Energy Management in Power Distribution Systems: Review, Classification, Limitations and Challenges

被引:83
作者
Alam, Md Shahin [1 ]
Arefifar, Seyed Ali [1 ]
机构
[1] Oakland Univ, Dept Elect & Comp Engn, Rochester, MI 48309 USA
关键词
Energy management; load management; power distribution; data analysis; smart grids; energy storage; wind energy; solar energy; electric vehicles; MODEL-PREDICTIVE CONTROL; DISTRIBUTION NETWORKS; DEMAND RESPONSE; MICROGRID OPERATION; OPTIMAL PLACEMENT; EXPERIMENTAL VALIDATION; ROBUST OPTIMIZATION; OPTIMAL ALLOCATION; ELECTRIC VEHICLES; LOSS MINIMIZATION;
D O I
10.1109/ACCESS.2019.2927303
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Energy management in distribution systems has gained attention in recent years. Coordination of electricity generation and consumption is crucial to save energy, reduce energy prices and achieve global emission targets. Due to the importance of the subject, this paper provides a literature review on recent research on energy management systems and classifies the works based on several factors including energy management goals, the approaches taken for performing energy management and solution algorithms. Furthermore, the paper reviews some of the most proficient techniques and methodologies adopted or developed to address energy management problem and provides a table to compare such techniques. The current challenges and limitations of energy management systems are explained and some future research directions have been provided at the end of the paper.
引用
收藏
页码:92979 / 93001
页数:23
相关论文
共 279 条
[1]   Market-Oriented Energy Management of a Hybrid Wind-Battery Energy Storage System Via Model Predictive Control With Constraint Optimizer [J].
Abdeltawab, Hussein Hassan ;
Mohamed, Yasser Abdel-Rady I. .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2015, 62 (11) :6658-6670
[2]   Presenting a multi-objective generation scheduling model for pricing demand response rate in micro-grid energy management [J].
Aghajani, G. R. ;
Shayanfar, H. A. ;
Shayeghi, H. .
ENERGY CONVERSION AND MANAGEMENT, 2015, 106 :308-321
[3]  
Alam MS, 2018, INT CONF ELECTRO INF, P667, DOI 10.1109/EIT.2018.8500168
[4]   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
[5]   Artificial Immune Systems Optimization Approach for Multiobjective Distribution System Reconfiguration [J].
Alonso, F. R. ;
Oliveira, D. Q. ;
Zambroni de Souza, A. C. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2015, 30 (02) :840-847
[6]   Energy Management Systems: State of the Art and Emerging Trends [J].
Aman, Saima ;
Simmhan, Yogesh ;
Prasanna, Viktor K. .
IEEE COMMUNICATIONS MAGAZINE, 2013, 51 (01) :114-119
[7]   Adaptive multi-objective distribution network reconfiguration using multi-objective discrete particles swarm optimisation algorithm and graph theory [J].
Andervazh, Mohammad-Reza ;
Olamaei, Javad ;
Haghifam, Mahmoud-Reza .
IET GENERATION TRANSMISSION & DISTRIBUTION, 2013, 7 (12) :1367-1382
[8]   Optimized Energy Management System to Reduce Fuel Consumption in Remote Military Microgrids [J].
Anglani, Norma ;
Oriti, Giovanna ;
Colombini, Michele .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2017, 53 (06) :5777-5785
[9]  
[Anonymous], J ENG
[10]  
[Anonymous], SCHNEID EL PARTN R D