Fault diagnostics in smart micro-grids: A survey

被引:116
作者
Hare, James [1 ]
Shi, Xiaofang [1 ,2 ]
Gupta, Shalabh [1 ]
Bazzi, Ali [1 ]
机构
[1] Univ Connecticut, Dept Elect & Comp Engn, Storrs, CT 06269 USA
[2] China Telecommun Corp, Beijing, Peoples R China
关键词
Smart micro-grids; Fault diagnostics; Classification methods; Clean energy; STATE-OF-HEALTH; NEURAL-NETWORKS; DIESEL-ENGINE; POWER; CLASSIFICATION; LOCATION; PROTECTION; SYSTEM; IDENTIFICATION; TECHNOLOGIES;
D O I
10.1016/j.rser.2016.01.122
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Due to rising awareness on environmental protection and for maintenance of clean habitable communities, current and next generation micro-grids are desired to have significant penetration of renewable and clean energy sources. However, a critical issue is the growth of faults in various components of micro-grids, which comprise the underlying energy generation and distribution infrastructure. Moreover, faults can manifest through different failure modes in the same component. If timely diagnostics and maintenance actions are not undertaken, then these faults can cause instabilities, inefficient power generation, and other losses. Therefore, it is important not only to understand the various failure modes, and their root causes and effects, but also to develop real-time automated diagnostics tools that can capture the early signatures of fault evolution for mitigating actions. In this respect, this paper presents a review of different failure modes occurring in various micro-grid components including both clean and conventional energy generation systems. Subsequently, the paper also provides a review on the state-of-the-art of various fault diagnosis approaches available in technical literature. Since multiple approaches can be implemented utilizing the model-based or data-driven methods given the system monitoring and communication infrastructures, the paper has presented the material in a systematic manner for easy understanding. The information presented in this paper will benefit not only the diagnostic engineers but also the control engineers who aim to develop control methodologies for fault-tolerance, mitigation, and equipment life extension based on the tools of early diagnostics. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1114 / 1124
页数:11
相关论文
共 105 条
[1]  
Akyol B., 2010, SURVEY WIRELESS COMM
[2]   A novel method for modeling dynamic air-gap eccentricity in synchronous machines based on modified winding function theory [J].
Al-Nuaim, NA ;
Toliyat, HA .
IEEE TRANSACTIONS ON ENERGY CONVERSION, 1998, 13 (02) :156-162
[3]   Structural vulnerability of the North American power grid [J].
Albert, R ;
Albert, I ;
Nakarado, GL .
PHYSICAL REVIEW E, 2004, 69 (02) :025103-1
[4]  
Alewine K, 2011, P IEEE EL INS C
[5]  
[Anonymous], 2000, Pattern Classification, DOI DOI 10.1007/978-3-319-57027-3_4
[6]  
[Anonymous], 2011, TIMK BEAR DAM AN LUB
[7]  
[Anonymous], 2009, P IEEE POW EN SOC GE
[8]   Failure Modes and Effects Analysis (FMEA) for wind turbines [J].
Arabian-Hoseynabadi, H. ;
Oraee, H. ;
Tavner, P. J. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2010, 32 (07) :817-824
[9]   A nonlinear observer design for fuel cell hydrogen estimation [J].
Arcak, M ;
Görgün, H ;
Pedersen, LM ;
Varigonda, S .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2004, 12 (01) :101-110
[10]   Diagnosis by parameter estimation of stator and rotor faults occurring in induction machines [J].
Bachir, Smail ;
Tnani, Slim ;
Trigeassou, Jean-Claude ;
Champenois, Gerard .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2006, 53 (03) :963-973