1932

Abstract

The benefits and costs of increasing solar electricity generation depend on the scale of the increase and on the time frame over which it occurs. Short-run analyses focus on the cost-effectiveness of incremental increases in solar capacity, holding the rest of the power system fixed. Solar’s variability adds value if its power occurs at high-demand times and displaces relatively carbon-intensive generation. Medium-run analyses consider the implications of nonincremental changes in solar capacity. The cost of each installation may fall through experience effects, but the cost of grid integration increases when solar requires ancillary services and fails to displace investment in other types of generation. Long-run analyses consider the role of solar in reaching twenty-first-century carbon targets. Solar’s contribution depends on the representation of grid integration costs, on the availability of other low-carbon technologies, and on the potential for technological advances. By surveying analyses for different time horizons, this article begins to connect and integrate a fairly disjointed literature on the economics of solar energy.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-resource-091912-151843
2013-06-01
2024-04-16
Loading full text...

Full text loading...

/deliver/fulltext/resource/5/1/annurev-resource-091912-151843.html?itemId=/content/journals/10.1146/annurev-resource-091912-151843&mimeType=html&fmt=ahah

Literature Cited

  1. Anadon LD, Bunn M, Chan G, Chan M, Jones C, et al. 2011. Transforming US energy innovation. Tech. Rep., Energy Technol. Innov. Policy Res. Group, Belfer Cent. Sci. Int. Aff., Kennedy Sch., Harvard Univ., Cambridge, Mass.
  2. Anderson D, Winne S. 2004. Modelling innovation and threshold effects in climate change mitigation. Work. Pap. 59, Tyndall Cent. Clim. Change Res., Univ. East Anglia, Norwich, UK
  3. Argote L, Epple D. 1990. Learning curves in manufacturing. Science 247:920–24 [Google Scholar]
  4. Arrow KJ. 1962. The economic implications of learning-by-doing. Rev. Econ. Stud. 29:155–73 [Google Scholar]
  5. Baker E, Chon H, Keisler J. 2009. Advanced solar R&D: combining economic analysis with expert elicitations to inform climate policy. Energy Econ. 31:S37–49 [Google Scholar]
  6. Baker E, Solak S. 2011. Climate change and optimal energy technology R&D policy. Eur. J. Oper. Res. 213:442–54 [Google Scholar]
  7. Baker E, Solak S. 2013. Management of energy technology for sustainability: how to fund energy technology R&D. Prod. Oper. Manag. In press
  8. Barbose G, Darghouth N, Wiser R. 2012. Tracking the sun. V. The installed cost of photovoltaics in the United States from 1998 to 2009. Tech. Rep. LBNL-5919E, Lawrence Berkeley Natl. Lab., Berkeley, Calif.
  9. Barbose GL, Darghouth N, Wiser R, Steel J. 2011. Tracking the sun. IV. An historical summary of the installed cost of photovoltaics in the United States from 1998 to 2010. Tech. Rep. LBNL-5047E, Lawrence Berkeley Natl. Lab., Berkeley, Calif.
  10. Bibas R, Méjean A. 2012. Potential and limitations of bioenergy options for low carbon transitions. Work. Pap. 42-2012, Cent. Int. Rech. Environ. Dév. (CIRED), Nogent-sur-Marne, Fr.
  11. Bollinger P, Gillingham K. 2012. Peer effects in the diffusion of solar photovoltaic panels. J. Mark. Sci. 31:900–12 [Google Scholar]
  12. Borenstein S. 2008. The market value and cost of solar photovoltaic electricity production. Work. Pap. 176, Cent. Stud. Energy Mark., Univ. Calif. Energy Inst., Berkeley, Calif.
