Review Article | Published:

Challenges and gaps for energy planning models in the developing-world context

Nature Energyvolume 3pages172184 (2018) | Download Citation

Abstract

Energy planning models (EPMs) support multi-criteria assessments of the impact of energy policies on the economy and environment. Most EPMs originated in developed countries and are primarily aimed at reducing greenhouse gas emissions while enhancing energy security. In contrast, most, if not all, developing countries are predominantly concerned with increasing energy access. Here, we review thirty-four widely used EPMs to investigate their applicability to developing countries and find an absence of consideration of the objectives, challenges, and nuances of the developing context. Key deficiencies arise from the lack of deliberation of the low energy demand resulting from lack of access and availability of supply. Other inadequacies include the lack of consideration of socio-economic nuances such as the prevalence of corruption and resulting cost inflation, the methods for adequately addressing the shortcomings in data quality, availability and adequacy, and the effects of climate change. We argue for further research on characterization and modelling of suppressed demand, climate change impacts, and socio-political feedback in developing countries, and the development of contextual EPMs.

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Change history

  • 04 May 2018

    In the version of this Review originally published, in Table 3 seven entries in the columns ‘Developer’ and ‘Country of origin’ were incorrect (see the Author Correction notice linked to this Review); these errors have now been corrected. All other entries in the Table are unaffected.

References

  1. 1.

    IPCC Climate Change 2014: Synthesis Report (eds Core Writing Team, Pachauri, R. K. & Meyer L. A.) (IPCC, 2015).

  2. 2.

    Raupach, M. R. et al. Global and regional drivers of accelerating CO2 emissions. Proc. Natl Acad. Sci. USA 104, 10288–10293 (2007).

  3. 3.

    Le Quéré, C. et al. Trends in the sources and sinks of carbon dioxide. Nat. Geosci. 2, 831–836 (2009).

  4. 4.

    CO 2 Emissions from Fuel Combustion Highlights (IEA, 2015).

  5. 5.

    IPCC Climate Change 2014: Mitigation of Climate Change Change (eds Edenhofer, O. et al.) (Cambridge Univ. Press, 2014).

  6. 6.

    Raftery, A. E., Zimmer, A., Frierson, D. M. W., Startz, R. & Liu, P. Less than 2 °C warming by 2100 unlikely. Nat. Clim. Change 7, 637–641 (2017).

  7. 7.

    Ramanathan, V. & Feng, Y. On avoiding dangerous anthropogenic interference with the climate system: Formidable challenges ahead. Proc. Natl Acad. Sci. USA 105, 14245–14250 (2008).

  8. 8.

    Clark, P. U. et al. Consequences of twenty-first-century policy for multi-millennial climate and sea-level change. Nat. Clim. Change 6, 360–369 (2016).

  9. 9.

    World Bank DataBank (2017); http://go.nature.com/2DZdFDH

  10. 10.

    IEA Energy Access Outlook 2017: From Poverty to Prosperity (International Energy Agency, 2017).

  11. 11.

    Climate Action Tracker: Rating Countries (CAT, 2014); http://go.nature.com/2GvblCB

  12. 12.

    Amorim, F. et al. Electricity decarbonisation pathways for 2050 in Portugal: A TIMES (The Integrated MARKAL-EFOM System) based approach in closed versus open systems modelling. Energy 69, 104–112 (2014).

  13. 13.

    Sterner, T. International Energy Economics (Springer Science & Business Media, 2012).

  14. 14.

    Barsky, R. & Kilian, L. Oil and the Macroeconomy Since the 1970s (National Bureau of Economic Research, 2004).

  15. 15.

    Craig, P. P., Gadgil, A. & Koomey, J. G. What can history teach us? A retrospective examination of long-term energy forecasts for the United States. Ann. Rev. Energy Environ. 27, 83–118 (2002).

  16. 16.

    IPCC Second Assessment: Climate Change 1995. A Synthesis Report (WMO, 1995).

  17. 17.

    IEA. World Outlook Energy 2017 (International Energy Agency, 2017).

  18. 18.

    Suganthi, L. & Samuel, A. A. Energy models for demand forecasting—A review. Renew. Sust. Energy Rev. 16, 1223–1240 (2012).

  19. 19.

    Bhattacharyya, S. C. & Timilsina, G. R. A review of energy system models. Int. J. Energy Sector Management 4, 494–518 (2010).

  20. 20.

    Pfenninger, S., Hawkes, A. & Keirstead, J. Energy systems modeling for twenty-first century energy challenges. Renew. Sust. Energy Rev. 33, 74–86 (2014).

  21. 21.

    Urban, F., Benders, R. M. J. & Moll, H. C. Modelling energy systems for developing countries. Energy Policy 35, 3473–3482 (2007).

