General Aspects, Islanding Detection, and Energy Management in Microgrids: A Review

被引:10
作者
Islam, Md Mainul [1 ]
Nagrial, Mahmood [1 ]
Rizk, Jamal [1 ]
Hellany, Ali [1 ]
机构
[1] Western Sydney Univ, Sch Engn Design & Built Environm, Locked Bag 1797, Penrith, NSW 2751, Australia
关键词
demand response; energy management; islanding detection; microgrid; PATTERN-RECOGNITION APPROACH; DISTRIBUTED GENERATION; OPERATION MANAGEMENT; NEURAL-NETWORK; PART II; ROBUST OPTIMIZATION; CURRENT CHALLENGES; TRANSIENT SIGNALS; VOLTAGE UNBALANCE; SYSTEM;
D O I
10.3390/su13169301
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Distributed generators (DGs) have emerged as an advanced technology for satisfying growing energy demands and significantly mitigating the pollution caused by emissions. Microgrids (MGs) are attractive energy systems because they offer the reliable integration of DGs into the utility grid. An MG-based approach uses a self-sustained system that can operate in a grid-tied mode under normal conditions, as well as in an islanded mode when grid disturbance occurs. Islanding detection is essential; islanding may injure utility operators and disturb electricity generation and supply because of unsynchronized re-closure. In MGs, an energy management system (EMS) is essential for the optimal use of DGs in intelligent, sustainable, reliable, and integrated ways. In this comprehensive review, the classification of different operating modes of MGs, islanding detection techniques (IDTs), and EMSs are presented and discussed. This review shows that the existing IDTs and EMSs can be used when operating MGs. However, further development of IDTs and EMSs is still required to achieve more reliable operation and cost-effective energy management of MGs in the future. This review also highlights various MG challenges and recommendations for the operation of MGs, which will enhance the cost, efficiency, and reliability of MG operation for next-generation smart grid applications.
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页数:45
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共 173 条
[1]   Islanding detection method for DFIG wind turbines using artificial neural networks [J].
Abd-Elkader, Ahmad G. ;
Allam, Dalia F. ;
Tageldin, Elsayed .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2014, 62 :335-343
[2]   Optimal management of microgrids including renewable energy scources using GPSO-GM algorithm [J].
Abedini, Mohammad ;
Moradi, Mohammad H. ;
Hosseinian, S. Mandi .
RENEWABLE ENERGY, 2016, 90 :430-439
[3]   Microgrid and load shedding scheme during islanded mode: A review [J].
Abu Bakar, Nur Najihah ;
Hassan, Mohammad Yusri ;
Sulaima, Mohamad Fani ;
Nasir, Mohamad Na'im Mohd ;
Khamis, Aziah .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2017, 71 :161-169
[4]   Multi-objective energy management in a micro-grid [J].
Aghajani, Gholamreza ;
Ghadimi, Noradin .
ENERGY REPORTS, 2018, 4 :218-225
[5]   A review of the islanding detection methods in grid-connected PV inverters [J].
Ahmad, Ku Nurul Edhura Ku ;
Selvaraj, Jeyraj ;
Abd Rahim, Nasrudin .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2013, 21 :756-766
[6]   Islanding Detection of Distributed Generation Using Electrical Variables in Space Vector Domain [J].
Alam, Mollah Rezaul ;
Begum, Most Tasneem Ara ;
Mather, Barry .
IEEE TRANSACTIONS ON POWER DELIVERY, 2020, 35 (02) :861-870
[7]   Optimal probabilistic energy management in a typical micro-grid based-on robust optimization and point estimate method [J].
Alavi, Seyed Arash ;
Ahmadian, Ali ;
Aliakbar-Golkar, Masoud .
ENERGY CONVERSION AND MANAGEMENT, 2015, 95 :314-325
[8]   Intelligent energy management: Evolving developments, current challenges, and research directions for sustainable future [J].
Ali, Muhammad ;
Prakash, Krishneel ;
Hossain, Md Alamgir ;
Pota, R. Hemanshu .
JOURNAL OF CLEANER PRODUCTION, 2021, 314
[9]   A centralized and heuristic approach for energy management of an AC microgrid [J].
Almada, J. B. ;
Leao, R. P. S. ;
Sampaio, R. F. ;
Barroso, G. C. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2016, 60 :1396-1404
[10]   A New Approach Based on Wavelet Design and Machine Learning for Islanding Detection of Distributed Generation [J].
Alshareef, Sami ;
Talwar, Saurabh ;
Morsi, Walid. G. .
IEEE TRANSACTIONS ON SMART GRID, 2014, 5 (04) :1575-1583