Prediction models and their role in advanced energy management systems supporting energy flexibility services

被引:0
|
作者
Uremović N. [1 ]
Lukač N. [1 ]
Sukic P. [1 ]
Štumberger G. [1 ]
机构
[1] Faculty of Electrical Engineering and Computer Science, University of Maribor, Koroška cesta 46, Maribor
来源
Renewable Energy and Power Quality Journal | 2023年 / 21卷
关键词
energy flexibility services; energy management system; prediction models; self-adaptation; self-establishment;
D O I
10.24084/repqj21.398
中图分类号
学科分类号
摘要
Automated decision tools, such as advanced energy management systems, are required to involve the electrical grid users in energy flexibility services. This paper focuses on the prediction models as a substantial part of decision strategy in advanced energy management systems and on advanced energy management systems as a tool that supports the active involvement of electrical grid users in energy flexibility services. Prediction models' desired properties are self-establishing and self-adaptation, which require new solutions in data selection, filtering, processing and model learning. Some of these properties are investigated within this paper. © 2023, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.
引用
收藏
页码:565 / 569
页数:4
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