In this study, a novel inexact two-stage stochastic robust-compensation programming (ITSP-RC) model is developed for CO2 emission reduction management under uncertainties. This model is attempted to integrate ITSP and stochastic RC programming into a general framework and apply the ITSP-RC for power management and CO2 emission reduction management, such that the developed model can tackle uncertainties described in terms of interval values and probability distributions over a two-stage context. Moreover, it can reflect dynamic and randomness of the energy systems during the planning horizon. The developed method has been applied to a case to solve CO2 emission management problem in electric supply environmental management. A number of scenarios corresponding to different adoption rate levels of carbon capture, utilization, and storage technology are examined. With the RC programming, regional energy systems would have a stable financial budget. The result suggests that the methodology is applicable for reflecting complexities of large-scale energy management systems and addressing CO2 emissions reduction issue with the planning period.
Issue Section:
Energy Systems Analysis
Keywords:
Energy systems analysis
References
1.
IPCC
, 2007
, Climate Change: Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change
, Cambridge University Press
, Cambridge, UK
.2.
IPCC
, 2007
, Climate Change: Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change
, Cambridge University Press
, Cambridge, UK
.3.
IPCC
, 2007
, Climate Change: Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change
, Cambridge University Press
, Cambridge, UK
.4.
ShivaPrasad
, B. G.
, 2010
, “Energy Efficiency, Sources and Sustainability
,” ASME J. Energy Resour. Technol.
, 132
(2
), p. 020301
.5.
Cohen
, S. M.
, Rochelle
, G. T.
, and Webber
, M. E.
, 2010
, “Turning CO2 Capture On and Off in Response to Electric Grid Demand: A Baseline Analysis of Emissions and Economics
,” ASME J. Energy Resour. Technol.
, 132
(2
), p. 021003
.6.
Mori
, Y.
, Masutani
, S. M.
, and Nihous
, G. C.
, 1992
, “Pre-Combustion Removal of Carbon Dioxide From Natural Gas Power Plants and the Transition to Hydrogen Energy Systems
,” ASME J. Energy Resour. Technol.
, 114
(3
), pp. 221
–226
.7.
Field
, C. B.
, and Raupach
, M. R.
, 2004
, The Global Carbon Cycle: Integrating Humans, Climate, and the Natural World
,” Island Press
, Washington, DC
.8.
Fronk
, B. M.
, Neal
, R.
, and Garimella
, S.
, 2010
, “Evolution of the Transition to a World Driven by Renewable Energy
,” ASME J. Energy Resour. Technol.
, 132
(2
), p. 021009
.9.
Rosenthal
, D. H.
, Edmonds
, J. A.
, Richards
, K. R.
, and Wise
, M. A.
, 1993
, “Stabilizing U.S. Net Carbon Emissions by Planting Trees
,” Energy Convers. Manage.
, 34
(9–11
), pp. 881
–887
.10.
Fujii
, Y.
, and Yamaji
, K.
, 1998
, “Assessment of Technological Options in the Global Energy System for Limiting the Atmospheric CO2 Concentration
,” Environ. Econ. Policy Stud.
, 1
(2
), pp. 113
–139
.11.
Ichinohe
, M.
, and Endo
, E.
, 2006
, “Analysis of the Vehicle Mix in the Passenger-Car Sector in Japan for CO2 Emissions Reduction by a MARKAL Model
,” Appl. Energy
, 83
(10
), pp. 1047
–1061
.12.
Crilly
, D.
, and Zhelev
, T.
, 2008
, “Emissions Targeting and Planning: An Application of CO2 Emissions Pinch Analysis (CEPA) to the Irish Electricity Generation Sector
,” Energy
, 33
(10
), pp. 1498
–1507
.13.
Cai
, Y. P.
, Huang
, G. H.
, Yang
, Z. F.
, Lin
, Q. G.
, Bass
, B.
, and Tan
, Q.
, 2008
, “Development of an Optimization Model for Energy Systems Planning in the Region of Waterloo
,” Int. J. Energy Res.
, 32
(11
), pp. 988
–1005
.14.
Heinricha
, G.
, Howells
, M.
, Bassona
, L.
, and Petrie
, J.
, 2007
, “Electricity Supply Industry Modeling for Multiple Objectives Under Demand Growth Uncertainty
,” Energy
, 32
(11
), pp. 2210
–2229
.15.
