Cost-effectiveness as energy policy mechanisms: The paradox of technology-neutral and technology-specific policies in the short and long term

When choosing policy mechanisms to design and deploy energy policies, policymakers typically seek cost-effective ones, linking cost effectiveness to the lowest cost of support for RES-E generation and/or consumer costs. The objectives of this paper are to analyze the cost-effectiveness of renewable portfolio standards (RPS), feed-in tariffs (FIT) and auctions in the short and long term, considering both technology-neutral and technology-specific approaches. Results show that RPS and auctions are more cost-effective than feed-in tariffs (FIT) in the short term if cost-effectiveness is defined as minimizing consumer costs. Also, if one or more emerging technologies with higher levelized life cycle costs (LCC), low cumulative production and high experience elasticity are considered in the pool of RES-E policy design, a technology-neutral approach in the short-term could lock out these emerging technologies, avoiding a long term LCC reduction. In this case, a technology-specific policy used in the short-term would reflect lower total generation policy costs in the long term if compared with a technology-neutral policy in both short and long term. This paper calls this phenomenon the paradox of technology-neutral and technology-specific policies in the long term. Considering the results, this paper suggests a mix of technology-neutral and technology-specific policies using RPS or auction mechanisms to promote RES-E.

[1]  R. Schmalensee.  Evaluating Policies to Increase the Generation of Electricity from Renewable Energy , 2011 .

[2]  Gregory F. Nemet,et al.  Beyond the learning curve: factors influencing cost reductions in photovoltaics , 2006 .

[3]  P. A. Østergaard,et al.  Electricity market auction settings in a future Danish electricity system with a high penetration of , 2011 .

[4]  Norzita Ngadi,et al.  Recent advances of feed-in tariff in Malaysia , 2015 .

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

[6]  V. Kathuria,et al.  Role of policy in deployment of wind energy: evidence across states of India , 2016 .

[7]  Eric Hu,et al.  Development of renewable energy in Australia and China: A comparison of policies and status , 2016 .

[8]  Christine Woerlen.  Experience Curves for Energy Technologies , 2004 .

[9]  Greg Buckman,et al.  The large-scale solar feed-in tariff reverse auction in the Australian Capital Territory, Australia , 2014 .

[10]  M. Makela,et al.  Pellet promotion in the Finnish sawmilling industry: The cost-effectiveness of different policy instruments , 2011 .

[11]  Chelsea Schelly,et al.  Implementing renewable energy portfolio standards: The good, the bad, and the ugly in a two state comparison , 2014 .

[12]  Martin Kumar Patel,et al.  A review of experience curve analyses for energy demand technologies , 2010 .

[13]  O. Edenhofer,et al.  Renewable Energy Sources and Climate Change Mitigation , 2011 .

[14]  S. Valentine.  Disputed wind directions: Reinvigorating wind power development in Taiwan , 2010 .

[15]  J. Huenteler.  International Support for Feed-In Tariffs in Developing Countries – A Review and Analysis of Proposed Mechanisms , 2014 .

[16]  Peng Sun,et al.  A comparative study of feed-in tariff and renewable portfolio standard policy in renewable energy industry , 2015 .

[17]  J. Sandeman,et al.  Feed‐In Tariffs: Accelerating the Deployment of Renewable Energy , 2010 .

[18]  Ushio Sumita,et al.  Importance of policy for energy system transformation: Diffusion of PV technology in Japan and Germany , 2014 .

[19]  Shih-Mo Lin,et al.  Policy target, feed-in tariff, and technological progress of PV in Taiwan , 2014 .

[20]  Erwin Schmid,et al.  Where the wind blows: Assessing the effect of fixed and premium based feed-in tariffs on the spatial diversification of wind turbines , 2013 .

[21]  Paris A. Fokaides,et al.  Competitive auction mechanisms for the promotion renewable energy technologies: The case of the 50MW photovoltaics projects in Cyprus , 2015 .

[22]  Felix Groba,et al.  Assessing the Strength and Effectiveness of Renewable Electricity Feed-In Tariffs in European Union Countries , 2011 .

[23]  W.G.J.H.M. van Sark,et al.  Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects , 2011 .

[24]  Tapas K. Mallick,et al.  Feed-in tariff for solar photovoltaic: The rise of Japan , 2014 .

[25]  C. Batlle,et al.  Electricity auctions in South America: Towards convergence of system adequacy and RES-E support , 2014 .

[26]  Friedemann Polzin,et al.  Public policy influence on renewable energy investments—A panel data study across OECD countries , 2015 .

[27]  Alireza Aslani,et al.  Analysis of renewable energy development to power generation in the United States , 2014 .

[28]  H. Kung.  Impact of deployment of renewable portfolio standard on the electricity price in the State of Illinois and implications on policies , 2012 .

[29]  Luke J.L. Eastin.  An Assessment of the Effectiveness of Renewable Portfolio Standards in the United States , 2014 .

[30]  Emilio Cerdá,et al.  The policy implications of the different interpretations of the cost-effectiveness of renewable electricity support , 2014 .

[31]  Paul Komor,et al.  Limiting the costs of renewable portfolio standards: A review and critique of current methods , 2012 .

[32]  Hugh Rudnick,et al.  Auction approaches of long-term contracts to ensure generation investment in electricity markets: Lessons from the Brazilian and Chilean experiences $ , 2010 .

[33]  Richard Schmalensee,et al.  Evaluating Policies to Increase Electricity Generation from Renewable Energy , 2012, Review of Environmental Economics and Policy.

[34]  Ron Cameron.  Projected Costs of Electricity Generation , 2010 .

[35]  Karin Ibenholt.  Explaining learning curves for wind power , 2002 .

[36]  F. Ferioli,et al.  Use and limitations of learning curves for energy technology policy: A component-learning hypothesis , 2009 .

[37]  Chuanwen Jiang,et al.  A review on promoting share of renewable energy by green-trading mechanisms in power system , 2014 .

[38]  R. Haas,et al.  Fixed feed-in tariff versus premium: A review of the current Spanish system , 2012 .

[39]  Ram M. Shrestha,et al.  Energy, environmental and economic effects of Renewable Portfolio Standards (RPS) in a Developing Country , 2013 .

[40]  E. E. Rego,et al.  Brazilian experience in electricity auctions: Comparing outcomes from new and old energy auctions as well as the application of the hybrid Anglo-Dutch design , 2013 .

[41]  Mario Ragwitz,et al.  Efficiency and effectiveness of promotion systems for electricity generation from renewable energy sources – Lessons from EU countries , 2011 .

[42]  Tugrul U. Daim,et al.  Assessing Renewable Energy Portfolio Futures with Multiple Perspectives: The Case of the Northwest US , 2010 .

[43]  V. Lauber,et al.  Assessing the performance of renewable electricity support instruments , 2012 .

[44]  Martin Junginger,et al.  Technological learning in the energy sector : lessons for policy, industry and science , 2010 .

[45]  Erik Eduardo Rego.  Reserve price: Lessons learned from Brazilian electricity procurement auctions , 2013 .

[46]  Makoto Tanaka,et al.  Market power in renewable portfolio standards , 2013 .