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

Paes, Carlos; Gandelman, Dan Abensur; Firmo, Heloísa Teixeira; Bahiense, Laura

doi:10.1016/j.renene.2021.11.060

Cited by 15 publications

(6 citation statements)

References 16 publications

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“…Paes et al [72] performed modeling of the Brazilian energy system, aggregating explicitly environmental parameters to the most commonly addressed socioeconomic parameters and imputing penalties, the restriction of greenhouse gas emissions or a carbon tax, relating a cost to environmental pollution within the objective function. The authors studied scenarios with and without the application of penalties.…”

Section: Case Studies Of Linear Programming In the Context Of Biomass...mentioning

confidence: 99%

“…Usually, in this stage the resource availability is promising but conversion technology has not been considered yet; • A second group involves Cundiff et al [64], Bruglieri and Liberti [66], Rocco and Morabito [67], Abdelhady et al [69], Yahya et al [33] and Saghaei et al [68]; their models aid the decision maker in the process of power plant location and/or storage location definition and multiple-facility operational status definition. Some of them also allow for uncertainty in the model (Saghaei et al [68], Cundiff et al [64]); • A third group focuses on the optimization for different uses for the considered biomasses; Ferretti [70] and Aghalari et al [71] could be included in this group; • A fourth group involves the research of Paes et al [72] that, despite optimizing the BSC from an economic standpoint, also uses explicit environmental constrains. Nienow et al [65] could also be placed in this group, since their research also helps the power plant comply with environmental regulations; • A fifth group involves Wu et al [38] whose research focuses on holistic approaches giving great attention to multidisciplinarity (geographic information systems and mathematical modeling with technical economic analysis and sensitivity analysis).…”

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confidence: 99%

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Tools for Optimization of Biomass-to-Energy Conversion Processes

et al. 2023

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Biomasses are renewable sources used in energy conversion processes to obtain diverse products through different technologies. The production chain, which involves delivery, logistics, pre-treatment, storage and conversion as general components, can be costly and uncertain due to inherent variability. Optimization methods are widely applied for modeling the biomass supply chain (BSC) for energy processes. In this qualitative review, the main aspects and global trends of using geographic information systems (GISs), linear programming (LP) and neural networks to optimize the BSC are presented. Modeling objectives and factors considered in studies published in the last 25 years are reviewed, enabling a broad overview of the BSC to support decisions at strategic, tactical and operational levels. Combined techniques have been used for different purposes: GISs for spatial analyses of biomass; neural networks for higher heating value (HHV) correlations; and linear programming and its variations for achieving objectives in general, such as costs and emissions reduction. This study reinforces the progress evidenced in the literature and envisions the increasing inclusion of socio-environmental criteria as a challenge in future modeling efforts.

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Section: Case Studies Of Linear Programming In the Context Of Biomass...mentioning

confidence: 99%

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confidence: 99%

Tools for Optimization of Biomass-to-Energy Conversion Processes

et al. 2023

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“…1 Apart from reducing greenhouse gas (GHG) emissions, the RESs provide low-cost energy. 2 As a result, they are the most valuable power source for the grid system. Due to its intermittent nature, RES cannot continuously supply power to meet the load demand.…”

Section: Highlightsmentioning

confidence: 99%

Toward an intelligent community microgrid energy management system based on optimal control schemes

Azaroual

Mbungu

Ouassaid

et al. 2022

Intl J of Energy Research

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This article investigates a modelization of the energy management strategy of a grid-tied photovoltaic (PV), wind generator, and battery system. The model uses a smart metering system to collect data from various electrical components of a microgrid. The power optimization strategy is modeled under demand response, including time-of-use pricing to create a home's energy flow more efficiently. Two optimal control strategies are developed to coordinate

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“…The hydropower operation is optimized using the NEWAVE model, being it a hydrothermal model [20]. Others researchers have formulation models to Brazilian case with greenhouse gas emission impact [21], however, without complementarity analyses.…”

Section: Introductionmentioning

confidence: 99%

Complementarity Between Renewable Energy Sources and Regions - Brazilian Case

Luz

Unsihuay-Vila

Aoki

2023

Braz. arch. biol. technol.

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The benefits of complementarity between renewable energy sources have been presented as having a positive impact, but it has been neglected in generation expansion planning studies. In this paper the complementarity between renewable energy sources and regions of Brazil is characterized and the correlation coefficients are analyzed. A methodology is also proposed to optimize the complementarity between the sources, reducing the energy storage requirements. The methodology is applied to the Brazilian case to meet the projected demand for 2050 with a 100% renewable system and the complementarity is analyzed. The characterization of the data allowed us to propose five solar regions, four wind regions, three hydro regions and a region to represent the biomass. It was possible to find complementarity (negative correlation) of: 0.97 between hydro regions; 0.86 between wind and hydro regions and; 0.96 between biomass and hydro. The proposed methodology allowed us to know which regions and their respective technologies best benefit the electrical system, being the North for solar and the Northeast for wind. Finally, it was possible to reduce the demand for water storage with sources and regions that complement the seasonal hydro drought period.

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

Cited by 15 publications

References 16 publications

Tools for Optimization of Biomass-to-Energy Conversion Processes

Tools for Optimization of Biomass-to-Energy Conversion Processes

Toward an intelligent community microgrid energy management system based on optimal control schemes

Complementarity Between Renewable Energy Sources and Regions - Brazilian Case

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