Facci
, A. L.
, Andreassi
, L.
, Martini
, F.
, and Ubertini
, S.
, 2014
, “Comparing Energy and Cost Optimization in Distributed Energy Systems Management
,” ASME J. Energy Resour. Technol.
, 136
(3
), p. 032001
.16.
Kwaczek
, A.
, Baker-Stariha
, B. D.
, Macrae
, K. M.
, and Reinsch
, A. E.
, 1996
, Modeling Air Emission Control Strategies for Saskatchewan
, Canadian Energy Research Institute (CERI)
, Calgary, Canada
.17.
Unger
, T.
, and Ekvall
, T.
, 2003
, “Benefits From Increased Cooperation and Energy Trade Under CO2 Commitments—The Nordic Case
,” Clim. Policy
, 3
(3
), pp. 279
–294
.18.
Chinese
, D.
, Meneghetti
, A.
, and Nardin
, G.
, 2005
, “Waste-to-Energy Based Greenhouse Heating: Exploring Viability Conditions Through Optimization Models
,” Renewable Energy
, 30
(10
), pp. 1573
–1586
.19.
Klaassen
, G.
, and Riahi
, K.
, 2007
, “Internalizing Externalities of Electricity Generation: An Analysis With MESSAGE-MACRO
,” Energy Policy
, 35
(2
), pp. 815
–827
.20.
Chung
, W. S.
, Tohno
, S.
, and Shim
, S. Y.
, 2009
, “An Estimation of Energy and GHG Emission Intensity Caused by Energy Consumption in Korea: An Energy IO Approach
,” Appl. Energy
, 86
(10
), pp. 1902
–1914
.21.
Loulou
, R.
, and Kanudia
, A.
, 1998
, “The Kyoto Protocol, Inter-Provincial Cooperation, and Energy Trading: A Systems Analysis With Integrated MARKAL Models
,” Energy Stud. Rev.
, 9
(1
), pp. 1
–23
.22.
Loulou
, R.
, and Kanudia
, A.
, 1999
, “Minimax Regret Strategies for Greenhouse Gas Abatement: Methodology and Application
,” Oper. Res. Lett.
, 25
(5
), pp. 219
–230
.23.
Kanudia
, A.
, and Loulou
, R.
, 1998
, “Robust Responses to Climate Change Via Stochastic MARKAL: The Case of Quebec
,” Eur. J. Oper. Res.
, 106
(1
), pp. 15
–30
.24.
Spangardt
, G.
, Lucht
, M.
, and Handschin
, E.
, 2006
, “Applications for Stochastic Optimization in the Power Industry
,” Electr. Eng.
, 88
(3
), pp. 177
–182
.25.
Li
, Y. P.
, Huang
, G. H.
, Chen
, X.
, and Cheng
, S. Y.
, 2009
, “Interval-Parameter Robust Minimax-Regret Programming and Its Application to Energy and Environmental Systems Planning
,” Energy Sources
, 4
(3
), pp. 278
–294
.26.
Chen
, W. T.
, Li
, Y. P.
, Huang
, G. H.
, Chen
, X.
, and Li
, Y. F.
, 2010
, “A Two-Stage Inexact-Stochastic Programming Model for Planning Carbon Dioxide Emission Trading Under Uncertainty
,” Appl. Energy
, 87
(3
), pp. 1033
–1047
.27.
Aghaei
, J.
, and Amjady
, N.
, 2012
, “A Scenario-Based Multiobjective Operation of Electricity Markets Enhancing Transient Stability
,” Int. J. Electr. Power Energy Syst.
, 35
(1
), pp. 112
–122
.28.
Ganguly
, S.
, Sahoo
, N. C.
, and Das
, D.
, 2013
, “Multi-Objective Planning of Electrical Distribution Systems Using Dynamic Programming
,” Int. J. Electr. Power Energy Syst.
, 46
, pp. 65
–78
.29.
Guo
, P.
, Huang
, G. H.
, He
, L.
, and Cai
, Y. P.
, 2008
, “An Inexact Chance-Constraint Semi-Infinite Programming Approach for Energy Management System Under Uncertainty
,” Energy Sources
, 30
(14
), pp. 1345
–1366
.30.
Mirzaesmaeeli
, H.
, Elkamel
, A.
