{"title":"Risk Analysis of Levelized Cost of Electricity to Renewable Energy in Brazil","authors":"Daywes Pinheiro-Neto, Elder GeraldoDomingues, Luane SchiochetPinto","doi":"10.1109/EEEIC.2018.8493850","DOIUrl":null,"url":null,"abstract":"This paper presents a risk analysis approach of levelized cost of electricity (LCOE) to renewable energy in Brazil: hydro, wind, and photovoltaic energy. The Monte Carlo method is applied to stochastic models to generate synthetic time series of four random variables: water inflow, wind speed, solar irradiance, and temperature of photovoltaic panel. Probability distribution of the levelized cost of electricity for the three sources are provided and analyzed. In addition, a sensitivity analysis was performed considering two key parameters: investment expenditure and discount rate, where a comparative analysis between sources is carried out. The results provide important risk information to assist policy makers and investors in the decision-making process.","PeriodicalId":6563,"journal":{"name":"2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)","volume":"65 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EEEIC.2018.8493850","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper presents a risk analysis approach of levelized cost of electricity (LCOE) to renewable energy in Brazil: hydro, wind, and photovoltaic energy. The Monte Carlo method is applied to stochastic models to generate synthetic time series of four random variables: water inflow, wind speed, solar irradiance, and temperature of photovoltaic panel. Probability distribution of the levelized cost of electricity for the three sources are provided and analyzed. In addition, a sensitivity analysis was performed considering two key parameters: investment expenditure and discount rate, where a comparative analysis between sources is carried out. The results provide important risk information to assist policy makers and investors in the decision-making process.