An inexact robust nonlinear optimization method for energy systems planning under uncertainty

In this study, an interval-robust nonlinear optimization (IRNO) method is developed for planning energy system and managing CO2 emissions with trading scheme, through incorporating interval-parameter programming (IPP) within a robust optimization (RO) framework. In the modeling formulation, two recourse actions were adopted to make the model robustness.One of recourse actions was launched to capture the notion of risk in stochastic programming. The other recourse action was seized the risk of shortage electricity amount during the energy system programming process, which successfully emphasizing the safety of energy system under high-variability. The IRNO method is applied to a case of planning energy system with considering the CO2 emissions management. A number of solutions under different robustness levels have been generated. The results obtained can help generate desired decision alternatives that will be able to enhance energy supply safety with a low system-failure risk level and particularly useful for risk-aversive decision makers in handling high-variability conditions.