Multiagent-Based Energy Trading Platform for Energy Storage Systems in Distribution Systems With Interconnected Microgrids

被引:99
作者
Nunna, H. S. V. S. Kumar [1 ]
Sesetti, Anudeep [2 ]
Rathore, Akshay Kumar [3 ]
Doolla, Suryanarayana [4 ]
机构
[1] Nazarbayev Univ, Nur Sultan 010000, Kazakhstan
[2] Enphase Energy, Digital Business Unit, Bangalore 560017, Karnataka, India
[3] Concordia Univ, Dept Elect & Comp Engn, Montreal, PQ H3G 1M8, Canada
[4] Indian Inst Technol, Dept Energy Sci & Engn, Mumbai 400076, Maharashtra, India
关键词
Microgrids; Energy storage; Load modeling; Energy management; Generators; Biological system modeling; Peer-to-peer computing; Electricity markets; energy storage systems (ESSs); microgrids; multiagent systems; transactive energy (TE); MANAGEMENT;
D O I
10.1109/TIA.2020.2979782
中图分类号
T [工业技术];
学科分类号
120111 [工业工程];
摘要
In this article, an agent-based transactive energy (TE) trading platform to integrate energy storage systems (ESSs) into themicrogrids' energy management system is proposed. Using this platform, two different types of energy storage market models are proposed to promote local-level (within the microgrid) and communal- or global-level ESSs' participation in the intra- and intermicrogridTEmarkets. Also, a reinforcement learning algorithm known as simulated-annealing-basedQ-learning is used to develop bidding strategies for ESSs to participate in the TE markets. Besides energy trading, the proposed system also accounts for the losses caused by energy transactions between ESSs andmicrogrids using a complex current-tracing-based loss allocation method. The overall efficacy of the proposed energy market management system is demonstrated using a modified IEEE 123-bus distribution system with multiple microgrids and ESSs. Based on simulation results, it is observed that the proposed model can effectively reinforce the balance between the supply and the demand in the microgrids using the mix of local and global ESSs.
引用
收藏
页码:3207 / 3217
页数:11
相关论文
共 26 条
[1]
[Anonymous], 2013, CHIN CONTR CONF
[2]
[Anonymous], 2019, IEEE ACCESS, DOI DOI 10.1109/ACCESS.2019.2913898
[3]
[Anonymous], 2012, IEEE T SMART GRID, DOI DOI 10.1109/TSG.2011.2173507
[5]
Distributed intelligent energy management system for a single-phase high-frequency AC microgrid [J].
Chakraborty, Sudipta ;
Weiss, Manoja D. ;
Simoes, M. Godoy .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2007, 54 (01) :97-109
[6]
Davison M, 2018, INT CONF RENEW ENERG, P80, DOI 10.1109/ICRERA.2018.8566753
[7]
A cooperative game approach for coordinating multi-microgrid operation within distribution systems [J].
Du, Yan ;
Wang, Zhiwei ;
Liu, Guangyi ;
Chen, Xi ;
Yuan, Haoyu ;
Wei, Yanli ;
Li, Fangxing .
APPLIED ENERGY, 2018, 222 :383-395
[8]
Energy Matters, 2019, AUSTR SOL FEED IN TA
[9]
Eyer J., 2010, ALBUQUERQUE
[10]
A new Q-learning algorithm based on the Metropolis criterion [J].
Guo, MZ ;
Liu, Y ;
Malec, J .
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2004, 34 (05) :2140-2143