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Author (up) Ramirez-Sagner, G.; Munoz, F.D. doi  openurl
  Title The effect of head-sensitive hydropower approximations on investments and operations in planning models for policy analysis Type Journal Article
  Year 2019 Publication Renewable & Sustainable Energy Reviews Abbreviated Journal Renew. Sust. Energ. Rev.  
  Volume 105 Issue Pages 38-47  
  Keywords Generation planning; Hydropower; Policy analysis; Simplifications; Uncertainty  
  Abstract Planning for new generation infrastructure in hydrothermal power systems requires consideration of a series of nonlinearities that are often ignored in planning models for policy analysis. In this article, three different capacity- planning models are used, one nonlinear and two linear ones, with different degrees of complexity, to quantify the impact of simplifying the head dependency of hydropower generation on investments in both conventional and renewable generators and system operations. It was found that simplified investment models can bias the optimal generation portfolios by, for example, understating the need for coal and combined-cycle gas units and overstating investments in wind capacity with respect to a more accurate nonlinear formulation, which could affect policy recommendations. It was also found that the economic cost of employing a simplified model can be below 10% of total system cost for most of the scenarios and system configurations analyzed, but as high as nearly 70% of total system cost for specific applications. Although these results are not general, they suggest that for certain system configurations both linear models can provide reasonable approximations to more complex nonlinear formulations. Uncertain water inflows were also considered using stochastic variants of all three planning models. Interestingly, if due to time or computational limitations only one of these two features could be accounted for, these results indicate that explicit modeling of the nonlinear-head effect in a deterministic model could yield better results (up to 0.6% of economic regret) than a stochastic linear model (up to 9.6% of economic regret) that considers the uncertainty of water inflows.  
  Address [Ramirez-Sagner, Gonzalo] Fraunhofer Chile Res, Ctr Solar Energy Technol, Santiago, Chile, Email: grramire@uc.cl;  
  Corporate Author Thesis  
  Publisher Pergamon-Elsevier Science Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1364-0321 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000460121000003 Approved no  
  Call Number UAI @ eduardo.moreno @ Serial 988  
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