Systemic value of electricity sources – What we can learn from the Brazilian experience?

Romeiro, Diogo Lisbona; Almeida, Edmar Luiz Fagundes de; Losekann, Luciano

doi:10.1016/j.enpol.2020.111247

Cited by 13 publications

(5 citation statements)

References 32 publications

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“…This lower time boundary is selected in line with the most updated reports by RES energy agencies currently publicly available [1]. In this sense, some references can be found dealing with auctions at particular countries [5][6][7][8][9][10][11][12][13][14][15][16] or for various country groupings [17][18][19].…”

Section: State-of-the-artmentioning

confidence: 99%

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Renewable Energy Auction Prices: Near Subsidy-Free?

et al. 2020

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The latest trend of low record bid prices in renewable energy auctions has raised concerns on the effective deployment of the winning projects. A survey of recent auction data from several countries, technologies and remuneration designs is analysed and compared with the corresponding levelised costs of energy (LCOEs) to draw first insights on their viability. A critical assessment of the ability of the LCOE for determining the adequate bid level is then performed and the preliminary unviable results of selected mature technologies are further investigated using improved profitability metrics as the project and equity net present value (NPV) and internal rate of return (IRR). As representative examples, the analysed Danish 2019 onshore wind and photovoltaics (PV) auctions require very specific scenarios to become viable, which cast doubts on their effective implementation. Under the assumptions of a realistic base case, the sensitivity analysis revealed that either 59% of decrease in the weighted average cost of capital (WACC), or 37% of discount on the investment cost or a 3.6% annual increment in the mean market price is needed for achieving the NPV break-even in the onshore wind case. Likewise, the PV case is unprofitable whatever the WACC may be, and either a 60% discount on the investment cost or a 6.8% annual increment in the mean market price is needed for the NPV to break-even. Although some projects could be relying on indirect revenues or additional sources of incomes beyond the auction support, it remains to see if they are finally materialised.

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Section: State-of-the-artmentioning

confidence: 99%

“…The auction programs and outcomes in Germany are analysed for PV in [11], for onshore wind in [12,13] and for offshore wind in [14,15]. A technological comparison of different energy sources is made for the centralised expansion auctions in Brazil [16].…”

Section: State-of-the-artmentioning

confidence: 99%

Renewable Energy Auction Prices: Near Subsidy-Free?

et al. 2020

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“…In Brazil, renewable energies already present a great share of the electricity matrix and have further potential to replace fossil-based options. Hydroelectricity is stagnated (Romeiro et al, 2020), but wind, solar, and biomass can considerably increase their contribution to the matrix. Currently, solar represents only 1% of the electricity matrix, but its contribution increased from only 16 GWh in 2014 to 6655 GWh in 2019, while wind increased 360% from 2014 to 2019 (EPE, 2016(EPE, , 2020.…”

Section: Sustainability Implications For Decarbonization Of Electrici...mentioning

confidence: 99%

Addressing the contributions of electricity from biomass in Brazil in the context of the Sustainable Development Goals using life cycle assessment methods

Souza

Chagas

et al. 2022

J of Industrial Ecology

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The implications of bioenergy deployment for sustainable development goals (SDGs) have been gaining importance worldwide, as bioenergy may contribute to other sustainability impacts besides climate change. Decarbonization of the energy sector can promote major co-benefits between Climate Action and other SDGs and lead to important tradeoffs. Life cycle assessment (LCA) methods have been proposed to monitor the SDGs as many of them are closely interconnected but often separately studied.A harmonized application of environmental and social LCA can reveal additional relevant aspects of SDGs. This work proposes an interpretation of combined environmental and socioeconomic LCA impacts by comparing the SDG impacts of electricity from sugarcane biomass with other technological options, which altogether represent 96% of the Brazilian electricity matrix. Our analysis indicates that sugarcane electricity has a higher SDGs score (58 points) compared to coal and oil electricity (42 and 47 points, respectively); however, it is lower than natural gas (78). Sugarcane SDG internal normalization related to the biosphere is very close to natural gas, varying only 3-4 points.On the Economy and Society SDG score, sugarcane electricity is also lower than natural gas. Key areas in sugarcane electricity production that need to be enhanced to better contribute to achieving the SDGs include improving its awareness levels, increasing wages and women representation on the workforce, and promoting measures to decrease work accidents as well as the use of fertilizers and pesticides. This approach may help design specific measures for different value chains for them to significantly contribute to the achievement of SDGs.

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“…No Brasil, o cenário do mercado de eletricidade é parecido com o mundial [9], sendo basicamente privado [10], exceto pelas grandes gerações hidráulicas de energia elétrica e suas longas linhas de transmissão [11] [12]. Também há um aumento no uso de geração eólica [13], com a região Nordeste do país sendo a grande fonte de energia primária.…”

Section: Introductionunclassified

Aplicação Híbrida com Redes Neurais Profundas e Algoritmo Genético para Previsão de Séries Temporais do Sistema de Energia Elétrica Brasileira

Conte¹,

Conte²,

Oliveira³

2021

Anais Do 15. Congresso Brasileiro De Inteligência Computacional

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O cenário da energia elétrica no Brasil é influenciado por fatores complexos, além de possuir relações não lineares, o que dificulta sua previsibilidade. Para superar esse problema, propomos uma adaptação baseada na combinação de Redes Neurais Artificiais Profundas e Algoritmo Genético – AG para uso na previsão de algumas séries temporais do setor de energia elétrica brasileira. O AG usa um genótipo binário, de 53 bits, que busca o melhor número de camadas intermediárias, melhor número de células e modificações por Dropout para projetar a estrutura do Long Short Term Memory – LSTM e assim aprimorar a predição. Simulações foram realizadas para verificar o desempenho do método proposto em conjuntos de dados do mundo real: Preço de Liquidação das Diferenças e Velocidade do Vento de aerogeradores do Nordeste do Brasil. Verificou-se que a combinação do AG e LSTM tem melhores predições, em comparação com modelo Perceptron Multicamadas – MLP. Esses resultados mostram que, a abordagem é de grande utilidade para aprimorar e consolidar práticas voltadas para regulação de setor elétrico com o uso do PLD, e também para conversão da energia eólica para energia elétrica.

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Systemic value of electricity sources – What we can learn from the Brazilian experience?

Cited by 13 publications

References 32 publications

Renewable Energy Auction Prices: Near Subsidy-Free?

Renewable Energy Auction Prices: Near Subsidy-Free?

Addressing the contributions of electricity from biomass in Brazil in the context of the Sustainable Development Goals using life cycle assessment methods

Aplicação Híbrida com Redes Neurais Profundas e Algoritmo Genético para Previsão de Séries Temporais do Sistema de Energia Elétrica Brasileira

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