不同误差度量的回顾:以太阳预报为例

Pardeep Singla, M. Duhan, Sumit Saroha
{"title":"不同误差度量的回顾:以太阳预报为例","authors":"Pardeep Singla, M. Duhan, Sumit Saroha","doi":"10.53799/ajse.v20i4.212","DOIUrl":null,"url":null,"abstract":"Renewable energy systems (RES) are no longer confined to being used as a stand-alone entity in the modern era. These RES, especially solar panels are also used with the grid power systems to supply electricity. However, precise forecasting of solar irradiance is necessary to ensure that the grid operates in a balanced and planned manner. Various solar forecasting models (SFM) are presented in the literature to produce an accurate solar forecast. Nevertheless, each model has gone through the step of evaluation of its accuracy using some error measures. Many error measures are discussed in the literature for deterministic as well as probabilistic solar forecasting. But, each study has its own selected error measure which sometimes landed on a wrong interpretation of results if not selected appropriately. As a result, this paper offers a critical assessment of several common error metrics with the goal of discussing alternative error metrics and establishing a viable set of error metrics for deterministic and probabilistic solar forecasting. Based on highly cited research from the last three years (2019-2021), error measures for both types of forecasting are presented with their basic functionalities, advantages & limitations which equipped the reader to pick the required compatible metrics","PeriodicalId":224436,"journal":{"name":"AIUB Journal of Science and Engineering (AJSE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Review of Different Error Metrics: A Case of Solar Forecasting\",\"authors\":\"Pardeep Singla, M. Duhan, Sumit Saroha\",\"doi\":\"10.53799/ajse.v20i4.212\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Renewable energy systems (RES) are no longer confined to being used as a stand-alone entity in the modern era. These RES, especially solar panels are also used with the grid power systems to supply electricity. However, precise forecasting of solar irradiance is necessary to ensure that the grid operates in a balanced and planned manner. Various solar forecasting models (SFM) are presented in the literature to produce an accurate solar forecast. Nevertheless, each model has gone through the step of evaluation of its accuracy using some error measures. Many error measures are discussed in the literature for deterministic as well as probabilistic solar forecasting. But, each study has its own selected error measure which sometimes landed on a wrong interpretation of results if not selected appropriately. As a result, this paper offers a critical assessment of several common error metrics with the goal of discussing alternative error metrics and establishing a viable set of error metrics for deterministic and probabilistic solar forecasting. Based on highly cited research from the last three years (2019-2021), error measures for both types of forecasting are presented with their basic functionalities, advantages & limitations which equipped the reader to pick the required compatible metrics\",\"PeriodicalId\":224436,\"journal\":{\"name\":\"AIUB Journal of Science and Engineering (AJSE)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AIUB Journal of Science and Engineering (AJSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.53799/ajse.v20i4.212\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AIUB Journal of Science and Engineering (AJSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53799/ajse.v20i4.212","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

在现代,可再生能源系统(RES)不再局限于作为一个独立的实体使用。这些可再生能源,特别是太阳能电池板也与电网电力系统一起使用来供电。然而,太阳辐照度的精确预测是必要的,以确保电网以平衡和有计划的方式运行。各种太阳预报模型(SFM)提出了在文献中产生一个准确的太阳预报。然而,每个模型都经过了使用一些误差度量来评估其准确性的步骤。对于确定性和概率太阳预报,文献中讨论了许多误差措施。但是,每个研究都有自己选择的误差测量方法,如果选择不当,有时会对结果产生错误的解释。因此,本文对几种常见误差指标进行了批判性评估,目的是讨论可选的误差指标,并为确定性和概率性太阳预报建立一套可行的误差指标。基于过去三年(2019-2021)被高度引用的研究,本文介绍了两种预测的误差测量方法及其基本功能、优势和局限性,使读者能够选择所需的兼容指标
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Review of Different Error Metrics: A Case of Solar Forecasting
Renewable energy systems (RES) are no longer confined to being used as a stand-alone entity in the modern era. These RES, especially solar panels are also used with the grid power systems to supply electricity. However, precise forecasting of solar irradiance is necessary to ensure that the grid operates in a balanced and planned manner. Various solar forecasting models (SFM) are presented in the literature to produce an accurate solar forecast. Nevertheless, each model has gone through the step of evaluation of its accuracy using some error measures. Many error measures are discussed in the literature for deterministic as well as probabilistic solar forecasting. But, each study has its own selected error measure which sometimes landed on a wrong interpretation of results if not selected appropriately. As a result, this paper offers a critical assessment of several common error metrics with the goal of discussing alternative error metrics and establishing a viable set of error metrics for deterministic and probabilistic solar forecasting. Based on highly cited research from the last three years (2019-2021), error measures for both types of forecasting are presented with their basic functionalities, advantages & limitations which equipped the reader to pick the required compatible metrics
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
期刊最新文献
Performance Prediction of A Power Generation Gas Turbine Using An Optimized Artificial Neural Network Model Advancing Fuzzy Logic: A Hierarchical Fuzzy System Approach WVEHDD: Weighted Voting based Ensemble System for Heart Disease Detection Predictions of Malaysia Age-Specific Fertility Rates using the Lee-Carter and the Functional Data Approaches Performance Analysis of Automatic Generation Control for a Multi-Area Interconnected System Using Genetic Algorithm and Particle Swarm Optimization Technique
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1