Estimation Error Cost Optimization of Demand Side Management Based on Massive MIMO Communication Network in Smart Grid

被引:2
作者
Ding, Qingfeng [1 ,2 ]
Shi, Hui [1 ,2 ]
Liu, Qianliang [1 ,2 ]
机构
[1] East China Jiaotong Univ, Dept Elect & Automat Engn, Nanchang 330013, Jiangxi, Peoples R China
[2] East China Jiaotong Univ, State Key Lab Performance Monitoring Protecting Ra, Nanchang 330013, Jiangxi, Peoples R China
基金
中国国家自然科学基金;
关键词
Smart grids; Costs; Load management; Wireless communication; Demand side management; Reliability; Interference; Estimation error cost; cost-priority; demand side management; massive MIMO; smart grid; OUTAGE PROBABILITY ANALYSIS; DESIGN; UPLINK;
D O I
10.1109/TSG.2023.3259011
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
The estimation error cost (EEC) of smart grid under the demand side management is related to the network behavior and the accuracy of energy dispatch. In this paper, a communication and energy bidirectional link connection network (CEBCN) is proposed for decreasing the EEC of smart grid under demand side management. In the CEBCN, the network behavior is quantified to communication reliability and response validity. And the communication, implemented by massive multi-input-multi-output (MIMO), and energy dispatch can be realized, simultaneously. Also, the EEC is further decreased through a cost-priority based energy dispatch strategy proposed in this paper. Based on the CEBCN, the closed-form expressions are derived about the communication reliability and response validity. Naturally, the closed-form solution is derived for the EEC in the communication and energy transmission model, the results of which are used to investigate the EEC performance in smart grid. Numerical results validate that the reliability and validity of the proposed CEBCN and reveal the effect of various parameters on the EEC. Notably, the high EEC caused by communication instability can be reduced by at least 40% with the massive MIMO, and the cost-priority based energy dispatch strategy can further improve the EEC performance on communication infrastructure.
引用
收藏
页码:4953 / 4963
页数:11
相关论文
共 27 条
[1]   Clustering Electricity Consumers: Challenges and Applications for Operating Smart Grids [J].
Alonso, Andres M. ;
Martin, Eduardo ;
Mateo, Alicia ;
Nogales, Francisco J. ;
Ruiz, Carlos ;
Veiga, Andrea .
IEEE POWER & ENERGY MAGAZINE, 2022, 20 (03) :54-63
[2]   Massive MIMO networks: Spectral, energy, and hardware efficiency [J].
Björnson, Emil ;
Hoydis, Jakob ;
Sanguinetti, Luca .
Foundations and Trends in Signal Processing, 2017, 11 (3-4) :154-655
[3]   A Quality-Aware Multi-Level Data Aggregation Approach to Manage Smart Grid AMI Traffic [J].
Das, Uddipan ;
Namboodiri, Vinod .
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, 2019, 30 (02) :245-256
[4]   Outage Probability Analysis and Resolution Profile Design for Massive MIMO Uplink With Mixed-ADC [J].
Ding, Qingfeng ;
Jing, Yindi .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2018, 17 (09) :6293-6306
[5]   Generating Scale-Free Topology for Wireless Neighborhood Area Networks in Smart Grid [J].
Ding, Yuemin ;
Li, Xiaohui ;
Tian, Yu-Chu ;
Ledwich, Gerard ;
Mishra, Yateendra ;
Zhou, Chunjie .
IEEE TRANSACTIONS ON SMART GRID, 2019, 10 (04) :4245-4252
[6]   A Stochastic Multi-Objective Framework for Optimal Scheduling of Energy Storage Systems in Microgrids [J].
Farzin, Hossein ;
Fotuhi-Firuzabad, Mahmud ;
Moeini-Aghtaie, Moein .
IEEE TRANSACTIONS ON SMART GRID, 2017, 8 (01) :117-127
[7]   Device Access Optimization for Virtual Power Plants in Heterogeneous Networks [J].
Feng, Cheng ;
Wang, Yi ;
Wang, Xuanyuan ;
Chen, Qixin .
IEEE TRANSACTIONS ON SMART GRID, 2022, 13 (02) :1478-1489
[8]   Interference and Outage Probability Analysis for Massive MIMO Downlink with MF Precoding [J].
Feng, Chi ;
Jing, Yindi ;
Jin, Shi .
IEEE SIGNAL PROCESSING LETTERS, 2016, 23 (03) :366-370
[9]  
Hassan M.U., 2023, IEEE Trans. Knowl. Data Eng., V35, P5724, DOI DOI 10.1109/TKDE.2022.3157472
[10]   Automatic Generation Method of Optimization Scheme for Orderly Power Utilization Based on Genetic Algorithm [J].
Huang Jian-jun ;
Zuo Qing-lin ;
Mu Fu-lin .
2013 IEEE 11TH INTERNATIONAL CONFERENCE ON DEPENDABLE, AUTONOMIC AND SECURE COMPUTING (DASC), 2013, :72-77