A Review of Reliability Research in Regional Integrated Energy System: Indicator, Modeling, and Assessment Methods

被引:0
作者
Li, Da [1 ]
Xu, Peng [1 ]
Gu, Jiefan [2 ]
Zhu, Yi [1 ]
机构
[1] Tongji Univ, Sch Mech Engn, Shanghai 201800, Peoples R China
[2] Tongji Univ, Sch Architecture & Urban Planning, Shanghai 201800, Peoples R China
基金
中国国家自然科学基金;
关键词
reliability; integrated energy system; energy hub; load flow; coupling relationship; review; DYNAMIC BAYESIAN NETWORK; PROBABILISTIC LOAD FLOW; OPTIMAL POWER-FLOW; FAILURE PROBABILITY; WIND ENERGY; MANAGEMENT; OPTIMIZATION; STORAGE; ELECTRICITY; HUB;
D O I
10.3390/buildings14113428
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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.
引用
收藏
页数:28
相关论文
共 138 条
  • [11] Optimization and estimation of reliability indices and cost of Power Distribution System of an urban area by a noble fuzzy-hybrid algorithm
    Banerjee, Avishek
    Chattopadhyay, Samiran
    Gavrilas, Mihai
    Grigoras, Gheorghe
    [J]. APPLIED SOFT COMPUTING, 2021, 102
  • [12] Batool K, 2017, COMPLEX ADAPT SYST M, V5, DOI 10.1186/s40294-017-0043-1
  • [13] Untitled
    Batty, Michael
    [J]. ENVIRONMENT AND PLANNING B-PLANNING & DESIGN, 2011, 38 (01) : 2 - 4
  • [14] Home energy management systems: A review of modelling and complexity
    Beaudin, Marc
    Zareipour, Hamidreza
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2015, 45 : 318 - 335
  • [15] A new model to evaluate water resource spatial equilibrium based on the game theory coupling weight method and the coupling coordination degree
    Bian, Dehui
    Yang, Xiaohua
    Xiang, Weiqi
    Sun, Boyang
    Chen, Yajing
    Babuna, Pius
    Li, Meishui
    Yuan, Zixing
    [J]. JOURNAL OF CLEANER PRODUCTION, 2022, 366
  • [16] Bian X., 2021, Trans. China Electrotech. Soc, V36, P4530
  • [17] Bie ZH, 2012, IEEE T POWER SYST, V27, P2342, DOI 10.1109/TPWRS.2012.2202695
  • [18] A SYSTEM STATE TRANSITION SAMPLING METHOD FOR COMPOSITE SYSTEM RELIABILITY EVALUATION
    BILLINTON, R
    LI, W
    [J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 1993, 8 (03) : 761 - 770
  • [19] POWER-SYSTEM RELIABILITY IN PERSPECTIVE
    BILLINTON, R
    ALLAN, RN
    [J]. ELECTRONICS AND POWER, 1984, 30 (03): : 231 - 236
  • [20] Billinton R., 1977, System Reliability Modeling and Evaluation