Communication and Security Technologies for Smart Grid

Dhaou, Imed Ben; Kondoro, Aron; Kelati, Amleset; Rwegasira, Diana; Naiman, Shililiandumi; Mvungi, Nerey H.; Tenhunen, Hannu

doi:10.4018/978-1-5225-5649-7.ch016

Cited by 4 publications

(3 citation statements)

References 98 publications

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“…Kondoro et al [ 33 ] investigated the security protocols in IoT communication for real-time properties to determine the impact of security on the Smart grid. To ensure security in the Fog environment, Verma et al [ 34 ] used Elliptic Curve Cryptography for authorization, and Dhaou et al [ 35 ] discussed security in a smart grid environment when communication is happening. A review of centralized security schemes is presented [ 36 ] for an IoT environment, carrying out a comparison over several factors like network model and architecture type.…”

Section: Related Workmentioning

confidence: 99%

Energy Aware Load Balancing Framework for Smart Grid Using Cloud and Fog Computing

Singhal

Athithan

Alomar

et al. 2023

Sensors

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Data centers are producing a lot of data as cloud-based smart grids replace traditional grids. The number of automated systems has increased rapidly, which in turn necessitates the rise of cloud computing. Cloud computing helps enterprises offer services cheaply and efficiently. Despite the challenges of managing resources, longer response plus processing time, and higher energy consumption, more people are using cloud computing. Fog computing extends cloud computing. It adds cloud services that minimize traffic, increase security, and speed up processes. Cloud and fog computing help smart grids save energy by aggregating and distributing the submitted requests. The paper discusses a load-balancing approach in Smart Grid using Rock Hyrax Optimization (RHO) to optimize response time and energy consumption. The proposed algorithm assigns tasks to virtual machines for execution and shuts off unused virtual machines, reducing the energy consumed by virtual machines. The proposed model is implemented on the CloudAnalyst simulator, and the results demonstrate that the proposed method has a better and quicker response time with lower energy requirements as compared with both static and dynamic algorithms. The suggested algorithm reduces processing time by 26%, response time by 15%, energy consumption by 29%, cost by 6%, and delay by 14%.

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Section: Related Workmentioning

confidence: 99%

Energy Aware Load Balancing Framework for Smart Grid Using Cloud and Fog Computing

Singhal

Athithan

Alomar

et al. 2023

Sensors

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“…The communication link between smart meters and the centralized controller can be assured by wireless or wireline WAN/LAN communication protocol. The classifications and comparisons among these protocols have been discussed in [61]. The LoRa communication protocol is a very attractive solution for building private, secure, and low-power communication infrastructure for microgrids [62,63].…”

Section: Design Of the Iot Communication Networkmentioning

confidence: 99%

Design of a Partially Grid-Connected Photovoltaic Microgrid Using IoT Technology

et al. 2021

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This study describes the design and control algorithms of an IoT-connected photovoltaic microgrid operating in a partially grid-connected mode. The proposed architecture and control design aim to connect or disconnect non-critical loads between the microgrid and utility grid. Different components of the microgrid, such as photovoltaic arrays, energy storage elements, inverters, solid-state transfer switches, smart-meters, and communication networks were modeled and simulated. The communication between smart meters and the microgrid controller is designed using LoRa communication protocol for the control and monitoring of loads in residential buildings. An IoT-enabled smart meter has been designed using ZigBee communication protocol to evaluate data transmission requirements in the microgrid. The loads were managed by a proposed under-voltage load-shedding algorithm that selects suitable loads to be disconnected from the microgrid and transferred to the utility grid. The simulation results showed that the duty cycle of LoRa and its bit rate can handle the communication requirements in the proposed PV microgrid architecture.

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“…Concerns about climate change and environmental concerns have also pushed numerous governments to establish new smart cities adopting innovative strategies to enhance the quality of life, illuminate environmental pollution, and thereby reduce carbon dioxide emissions [1,2]. Power systems have recently responded to these modern trends by implementing intelligent tools that rely on enhanced sensors and information and communication technologies (ICTs), besides advanced digital technology [3,4]. Power systems must adapt to changing generation profiles by developing intelligent tools that depend on modern sensors, ICTs, and digital control technologies [5].…”

Section: Introductionmentioning

confidence: 99%

Design of a Smart Distribution Panelboard Using IoT Connectivity and Machine Learning Techniques

Shaban

Alsharekh

2022

Energies

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Electric load management through continuous monitoring and intelligent controlling has become a pressing requirement, particularly in light of rising electrical energy costs. The main purpose of this work is to realize a low-voltage electrical distribution panelboard that allows for real-time load monitoring and that provides a load forecasting feature at the household level. In this regard, we demonstrate the design and the implementation details of an IoT-enabled panelboard with smart features. An IoT dashboard was used to display the most significant information in terms of voltage, current, real power, reactive power, apparent power, power factor, and energy consumption. Additionally, the panel system offers visualization capabilities that were integrated into a cloud-based machine learning modeling. Among several algorithms used, the Gaussian SVM regression exhibited the best training and validation results for the load forecasting feature. It is possible for the proposed design to be simply developed to add more smart features such as fault detection and identification. This assists in an efficient management of energy demand at the consumer level.

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Communication and Security Technologies for Smart Grid

Cited by 4 publications

References 98 publications

Energy Aware Load Balancing Framework for Smart Grid Using Cloud and Fog Computing

Energy Aware Load Balancing Framework for Smart Grid Using Cloud and Fog Computing

Design of a Partially Grid-Connected Photovoltaic Microgrid Using IoT Technology

Design of a Smart Distribution Panelboard Using IoT Connectivity and Machine Learning Techniques

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