An Interval Probability-based Inexact Two-stage Stochastic Model for Regional Electricity Supply and GHG Mitigation Management under Uncertainty

Yulei Xie, Guohe Huang, Wei Li, Ye Tang

North China Electric Power University, Key Laboratory of Regional Energy System Optimization, Ministry of Education, Beijing, China.

DOI: 10.4236/epe.2013.54B157                

Abstract

In this study, an interval probability-based inexact two-stage stochastic (IP-ITSP) model is developed for environmental pollutants control and greenhouse gas (GHG) emissions reduction management in regional energy system under uncertainties. In the IP-ITSP model, methods of interval probability, interval-parameter programming (IPP) and two-stage stochastic programming (TSP) are introduced into an integer programming framework; the developed model can tackle uncertainties described in terms of interval values and interval probability distributions. The developed model is applied to a case of planning GHG -emission mitigation in a regional electricity system, demonstrating that IP-ITSP is applicable to reflecting complexities of multi-uncertainty, and capable of addressing the problem of GHG-emission reduction. 4 scenarios corresponding to different GHG -emission mitigation levels are examined; the results indicates that the model could help decision makers identify desired GHG mitigation policies under various economic costs and environmental requirements.

Keywords

Interval Probability; Inexact Two-stage Stochastic Programming; Electricity Generation; GHG-Mitigation; Energy System

Conflicts of Interest

The authors declare no conflicts of interest.

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