Internet of Things (IoT) and the Energy Sector

Motlagh, Naser Hossein; Mohammadrezaei, Mahsa; Hunt, Julian David; Zakeri, Behnam

doi:10.3390/en13020494

Cited by 510 publications

(213 citation statements)

References 145 publications

(160 reference statements)

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“…For instance, an IoT gateway device allows the data to be routed through the IoT network and bi-directional communication (i.e., device-to-gateway and gateway-to-cloud) [136,138,140]. SG, ESN, and IoT nodes may be the potential solution to tomorrow's global energy crisis [142]. The existing SG framework, combined with IoT and EI, can be applied to numerous energy-related applications.…”

Section: Application Of Internet-of-things and Energy Internet In Smamentioning

confidence: 99%

“…One of SG's critical components is continuous connectivity and communication, which provides equipped devices with these capabilities. In Reference [143], Kabalci SG, ESN, and IoT nodes may be the potential solution to tomorrow's global energy crisis [142]. The existing SG framework, combined with IoT and EI, can be applied to numerous energy-related applications.…”

Section: Application Of Internet-of-things and Energy Internet In Smamentioning

confidence: 99%

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Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids

et al. 2020

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Smart grid (SG), an evolving concept in the modern power infrastructure, enables the two-way flow of electricity and data between the peers within the electricity system networks (ESN) and its clusters. The self-healing capabilities of SG allow the peers to become active partakers in ESN. In general, the SG is intended to replace the fossil fuel-rich conventional grid with the distributed energy resources (DER) and pools numerous existing and emerging know-hows like information and digital communications technologies together to manage countless operations. With this, the SG will able to “detect, react, and pro-act” to changes in usage and address multiple issues, thereby ensuring timely grid operations. However, the “detect, react, and pro-act” features in DER-based SG can only be accomplished at the fullest level with the use of technologies like Artificial Intelligence (AI), the Internet of Things (IoT), and the Blockchain (BC). The techniques associated with AI include fuzzy logic, knowledge-based systems, and neural networks. They have brought advances in controlling DER-based SG. The IoT and BC have also enabled various services like data sensing, data storage, secured, transparent, and traceable digital transactions among ESN peers and its clusters. These promising technologies have gone through fast technological evolution in the past decade, and their applications have increased rapidly in ESN. Hence, this study discusses the SG and applications of AI, IoT, and BC. First, a comprehensive survey of the DER, power electronics components and their control, electric vehicles (EVs) as load components, and communication and cybersecurity issues are carried out. Second, the role played by AI-based analytics, IoT components along with energy internet architecture, and the BC assistance in improving SG services are thoroughly discussed. This study revealed that AI, IoT, and BC provide automated services to peers by monitoring real-time information about the ESN, thereby enhancing reliability, availability, resilience, stability, security, and sustainability.

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Section: Application Of Internet-of-things and Energy Internet In Smamentioning

confidence: 99%

Section: Application Of Internet-of-things and Energy Internet In Smamentioning

confidence: 99%

Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids

et al. 2020

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“…The proposed scheme was tested using simulation, and results reveal that the proposed scheme provides significant energy saving. According to [37], IoT helps to improve energy efficiency, reduce negative environmental impacts and increasing renewable energy share. This paper generally provides a detailed survey on IoT applications in energy and particularly in smart grid context.…”

Section: B Energy Optimization In 5gmentioning

confidence: 99%

Privacy Protection and Energy Optimization for 5G-Aided Industrial Internet of Things

et al. 2020

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The 5G is expected to revolutionize every sector of life by providing interconnectivity of everything everywhere at high speed. However, massively interconnected devices and fast data transmission will bring the challenge of privacy as well as energy deficiency. In today's fast-paced economy, almost every sector of the economy is dependent on energy resources. On the other hand, the energy sector is mainly dependent on fossil fuels and is constituting about 80% of energy globally. This massive extraction and combustion of fossil fuels lead to a lot of adverse impacts on health, environment, and economy. The newly emerging 5G technology has changed the existing phenomenon of life by connecting everything everywhere using IoT devices. 5G enabled IIoT devices has transformed everything from traditional to smart, e.g. smart city, smart healthcare, smart industry, smart manufacturing etc. However, massive I/O technologies for providing D2D connection has also created the issue of privacy that need to be addressed. Privacy is the fundamental right of every individual. 5G industries and organizations need to preserve it for their stability and competency. Therefore, privacy at all three levels (data, identity and location) need to be maintained. Further, energy optimization is a big challenge that needs to be addressed for leveraging the potential benefits of 5G and 5G aided IIoT. Billions of IIoT devices that are expected to communicate using the 5G network will consume a considerable amount of energy while energy resources are limited. Therefore, energy optimization is a future challenge faced by 5G industries that need to be addressed. To fill these gaps, we have provided a comprehensive framework that will help energy researchers and practitioners in better understanding of 5G aided industry 4.0 infrastructure and energy resource optimization by improving privacy. The proposed framework is evaluated using case studies and mathematical modelling.

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“…Turning the current power grid into an IoT technology-dependent one means that a large number of data are harvested from the physical assets' sensors and the cyber assets' controllers. This will greatly affect our current understanding of the energy sector [6][7][8][9][10][11][12]. An example of the sensors and data shared in a microgrid can be found in [13], where energy management as a cloud service was explored to provide a control platform for a residential microgrid.…”

Section: Introductionmentioning

confidence: 99%

IoT-Based Digital Twin for Energy Cyber-Physical Systems: Design and Implementation

2020

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With the emergence of distributed energy resources (DERs), with their associated communication and control complexities, there is a need for an efficient platform that can digest all the incoming data and ensure the reliable operation of the power system. The digital twin (DT) is a new concept that can unleash tremendous opportunities and can be used at the different control and security levels of power systems. This paper provides a methodology for the modelling of the implementation of energy cyber-physical systems (ECPSs) that can be used for multiple applications. Two DT types are introduced to cover the high-bandwidth and the low-bandwidth applications that need centric oversight decision making. The concept of the digital twin is validated and tested using Amazon Web Services (AWS) as a cloud host that can incorporate physical and data models as well as being able to receive live measurements from the different actual power and control entities. The experimental results demonstrate the feasibility of the real-time implementation of the DT for the ECPS based on internet of things (IoT) and cloud computing technologies. The normalized mean-square error for the low-bandwidth DT case was 3.7%. In the case of a high-bandwidth DT, the proposed method showed superior performance in reconstructing the voltage estimates, with 98.2% accuracy from only the controllers’ states.

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Internet of Things (IoT) and the Energy Sector

Cited by 510 publications

References 145 publications

Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids

Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids

Privacy Protection and Energy Optimization for 5G-Aided Industrial Internet of Things

IoT-Based Digital Twin for Energy Cyber-Physical Systems: Design and Implementation

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