Decentralised strategy for energy management of collaborative microgrids using multi-agent system

被引:7
作者
El Zerk, Abdallah [1 ]
Ouassaid, Mohammed [1 ]
Zidani, Youssef [2 ]
机构
[1] Mohammed V Univ Rabat, Engn Smart & Sustainable Syst Res Ctr, Mohammadia Sch Engineers, Rabat, Morocco
[2] Cadi Ayyad Univ, Fac Sci & Technol, Dept Elect Engn, Marrakech, Morocco
关键词
INTERCONNECTED MICROGRIDS;
D O I
10.1049/stg2.12077
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this study, the concept of collaborative microgrids (MGs) with shareable resources is introduced. The developed concept enables the householders of an isolated district or neighbourhood to cooperate and communicate intelligently in order to establish a reliable and proprietary MG. Therefore, a multi-agent system solution for a distributed energy management system is designed. The proposed approach should first supply households while maintaining MG stability. Second, it offers designers decent programing flexibility and ensures system adaptability when households are added or removed. Three agents are developed, the nanogrid (NG) agent which handles the centralised energy management of the NG and messages the Master agent with the necessary information. The Master agent is responsible for the decentralised management of energy over the microgrid and controls the switches. The management strategy using multi-agent systems aims to encourage customers considered as NG to contribute energy to the MG. The strategy relies on the implementation of a point-based remuneration model in which the collected points depend on the contribution. The results highlight the importance of the proposed approach, which can be exploited to connect and supply isolated facilities intelligently.
引用
收藏
页码:440 / 462
页数:23
相关论文
共 51 条
[1]   Modeling of lead acid batteries in PV systems [J].
Achaibou, N. ;
Haddadi, M. ;
Malek, A. .
TERRAGREEN 2012: CLEAN ENERGY SOLUTIONS FOR SUSTAINABLE ENVIRONMENT (CESSE), 2012, 18 :538-544
[2]   Power system flexibility: an overview of emergence to evolution [J].
Akrami, Alireza ;
Doostizadeh, Meysam ;
Aminifar, Farrokh .
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY, 2019, 7 (05) :987-1007
[3]   A multi-agent based energy management solution for integrated buildings and microgrid system [J].
Anvari-Moghaddam, Amjad ;
Rahimi-Kian, Ashkan ;
Mirian, Maryam S. ;
Guerrero, Josep M. .
APPLIED ENERGY, 2017, 203 :41-56
[4]   Stochastic Predictive Control of Multi-Microgrid Systems [J].
Bazmohammadi, Najmeh ;
Tahsiri, Ahmadreza ;
Anvari-Moghaddam, Amjad ;
Guerrero, Josep M. .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2019, 55 (05) :5311-5319
[5]   A hierarchical energy management strategy for interconnected microgrids considering uncertainty [J].
Bazmohammadi, Najmeh ;
Tahsiri, Ahmadreza ;
Anvari-Moghaddam, Amjad ;
Guerrero, Josep M. .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2019, 109 :597-608
[6]  
Bhatia S.C., 2014, Advanced Renewable Energy Systems, P144
[7]   Multi agent system solution to microgrid implementation [J].
Boudoudouh, Soukaina ;
Maaroufi, Mohamed .
SUSTAINABLE CITIES AND SOCIETY, 2018, 39 :252-261
[8]   A Multiagent-Based Hierarchical Energy Management Strategy for Multi-Microgrids Considering Adjustable Power and Demand Response [J].
Bui, Van-Hai ;
Hussain, Akhtar ;
Kim, Hak-Man .
IEEE TRANSACTIONS ON SMART GRID, 2018, 9 (02) :1323-1333
[9]   A review of nanogrid topologies and technologies [J].
Burmester, Daniel ;
Rayudu, Ramesh ;
Seah, Winston ;
Akinyele, Daniel .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2017, 67 :760-775
[10]   MAS-Based Management and Control Strategies for Integrated Hybrid Energy System [J].
Dou, Chunxia ;
Yue, Dong ;
Li, Xinbin ;
Xue, Yusheng .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2016, 12 (04) :1332-1349