Forecasting of SPP Generation at Different Stages of its Existence Using the Example of the 2.3 MW Plant in the Kharkiv Region of Ukraine

Andriy Pavlov, O. Moroz, O. Miroshnyk, Anton Mishyn, Denys Myrhorod, V. Paziy
{"title":"Forecasting of SPP Generation at Different Stages of its Existence Using the Example of the 2.3 MW Plant in the Kharkiv Region of Ukraine","authors":"Andriy Pavlov, O. Moroz, O. Miroshnyk, Anton Mishyn, Denys Myrhorod, V. Paziy","doi":"10.1109/MEES58014.2022.10005752","DOIUrl":null,"url":null,"abstract":"The results of studies of the generation of a solar power plant (SPP) with a capacity of 2.336 MW, which is located in the Kharkiv region of Ukraine, are presented. The results of the forecast generation, which were determined using the PHOTOVOLTAIC GEOGRAPHICAL INFORMATION SYSTEM (PV-GIS) program. Analysis of the forecast and actual generation data showed that the actual annual deviation from the forecast ranged from +5.47% to −5.24%, which is slightly higher than the annual generation variability of 4.87% determined by PV-GIS. The economic performance of a solar power plant is affected by the accuracy of forecasting hourly generation a day in advance. In order to improve the accuracy of forecasting the hourly generation of the SPP, an analysis of data from the guaranteed buyer, who buys all the generated electricity, and the plant's SmartLogger1000 monitoring system was performed. According to the results of the analysis, it was found that there is a difference in the data of the guaranteed buyer and the monitoring system, which arose as a result of the non-synchronization of the SmartLogger1000 monitoring system with the guaranteed buyer. The analysis of the hourly forecasts of the guaranteed buyer and the forecasting service showed that the sum of the hourly deviations of the forecast of the SPP service from the actual generation for December 2022 was 71.4%, and the sum of the hourly deviations of the forecast of the guaranteed buyer was 117.9%. An increase in the accuracy of forecasting was achieved due to the accumulation of statistical data and the study of factors influencing the generation of SPP.","PeriodicalId":244144,"journal":{"name":"2022 IEEE 4th International Conference on Modern Electrical and Energy System (MEES)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 4th International Conference on Modern Electrical and Energy System (MEES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MEES58014.2022.10005752","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The results of studies of the generation of a solar power plant (SPP) with a capacity of 2.336 MW, which is located in the Kharkiv region of Ukraine, are presented. The results of the forecast generation, which were determined using the PHOTOVOLTAIC GEOGRAPHICAL INFORMATION SYSTEM (PV-GIS) program. Analysis of the forecast and actual generation data showed that the actual annual deviation from the forecast ranged from +5.47% to −5.24%, which is slightly higher than the annual generation variability of 4.87% determined by PV-GIS. The economic performance of a solar power plant is affected by the accuracy of forecasting hourly generation a day in advance. In order to improve the accuracy of forecasting the hourly generation of the SPP, an analysis of data from the guaranteed buyer, who buys all the generated electricity, and the plant's SmartLogger1000 monitoring system was performed. According to the results of the analysis, it was found that there is a difference in the data of the guaranteed buyer and the monitoring system, which arose as a result of the non-synchronization of the SmartLogger1000 monitoring system with the guaranteed buyer. The analysis of the hourly forecasts of the guaranteed buyer and the forecasting service showed that the sum of the hourly deviations of the forecast of the SPP service from the actual generation for December 2022 was 71.4%, and the sum of the hourly deviations of the forecast of the guaranteed buyer was 117.9%. An increase in the accuracy of forecasting was achieved due to the accumulation of statistical data and the study of factors influencing the generation of SPP.
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
以乌克兰哈尔科夫地区2.3 MW电站为例的SPP发电存在不同阶段的预测
本文介绍了位于乌克兰哈尔科夫地区的容量为2.336兆瓦的太阳能发电厂(SPP)的发电研究结果。利用光伏地理信息系统(PV-GIS)程序确定预测生成结果。对预测和实际发电量数据的分析表明,实际发电量与预测的年偏差在+5.47% ~ - 5.24%之间,略高于PV-GIS确定的年发电量变异率4.87%。太阳能发电厂每小时发电量预测的准确性直接影响到电厂的经济效益。为了提高预测SPP每小时发电量的准确性,对购买所有发电的保证买方和工厂的SmartLogger1000监测系统的数据进行了分析。根据分析结果,发现被担保买方的数据与监控系统的数据存在差异,这是由于SmartLogger1000监控系统与被担保买方未同步造成的。对担保买方和预测服务的小时预报分析表明,2022年12月SPP服务预报与实际发电量的小时偏差之和为71.4%,担保买方预报的小时偏差之和为117.9%。由于统计数据的积累和对SPP产生的影响因素的研究,预报的准确性得到了提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Assessment of Learning Outcomes in Distance Learning Using the Moodle Platform UAVs Intercepting Possibility Substantiation: Economic and Technical Aspects Asynchronous Motor with Ferromagnetic Sections of Squirrel-Cage Winding Industry 4.0 Technologies in Ensuring Environmental Friendliness of Production and Product Quality Features of Manufacturing a Two-layer Electrical Contact
×
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