利用人工神经网络和双向长短期记忆为土耳其安装太阳能发电预测

M. Özdemir, Murat Ince, Batin Latif Aylak, O. Oral, M. Taş
{"title":"利用人工神经网络和双向长短期记忆为土耳其安装太阳能发电预测","authors":"M. Özdemir, Murat Ince, Batin Latif Aylak, O. Oral, M. Taş","doi":"10.15295/bmij.v8i5.1639","DOIUrl":null,"url":null,"abstract":"Renewable energy sources play an essential role in sustainable development. The share of renewable energy-based energy generation is rapidly increasing all over the world. Turkey has a great potential in terms of both solar and wind energy due to its geographical location. The desired level has not yet been reached in using this potential. Nevertheless, with the increase in installed power in recent years, electricity generation from solar energy has gained momentum. In this study, data on cumulative installed solar power in Turkey in the 2009-2019 period were used. Artificial Neural Network (ANN) and Bidirectional Long Short-Term Memory (BLSTM) methods were selected to predict the cumulative installed solar power for 2020 with these data. The cumulative installed power was predicted, and the results were compared and interpreted.","PeriodicalId":333522,"journal":{"name":"Business & Management Studies: An International Journal","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"INSTALLED SOLAR POWER PREDICTION FOR TURKEY USING ARTIFICIAL NEURAL NETWORK AND BIDIRECTIONAL LONG SHORT-TERM MEMORY\",\"authors\":\"M. Özdemir, Murat Ince, Batin Latif Aylak, O. Oral, M. Taş\",\"doi\":\"10.15295/bmij.v8i5.1639\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Renewable energy sources play an essential role in sustainable development. The share of renewable energy-based energy generation is rapidly increasing all over the world. Turkey has a great potential in terms of both solar and wind energy due to its geographical location. The desired level has not yet been reached in using this potential. Nevertheless, with the increase in installed power in recent years, electricity generation from solar energy has gained momentum. In this study, data on cumulative installed solar power in Turkey in the 2009-2019 period were used. Artificial Neural Network (ANN) and Bidirectional Long Short-Term Memory (BLSTM) methods were selected to predict the cumulative installed solar power for 2020 with these data. The cumulative installed power was predicted, and the results were compared and interpreted.\",\"PeriodicalId\":333522,\"journal\":{\"name\":\"Business & Management Studies: An International Journal\",\"volume\":\"82 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Business & Management Studies: An International Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15295/bmij.v8i5.1639\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Business & Management Studies: An International Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15295/bmij.v8i5.1639","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

可再生能源在可持续发展中发挥着重要作用。在世界范围内,可再生能源发电的份额正在迅速增加。由于其地理位置,土耳其在太阳能和风能方面都有很大的潜力。在利用这一潜力方面尚未达到理想的水平。然而,随着近年来装机容量的增加,太阳能发电势头强劲。在这项研究中,使用了2009-2019年期间土耳其累计安装的太阳能发电数据。采用人工神经网络(ANN)和双向长短期记忆(BLSTM)方法对2020年太阳能累计装机容量进行预测。对累计装机功率进行了预测,并对预测结果进行了比较和解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
INSTALLED SOLAR POWER PREDICTION FOR TURKEY USING ARTIFICIAL NEURAL NETWORK AND BIDIRECTIONAL LONG SHORT-TERM MEMORY
Renewable energy sources play an essential role in sustainable development. The share of renewable energy-based energy generation is rapidly increasing all over the world. Turkey has a great potential in terms of both solar and wind energy due to its geographical location. The desired level has not yet been reached in using this potential. Nevertheless, with the increase in installed power in recent years, electricity generation from solar energy has gained momentum. In this study, data on cumulative installed solar power in Turkey in the 2009-2019 period were used. Artificial Neural Network (ANN) and Bidirectional Long Short-Term Memory (BLSTM) methods were selected to predict the cumulative installed solar power for 2020 with these data. The cumulative installed power was predicted, and the results were compared and interpreted.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信