A Review of Reliability Research in Regional Integrated Energy System: Indicator, Modeling, and Assessment Methods
Auteur(s): |
Da Li
Peng Xu Jiefan Gu Yi Zhu |
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Médium: | article de revue |
Langue(s): | anglais |
Publié dans: | Buildings, 22 octobre 2024, n. 11, v. 14 |
Page(s): | 3428 |
DOI: | 10.3390/buildings14113428 |
Abstrait: |
The increasing complexity of integrated energy systems has made reliability assessment a critical challenge. This paper presents a comprehensive review of reliability assessment in Regional Integrated Energy Systems (RIES), focusing on key aspects such as reliability indicators, modeling approaches, and evaluation techniques. This study highlights the role of renewable energy sources and examines the coupling relationships within RIES. Energy hub models and complex network theory are identified as significant in RIES modeling, while probabilistic load flow analysis shows promise in handling renewable energy uncertainties. This paper also explores the potential of machine learning methods and multi-objective optimization approaches in enhancing system reliability. By proposing an integrated assessment framework, this study addresses this research gap in reliability evaluation under high renewable energy penetration scenarios. The findings contribute to the advancement of reliability assessment methodologies for integrated energy systems, supporting the development of more resilient and sustainable energy infrastructures. |
Copyright: | © 2024 by the authors; licensee MDPI, Basel, Switzerland. |
License: | Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original. |
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10804857 - Publié(e) le:
10.11.2024 - Modifié(e) le:
10.11.2024