Data Distribution Service (DDS) based implementation of Smart grid devices using ANSI C12.19 standard

被引:10
作者
AL-Madani, Basem [1 ]
Ali, Hassan [1 ]
机构
[1] King Fahd Univ Petr & Minerals, Comp Engn Dept, Dhahran, Saudi Arabia
来源
14TH INTERNATIONAL CONFERENCE ON MOBILE SYSTEMS AND PERVASIVE COMPUTING (MOBISPC 2017) / 12TH INTERNATIONAL CONFERENCE ON FUTURE NETWORKS AND COMMUNICATIONS (FNC 2017) / AFFILIATED WORKSHOPS | 2017年 / 110卷
关键词
DDS; Smart grid; RTI Connext; RTPS; QoS; performance metrics; ANSI C12.19; MIDDLEWARE;
D O I
10.1016/j.procs.2017.06.082
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Today's power grid has so many challenges in terms of centralized power generation, limited flow of information, limited support for distribution, poor management of peak loads and power disruptions. Due to these limitations several organizations are working on Smart grid. Smart grid consists of numerous kind of heterogeneous devices that increase the complexity and inefficiency. To cope with heterogeneity and provide interoperability among the communication of these devices, middleware is considered to be the best approach. There are so many middlewares that have been proposed so far but Data Distribution Service (DDS) middleware provides high level of reliability and efficiency by addressing more performance metrics and several QoS policies especially in real time and mission critical applications. We have considered Smart grid standard ANSI C12.19 based DDS deployment in transmission and consumption sides. Data structures are obtained for topics formation over RTI Connext to establish communication and to conduct experimental study for the analysis of interoperability and other performance metrics to prove that DDS is better solution for Smart grid data interoperability and high reliability. (C) 2017 The Authors. Published by Elsevier B.V.
引用
收藏
页码:394 / 401
页数:8
相关论文
共 17 条
[1]  
Alkhawaja AbdelRahman., 2012, Qos-enabled middleware for smart grids
[2]  
[Anonymous], WEB SERV ARCH
[3]  
Bi Y.B., 2013, IEEE Power and Energy Society General Meeting, P1, DOI [DOI 10.1109/PESMG.2013.6672970, 10.1109/PESMG.2013.6672970]
[4]  
Deotare Punam, 2015, 2015 IEEE 9th International Conference on Intelligent Systems and Control (ISCO), P1, DOI 10.1109/ISCO.2015.7282390
[5]   GridStat: A Flexible QoS-Managed Data Dissemination Framework for the Power Grid [J].
Gjermundrod, Harald ;
Bakken, David E. ;
Hauser, Carl H. ;
Bose, Anjan .
IEEE TRANSACTIONS ON POWER DELIVERY, 2009, 24 (01) :136-143
[6]  
Jaloudi S., 2011, 2011 IEEE 20th International Symposium on Industrial Electronics (ISIE 2011), P1033, DOI 10.1109/ISIE.2011.5984302
[7]  
Le T., 2013, P INT JOINT C NEUR N, P1, DOI DOI 10.1109/IJCNN.2013.6707033
[8]   Middleware Architectures for the Smart Grid: Survey and Challenges in the Foreseeable Future [J].
Martinez, Jose-Fernan ;
Rodriguez-Molina, Jesus ;
Castillejo, Pedro ;
de Diego, Ruben .
ENERGIES, 2013, 6 (07) :3593-3621
[9]  
Object Management Group, 2012, CORBA SPEC VERS 3 3
[10]  
Omg O, 2006, DATA DISTRIBUTION SE