Abstract
Energy storage technologies are receiving increasing attention due to the trend toward renewable energy sources. Energy storage systems are a promising technology as they provide the low carbon emissions needed in the future, contribute to renewable energy production, and offer an alternative to petroleum-derived fuels. It is not possible to say precisely how the energy will be stored, and often more than one method must be used together. In this study, battery technologies from electrochemical energy storage systems are discussed. This chapter proposes a multi-criteria decision-making (MCDM) model combining fuzzy IVIF-Z-AHP and fuzzy IVIF-Z-CODAS methods to choose the optimal battery ESS. The priority weights of 4 main and 11 sub-criteria related to energy storage efficiency are determined using the IVIF-Z-AHP method. After that, 5 different batteries are evaluated using the IVIF-Z-CODAS method, and the most appropriate battery ESS is selected by doing a performance evaluation regarding the storage of energy at maximum efficiency.
| Original language | English |
|---|---|
| Title of host publication | Studies in Fuzziness and Soft Computing |
| Publisher | Springer Science and Business Media Deutschland GmbH |
| Pages | 153-176 |
| Number of pages | 24 |
| DOIs | |
| Publication status | Published - 2023 |
Publication series
| Name | Studies in Fuzziness and Soft Computing |
|---|---|
| Volume | 428 |
| ISSN (Print) | 1434-9922 |
| ISSN (Electronic) | 1860-0808 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
Keywords
- Battery technologies
- Energy storage systems
- Interval-valued intuitionistic fuzzy Z-AHP
- Interval-valued intuitionistic fuzzy Z-CODAS