  22. 22.

    Pandey, R. Energy policy modelling: agenda for developing countries. Energy Policy 30, 97–106 (2002).

  23. 23.

    Guidelines on the Consideration of Suppressed Demand in CDM Methodologies v.02.0 (UNFCCC, CCNUCC, 2012).

  24. 24.

    Gavaldão, M., Battye, W., Grapeloup, M. & François, Y. Suppressed demand and the carbon markets: Does development have to become dirty before it qualifies to become clean? Field Actions Sci. Rep. 7, 2175 (2013).

  25. 25.

    Spalding-Fecher, R. Suppressed demand in the clean development mechanism: Conceptual and practical issues. J. Energy Southern Africa 26, 2–10 (2015).

  26. 26.

    Barnes, D., Domdom, A., Peskin, V. & Peskin, H. Rural Electrification and Development in the Philippines: Measuring the Social and Economic Benefits (International Bank for Reconstruction and Development, World Bank, 2002).

  27. 27.

    IEG. The Welfare Impact of Rural Electrification: A Reassessment of the Costs and Benefits (World Bank, 2008).

  28. 28.

    Clean Development Mechanism (UNFCCC, 2017); http://go.nature.com/2nutjwx

  29. 29.

    Modalities and Procedures for a Clean Development Mechanism as Defined in Article 12 of the Kyoto Protocol (UNFCCC, 2001).

  30. 30.

    Report of the Conference of the Parties Serving as the Meeting of the Parties to the Kyoto Protocol on its Fifth Session (UNFCCC, 2010).

  31. 31.

    Alesina, A., Özler, S., Roubini, N. & Swagel, P. Political instability and economic growth. J. Econ. Growth 1, 189–211 (1996).

  32. 32.

    Aisen, A. & Veiga, F. J. How does political instability affect economic growth? Eu. J. Political Econ. 29, 151–167 (2013).

  33. 33.

    Debnath, K. B., Mourshed, M. & Chew, S. P. K. Modelling and forecasting energy demand in rural households of Bangladesh. Energy Procedia 75, 2731–2737 (2015).

  34. 34.

    Medlock, K. B. & Soligo, R. Economic development and end-use energy demand. Energy J. 22, 77–105 (2001).

  35. 35.

    Mauro, P. Corruption and growth. Q. J. Econ. 110, 681–712 (1995).

  36. 36.

    Aladwani, A. M. Corruption as a source of e-Government projects failure in developing countries: A theoretical exposition. Int. J. Information Management 36, 105–112 (2016).

  37. 37.

    Mourshed, M. Pitfalls of oil-based expansion of electricity generation in a developing context. Energy Strategy Rev. 1, 205–210 (2013).

  38. 38.

    Wells, J. Corruption in the Construction of Public Infrastructure: Critical Issues in Project Preparation (U4 Anti-Corruption Resource Centre, Bergen, Norway, 2015).

  39. 39.

    Lovei, L. & McKechnie, A. The costs of corruption for the poor–the energy sector. Public Policy Private Sector 207, 1–8 (2000).

  40. 40.

    Nye, J. S. Corruption and political development: a cost-benefit analysis. Am. Political Sci. Rev. 61, 417–427 (1967).

  41. 41.

    Vera, I. & Langlois, L. Energy indicators for sustainable development. Energy 32, 875–882 (2007).

  42. 42.

    Geng, Y. et al. Recent trend of industrial emissions in developing countries. Appl. Energy 166, 187–190 (2016).

  43. 43.

    McLellan, B., Zhang, Q., Farzaneh, H., Utama, N. A. & Ishihara, K. N. Resilience, sustainability and risk management: a focus on energy. Challenges 3, 153–182 (2012).

  44. 44.

    Alcántara-Ayala, I. Geomorphology, natural hazards, vulnerability and prevention of natural disasters in developing countries. Geomorphology 47, 107–124 (2002).

  45. 45.

    Butzengeiger, S. & Horstmann, B. Sea Level Rise in Bangladesh and the Netherlands: One Phenomenon, Many Consequences (Germanwatch, 2004).

  46. 46.

    Workshop on Climate Change Impact Modeling: Report and Presentations (Climate Change Cell, Department of Environment, Bangladesh, 2006).

  47. 47.

    Khan, I., Alam, F. & Alam, Q. The global climate change and its effect on power generation in Bangladesh. Energy Policy 61, 1460–1470 (2013).

  48. 48.

    Wadey, M. P., Roberts, H. & Harris, J. Impacts of Climate Change on Built Structures (Onshore and Coastal) (MCCIP, 2013).

  49. 49.