  13. Borenstein S. 2012. The private and public economics of renewable electricity generation. J. Econ. Perspect. 26(1):67–92
  14. Bosetti V, Carraro C, Galeotti M, Massetti E, Tavoni M. 2006. WITCH—a World Induced Technical Change Hybrid model. Energy J. 27:13–37 [Google Scholar]
  15. Bosetti V, Catenacci M, Fiorese G, Verdolini E. 2012. The future prospect of PV and CSP solar technologies: an expert elicitation survey. Energy Policy 49:308–17 [Google Scholar]
  16. Bosetti V, Massetti E, Tavoni M. 2007. The WITCH model. Structure, baseline, solutions. Work. Pap. 2007.010 Fond. Eni Enrico Mattei [Google Scholar]
  17. Bosetti V, Tavoni M, De Cian E, Sgobbi A. 2009. The 2008 WITCH model: new model features and baseline. Work. Pap. 2009.085 Fond. Eni Enrico Mattei [Google Scholar]
  18. Branker K, Pathak M, Pearce J. 2011. A review of solar photovoltaic levelized cost of electricity. Renew. Sustain. Energy Rev. 15:4470–82 [Google Scholar]
  19. Broekhoff D. 2007. Guidelines for quantifying GHG reductions from grid-connected electricity projectsRep., World Resour. Inst., Washington, DC
  20. Bryan WL, Harter N. 1899. Studies on the telegraphic language: the acquisition of a hierarchy of habits. Psychol. Rev. 6:345–75 [Google Scholar]
  21. Bushnell J. 2005. Electricity resource adequacy: matching policies and goals. Electr. J. 18:11–21 [Google Scholar]
  22. Callaway D, Fowlie M, McCormick G. 2013. Marginal benefits of renewable energy generation: location, location, location? Unpubl. Manuscr., Univ. Calif., Berkeley
  23. Clarke L, Weyant J, Birky A. 2006. On the sources of technological change: assessing the evidence. Energy Econ. 28:579–95
  24. Cullen J. 2012. Measuring the environmental benefits of wind-generated electricity. Work. Pap., Harvard Univ. Cent. Environ.
  25. Curtright A, Morgan MG, Kieth D. 2008. Expert assessment of future photovoltaic technology. Environ. Sci. Technol. 42:9031–38 [Google Scholar]
  26. de Vries BJ, van Vuuren DP, Hoogwijk MM. 2007. Renewable energy sources: their global potential for the first-half of the 21st century at a global level: an integrated approach. Energy Policy 35:2590–610 [Google Scholar]
  27. Deane J, Gallachoir BO, McKeogh E. 2010. Techno-economic review of existing and new pumped hydro energy storage plant. Renew. Sustain. Energy Rev. 14:1293–302 [Google Scholar]
  28. Denholm P, Margolis R. 2007. Evaluating the limits of solar photovoltaics (PV) in traditional electric power systems. Energy Policy 35:2852–61
  29. Dep. Energy (DOE) 2012. SunShot Vision Study Washington, DC: DOE
  30. Dosi G. 1988. Sources, procedures, and microeconomic effects of innovation. J. Econ. Lit. 26:1120–71 [Google Scholar]
  31. Dunn B, Kamath H, Tarascon JM. 2011. Electrical energy storage for the grid: a battery of choices. Science 334:928–35 [Google Scholar]
  32. Dutton JM, Thomas A. 1984. Treating progress functions as a managerial opportunity. Acad. Manag. Rev. 9:235–47 [Google Scholar]
  33. Edenhofer O, Knopf B, Barker T, Baumstark L, Bellevrat E et al. 2010. The economics of low stabilization: model comparison of mitigation strategies and costs. Energy J. 31:11–48 [Google Scholar]
  34. US Energy Inf. Admin. (EIA). 2010. Annual energy outlook 2010. Rep. DOE/EIA-0383(2010), EIA, Washington, DC
  35. Freeman C, Perez C. 1988. Structural crises of adjustment, business cycles, and investment behavior. Technical Change and Economic Theory Dosi G, Freeman C, Nelson R, Silverberg G, Soete L. 38–66 London: Pinter [Google Scholar]
  36. GE Energy. 2008. Analysis of wind generation impact on ERCOT ancillary services requirements. Rep. for Electr. Reliab. Counc. Tex.
