TITLE:
An Interval Probability-based Inexact Two-stage Stochastic Model for Regional Electricity Supply and GHG Mitigation Management under Uncertainty
AUTHORS:
Yulei Xie, Guohe Huang, Wei Li, Ye Tang
KEYWORDS:
Interval Probability; Inexact Two-stage Stochastic Programming; Electricity Generation; GHG-Mitigation; Energy System
JOURNAL NAME:
Energy and Power Engineering,
Vol.5 No.4B,
November
11,
2013
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.