基于自适应神经模糊推理系统(ANFIS)的间歇性风能和光伏资源长期预测

S. Makhloufi, M. Debbache, S. Boulahchiche
{"title":"基于自适应神经模糊推理系统(ANFIS)的间歇性风能和光伏资源长期预测","authors":"S. Makhloufi, M. Debbache, S. Boulahchiche","doi":"10.1109/ICWEAA.2018.8605102","DOIUrl":null,"url":null,"abstract":"Forecasting of intermittent solar photovoltaic (PV) and wind resources is crucial for future power system efficient operation. This paper presents the use of Adaptive Neuro Fuzzy Inference System (ANFIS) approach for predicting wind and PV power outputs of the isolated Adrar’s power system. The model formed by using real numerical weather measurements (wind speed, temperature, pressure, humidity, and solar irradiation), taken as input variables, and power outputs values as the output. Besides, metrics to calculate the Mean Absolute Error (MAE), Mean Square Error (MSE), and Root Mean Square Error (RMSE), have applied to denote forecast accuracy. The result verifies that ANFIS has a good perfection, and can be used as a reliable tool for modelling and prediction renewable energies.","PeriodicalId":110091,"journal":{"name":"2018 International Conference on Wind Energy and Applications in Algeria (ICWEAA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Long-term Forecasting of Intermittent Wind and Photovoltaic Resources by using Adaptive Neuro Fuzzy Inference System (ANFIS)\",\"authors\":\"S. Makhloufi, M. Debbache, S. Boulahchiche\",\"doi\":\"10.1109/ICWEAA.2018.8605102\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Forecasting of intermittent solar photovoltaic (PV) and wind resources is crucial for future power system efficient operation. This paper presents the use of Adaptive Neuro Fuzzy Inference System (ANFIS) approach for predicting wind and PV power outputs of the isolated Adrar’s power system. The model formed by using real numerical weather measurements (wind speed, temperature, pressure, humidity, and solar irradiation), taken as input variables, and power outputs values as the output. Besides, metrics to calculate the Mean Absolute Error (MAE), Mean Square Error (MSE), and Root Mean Square Error (RMSE), have applied to denote forecast accuracy. The result verifies that ANFIS has a good perfection, and can be used as a reliable tool for modelling and prediction renewable energies.\",\"PeriodicalId\":110091,\"journal\":{\"name\":\"2018 International Conference on Wind Energy and Applications in Algeria (ICWEAA)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Wind Energy and Applications in Algeria (ICWEAA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICWEAA.2018.8605102\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Wind Energy and Applications in Algeria (ICWEAA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICWEAA.2018.8605102","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

摘要

间歇性太阳能光伏和风能资源的预测对未来电力系统的高效运行至关重要。本文介绍了利用自适应神经模糊推理系统(ANFIS)方法预测孤立Adrar电力系统的风电和光伏发电输出。以实际数值天气测量值(风速、温度、压力、湿度、太阳辐照度)作为输入变量,以功率输出值作为输出而形成的模型。此外,还采用了计算平均绝对误差(MAE)、均方误差(MSE)和均方根误差(RMSE)的指标来表示预测精度。结果表明,ANFIS具有良好的完善性,可以作为可再生能源建模和预测的可靠工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Long-term Forecasting of Intermittent Wind and Photovoltaic Resources by using Adaptive Neuro Fuzzy Inference System (ANFIS)
Forecasting of intermittent solar photovoltaic (PV) and wind resources is crucial for future power system efficient operation. This paper presents the use of Adaptive Neuro Fuzzy Inference System (ANFIS) approach for predicting wind and PV power outputs of the isolated Adrar’s power system. The model formed by using real numerical weather measurements (wind speed, temperature, pressure, humidity, and solar irradiation), taken as input variables, and power outputs values as the output. Besides, metrics to calculate the Mean Absolute Error (MAE), Mean Square Error (MSE), and Root Mean Square Error (RMSE), have applied to denote forecast accuracy. The result verifies that ANFIS has a good perfection, and can be used as a reliable tool for modelling and prediction renewable energies.
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:481959085
Book学术官方微信