An inexact credibility chance-constrained integer programming for greenhouse gas mitigation management in regional electric power system under uncertainty

Abstract

Electric power system (EPS) management considering greenhouse gas (GHG) mitigation is a challenging task, since many system parameters such as electric demand, resource availability, system cost as well as their interrelationships may appear uncertain. To reflect these uncertainties, in this study, an interval-parameter credibility constrained programming (ICCP) method was developed for electric power system planning in light of GHG mitigation. The method was advantageous in tackling uncertainties expressed as not only fuzzy possibilistic distributions associated with the right-hand-side components of model constraints but also discrete intervals in the objective function. In addition, ICCP allowed satisfaction of system constraints at specified confidence level, leading to model solutions with low system cost under acceptable risk magnitudes. The obtained results indicated that stable intervals for the objective function and decision variables could be generated, which were useful for helping decision makers identify the desired electric power generation patterns, capacity expansion schemes and GHG-emission reduction under complex uncertainties, and gain in-depth insights into the trade-offs between system economy and reliability.