Long-term energy planning with uncertain environmental performance metrics

Environmental performance (EP) uncertainties span a number of energy technology options, and pose planning risk when the energy system is subject to environmental constraints. This paper presents two approaches to integrating EP uncertainty into the long-term energy planning framework. The methodologies consider stochastic EP metrics across multiple energy technology options, and produce a development strategy that hedges against the risk of exceeding environmental targets. Both methods are compared within a case study of emission-constrained electricity generation planning in British Columbia, Canada. The analysis provides important insight into model formulation and the interactions with concurrent environmental policy uncertainties. EP risk is found to be particularly important in situations where environmental constraints become increasingly stringent. Model results indicate allocation of a modest risk premium in these situations can provide valuable hedging against EP risk.

[1]  Semida Silveira,et al.  OSeMOSYS: The Open Source Energy Modeling System: An introduction to its ethos, structure and development , 2011 .

[2]  Gordon H. Huang,et al.  Identification of optimal strategies for energy management systems planning under multiple uncertainties , 2009 .

[3]  A. Patt,et al.  Electricity capacity investment under risk aversion: A case study of coal, gas, and concentrated solar power , 2012 .

[4]  Eiji Oki,et al.  GLPK (GNU Linear Programming Kit) , 2012 .

[5]  Brett Cohen,et al.  Ranking and selection of power expansion alternatives for multiple objectives under uncertainty , 2007 .

[6]  Tom M. L. Wigley,et al.  Coal to gas: the influence of methane leakage , 2011 .

[7]  Maryse Labriet,et al.  Deterministic and stochastic analysis of alternative climate targets under differentiated cooperation regimes , 2009 .

[8]  S. Messner,et al.  A stochastic version of the dynamic linear programming model MESSAGE III , 1996 .

[9]  Bob van der Zwaan,et al.  The Impact of Uncertainty in Climate Targets and CO2 Storage Availability on Long-Term Emissions Abatement , 2012, Environmental Modeling & Assessment.

[10]  Amit Kanudia,et al.  Robust responses to climate change via stochastic MARKAL: The case of Québec , 1996, Eur. J. Oper. Res..

[11]  H. Wagner,et al.  Effects of stochastic energy prices on long-term energy-economic scenarios , 2007 .

[12]  T. Ekholm.  Hedging the climate sensitivity risks of a temperature target , 2014, Climatic Change.

[13]  B. Palmintier,et al.  Water-CO2 trade-offs in electricity generation planning , 2013 .

[14]  Peter B. R. Hazell,et al.  A Linear Alternative to Quadratic and Semivariance Programming for Farm Planning under Uncertainty , 1971 .

[15]  E. Cian,et al.  Mitigation Portfolio and Policy Instruments When Hedging Against Climate Policy and Technology Uncertainty , 2012, Environmental Modeling & Assessment.

[16]  S. Fuss,et al.  Investment under market and climate policy uncertainty , 2008 .

[17]  Helmut Haberl,et al.  Large‐scale bioenergy from additional harvest of forest biomass is neither sustainable nor greenhouse gas neutral , 2012 .

[18]  A. Ingraffea,et al.  Methane and the greenhouse-gas footprint of natural gas from shale formations , 2011 .

[19]  R. Loulou,et al.  Effectiveness and efficiency of climate change mitigation in a technologically uncertain World , 2014, Climatic Change.

[20]  D. Bunn,et al.  Evaluating the power investment options with uncertainty in climate policy , 2008 .

[21]  E. Kort,et al.  Methane Leaks from North American Natural Gas Systems , 2014, Science.

[22]  Keywan Riahi,et al.  Energy Pathways for Sustainable Development , 2012 .

[23]  Ad Seebregts,et al.  Energy/Environmental Modeling with the MARKAL Family of Models , 2002 .

[24]  Vasilis Fthenakis,et al.  Land use and electricity generation: A life-cycle analysis , 2009 .

[25]  Amy Sopinka,et al.  Reconciling self-sufficiency and renewable energy targets in a hydro dominated system: The view from British Columbia , 2013 .

[26]  Vikas Khanna,et al.  Process based life-cycle assessment of natural gas from the Marcellus Shale. , 2013, Environmental science & technology.

[27]  Martin Pehnt,et al.  Dynamic life cycle assessment (LCA) of renewable energy technologies , 2006 .

