Full-infinite interval two-stage credibility constrained programming for electric power system management by considering carbon emission trading

Abstract

In this study, a full-infinite interval two-stage credibility constrained programming (FITCP) method is developed for optimizing electric power system (EPS) by considering CO2 mitigation and air pollutant emission control. Through integrating full-infinite programming (FIP), interval two-stage programming (ITSP) and credibility constrained programming (CCP) within a general framework, the developed FITCP method can tackle multiple uncertainties in terms of interval values (both crisp and functional interval values), probabilistic and possibilistic distributions. Then, a FITCP-based electric power system (FITCP-EPS) model has been formulated for EPS planning where carbon emission trading (CET) scheme and air pollutant emission limitation are introduced to cope with the problem of carbon and air pollutant mitigation. Scenarios in response to diverse carbon mitigation levels, different trading schemes and different environmental policies are generated. Moreover, sensitive analysis and value of information analysis are conducted to help decision makers to have a clear view of the effects of data variation and uncertainty data collection. Results reveal that (i) CET scheme can bring more economic benefits for power plants especially when mitigation level is high; (ii) whether the CET is carried out or not, a corresponding construction of carbon capture and storage infrastructure should be implemented to achieve the mitigation target; (iii) the expected system benefit would increase [0, 2.17] % by resolving the uncertainty of CO2 emission levels. The results also indicate that FITCP-EPS model can not only provide an effective linkage between the pre-regulated generation targets and environmental policies, but also generate more decision options under different credibility levels and CO2 emission levels, which are useful for helping decision makers to make appropriate generation targets, plan electricity generation mix, as well as gain in-depth insight into the effects of carbon emission trading and pollutant control on EPS.