Details
| Original language | English |
|---|---|
| Article number | 105672 |
| Number of pages | 19 |
| Journal | Sustainable cities and society |
| Volume | 113 |
| Early online date | 17 Jul 2024 |
| Publication status | Published - 15 Oct 2024 |
Abstract
Microgrids are custom-designed, but their extensive design options hinder their dissemination. Consequently, microgrid-interested parties need strategic support to identify suitable design options for their use case. This paper develops a decision support artifact in the form of a decision tree for recommending the most suitable microgrid design for a project. A multi-step design science-oriented process was used. First, a morphological analysis of academic literature was conducted to deduce all possible microgrid design options and visualize them in a morphological box. Once done, 62 real-world microgrids of diverse types and locations were classified according to the morphological box. The produced dataset was used to derive five microgrid design archetypes algorithmically using cluster analysis. The dataset and their associated archetypes were then fed into a rule-mining algorithm to generate a decision tree that recommends the appropriate microgrid archetype based on up to four questions about, for instance, the microgrid's objective and the connectivity to the main grid. Furthermore, design principles for each microgrid archetype recommendation were formulated. The developed design artifact serves as applicable knowledge and a benchmark framework for researchers, as well as a comprehensive and simultaneously simplified decision-making framework for practitioners.
Keywords
- Archetypes, Decision support, Decision tree, Design principles, Morphological analysis, Real-world microgrids
ASJC Scopus subject areas
- Social Sciences(all)
- Geography, Planning and Development
- Engineering(all)
- Civil and Structural Engineering
- Energy(all)
- Renewable Energy, Sustainability and the Environment
- Social Sciences(all)
- Transportation
Sustainable Development Goals
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In: Sustainable cities and society, Vol. 113, 105672, 15.10.2024.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Decision support for strategic microgrid design integrating governance, business, intelligence, communication, and physical perspectives
AU - Gerlach, Jana
AU - Eckhoff, Sarah
AU - Breitner, Michael H.
N1 - Publisher Copyright: © 2024 The Author(s)
PY - 2024/10/15
Y1 - 2024/10/15
N2 - Microgrids are custom-designed, but their extensive design options hinder their dissemination. Consequently, microgrid-interested parties need strategic support to identify suitable design options for their use case. This paper develops a decision support artifact in the form of a decision tree for recommending the most suitable microgrid design for a project. A multi-step design science-oriented process was used. First, a morphological analysis of academic literature was conducted to deduce all possible microgrid design options and visualize them in a morphological box. Once done, 62 real-world microgrids of diverse types and locations were classified according to the morphological box. The produced dataset was used to derive five microgrid design archetypes algorithmically using cluster analysis. The dataset and their associated archetypes were then fed into a rule-mining algorithm to generate a decision tree that recommends the appropriate microgrid archetype based on up to four questions about, for instance, the microgrid's objective and the connectivity to the main grid. Furthermore, design principles for each microgrid archetype recommendation were formulated. The developed design artifact serves as applicable knowledge and a benchmark framework for researchers, as well as a comprehensive and simultaneously simplified decision-making framework for practitioners.
AB - Microgrids are custom-designed, but their extensive design options hinder their dissemination. Consequently, microgrid-interested parties need strategic support to identify suitable design options for their use case. This paper develops a decision support artifact in the form of a decision tree for recommending the most suitable microgrid design for a project. A multi-step design science-oriented process was used. First, a morphological analysis of academic literature was conducted to deduce all possible microgrid design options and visualize them in a morphological box. Once done, 62 real-world microgrids of diverse types and locations were classified according to the morphological box. The produced dataset was used to derive five microgrid design archetypes algorithmically using cluster analysis. The dataset and their associated archetypes were then fed into a rule-mining algorithm to generate a decision tree that recommends the appropriate microgrid archetype based on up to four questions about, for instance, the microgrid's objective and the connectivity to the main grid. Furthermore, design principles for each microgrid archetype recommendation were formulated. The developed design artifact serves as applicable knowledge and a benchmark framework for researchers, as well as a comprehensive and simultaneously simplified decision-making framework for practitioners.
KW - Archetypes
KW - Decision support
KW - Decision tree
KW - Design principles
KW - Morphological analysis
KW - Real-world microgrids
UR - http://www.scopus.com/inward/record.url?scp=85199423543&partnerID=8YFLogxK
U2 - 10.1016/j.scs.2024.105672
DO - 10.1016/j.scs.2024.105672
M3 - Article
AN - SCOPUS:85199423543
VL - 113
JO - Sustainable cities and society
JF - Sustainable cities and society
SN - 2210-6707
M1 - 105672
ER -