Optimum aggregation of geographically distributed flexible resources in strategic smart-grid/microgrid locations

Smart substation is the intelligent node of the smart grid, which plays a fundamental part in the construction of the smart grid. This paper presents the concept and the technical characteristics of the smart substation and some important aspects in the development of Substation Automation System (SAS): the meaning, technical characteristics and the development of IEC61850 which is the international and the best standard for the construction of SAS; different Substation Communication (SC) architecture to ensure the reliability, availability and survivability of the geographically distributed complex power; the characteristics of Non Conventional Instrument Transformer(NCIT), the Intelligent Switchgear as well as their implement.

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Real-Time Coupling of Geographically Distributed Research Infrastructures: Taxonomy, Overview and Real-World Smart Grid Applications

IEEE Transactions on Smart Grid ◽

10.1109/tsg.2020.3033070 ◽

2020 ◽

pp. 1-1 ◽

Cited By ~ 1

Author(s):

M. H. Syed ◽

E. Guillo-Sansano ◽

Y. Wang ◽

S. Vogel ◽

P. Palensky ◽

...

Keyword(s):

Smart Grid ◽

Real Time ◽

Real World ◽

Research Infrastructures ◽

Geographically Distributed ◽

Grid Applications

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IoT ReDy Architecture for Smart Grid Management

Computer and Information Science ◽

10.5539/cis.v11n4p36 ◽

2018 ◽

Vol 11 (4) ◽

pp. 36

Author(s):

Kaoutar Hafdi ◽

Abderahman Kriouile ◽

Abdelaziz Kriouile

Keyword(s):

Smart Grid ◽

Power Plants ◽

Sensors And Actuators ◽

Large Power ◽

Management Algorithm ◽

Production And Consumption ◽

Membership Management ◽

Geographically Distributed ◽

Energy Plants ◽

Grid Management

Smart Grid introduces intelligent infrastructure to the existing power grid. Energy production is no longer confined just to large power plants, but is becoming geographically distributed on small renewable energy plants that can inject electricity directly into the grid. IoT proposes a good solution to connect the producers to the consumers and to propose a reactive balancing of power production and consumption. The ReDy architecture, which is intended for IoT applications, provides a base to implement a scalable, reliable, and dynamic IoT network ready to meet Smart Grid needs. The different producers and consumers represent nodes of a decentralized network managed with a dynamic membership management algorithm. Each node is a centralized sub-network composed of one gateway making decisions and several sensors and actuators.

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

Big Data and Cognitive Computing ◽

10.3390/bdcc3010008 ◽

2019 ◽

Vol 3 (1) ◽

pp. 8 ◽

Cited By ~ 9

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%.

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