An interval-valued minimax-regret analysis approach for the identification of optimal greenhouse-gas abatement strategies under uncertainty

Energy Policy

Volumn 39, Issue 7, 2011, Pages 4313-4324

  Li, Y P ^a   Huang, G H ^a   Chen, X ^b  

^a NORTH CHINA ELECTRIC POWER UNIVERSITY   (China)

^b XINJIANG INSTITUTE OF ECOLOGY AND GEOGRAPHY   (China)

Author keywords

Energy systems; Greenhouse gas; Minimax regret

Indexed keywords

ANALYSIS APPROACH; CAPACITY EXPANSION; DECISION MAKERS; ENERGY SYSTEMS; FIXED CHARGES; GHG EMISSION; GHG MITIGATION; INTERVAL-VALUED; LONG TERM PLANNING; MINIMAX REGRET; MIXED-INTEGER LINEAR PROGRAMMING; OPTIMAL STRATEGIES; RENEWABLE ENERGY SOURCE; WIND AND SOLAR POWER;

DYNAMIC ANALYSIS; FOSSIL FUELS; GLOBAL WARMING; GREENHOUSE GASES; INTEGER PROGRAMMING; OPTIMIZATION; SOLAR ENERGY;

UNCERTAINTY ANALYSIS;

DECISION MAKING; DYNAMIC ANALYSIS; EMISSION CONTROL; ENERGY PLANNING; ENERGY RESOURCE; GREENHOUSE GAS; LINEAR PROGRAMING; METHODOLOGY; RENEWABLE RESOURCE;

EID: 79957640366     PISSN: 03014215     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enpol.2011.04.049     Document Type: Article

References (39)

