Alessandra Maciel de Lima Barros, M. Sobral, Janaina Maria Oliveira de Assis, Werônica Meira de Souza
{"title":"Influence of rainfall on wind power generation in Northeast Brazil","authors":"Alessandra Maciel de Lima Barros, M. Sobral, Janaina Maria Oliveira de Assis, Werônica Meira de Souza","doi":"10.5327/z21769478769","DOIUrl":null,"url":null,"abstract":"Wind power has been emerging as one of the main renewable energy sources in Northeast Brazil, which concentrates 87% of the country’s installed wind capacity, especially in recent years, due to water scarcity and its seasonal energy complementarity to hydraulic generation. The objective of this article is to present a method to evaluate the influence of rainfall on the behavior of wind power generation, considering rainfall anomaly index and extreme climatic indices of precipitation. We utilized daily rainfall data from cities located near wind farms CE1 and CE2 in the state of Ceará — Aracati, in the 1974-2016 period, and Trairi, in the 1976-2016 period —, as well as daily wind power generation data for the same period, provided by the Electric System National Operator (ONS). The RClimdex software was used to calculate 11 indices of climatic extremes dependent on rainfall. The capacity factor for wind power generation was calculated for the period from 2011 to 2016 for the CE1 and CE2 wind farms. The application of this method found an inversely proportional relation between rainfall anomaly index (RAI) and the wind power capacity factor, with a decrease in total rainfall and a greater number of consecutive dry days and concentrated rain in the short term. From 2012 to 2016, the rainfall anomaly index was negative. However, wind power factors were higher than in 2011. The developed methodology can be applied to other wind farms, contributing to the medium and long term energy planning of the National Interconnected System.","PeriodicalId":33560,"journal":{"name":"Revista Brasileira de Ciencias Ambientais","volume":" ","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2021-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista Brasileira de Ciencias Ambientais","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5327/z21769478769","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 1
Abstract
Wind power has been emerging as one of the main renewable energy sources in Northeast Brazil, which concentrates 87% of the country’s installed wind capacity, especially in recent years, due to water scarcity and its seasonal energy complementarity to hydraulic generation. The objective of this article is to present a method to evaluate the influence of rainfall on the behavior of wind power generation, considering rainfall anomaly index and extreme climatic indices of precipitation. We utilized daily rainfall data from cities located near wind farms CE1 and CE2 in the state of Ceará — Aracati, in the 1974-2016 period, and Trairi, in the 1976-2016 period —, as well as daily wind power generation data for the same period, provided by the Electric System National Operator (ONS). The RClimdex software was used to calculate 11 indices of climatic extremes dependent on rainfall. The capacity factor for wind power generation was calculated for the period from 2011 to 2016 for the CE1 and CE2 wind farms. The application of this method found an inversely proportional relation between rainfall anomaly index (RAI) and the wind power capacity factor, with a decrease in total rainfall and a greater number of consecutive dry days and concentrated rain in the short term. From 2012 to 2016, the rainfall anomaly index was negative. However, wind power factors were higher than in 2011. The developed methodology can be applied to other wind farms, contributing to the medium and long term energy planning of the National Interconnected System.