  37. Gil H, Joos G. 2007. Generalized estimation of average displaced emissions by wind generation. IEEE Trans. Power Syst. 22:1035–43
  38. Goetzberger A, Hebling C. 2000. Photovoltaic materials, past, present, future. Sol. Energy Mater. Sol. Cells 62:1–19 [Google Scholar]
  39. Goodrich A, James T, Woodhouse M. 2012. Residential, commercial, and utility-scale photovoltaic (PV) system prices in the United States: current drivers and cost-reduction opportunities. Tech. Rep. NREL/TP-6A20-53347, Natl. Renew. Energy Lab., Washington, DC
  40. Gowrisankaran G, Reynolds S, Samano M. 2013. Intermittency and the value of renewable energy. Tech. Rep., Natl. Bur. Econ. Res., Cambridge, Mass.
  41. Green M, Emery K, King D, Igari S, Warta W. 2001. Solar cell efficiency tables (version 17). Prog. Photovolt. Res. Appl. 9:49–56 [Google Scholar]
  42. Green Tech Media 2012. Polysilicon prices hit record low in 2011; will head even lower, enabling $0.70/W PV in 2012. Green Tech Media, Feb. 10. http://www.greentechmedia.com/articles/read/polysilicon-prices-hit-record-lows-in-2011-will-head-even-lower-enabling-0/
  43. Greenstone M, Kopits E, Wolverton A. 2011. Estimating the social cost of carbon for use in US federal rulemakings: a summary and interpretation. Work. Pap. 16913, Natl. Bur. Econ. Res., Cambridge, Mass.
  44. Grübler A, Nakicenovic N, Victor DG. 1999. Modeling technological change: implications for the global environment. Annu. Rev. Energy Environ. 24:545–69 [Google Scholar]
  45. Halme J. 2002. Dye-sensitized nanostructured and organic photovoltaic cells: technical review and preliminary tests. Master’s thesis, Helsinki Univ. Technol.
  46. Hansen T. 2007. Utility solar generation valuation methods. Rep., DOE Sol. Am. Initiat., Washington, DC
  47. Harmon C. 2000. Experience curves of photovoltaic technology. Tech. Rep. IR-00-014, Int. Inst. Appl. Syst. Anal., Laxenburg, Austria
  48. Hoff T, Perez R. 2010. Quantifying PV power output variability. Sol. Energy 84:1782–93
  49. Hoff T, Perez R, Ross JP, Taylor M. 2008. Photovoltaic capacity valuation methods. Tech. Rep., Sol. Electr. Power Assoc., Washington, DC
  50. Hoffert MI, Caldeira K, Benford G, Criswell DR, Green C et al. 2002. Advanced technology paths to global climate stability: energy for a greenhouse planet. Science 298:981–87 [Google Scholar]
  51. Hoogwijk MM. 2004. On the global and regional potential of renewable energy sources. PhD thesis, Utrecht Univ.
  52. Horbach J. 2007. Determinants of environmental innovation—new evidence from German panel data sources. Res. Policy 37:163–73 [Google Scholar]
  53. Hourcade JC, Jaccard M, Bataille C, Ghersi F. 2006. Hybrid modeling: new answers to old challenges—introduction to the special issue of the Energy Journal. Energy J. 27:1–11 [Google Scholar]
  54. Jamasb T, Kohler J. 2007. Learning curves for energy technology: a critical assessment. Work. Pap., Electr. Policy Res. Group, Univ. Cambridge, Cambridge, UK
  55. Joskow P. 2011. Comparing the costs of intermittent and dispatchable electricity generating technologies. Am. Econ. Rev. 100:238–41 [Google Scholar]
  56. Kaffine DT, McBee BJ, Lieskovsky J. 2013. Emissions savings from wind power generation in Texas. Energy J. 34:155–75 [Google Scholar]
  57. Kalowekamo J, Baker E. 2009. Estimating the manufacturing cost of purely organic solar cells. Sol. Energy 83:1224–31 [Google Scholar]
  58. Kelly H, Weinberg C. 1993. Utility strategies for using renewables. Renewable Energy: Sources for Fuels and Electricityed. Johansson T, Kelly H, Reddy A, Williams R. 1011–68 Washington, DC: Island [Google Scholar]
  59. Kolstad C. 1998. Integrated assessment modeling of climate change. Economics and Policy Issues in Climate Changeed. Nordhaus WD. 263–86 Washington, DC: Resour. Future [Google Scholar]
  60. Krey V, Clarke L. 2011. Role of renewable energy in climate mitigation: a synthesis of recent scenarios. Clim. Policy 11:1131–58 [Google Scholar]
  61. Lamont A. 2008. Assessing the long-term system value of intermittent electric generation technologies. Energy Econ. 30:1208–31 [Google Scholar]
  62. Lemoine DM, Fuss S, Szolgayova J, Obersteiner M, Kammen DM. 2012. The influence of negative emission technologies and technology policies on the optimal climate mitigation portfolio. Clim. Change 113:141–62 [Google Scholar]
