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Assessment of Initial Investment Valuation Methodology of Brazilian Power Transmissions Auction
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作者 André L. V. Gimenes Raphael B. Heideier +1 位作者 Miguel E. M. Udaeta Marco A. Saidel 《Journal of Power and Energy Engineering》 2017年第1期75-90,共16页
This paper aims to assess the Initial Investment Valuation Methodology of the local regulator, facing the results of auctions, due to the high occurrence of low clearing prices observed from 2003 to 2008 and the high ... This paper aims to assess the Initial Investment Valuation Methodology of the local regulator, facing the results of auctions, due to the high occurrence of low clearing prices observed from 2003 to 2008 and the high percentage of auctions without any bidder recently. The regulator investment forecasted defines the maximum value of Yearly Allowed Revenue and the bidder that offers the lowest YAR value wins the auction. The first type of analysis considers project cost, location, execution deadline, transmission line extension and type of all actions from 1999 to 2015, totalling about 3.361 billion USD. It was not found any correlation of those variables and the result of the actions. The second analysis compared the equipment and the additional costs breakdown of the regulator investment forecast with the real investment in projects from 2009 to 2013 and it rarely surpasses 5%. Suggestions are proposed based on the analysis. 展开更多
关键词 BRAZILIAN AUCTION CLEARING PRICES Transmission Line VALUATION
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Application of data science in the prediction of solar energy for the Amazon basin:a study case
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作者 AndréLuis Ferreira Marques Márcio JoséTeixeira +1 位作者 Felipe Valencia de Almeida Pedro Luiz Pizzigatti Corrêa 《Clean Energy》 EI CSCD 2023年第6期1344-1355,共12页
The need for renewable energy sources has challenged most countries to comply with environmental protection actions and to handle climate change.Solar energy figures as a natural option,despite its intermittence.Brazi... The need for renewable energy sources has challenged most countries to comply with environmental protection actions and to handle climate change.Solar energy figures as a natural option,despite its intermittence.Brazil has a green energy matrix with significant expansion of solar form in recent years.To preserve the Amazon basin,the use of solar energy can help communities and cities improve their living standards without new hydroelectric units or even to burn biomass,avoiding harsh environmental consequences.The novelty of this work is using data science with machine-learning tools to predict the solar incidence(W.h/m^(2))in four cities in Amazonas state(north-west Brazil),using data from NASA satellites within the period of 2013-22.Decision-tree-based models and vector autoregressive(time-series)models were used with three time aggregations:day,week and month.The predictor model can aid in the economic assessment of solar energy in the Amazon basin and the use of satellite data was encouraged by the lack of data from ground stations.The mean absolute error was selected as the output indicator,with the lowest values obtained close to 0.20,from the adaptive boosting and light gradient boosting algorithms,in the same order of magnitude of similar references. 展开更多
关键词 solar energy renewable energy Amazon basin machine learning time series data science decision-trees ensemble vector autoregression
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