1. Albornoz V.M., Benario P., Rojas M.E. A two-stage stochastic integer programming model for a thermal power system expansion. International Transactions in Operational Research 2004, 11:243-257.
2. Baede A.P.M., Ahlonsou E., Ding Y., Schimel D. The climate system: an overview. Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, The Intergovernmental Panel on Climate Change (IPCC) 2001, 87-98. Cambridge University Press, Cambridge, UK. J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. Maskell, C.A. Johnson (Eds.).
3. Birge J.R., Louveaux F.V. Introduction to Stochastic Programming 1997, Springer, New York, NY.
4. Cai Y.P., Huang G.H., Yang Z.F., Lin Q.G., Tan Q. Community-scale renewable energy systems planning under uncertainty-an interval chance-constrained programming approach. Renewable and Sustainable Energy Reviews 2009, 13:721-735.
5. Charnes A., Cooper W.W. Response to decision problems under risk and chance constrained programming: dilemmas in the transitions. Management Science 1983, 29:750-753.
6. Chen W.T., Li Y.P., Huang G.H., Chen X., Li Y.F. A two-stage inexact-stochastic programming model for planning carbon dioxide emission trading under uncertainty. Applied Energy 2010, 87:1033-1047.
7. Cofala J., Amann M., Gyarfas F., Schoepp W., Boudri J.C., Hordijk L., Kroeze C., Junfeng Li, Lin Dai, Panwar T.S., Gupta S. Cost-effective control of SO2 emissions in Asia. Journal of Environmental Management 2004, 72:149-161.
8. Fishbone L.G., Abilock H. MARKAL-A linear programming model for energy systems analysis: technical description of the BNL version. International Journal of Energy Research 1981, 5:353-375.
9. Gibbons J.M., Ramsden S.J., Blake A. Modelling uncertainty in greenhouse gas emissions from UK agriculture at the farm level. Agriculture, Ecosystems and Environment 2006, 112:347-355.
10. Hoaga D.L., Ascough J.C., Engler-Palma A. The impact matrix approach and decision rules to enhance dimensionality, flexibility and representation. Ecological Indicators 2002, 2:161-168.
11. Huang G.H., Baetz B.W., Patry G.G. An interval linear programming approach for municipal solid waste management planning under uncertainty. Civil Engineering Systems 1992, 9:319-335.
12. Huang G.H. A hybrid inexact-stochastic water management model. European Journal of Operational Research 1998, 107:137-158.
13. Huang G.H., Baetz B.W., Patry G.G. Grey integer programming: an application to waste management planning under uncertainty. European Journal of Operational Research 1995, 83:594-620.
14. Huang Q., Cheng S.Y., Li Y.P., Li J.B., Chen D.S., Wang H.Y. An integrated MM5-CAMx modeling approach for assessing PM10 contribution from different sources in Beijing, China. Journal of Environmental Informatics 2010, 15(2):47-61.
15. Inuiguchi M., Tanino T. Portfolio selection under independent possibilistic information. Fuzzy Sets and Systems 2000, 115:83-92.
16. IPCC (Intergovernmental Panel on Climate Change), 1995. Climate change 1995: economic and social dimensions of climate change. In: Contribution of Working Group III to the Second Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge.
17. IPCC (Intergovernmental Panel on Climate Change) Climate change 2001: the scientific basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) 2001, 944. Cambridge University Press, Cambridge, UK. J.T. Houghton, Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, D. Xiaosu (Eds.).
18. Kanudia A., Loulou R. Robust energy technologies via stochastic MARKAL: the case of Quebec. European Journal of Operational Research 1998, 106(1):15-30.
19. Kanudia A., Shukla P.R. Modelling of uncertainties and price elastic demands in energy-environment planning for India. Omega 1998, 26(3):409-423.
20. Li Y.P., Huang G.H., Nie S.L., Liu L. Inexact multistage stochastic integer programming for water resources management under uncertainty. Journal of Environmental Management 2008, 88:93-107.
21. Li Y.P., Huang G.H. Minimax regret analysis for municipal solid waste management: an interval-stochastic programming approach. Journal of Air & Waste Management Association 2006, 56:931-944.
22. Li Y.P., Huang G.H. An inexact two-stage mixed integer linear programming method for solid waste management in the City of Regina. Journal of Environmental Management 2006, 81:188-209.
23. Li Y.P., Huang G.H., Nie S.L., Qin X.S. ITCLP: an inexact two-stage chance-constrained program for planning waste management systems. Resources, Conservation and Recycling 2007, 49(3):284-307.
24. Li Y.F., Huang G.H., Li Y.P., Xu Y., Chen W.T. Regional-scale electric power systems planning under uncertainty-a multistage interval stochastic integer linear programming approach. Energy Policy 2010, 38:475-490.
25. Lin Q.G., Huang G.H. Planning of energy system management and GHG-emission control in the municipality of Beijing-an inexact-dynamic stochastic programming model. Energy Policy 2009, 37:4463-4473.
26. Loulou R., Kanudia A. Minimax regret strategies for greenhouse gas abatement: methodology and application. Operations Research Letters 1999, 25:219-230.
27. Manne A., Mendelsohn R., Richels R. MERGE: a model for evaluating regional and global effects of GHG reduction policies. Energy Policy 1995, 23(1):17-34.
28. Muela E., Schweickardt G., Garces F. Fuzzy possibilistic model for mediumterm power generation planning with environmental criteria. Energy Policy 2007, 35:5643-5655.
29. Peck S.C., Teisberg T.J. Optimal CO2 control policy with stochastic losses from temperature rise. Climatic Change 1995, 31(1):19-34.
30. Ramírez A., de Keizer C., Van der Sluijs J.P., Olivier J., Brandes L. Monte Carlo analysis of uncertainties in the Netherlands greenhouse gas emission inventory for 1990-2004. Atmospheric Environment 2008, 42:8263-8272.
31. Sadeghi M., Hosseini H.M. Energy supply planning in Iran using fuzzy linear programming approach (regarding uncertainties of investment costs). Energy Policy 2006, 34:993-1003.
32. Savage L.J. The Foundations of Statistics 1954, Wiley, New York.
33. Singer C.E., Rethinaraj T.S.G., Addy S., Durham D., Isik M., Khanna M., Kuehl B., Luo J.D., Quimio W., Rajendran K., Ramirez D., Qiang J., Scheffran J., Tiouririne T.N., Zhang J.L. Probability distributions for carbon emissions and atmospheric response. Climatic Change 2008, 88:309-342.
34. Swain D.K., Thomas D. Climate change impact assessment and evaluation of agro-adaptation measures for rice production in Eastern India. Journal of Environmental Informatics 2010, 16(2):94-101.
35. Tennakoon M., Mayorga R.V., Shirif E. A fuzzy inference system prototype for indoor air and temperature quality monitoring and hazard detection. Journal of Environmental Informatics 2010, 16(2):70-79.
36. Tummala R.V.M. Decision Analysis with Business Applications 1973, Intext Educational Publishers, New York and London.
37. USEPA, 2002. Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2000, U.S. Environmental Protection Agency, Office of Atmospheric Programs, EPA 430-R-02-003, April 2002. http://www.epa.gov/globalwarming/publications/emissions.
38. Winiwarter W., Rypdal K. Assessing the uncertainty associated with national greenhouse gas emission inventories: a case study for Austria. Atmospheric Environment 2001, 35:5425-5440.
39. Yager R.R. Decision making using minimization of regret. International Journal of Approximate Reasoning 2004, 36:109-128.