  63. Lew D, Piwko R. 2010. Western wind and solar integration study. Natl. Renew. Energy Lab., Golden, Colo.
  64. Little R, Nowlan M. 1997. Crystalline silicon photovoltaics: the hurdle for thin films. Prog. Photovolt. Res. Appl. 5:309–15 [Google Scholar]
  65. Lorenz E, Scheidsteger T, Hurka J, Heinemann D, Kurz C. 2011. Regional PV power prediction for improved grid integration. Prog. Photovolt. Res. Appl. 19:757–71 [Google Scholar]
  66. Luderer G, Leimbach M, Bauer N, Kriegler E. 2011. Description of the ReMIND-R model. Potsdam Inst. Clim. Impact Res.
  67. Madaeni S, Sioshansi R, Denholm P. 2012. Comparing capacity value estimation techniques for photovoltaic solar power. IEEE J. Photovolt. 3:407–15
  68. Magné B, Kypreos S, Turton H. 2010. Technology options for low stabilization pathways with MERGE. Energy J. 31:83–107 [Google Scholar]
  69. Marquez R, Coimbra CF. 2011. Forecasting of global and direct solar irradiance using stochastic learning methods, ground experiments and the NWS database. Sol. Energy 85:746–56 [Google Scholar]
  70. Masui T, Ashina S, Fujino J. 2010. Analysis of 4.5 W/m2 stabilization scenarios with renewable energies and advanced technologies using AIM/CGE[Global] model. AIM Team, Natl. Inst. Environ. Stud., Jpn.
  71. Mathiesen P, Kleissl J. 2011. Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States. Sol. Energy 85:967–77 [Google Scholar]
  72. McDonald A, Schrattenholzer L. 2001. Learning rates for energy technologies. Energy Policy 29:255–61 [Google Scholar]
  73. McJeon HC, Clarke L, Kyle P, Wise M, Hackbarth A et al. 2011. Technology interactions among low-carbon energy technologies: What can we learn from a large number of scenarios?. Energy Econ. 33:619–31 [Google Scholar]
  74. Meyer T. 1996. Solid state nanocrystalline titanium oxide photovoltaic cells. PhD thesis, Dep. Chim., EPFL, Lausanne
  75. Miketa A, Schrattenholzer L. 2004. Experiments with a methodology to model the role of R&D expenditures in energy technology learning processes: first results. Energy Policy 32:1679–92 [Google Scholar]
  76. Mills A, Wiser R. 2010. Implications of wide-area geographic diversity for short-term variability of solar power. Rep. LBNL-3884E, Lawrence Berkeley Natl. Lab., Berkeley, Calif.
  77. Mills A, Wiser R. 2012a. Changes in the economic value of variable generation at high penetration levels: a pilot case study of California. Rep. LBNL-5445E, Lawrence Berkeley Natl. Lab., Berkeley, Calif.
  78. Mills A, Wiser R. 2012b. An evaluation of solar valuation methods used in utility planning and procurement processes. Rep. LBNL-5933E, Lawrence Berkeley Natl. Lab., Berkeley, Calif.
