MACROMODELING OF LOCAL POWER SUPPLY SYSTEM BALANCE FORECASTING USING FRACTAL PROPERTIES OF LOAD AND GENERATION SCHEDULES

Q4 Engineering
Daniyar Jarykbassov, Petr Lezhniuk, Iryna Hunko, Vladyslav Lysyi, Lyubov Dobrovolska
{"title":"MACROMODELING OF LOCAL POWER SUPPLY SYSTEM BALANCE FORECASTING USING FRACTAL PROPERTIES OF LOAD AND GENERATION SCHEDULES","authors":"Daniyar Jarykbassov, Petr Lezhniuk, Iryna Hunko, Vladyslav Lysyi, Lyubov Dobrovolska","doi":"10.35784/iapgos.4457","DOIUrl":null,"url":null,"abstract":"A method of forecasting the balance of electricity consumption of urban development objects, civil purposes using discrete macromodels is proposed. We consider the power supply system (PSS) of the district, which is characterised by power supply from general-purpose power grids, as well as having its own generation of electricity from renewable energy sources (RES). Such a local electric power system (LES) under certain conditions can be operated as an independent balanced electrical facility. For optimal operation of the LES under these conditions, it is necessary to predict its power consumption schedules. The proposed macromodelling method allows to develop deterministic models of power consumption with the required accuracy on the basis of retrospective information without the use of data preprocessing procedures. The solution to the problem of forecasting electricity consumption schedules is simplified by using only basic or deterministic characteristics in the construction of the model. These include fractal properties of PSS load schedules.","PeriodicalId":53131,"journal":{"name":"Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35784/iapgos.4457","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0

Abstract

A method of forecasting the balance of electricity consumption of urban development objects, civil purposes using discrete macromodels is proposed. We consider the power supply system (PSS) of the district, which is characterised by power supply from general-purpose power grids, as well as having its own generation of electricity from renewable energy sources (RES). Such a local electric power system (LES) under certain conditions can be operated as an independent balanced electrical facility. For optimal operation of the LES under these conditions, it is necessary to predict its power consumption schedules. The proposed macromodelling method allows to develop deterministic models of power consumption with the required accuracy on the basis of retrospective information without the use of data preprocessing procedures. The solution to the problem of forecasting electricity consumption schedules is simplified by using only basic or deterministic characteristics in the construction of the model. These include fractal properties of PSS load schedules.
基于负荷和发电计划分形特性的局部供电系统平衡预测宏观建模
提出了一种利用离散宏观模型预测城市发展对象民用用电平衡的方法。我们考虑的是该地区的电力供应系统(PSS),其特点是由通用电网供电,同时拥有自己的可再生能源发电(RES)。这种局部电力系统在一定条件下可以作为独立的平衡电力设施运行。为了在这些条件下优化LES的运行,有必要对其功耗计划进行预测。提出的宏观建模方法允许在不使用数据预处理程序的情况下,在回顾性信息的基础上开发具有所需精度的功耗确定性模型。通过在模型构建中仅使用基本特征或确定性特征,简化了电力消费计划预测问题的求解。其中包括PSS负荷计划的分形特性。
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 求助全文
来源期刊
CiteScore
0.90
自引率
0.00%
发文量
40
审稿时长
10 weeks
×
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