Hydropower revenues under the threat of climate change in Brazil

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2019-04-01

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© 2018 Elsevier Ltd This work analyzes the impacts of climate change in the revenues of hydropower plants. One important input for designing and evaluating investment opportunities in hydropower is the water inflows historical data. Unfortunately, the use of such information alone may not project well the future power generation due to the influence of climate change in the water inflow patterns. This paper introduces spatio-temporal information of the future climate into the operational planning of the Brazilian hydropower system. Global climate models from IPCC are considered along with downscaled regional climate models. Our results at the individual hydro plant level show the importance of taking into account climate change information when performing hydro generation planning studies.

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10.1016/j.renene.2018.10.050

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de Queiroz, AR, VAD Faria, LMM Lima and JWM Lima (2019). Hydropower revenues under the threat of climate change in Brazil. Renewable Energy, 133. pp. 873–882. 10.1016/j.renene.2018.10.050 Retrieved from https://hdl.handle.net/10161/18148.

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Lima

Luana Marangon Lima

Gendell Family Assistant Professor of the Practice

Dr. Luana Marangon Lima is an assistant professor of the practice for energy and environmental analytics at Duke University’s Nicholas School of the Environment. As faculty fellow at the Nicholas Institute for Energy, Environment & Sustainability, she works with faculty, staff, and students to enhance energy education offerings at Duke University.

She received her Ph.D. in operations research and industrial engineering from the Cockrell School of Engineering at University of Texas at Austin (2011). She holds a M.Sc. (2007) and B.Sc. (2005) in electrical engineering from Universidade Federal de Itajuba (Brazil).

Prior to joining Duke, she was an assistant professor in the electrical and energy systems department at Universidade Federal de Itajuba (Brazil). She also worked as a consultant for several years at MC&E.

Her research and teaching focus on optimization methods and data analytics applications to energy systems—more specifically, renewable energy integration, electricity markets, power generation planning and scheduling, and transmission and distribution grid regulation.


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