  79. Morgan MG, Henrion M. 1990. Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis Cambridge, UK: Cambridge Univ. Press
  80. Mowery D, Rosenberg N. 1979. The influence of market demand upon innovation: a critical review of some recent empirical studies. Res. Policy 8:102–53 [Google Scholar]
  81. Nagy B, Farmer JD, Bui QM, Trancik JE. 2012. Statistical basis for predicting technological progress. arXiv:1207.1463 [physics.soc-ph]
  82. Natl. Res. Counc 2007. Prospective Evaluation of Applied Energy Research and Development at DOE (Phase Two) Washington, DC: Natl. Acad. Press
  83. Navigant Consult. 2006. A review of PV inverter technology cost and performance projections. Subcontract. Rep. NREL/SR-620-38771, Natl. Renew. Energy Lab., Washington, DC. http://www.nrel.gov/docs/fy06osti/38771.pdf
  84. Neij L. 1997. Use of experience curves to analyse the prospects for diffusion and adoption of renewable energy technology. Energy Policy 25:1099–107 [Google Scholar]
  85. Nemet GF. 2006. Beyond the learning curve: factors influencing the cost reductions in photovoltaics. Energy Policy 34:3218–32 [Google Scholar]
  86. Nemet GF, Baker E. 2009. Demand subsidies versus R&D: comparing the uncertain impacts of policy on a pre-commercial low-carbon energy technology. Energy J. 30:49–80 [Google Scholar]
  87. Nemet GF, Kammen DM. 2007. US energy research and development: declining investment, increasing need, and the feasibility of expansion. Energy Policy 35:746–55 [Google Scholar]
  88. Norberg-Bohm V. 1999. Stimulating green technological innovation: an analysis of alternative policy mechanisms. Policy Sci. 32:13–38 [Google Scholar]
  89. Nordhaus WD. 2009. The perils of the learning model for modeling endogenous technological change. Work. Pap. 14638, Natl. Bur. Econ. Res., Cambridge, Mass.
  90. Novan K. 2012. Valuing the wind: renewable energy policies and air pollution avoided. Work. Pap., Cent. Energy Environ. Econ., Univ. Calif., Davis
  91. O’Neill B, Grübler A, Nakicenovic N, Obersteiner M, Riahi K, et al. 2003. Planning for future energy resources. Science 300:581–84
  92. Organ. Econ. Co-op. Dev. (OECD)/Int. Energy Agency (IEA). 2000. Experience Curves for Energy Technology Policy. Paris: OECD/IEA
  93. Osborne M. 2010. Manufacturing cost per watt at First Solar falls to US$0.76 cents: Module faults hit earnings. PV-Tech, July 29. http://www.pv-tech.org/news/manufacturing_cost_per_watt_at_first_solar_falls_to_us0.76_cents_module_fau
  94. Pacala S, Socolow R. 2004. Stabilization wedges: solving the climate problem for the next 50 years with current technologies. Science 305:968–72 [Google Scholar]
  95. Paltsev S, Reilly JM, Jacoby HD, Morris JF. 2009. The cost of climate policy in the United States. Energy Econ. 31:S235–43 [Google Scholar]
  96. Perez R, Kivalov S, Schlemmer J. Hemker K Jr, Renné D, Hoff TE 2010. Validation of short and medium term operational solar radiation forecasts in the US. Sol. Energy 84:91–137 [Google Scholar]
  97. Perez R, Margolis R, Kmiecik M, Schwab M, Perez M. 2006. Update: Effective load-carrying capability of photovoltaics in the United States. Conf. Pap. NREL/CP-620-40068, Natl. Renew. Energy Lab., Washington, DC
  98. Pietzcker R, Manger S, Bauer N, Luderer G, Bruckner T. 2009. The role of concentrating solar power and photovoltaics for climate protection. Presented at IAEE Eur. Conf., 10th, Vienna
  99. Prins G, Rayner S. 2007. Time to ditch Kyoto. Nature 449:973–75 [Google Scholar]
  100. Requate T. 2005. Dynamic incentives by environmental policy instruments—a survey. Ecol. Econ. 54:175–95 [Google Scholar]
  101. Riahi K, Rao S, Krey V, Cho C, Chirkov V et al. 2011. RCP 8.5—a scenario of comparatively high greenhouse gas emissions. Clim. Change 109:33–57 [Google Scholar]
  102. Rothleder M, Helman U, Loutan C, Guo T, Xie J, Ventakaraman S. 2012. Integration of wind and solar under a 20% RPS: stochastic simulation methods and results from California ISO studies. Presented at IEEE Power Energy Soc. Gen. Meet., July, pp. 1–8
  103. Schaeffer G, Seebregts A, Beurskens L, de Moor H, Alsema E, et al. 2004. Learning from the sun; analysis of the use of experience curves for energy policy purposes: the case of photovoltaic power. Final report of the PHOTEX project. Rep. ECN-C–04-035, ECN, Petten, Neth.
