Pricing analysis in the Brazilian energy market: A decision tree approach

Filho, José Carlos Reston; Affonso, Carolina M.; Oliveira, Roberto Célio Limão de

doi:10.1109/ptc.2009.5282272

Cited by 12 publications

(9 citation statements)

References 7 publications

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“…Both importance studies [17,18] agree with ours. When production technologies, demand, stored energy are included as explanatory variables they share the first positions of the ranking with prices and lagged prices.…”

Section: Comparison With Other Data Mining Based Modelssupporting

confidence: 90%

“…For variable importance comparison purposes, only two studies have been found in the literature. Reston Filho et al [ 18] use clustering techniques and decision/classification tree approach for short term pricing analysis in the Brazilian energy market with predominance of hydro generation. In particular they also identify those variables that most influence the short-term electricity price.…”

Section: Comparison With Other Data Mining Based Modelsmentioning

confidence: 99%

“…Explanatory variables include lagged prices, load and lagged load, which are in common with our study, and some others such as temperature, dew point, but regardless of the technologies involved in the generation. In [18] clustering techniques are used to identify those variables that most influence the short-term electricity price in the Brazilian market. These variables include load, hydro and thermal generation and calendar variables denoting season and month.…”

Section: Introductionmentioning

confidence: 99%

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Important variable assessment and electricity price forecasting based on regression tree models: classification and regression trees, Bagging and Random Forests

González

Mira-McWilliams

Juárez³

2015

IET Generation, Transmission & Distribution

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Section: Comparison With Other Data Mining Based Modelssupporting

confidence: 90%

Section: Comparison With Other Data Mining Based Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Important variable assessment and electricity price forecasting based on regression tree models: classification and regression trees, Bagging and Random Forests

González

Mira-McWilliams

Juárez³

2015

IET Generation, Transmission & Distribution

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“…Desde 2010, o MLE ganhou força devido ao aumento de consumidores especiais. Isto se deve, em grande parte, ao desconto na TUSD que torna as fontes de incentivo competitivas para suprir esse tipo de consumidor médio (formado por pequenas indústrias e shopping centers de médio e grande porte) (Filho et al, 2009;Freire et al, 2012).…”

Section: Mercado Livre De Energia -Brasilunclassified

Migração de Consumidor Cativo para Consumidor Livre – Estudo de Caso em Santa Catarina

et al. 2020

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Este artigo apresenta um estudo para a migração do mercado cativo para o mercado livre de eletricidade para uma indústria do sul de Santa Catarina - Brasil. O trabalho visa reduzir os gastos com eletricidade e demonstrar as vantagens, desvantagens e condições técnicas necessárias para se tornar um consumidor livre. Para o desenvolvimento desta análise, considera-se o consumo médio de energia e os geradores de conjuntos com os quais conta a unidade industrial. Além disso, a análise de viabilidade econômica é baseada em projeções de demanda por ano e simulações de consumo para dois períodos diferentes, 2014 e 2015. Os resultados obtidos mostram que a reclassificação da unidade industrial no tipo de consumidor, resultando em uma economia significativa no custo de eletricidade. Este estudo demonstra que a migração para o mercado livre de eletricidade é tecnicamente viável e tem benefícios econômicos muito significativos para a empresa analisada.

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“…A review of different electricity price forecasting methods can be found in [1], and most methods are applied to PJM, New England and Spain markets. It is important to mention that few studies were developed in energy price prediction area applied to the Brazilian market [11,12].…”

Section: Introductionmentioning

confidence: 99%

Energy price prediction multi-step ahead using hybrid model in the Brazilian market

Filho¹,

Affonso

Oliveira

2014

Electric Power Systems Research

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Pricing analysis in the Brazilian energy market: A decision tree approach

Cited by 12 publications

References 7 publications

Important variable assessment and electricity price forecasting based on regression tree models: classification and regression trees, Bagging and Random Forests

Important variable assessment and electricity price forecasting based on regression tree models: classification and regression trees, Bagging and Random Forests

Migração de Consumidor Cativo para Consumidor Livre – Estudo de Caso em Santa Catarina

Energy price prediction multi-step ahead using hybrid model in the Brazilian market

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