    The Impacts of Climate Change on Nuclear Power Stations Sites: a Review of Four Proposed New-Build Sites on the UK Coastline (Greenpeace, 2007).

  50. 50.

    Archibugi, D. Technology, Globalisation and Economic Performance (Cambridge Univ. Press, 1997).

  51. 51.

    Bangladesh 2050 Energy and Emissions Pathways (BD2050, 2015); http://go.nature.com/2E0ylLo

  52. 52.

    Understanding the Link Between Climate Change and Extreme Weather (EPA, 2016).

  53. 53.

    Ravanelli, N. M. & Jay, O. Electric fan use in heat waves: Turn on or turn off? Temperature 3, 358–360 (2016).

  54. 54.

    Herring, S. C. et al. Explaining extreme events of 2015 from a climate perspective. Bull. Am. Meteorol. Soc. 97 (Suppl.) (2016).

  55. 55.

    Johansson, T. B., Patwardhan, A. P., Nakićenović, N. & Gomez-Echeverri, L. Global Energy Assessment: Toward a Sustainable Future (Cambridge Univ. Press, 2012).

  56. 56.

    Conti, J. et al. International Energy Outlook 2016 With Projections to 2040 Report No. DOE/EIA-0484 (Office of Energy Analysis, 2016).

  57. 57.

    McNeil, M. A. & Iyer, M. Techno-Economic Analysis of Indian Draft Standard Levels for Room Air Conditioners (Lawrence Berkeley National Laboratory, 2008).

  58. 58.

    Miller, N. L., Hayhoe, K., Jin, J. & Auffhammer, M. Climate, extreme heat, and electricity demand in California. J. Appl. Meteorol. Climatol. 47, 1834–1844 (2008).

  59. 59.

    Yohe, G. W. et al. Global distributions of vulnerability to climate change. Int. Assess 6, 35–44 (2006).

  60. 60.

    Marchal, V. et al. Environmental Outlook to 2050 (OECD, 2011).

  61. 61.

    Lawson, S., Heacock, D. & Stupnytska, A. In BRICS and Beyond 131–164 (2007).

  62. 62.

    JICA & TEPCO. The Study for Master Plan on Coal Power Development in the People’s Republic of Bangladesh (Energy and Mineral Resources, Ministry of Power, People’s Republic of Bangladesh, 2011).

  63. 63.

    JICA, TEPSCO & TEPCO. People’s Republic of Bangladesh: Survey on Power System Master Plan 2015 (Draft Final Report) (Energy and Mineral Resources, Ministry of Power, People’s Republic of Bangladesh, 2016).

  64. 64.

    Kaufmann, D. & Kraay, A. The Worldwide Governance Indicators, 2014 Update (2014).

  65. 65.

    DataBank (World Bank, 2014); https://data.worldbank.org/

  66. 66.

    Corruption Perceptions Index 2014 (Transparency International, 2014).

  67. 67.

    An Introduction into the Life-Cycle Analysis Calculation Tool (LBST, 2008).

  68. 68.

    Strubegger, M. CO2DB Software — Carbon Dioxide (Technology) Database Users Manual (International Institute for Applied Systems Analysis, 2003).

  69. 69.

    Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System (EIA, 2014).

  70. 70.

    Manne, A. S. & Wene, C.-O. MARKAL-MACRO: A Linked Model for Energy-Economy Analysis (Brookhaven National Lab, Upton, 1992).

  71. 71.

    Van Beeck, N. Classification of Energy Models (Tilburg University, Faculty of Economics and Business Administration, 1999).

  72. 72.

    Remme, U. & Blesl, M. Documentation of the TIMES-MACRO Model (Energy Technology Systems Analysis Programme, 2006).

  73. 73.

    Case Studies to Assess and Compare Different Energy Sources in Sustainable Energy and Electricity Supply Strategies (International Atomic Energy Agency, 2003).

  74. 74.

    Martinsen, D., Krey, V., Markewitz, P. & Vögele, S. IAEE Proceedings 2004 (International Association for Energy Economics, 2004).

  75. 75.

    Sahir, M. H. & Qureshi, A. H. In 6th WSEAS International Conference on Simulation, Modeling and Optimization 227–233 (World Scientific and Engineering Academy and Society, 2006).

  76. 76.

    Heaps, C. G. Long-range Energy Alternatives Planning (LEAP) System v.2014.0.1.29 (2012); www.energycommunity.org

  77. 77.

    Takase, K. & Suzuki, T. The Japanese energy sector: Current situation, and future paths. Energy Policy 39, 6731–6744 (2011).

  78. 78.

    Cai, W. et al. Comparison of CO2 emission scenarios and mitigation opportunities in China’s five sectors in 2020. Energy Policy 36, 1181–1194 (2008).

