conditional value at risk method (CVaR) for multi-period electric system planning problem was developed in this study. Under the optimization framework, more realistic problems such as the demand growth, technology development and environmental policy changes were taken into consideration. CVaR was employed as a risk aversion criterion to reflect the decision maker’s risk preference. A case study for regional electric system planning was demonstrated to verify the capabilities of this optimal approach. The series results provided decision makers with trade-off between the expected system cost and CVaR. It provided valuable insights to make informed long term electric system planning decisions with respect to CCS technology and political and market uncertainties.