Assessing Economic Complementarity in Wind–Solar Hybrid Power Plants Connected to the Brazilian Grid
Rafael B. S. Veras (),
Clóvis B. M. Oliveira,
Shigeaki L. de Lima,
Osvaldo R. Saavedra,
Denisson Q. Oliveira,
Felipe M. Pimenta,
Denivaldo C. P. Lopes,
Audálio R. Torres Junior,
Francisco L. A. Neto,
Ramon M. de Freitas and
Arcilan T. Assireu
Additional contact information
Rafael B. S. Veras: Institute of Electrical Energy, Federal University of Maranhão, Av. dos Portugueses s/n, São Luís 65080-040, MA, Brazil
Clóvis B. M. Oliveira: Institute of Electrical Energy, Federal University of Maranhão, Av. dos Portugueses s/n, São Luís 65080-040, MA, Brazil
Shigeaki L. de Lima: Institute of Electrical Energy, Federal University of Maranhão, Av. dos Portugueses s/n, São Luís 65080-040, MA, Brazil
Osvaldo R. Saavedra: Institute of Electrical Energy, Federal University of Maranhão, Av. dos Portugueses s/n, São Luís 65080-040, MA, Brazil
Denisson Q. Oliveira: Institute of Electrical Energy, Federal University of Maranhão, Av. dos Portugueses s/n, São Luís 65080-040, MA, Brazil
Felipe M. Pimenta: Center for Physical and Mathematical Sciences, Postgraduate Program in Oceanography, Trindade Campus, Federal University of Santa Catarina, Florianópolis 88040-900, SC, Brazil
Denivaldo C. P. Lopes: Institute of Electrical Energy, Federal University of Maranhão, Av. dos Portugueses s/n, São Luís 65080-040, MA, Brazil
Audálio R. Torres Junior: Institute of Electrical Energy, Federal University of Maranhão, Av. dos Portugueses s/n, São Luís 65080-040, MA, Brazil
Francisco L. A. Neto: Laboratory of Applied Meteorology, Federal University of Rio de Janeiro, Rio de Janeiro 21941-916, RJ, Brazil
Ramon M. de Freitas: Camargo Schubert Wind Engineering, Rua Juvenal Galeno-55, Curitiba 82520-030, PR, Brazil
Arcilan T. Assireu: Institute of Natural Resources, Federal University of Itajubá, Av. BPS 1303, Pinheirinho, Itajubá 37500-903, MG, Brazil
Sustainability, 2023, vol. 15, issue 11, 1-20
Abstract:
The share of electricity generation from Variable Renewable Energy Sources (VRES) has increased over the last 20 years. Despite promoting the decarbonization of the energy mix, these sources bring negative characteristics to the energy mix, such as power ramps, load mismatch, unpredictability, and fluctuation. One of the ways to mitigate these characteristics is the hybridization of power plants. This paper evaluates the benefits of hybridizing a plant using an AI-based methodology for optimizing the wind–solar ratio based on the Brazilian regulatory system. For this study, the hybrid plant was modeled using data collected over a period of 10 months. The measurements were obtained using two wind profilers (LIDAR and SODAR) and a sun tracker (Solys 2) as part of the EOSOLAR R&D project conducted in the state of Maranhão, Brazil. After the power plant modeling, a Genetic Algorithm (GA) was used to determine the optimal wind–solar ratio, considering costs with transmission systems. The algorithm achieved a monthly profit increase of more than 39% with an energy curtailment inferior to 1%, which indicates economic complementarity. Later, the same methodology was also applied to verify the wind–solar ratio’s sensitivity to solar energy pricing. The results show that a price increase of 15% would change the power plant’s optimal configuration.
Keywords: wind power; solar power; hybrid power plants; optimization; economic complementarity; Maranhão state; Brazil Interconnected System (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:11:p:8862-:d:1160509
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