An Interval Probability-based Inexact Two-stage Stochastic Model for Regional Electricity Supply and GHG Mitigation Management under Uncertainty
- 1 North China Electric Power University, Key Laboratory of Regional Energy System Optimization, Ministry of Education, Beijing, China
- 2 North China Electric Power University, Key Laboratory of Regional Energy System Optimization, Ministry of Education, Beijing, China
- 3 North China Electric Power University, Key Laboratory of Regional Energy System Optimization, Ministry of Education, Beijing, China
- 4 North China Electric Power University, Key Laboratory of Regional Energy System Optimization, Ministry of Education, Beijing, China
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.
- C. B. Field and M. R. Raupach, “The Global Carbon Cycle: Integrating Humans, Climate, and the Natural World,” Island Press, 2004.
- IPCC, “Climate Change Contribution of Working Group I to the Fourth Assessment Report of the Intergovern Mental Panel on Climate Change,” Cambridge, United Kingdom/New York, NY, USA: Cambridge University Press, 2007.
- S. E. Fleten and T. K. Kristoffersen, “Short-term HydroPower Production Planning by Stochastic Programming,” Computers and Operations Research, Vol. 35, No. 8, 2008, pp. 2656-2671. doi:10.1016/j.cor.2006.12.022
- Q. G. Lin and G. H. Huang, “IPEM: An interval-parameter energy systems planning model,” Energy Sources A: Recovery, Utilization, and Environmental Effects, Vol.30, No.14, 2008, pp.1382-1399. doi:10.1080/15567030801929043
- Y.Y. Liu, “A dynamic two-stage energy systems planning model for Saskatchewan, Canada,” M. S. Dissertation, Faculty of Graduate Studies and Research, Regina, Saskatchewan, Canada. 2007.
- L. Liu, G. H. Huang, G. A. Fuller, A. Chakma and H. C. Guo, “A Dynamic Optimization Approach for Nonrenewable Energy Resources Management Under Uncertainty,” Journal of Petroleum Science and Engineering, Vol. 26, 2000, pp. 301-309. doi:10.1016/S0920-4105(00)00044-9
- Y. P. Li, G. H. Huang, S. L. Nie, X. H. Nie and I. Maqsood, “An Interval-parameter Two-stage Stochastic Integer Programming Model for Environmental Systems Planning under Uncertainty,” Engineering Optimization, Vol. 38, No. 4, 2006, pp. 461-483. doi:10.1080/03052150600557742
- R. R. Yager, “Decision Making under Interval Probabilities,” International Journal of Appeoximate Reasoning, Vol. 22, No. 3, 1999, pp. 195-215. doi:10.1016/S0888-613X(99)00028-6
- G. H. Huang and D. P. Loucks, “An Inexact Two-stage Stochastic Programming Model for Water Resources Management under Uncertainty,” Civil Engineering and Environmental Systems, Vol. 17, 2000, pp. 95-118. doi:10.1080/02630250008970277
- Y. L. Xie, Y. P. Li, G. H. Huang and Y. F. Li, “An Interval Fixed-mix Stochastic Programming Method for Greenhouse Gas Mitigation in Energy Systems under Uncertainty,” Energy, Vol. 35, 2010, pp. 4627-4644. doi:10.1016/j.energy.2010.09.045