  104. Shaalan H. 2003. Generation of electric power. In Handbook of Electric Power Calculations, ed. HW Beaty, 8:1–38. New York: McGraw-Hill
  105. Shiao MJ. 2012. Thin film 2012–2016: technologies, markets and strategies for survival. Rep., GTM Res., Boston. http://www.greentechmedia.com/research/report/thin-film-2012-2016
  106. Silva Herran D. 2012. Renewable energy potential model manual (solar, wind). Vers. of 2012/01/16, Sustain. Soc. Syst. Sect., Cent. Soc. Environ. Syst. Res., NIES. http://www-iam.nies.go.jp/aim/AIM_datalib/RenewPotentialModel-AIM-Manual-20120116-1.pdf
  107. Sioshansi R, Denholm P, Jenkin T. 2012. Market and policy barriers to deployment of energy storage. Econ. Energy Environ. Policy 1:47–63
  108. Skoczek A, Sample T, Dunlop E. 2008. The results of performance measurements of field-aged crystalline silicon photovoltaic modules. Prog. Photovolt. Res. Appl. 17:227–40 [Google Scholar]
  109. Smestad G. 1994. Testing of dye-sensitized TiO2 solar cells. II. Theoretical voltage output and photoluminescence efficiencies. Sol. Energy Mater. Sol. Cells 32:273–88 [Google Scholar]
  110. Stoft S. 2002. Power System Economics: Designing Markets for Electricity. New York: Wiley-Intersci.
  111. Sullivan P, Krey V, Riahi K. 2013. Impacts of considering electric sector variability and reliability in the MESSAGE model. Energy Strategy Rev. 1(3):157–63
  112. Surek T. 2003. Progress in US photovoltaics: looking back 30 years and looking ahead 20. Proc. World Conf. Photovolt. Energy Convers., 3rd, May 18, 3:2507–12. Golden, CO: Natl. Renew. Energy Lab.
  113. Tavoni M, De Cian E, Luderer G, Steckel J, Waisman H. 2012. The value of technology and of its evolution towards a low carbon economy. Clim. Change 114:39–57 [Google Scholar]
  114. Taylor M. 2008. Beyond technology-push and demand-pull: lessons from California’s solar policy. Energy Econ. 30:2829–54 [Google Scholar]
  115. Thompson P. 2007. How much did the Liberty shipbuilders forget?. Manag. Sci. 53:908–18 [Google Scholar]
  116. van Benthem A, Gillingham K, Sweeney J. 2008. Learning-by-doing and the optimal solar policy in California. Energy J. 29:131–51 [Google Scholar]
  117. van der Zwaan B, Rabl A. 2004. The learning potential of photovoltaics: implications for energy policy. Energy Policy 32:1545–54 [Google Scholar]
  118. van Sarka W, Brandsen G, Fleuster M, Hekkert M. 2007. Analysis of the silicon market: Will thin films profit?. Energy Policy 35:3121–25 [Google Scholar]
  119. van Vuuren DP, van Ruijven B, Hoogwijk M, Isaac M, de Vries HJM. 2006. TIMER 2: model description and application. Integrated Modelling of Global Environmental Change. An Overview of IMAGE 2.4ed. Bouwman AF, Kram T, Klein Goldewijk K. 39–59 Bilthoven: Neth. Environ. Assess. Agency [Google Scholar]
  120. Williams RH, Terzian G. 1993. A benefit/cost analysis of accelerated development of photovoltaic technology. Tech. Rep. 281, Cent. Energy Environ. Stud., Princeton Univ.
  121. Wright TP. 1936. Factors affecting the costs of airplanes. J. Aeronaut. Sci. 3:122–28 [Google Scholar]
  122. Yang CJ, Oppenheimer M. 2007. A “Manhattan project” for climate change?. Clim. Change 80:199–204 [Google Scholar]
  123. Zweibel K. 1999. Issues in thin film PV manufacturing cost reduction. Sol. Energy Mater. Sol. Cells 59:1–18 [Google Scholar]
/content/journals/10.1146/annurev-resource-091912-151843
Loading
/content/journals/10.1146/annurev-resource-091912-151843
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error