, Douglasa
, P. L.
, Croiseta
, E.
, and Guptab
, M.
, 2010
, “A Multi-Period Optimization Model for Energy Planning With CO2 Emission Consideration
,” J. Environ. Manage.
, 91
(5
), pp. 1063
–1070
.31.
Unsihuay-Vilaa
, C.
, Marangon-Limab
, J. W.
, Zambroni de Souzab
, A. C.
, and Perez-Arriagac
, I. J.
, 2011
, “Multistage Expansion Planning of Generation and Interconnections With Sustainable Energy Development Criteria: A Multiobjective Model
,” Int. J. Electr. Power Energy Syst.
, 33
(2
), pp. 258
–270
.32.
Loucks
, D. P.
, Stendiger
, J. R.
, and Hait
, D. A.
, 1981
, Water Resources Planning Systems Planning and Analysis
, Prentice Hall
, Upper Saddle River, NJ
, p. 55
.33.
Birge
, J. R.
, and Louveaux
, F. V.
, 1988
, “A Multicut Algorithm for Two-Stage Stochastic Linear Programs
,” Eur. J. Oper. Res.
, 34
(3
), pp. 384
–392
.34.
Birge
, J. R.
, and Louveaux
, F. V.
, 1997
, Introduction to Stochastic Programming
, Springer
, New York
.35.
Paraskevopoulos
, D.
, Karakitsos
, E.
, and Rustem
, B.
, 1991
, “Robust Capacity Planning Under Uncertainty
,” Manage. Sci.
, 37
(7
), pp. 787
–800
.36.
Malcolm
, S. A.
, and Zenios
, S. A.
, 1994
, “Robust Optimization for Power Systems Capacity Expansion Under Uncertainty
,” J. Oper. Res. Soc.
, 45
(9
), pp. 1040
–1049
.37.
Escudero
, L. F.
, Kamesam
, P. V.
, King
, A. J.
, and Wets
, R. J.-B.
, 1993
, “Production Planning Via Scenario Modeling
,” Ann. Oper. Res.
, 43
(6
), pp. 309
–335
.38.
Mulvey
, J. M.
, and Ruszczyński
, A.
, 1995
, “A New Scenario Decomposition Method for Large-Scale Stochastic Optimization
,” Oper. Res.
, 43
(3
), pp. 477
–490
.39.
Mulvey
, J. M.
, Vanderbei
, R. J.
, and Zenios
, S. A.
, 1995
, “Robust Optimization of Large-Scale Systems
,” Oper. Res.
, 43
(2
), pp. 264
–281
.40.
Soteriou
, A. C.
, and Chase
, R. B.
, 2000
, “A Robust Optimization Approach for Improving Service Quality
,” Manuf. Serv. Oper. Manage.
, 2
(3
), pp. 264
–286
.41.
Yu
, C.-S.
, and Li
, H.
, 2000
, “A Robust Optimization Model for Stochastic Logistic Problems
,” Int. J. Prod. Econ.
, 64
(1–3
), pp. 385
–397
.42.
Yeomans
, J. S.
, Huang
, G. H.
, and Yoogalingam
, R.
, 2003
, “Combining Simulation With Evolutionary Algorithms for Optimal Planning Under Uncertainty: An Application to Municipal Solid Waste Management Planning in the Regional Municipality of Hamilton-Wentworth
,” J. Environ. Inf.
, 2
(1
), pp. 11
–30
.43.
Huang
, G. H.
, and Loucks
, D. P.
, 2003
, “An Inexact Two-Stage Stochastic Programming Model for Water Resources Management Under Uncertainty
,” Civ. Eng. Environ. Syst.
, 17
(2
), pp. 95
–118
.44.
Li
, Y. P.
, Huang
, G. H.
, and Nie
, S. L.
, 2006
, “An Interval-Parameter Multi-Stage Stochastic Programming Model for Water Resources Management Under Uncertainty
,” Adv. Water Resour.
, 29
(5
), pp. 776
–789
.45.
Xie
, Y. L.
, Li
, Y. P.
, Huang
, G. H.
, and Li
, Y. F.
, 2010
, “An Interval Fixed-Mix Stochastic Programming Method for Greenhouse Gas Mitigation in Energy Systems Under Uncertainty
,” Energy
, 35
(12
), pp. 4627
–4644
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