基于太阳能资源预测的光伏/电池智能电网能源管理改进

G. Notton, G. Faggianelli, J. Duchaud, C. Voyant, S. Ouédraogo, Fabien Bouisset
{"title":"基于太阳能资源预测的光伏/电池智能电网能源管理改进","authors":"G. Notton, G. Faggianelli, J. Duchaud, C. Voyant, S. Ouédraogo, Fabien Bouisset","doi":"10.1109/eeae53789.2022.9831213","DOIUrl":null,"url":null,"abstract":"In an Energy Management Systems (EMS), a weather forecasting platform is often incorporated to anticipate meteorological events influencing both the electrical production and consumption and to react accordingly. After a short presentation of solar resources forecasting tools, we focus on short-time horizon using statistical and Artificial Intelligence methods. A validation is realized on Ajaccio, France, the most efficient method is used into an EMS which optimizes the electricity exchanges into a microgrid with photovoltaic/battery energy system supplying a building and an electrical vehicle. The objective of the paper is to show the cost benefit induced by the implementation of the forecasting platform.","PeriodicalId":441906,"journal":{"name":"2022 8th International Conference on Energy Efficiency and Agricultural Engineering (EE&AE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Energy Management Improvement in a PV/Battery Smart-grid by Integration of Solar Resource Forecasting\",\"authors\":\"G. Notton, G. Faggianelli, J. Duchaud, C. Voyant, S. Ouédraogo, Fabien Bouisset\",\"doi\":\"10.1109/eeae53789.2022.9831213\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In an Energy Management Systems (EMS), a weather forecasting platform is often incorporated to anticipate meteorological events influencing both the electrical production and consumption and to react accordingly. After a short presentation of solar resources forecasting tools, we focus on short-time horizon using statistical and Artificial Intelligence methods. A validation is realized on Ajaccio, France, the most efficient method is used into an EMS which optimizes the electricity exchanges into a microgrid with photovoltaic/battery energy system supplying a building and an electrical vehicle. The objective of the paper is to show the cost benefit induced by the implementation of the forecasting platform.\",\"PeriodicalId\":441906,\"journal\":{\"name\":\"2022 8th International Conference on Energy Efficiency and Agricultural Engineering (EE&AE)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 8th International Conference on Energy Efficiency and Agricultural Engineering (EE&AE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/eeae53789.2022.9831213\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 8th International Conference on Energy Efficiency and Agricultural Engineering (EE&AE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/eeae53789.2022.9831213","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

在能源管理系统(EMS)中,天气预报平台通常用于预测影响电力生产和消费的气象事件,并作出相应的反应。在简要介绍了太阳能资源预测工具之后,我们将重点介绍利用统计和人工智能方法进行短期预测的方法。在法国的Ajaccio进行了验证,最有效的方法被用于EMS中,该EMS优化了电力交换到具有光伏/电池能源系统的微电网,为建筑物和电动汽车供电。本文的目的是展示实施预测平台所带来的成本效益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy Management Improvement in a PV/Battery Smart-grid by Integration of Solar Resource Forecasting
In an Energy Management Systems (EMS), a weather forecasting platform is often incorporated to anticipate meteorological events influencing both the electrical production and consumption and to react accordingly. After a short presentation of solar resources forecasting tools, we focus on short-time horizon using statistical and Artificial Intelligence methods. A validation is realized on Ajaccio, France, the most efficient method is used into an EMS which optimizes the electricity exchanges into a microgrid with photovoltaic/battery energy system supplying a building and an electrical vehicle. The objective of the paper is to show the cost benefit induced by the implementation of the forecasting platform.
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