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Developing a module for estimating climate warming effects on hydropower pricing in California

Guegan, Marion; Bertacchi Uvo, Cintia LU and Madani, Kaveh (2012) In Energy Policy 42. p.261-271
Abstract
Climate warming is expected to alter hydropower generation in California through affecting the annual stream-flow regimes and reducing snowpack. On the other hand, increased temperatures are expected to increase hydropower demand for cooling in warm periods while decreasing demand for heating in winter, subsequently altering the annual hydropower pricing patterns. The resulting variations in hydropower supply and pricing regimes necessitate changes in reservoir operations to minimize the revenue losses from climate warming. Previous studies in California have only explored the effects of hydrological changes on hydropower generation and revenues. This study builds a long-term hydropower pricing estimation tool, based on artificial neural... (More)
Climate warming is expected to alter hydropower generation in California through affecting the annual stream-flow regimes and reducing snowpack. On the other hand, increased temperatures are expected to increase hydropower demand for cooling in warm periods while decreasing demand for heating in winter, subsequently altering the annual hydropower pricing patterns. The resulting variations in hydropower supply and pricing regimes necessitate changes in reservoir operations to minimize the revenue losses from climate warming. Previous studies in California have only explored the effects of hydrological changes on hydropower generation and revenues. This study builds a long-term hydropower pricing estimation tool, based on artificial neural network (ANN), to develop pricing scenarios under different climate warming scenarios. Results suggest higher average hydropower prices under climate warming scenarios than under historical climate. The developed tool is integrated with California's Energy-Based Hydropower Optimization Model (EBHOM) to facilitate simultaneous consideration of climate warming on hydropower supply, demand and pricing. EBHOM estimates an additional 5% drop in annual revenues under a dry warming scenario when climate change impacts on pricing are considered, with respect to when such effects are ignored, underlining the importance of considering changes in hydropower demand and pricing in future studies and policy making. (C) 2011 Elsevier Ltd. All rights reserved. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Climate change, Hydropower, Artificial Neural Network
in
Energy Policy
volume
42
pages
261 - 271
publisher
Elsevier
external identifiers
  • wos:000301616000028
  • scopus:84856276335
ISSN
1873-6777
DOI
10.1016/j.enpol.2011.11.083
project
MERGE
language
English
LU publication?
yes
id
834ed57d-d243-41e6-9b6c-5c0216f92a58 (old id 2580995)
date added to LUP
2012-06-04 13:01:14
date last changed
2017-10-01 04:02:40
@article{834ed57d-d243-41e6-9b6c-5c0216f92a58,
  abstract     = {Climate warming is expected to alter hydropower generation in California through affecting the annual stream-flow regimes and reducing snowpack. On the other hand, increased temperatures are expected to increase hydropower demand for cooling in warm periods while decreasing demand for heating in winter, subsequently altering the annual hydropower pricing patterns. The resulting variations in hydropower supply and pricing regimes necessitate changes in reservoir operations to minimize the revenue losses from climate warming. Previous studies in California have only explored the effects of hydrological changes on hydropower generation and revenues. This study builds a long-term hydropower pricing estimation tool, based on artificial neural network (ANN), to develop pricing scenarios under different climate warming scenarios. Results suggest higher average hydropower prices under climate warming scenarios than under historical climate. The developed tool is integrated with California's Energy-Based Hydropower Optimization Model (EBHOM) to facilitate simultaneous consideration of climate warming on hydropower supply, demand and pricing. EBHOM estimates an additional 5% drop in annual revenues under a dry warming scenario when climate change impacts on pricing are considered, with respect to when such effects are ignored, underlining the importance of considering changes in hydropower demand and pricing in future studies and policy making. (C) 2011 Elsevier Ltd. All rights reserved.},
  author       = {Guegan, Marion and Bertacchi Uvo, Cintia and Madani, Kaveh},
  issn         = {1873-6777},
  keyword      = {Climate change,Hydropower,Artificial Neural Network},
  language     = {eng},
  pages        = {261--271},
  publisher    = {Elsevier},
  series       = {Energy Policy},
  title        = {Developing a module for estimating climate warming effects on hydropower pricing in California},
  url          = {http://dx.doi.org/10.1016/j.enpol.2011.11.083},
  volume       = {42},
  year         = {2012},
}