Journal
RENEWABLE ENERGY
Volume 184, Issue -, Pages 225-238Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.renene.2021.11.060
Keywords
Power generation expansion planning; Renewable energy; Greenhouse gases emission; Mathematical programming decision model
Funding
- Coordenacao de Aper-feicoamento de Pessoal de Nivel Superior-Brazil (CAPES) [001]
- National Council for Scientific and Technological Development-Brazil (CNPq) [309661/2019-6]
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The Generation Expansion Planning (GEP) process in Brazil takes into account various factors and constraints, including technical, economic, environmental, and climatic aspects. This study introduces scenarios that penalize or limit greenhouse gas emissions into the investment decision model (MDI) used in Brazil, aiming to assess the impact of emission reduction objectives on the optimum expansion planning. The results show that adopting a monetary penalty for fossil fuel combustion of US$25.00/tCO(2eq) leads to the largest reduction in emissions, with a corresponding increase in the expansion of wind and biomass sources.
The Generation Expansion Planning (GEP) process in Brazil involves computational models with a range of variables and constraints inherent in a mostly hydrothermal system. Such models generally use technical and economic parameters to represent the system, but with the growing concern about environmental and climatic issues, the need has arisen for environmental parameter analysis to promote a better representation of a more comprehensive optimum. In view of the recent Paris Agreement, through which the Brazilian government committed itself to significantly reduce its greenhouse gas emissions (GHG) by 2030, it has become essential that the GEP take into account the emission of gases. In this work, scenarios that penalize or limit the emission of greenhouse gases are created and compared inside the existent Investment Decision Model (MDI) used in Brazil. The main objective is to verify how the objective of reducing emissions would change the optimum expansion planning originally provided by the investment model. The results show that within the created scenarios, the largest reduction is achieved when considering a monetary penalty of US$ 25.00/tCO(2eq) in the burning of fossil fuels for power generation. In this case, to reduce the emissions, the investment model chooses a larger expansion of wind and biomass sources with a corresponding raise in the cost of approximately 5.3%, allowing a total reduction of about 39 MtCO(2eq) in relation to the reference scenario at the end of the planning horizon. (C) 2021 Elsevier Ltd. All rights reserved.
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