[28]  Amy Sopinka,et al.  Optimal electricity system planning in a large hydro jurisdiction: Will British Columbia soon become a major importer of electricity? , 2013 .

[29]  Christian Wirth,et al.  Regional carbon dioxide implications of forest bioenergy production , 2011 .

[30]  Joseph F. DeCarolis,et al.  Modeling for insight using Tools for Energy Model Optimization and Analysis (Temoa) , 2013 .

[31]  A. Valle,et al.  Diffusion of nuclear energy in some developing countries , 2014 .

[32]  Manfred Lenzen,et al.  Renewable Energy Sources and Climate Change Mitigation: Methodology , 2011 .

[33]  B. Hobbs,et al.  Analysis of multi-pollutant policies for the U.S. power sector under technology and policy uncertainty using MARKAL , 2010 .

[34]  Ramkumar Karuppiah,et al.  How to quantify uncertainty and variability in life cycle assessment: the case of greenhouse gas emissions of gas power generation in the US , 2014 .

[35]  Charles E. Bland,et al.  3 – Structure and Development , 1985 .

[36]  Benjamin D. Leibowicz,et al.  Evaluation of post‐Fukushima Japanese electricity strategies: A stochastic simulation model , 2014 .

[37]  D. McCollum,et al.  Stranded on a low-carbon planet: Implications of climate policy for the phase-out of coal-based power plants , 2015 .

[38]  Leo Schrattenholzer,et al.  Achieving a sustainable global energy system : identifying possibilities using long-term energy scenarios , 2005 .

[39]  B. Hobbs,et al.  Risk aversion and CO2 regulatory uncertainty in power generation investment: Policy and modeling implications , 2010 .

[40]  Danièle Revel,et al.  IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation , 2011 .

[41]  Andrii Gritsevskyi,et al.  Modeling uncertainty of induced technological change , 2000 .

[42]  K. Riahi,et al.  Risk Hedging Strategies under Energy System and Climate Policy Uncertainties , 2013 .

[43]  Maged M. Dessouky,et al.  A Stochastic Mixed-Integer Programming approach to the energy-technology management problem , 2012, Comput. Ind. Eng..

[44]  Ned Djilali,et al.  Robust response to hydro-climatic change in electricity generation planning , 2015, Climatic Change.

[45]  Rebecca S. Dodder,et al.  Strategic responses to CO2 emission reduction targets drive shift in U.S. electric sector water use , 2014 .

[46]  George B. Dantzig,et al.  Linear Programming Under Uncertainty , 2004, Manag. Sci..

[47]  John P. Weyant,et al.  Electric sector investments under technological and policy-related uncertainties: a stochastic programming approach , 2013, Climatic Change.

[48]  Tieju Ma,et al.  Technology adoption with limited foresight and uncertain technological learning , 2014, Eur. J. Oper. Res..

[49]  Amit Kanudia,et al.  Minimax regret strategies for greenhouse gas abatement: methodology and application , 1997, Oper. Res. Lett..

[50]  R. Loulou,et al.  Climate mitigation under an uncertain technology future: A TIAM-World analysis , 2012 .

[51]  Guohe Huang,et al.  Planning regional energy system in association with greenhouse gas mitigation under uncertainty , 2011 .

[52]  H. Holttinen,et al.  Global energy and emissions scenarios for effective climate change mitigation - Deterministic and stochastic scenarios with the TIAM model , 2008 .

[53]  Ekundayo Shittu,et al.  Energy Technological Change and Capacity Under Uncertainty in Learning , 2014, IEEE Transactions on Engineering Management.

[54]  John A. Wicks,et al.  An Alternative Solution To Linear Programming Problems With Stochastic Input‐Output Coefficients , 1978 .

[55]  N. Strachan,et al.  Critical mid-term uncertainties in long-term decarbonisation pathways , 2012 .

[56]  Alain Haurie,et al.  Combining Stochastic Optimization and Monte Carlo Simulation to Deal with Uncertainties in Climate Policy Assessment , 2012, Environmental Modeling & Assessment.

[57]  Keywan Riahi,et al.  Impacts of considering electric sector variability and reliability in the MESSAGE model , 2013 .

[58]  C. Weber,et al.  Life cycle assessment and grid electricity: what do we know and what can we know? , 2010, Environmental science & technology.