Tool-assisted Surrogate Selection for Simulation Models in Energy Systems

被引:1
作者
Balduin, Stephan [1 ]
Oest, Frauke [1 ]
Blank-Babazadeh, Marita [1 ]
Niess, Astrid [2 ]
Lehnhoff, Sebastian [1 ]
机构
[1] OFFIS Inst Informat Technol, Oldenburg, Germany
[2] Leibniz Univ Hannover, Hannover, Germany
来源
PROCEEDINGS OF THE 2019 FEDERATED CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS (FEDCSIS) | 2019年
关键词
REGRESSION;
D O I
10.15439/2019F242
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Surrogate models have proved to be a suitable replacement for complex simulation models in various applications. Runtime considerations, complexity reduction, and privacy concerns play a role in the decision to use a surrogate model. The choice of an appropriate surrogate model though is often tedious and largely dependent on the individual model properties. A tool can help to facilitate this process. To this end, we present a surrogate modeling process supporting tool that simplifies the process of generation and application of surrogate models in a co-simulation framework. We evaluate the tool in our application context, energy system co-simulation, and apply it to different simulation models from that domain with a focus on decentralized energy units.
引用
收藏
页码:185 / 192
页数:8
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