scholarly journals Intelligent Systems and Synchro Phasors Protocols in Smart Grid Applications

2019 ◽  
Vol 8 (4) ◽  
pp. 1874-1878
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Phase Measurement ◽  
Harmonic Distortion ◽  
Quality Measurement ◽  
Communication Delays ◽  
Real Time Control ◽  
Grid Application

Supervisory control and data acquisition (SCADA) is one of the existing phase measurement system provides the real-time control of power switching relays, attains information of the system status. Usually it accomplishes three-phase measurement in distributed network of smart grid through ample power quality measurement of voltage, current, and mostly the total harmonic distortion. However, the investigation of the paper suggests that SCADA delivers the updates of the grid information in times with the communication delays of 15 seconds. Of course, these timing delays can be higher, since it varies on the system complexity. Therefore, this communication delays too high in terms of synchronization, fault monitoring, and the measurement of the system variables in real-time. Therefore, this study covers the communication framework and its protocols of the smart grid application. To make the study more concise, this paper also assessed the delay of IEEE 1588 and IEEE C37.118 for the synchronization performance measurement. Moreover, this paper also includes the performance analysis of the existing the intelligent system and its protocols for smart grid application.

scholarly journals Design and Implementation of Security Gateway for Synchrophasor Based Real-Time Control and Monitoring in Smart Grid

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 11626-11644 ◽  
Author(s):  
Rafiullah Khan ◽  
Kieran Mclaughlin ◽  
David Laverty ◽  
Sakir Sezer
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
Real Time Control ◽  
Design And Implementation ◽  
Time Control ◽  
Security Gateway

Design and Implementation of Cloud-Dust Based Intelligent System

2015 ◽  
Vol 764-765 ◽  
pp. 872-876
Author(s):  
Chung Chi Huang ◽  
Chung Lin Huang ◽  
Cong Hui Huang ◽  
Sheng Fone Yang
Keyword(s):  
Embedded System ◽  
Real Time ◽  
Intelligent Systems ◽  
Wireless Sensors ◽  
Intelligent System ◽  
Cloud System ◽  
Intelligent Computing ◽  
Design And Implementation ◽  
Machine Interface ◽  
Dust System

In the paper, design and Implementation of cloud-dust based intelligent system is proposed. For achieving applications of intelligent system, such as records, surveillance, assessments, predictions, diagnosis, prescription, scheduling and fool-proofing checks, an architecture named Cloud-Dust is developed. The intelligent system is separated into the cloud system and the dust system. The dust system contains (1) Wireless sensors network (2) Features extraction circuits (3) Intelligent computing circuits (4) Embedded system. It can play a role as real-time preprocessor very well, just like an intelligent agent. However, the cloud system contains (1) Cloud database (2) Intelligent computing engine (3) Ubiquitous human-machine-interface. It can flexibly use computing resources and integrate information from many different dust systems. By the experiments, we can find the advantages of the cloud-dust based intelligent system. It meets the both needs of real-time and integration for intelligent systems. So it is necessary to develop the cloud-dust based system for design and implementation of the intelligent system.

scholarly journals Real time control and monitoring of grid power systems using cloud computing

2019 ◽  
Vol 9 (2) ◽  
pp. 941 ◽  
Author(s):  
Nachiket Kulkarni ◽  
S. V. N. L. Lalitha ◽  
Sanjay A. Deokar
Keyword(s):  
Smart Grid ◽  
Power Systems ◽  
Power System ◽  
Real Time ◽  
Monitoring And Control ◽  
Real Time Control ◽  
Grid Systems ◽  
The Real ◽  
Time Control ◽  
And Control

The use of grid power systems based on the combinations of various electrical networks, information technology, and communication layers called as Smart Grid systems. The technique of smart grid suppressed the problems faced by conventional grid systems such as inefficient energy management, improper control actions, grid faults, human errors, etc. The recent research on smart grid provides the approach for the real-time control and monitoring of grid power systems based on bidirectional communications. However, the smart grid is yet to improve regarding efficiency, energy management, reliability, and cost-effectiveness by considering its real-time implementation. In this paper, we present the real-time design of efficient monitoring and control of grid power system using the remote cloud server. We utilized the remote cloud server to fetch, monitor and control the real-time power system data to improve the universal control and response time. The proper hardware panel designed and fabricated to establish the connection with the grid as well as remote cloud users. The authenticated cloud users are provisioned to access and control the grid power system from anywhere securely. For the user authentication, we proposed the novel approach to secure the complete smart grid system. Finally, we demonstrated the effectiveness of real-time monitoring and control of the grid power method with the use of structure of practical framework.

scholarly journals Fog Computing for Internet of Things (IoT)-Aided Smart Grid Architectures

2019 ◽  
Vol 3 (1) ◽  
pp. 8 ◽  
Author(s):  
Md. Hussain ◽  
M.M. Beg
Keyword(s):  
Internet Of Things ◽  
Smart Grid ◽  
Real Time ◽  
Fog Computing ◽  
Mixed Integer ◽  
Location Awareness ◽  
Real Time Control ◽  
Cloud Data ◽  
Flexible Resources

The fast-paced development of power systems necessitates the smart grid (SG) to facilitate real-time control and monitoring with bidirectional communication and electricity flows. In order to meet the computational requirements for SG applications, cloud computing (CC) provides flexible resources and services shared in network, parallel processing, and omnipresent access. Even though CC model is considered to be efficient for SG, it fails to guarantee the Quality-of-Experience (QoE) requirements for the SG services, viz. latency, bandwidth, energy consumption, and network cost. Fog Computing (FC) extends CC by deploying localized computing and processing facilities into the edge of the network, offering location-awareness, low latency, and latency-sensitive analytics for mission critical requirements of SG applications. By deploying localized computing facilities at the premise of users, it pre-stores the cloud data and distributes to SG users with fast-rate local connections. In this paper, we first examine the current state of cloud based SG architectures and highlight the motivation(s) for adopting FC as a technology enabler for real-time SG analytics. We also present a three layer FC-based SG architecture, characterizing its features towards integrating massive number of Internet of Things (IoT) devices into future SG. We then propose a cost optimization model for FC that jointly investigates data consumer association, workload distribution, virtual machine placement and Quality-of-Service (QoS) constraints. The formulated model is a Mixed-Integer Nonlinear Programming (MINLP) problem which is solved using Modified Differential Evolution (MDE) algorithm. We evaluate the proposed framework on real world parameters and show that for a network with approximately 50% time critical applications, the overall service latency for FC is nearly half to that of cloud paradigm. We also observed that the FC lowers the aggregated power consumption of the generic CC model by more than 44%.

Sign in / Sign up

Export Citation Format

Share Document