The power generation expansion planning in Brazil: Considering the impact of greenhouse gas emissions in an Investment Decision Model

Carlos Eduardo Paes, Dan Abensur Gandelman, Heloisa Teixeira Firmo and Laura Bahiense

Renewable Energy, 2022, vol. 184, issue C, 225-238

Abstract: 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/tCO2eq 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 MtCO2eq in relation to the reference scenario at the end of the planning horizon.

Keywords: Power generation expansion planning; Renewable energy; Greenhouse gases emission; Mathematical programming decision model (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:184:y:2022:i:c:p:225-238

DOI: 10.1016/j.renene.2021.11.060

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