  79. 79.

    Kitous, A. POLES Model — Prospective Outlook on Long-term Energy Systems (2006).

  80. 80.

    Messner, S., Golodnikov, A. & Gritsevskii, A. A stochastic version of the dynamic linear programming model MESSAGE III. Energy 21, 775–784 (1996).

  81. 81.

    IAEA Wien Automatic System Planning (WASP) Package (International Atomic Energy Agency, 2001).

  82. 82.

    Loulou, R., Goldstein, G. & Noble, K. Documentation for the MARKAL Family of Models 65–73 (Energy Technology Systems Analysis Programme, 2004).

  83. 83.

    Loulou, R., Remme, U., Kanudia, A., Lehtila, A. & Goldstein, G. Documentation for the TIMES Model Part II (Energy Technology Systems Analysis Programme, 2005).

  84. 84.

    MacKenzie, G. A. Energy Models for Denmark MEDEE 3: Application of the Long Term Energy Demand Model to Denmark (Part III) (1982).

  85. 85.

    Model for Analysis of Energy Demand (MAED-2) (International Atomic Energy Agency, 2006).

  86. 86.

    The National Energy Modeling System: An Overview 2009 (EIA, 2009).

  87. 87.

    The UK 2050 Calculator (DECC, 2013); http://go.nature.com/2EvKxl9

  88. 88.

    Schlenzig, C. & Steidle, T. MESAP — A Co-operative Modelling System for Sustainable Local Energy and Environmental Planning (2001).

  89. 89.

    Schlenzig, C. Energy planning and environmental management with the information and decision support system MESAP. Int. J. Global Energy Issues 12, 81–91 (1999).

  90. 90.

    Van Den Broek, M., Van Oostvoorn, F., Van Harmelen, T. & Van Arkel, W. The EC Energy and Environment Model EFOM-ENV Specified in GAMS (1992).

  91. 91.

    Stehfest, E., van Vuuren, D., Bouwman, L. & Kram, T. Integrated Assessment of Global Environmental Change with IMAGE 3.0: Model Description and Policy Applications (2014).

  92. 92.

    Kainuma, M., Matsuoka, Y. & Morita, T. The AIM ⁄ ENDUSE Model and Case Studies in Japan (1999).

  93. 93.

    Sankovski, A., Barbour, W. & Pepper, W. Quantification of the IS99 emission scenario storylines using the atmospheric stabilization framework. Technol. Forecasting Soc. Change 63, 263–287 (2000).

  94. 94.

    Burniaux, J.-M., Martin, J. P., Nicoletti, G. & Martins, J. O. GREEN a Multi-Sector, Multi-Region General Equilibrium Model for Quantifying the Costs of Curbing CO 2 Emissions (1992).

  95. 95.

    Weyant, J. P. Costs of reducing global carbon emissions. J. Econ. Persp. 7, 27–46 (1993).

  96. 96.

    Dean, A. & Hoeller, P. Costs of Reducing CO 2 Emissions: Evidence from Six Global Models (OECD, 1992).

  97. 97.

    Brenkert, A. L., Sands, R. D., Kim, S. H. & Pitcher, H. M. Model Documentation: Second Generation Model (2004).

  98. 98.

    Planning & Economic Studies Section (PESS): Capacity Building for Sustainable Energy Development (IAEA, 2014).

  99. 99.

    LEAP: Long-Range Energy Alternatives Planning System (SEI, 2017).

  100. 100.

    Tools and Models (CEERD. 2017).

  101. 101.

    POLES: Prospective Outlook on Long-term Energy Systems (Enerdata, 2012).

  102. 102.

    Munasinghe, M. & Meier, P. Energy Policy Analysis and Modelling (Cambridge Univ. Press, 1993).

  103. 103.

    Giannakidis, G., Labriet, M., Gallachóir, B. Ó. & Tosato, G. Informing Energy and Climate Policies Using Energy Systems Models: Insights from Scenario Analysis Increasing the Evidence Base. Vol. 30 (Springer, 2015).

  104. 104.

    Voβ, A., Schlenzig, C. & Reuter, A. MESAP-III: a Tool for Energy Planning and Environmental Management: History and New Developments http://doi.org/cj3s (1994).

  105. 105.

    Completed Calculators (DECC, 2014); http://go.nature.com/2rVCaN7

  106. 106.

    How to Bu ild a 2050 Calculator (DECC, 2014).

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  1. BRE Trust Centre for Sustainable Engineering, School of Engineering, Cardiff University, Cardiff, UK

    • Kumar Biswajit Debnath
    •  & Monjur Mourshed

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Correspondence to Kumar Biswajit Debnath.

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https://doi.org/10.1038/s41560-018-0095-2