Distributed load shedding algorithm for islanded microgrid using fog computing paradigm

Rwegasira, Diana; Dhaou, Imed Ben; Kakakhel, Syed Rameez Ullah; Westerlund, Tomi; Tenhunen, Hannu

doi:10.1109/energycon48941.2020.9236574

Cited by 3 publications

(3 citation statements)

References 11 publications

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“…The growth of intelligent technology is outlined on Statista's website [128] under Figure 4. As has been suggested, an enormous increase in smart homes as well as commercial buildings, and important requirements for these buildings will include intelligent electricity and water management [129]. Statista projects that the number of IoT devices will nearly triple between 2020 and 2030, going from 9.7 billion in 2020 to more than 29 billion in 2030.…”

Section: Iot Systemsmentioning

confidence: 99%

Early Detection of Earthquakes Using IoT and Cloud Infrastructure: A Survey

Abdalzaher,

Krichen,

Yiltas-Kaplan

et al. 2023

Sustainability

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Earthquake early warning systems (EEWS) are crucial for saving lives in earthquake-prone areas. In this study, we explore the potential of IoT and cloud infrastructure in realizing a sustainable EEWS that is capable of providing early warning to people and coordinating disaster response efforts. To achieve this goal, we provide an overview of the fundamental concepts of seismic waves and associated signal processing. We then present a detailed discussion of the IoT-enabled EEWS, including the use of IoT networks to track the actions taken by various EEWS organizations and the cloud infrastructure to gather data, analyze it, and send alarms when necessary. Furthermore, we present a taxonomy of emerging EEWS approaches using IoT and cloud facilities, which includes the integration of advanced technologies such as machine learning (ML) algorithms, distributed computing, and edge computing. We also elaborate on a generic EEWS architecture that is sustainable and efficient and highlight the importance of considering sustainability in the design of such systems. Additionally, we discuss the role of drones in disaster management and their potential to enhance the effectiveness of EEWS. Furthermore, we provide a summary of the primary verification and validation methods required for the systems under consideration. In addition to the contributions mentioned above, this study also highlights the implications of using IoT and cloud infrastructure in early earthquake detection and disaster management. Our research design involved a comprehensive survey of the existing literature on early earthquake warning systems and the use of IoT and cloud infrastructure. We also conducted a thorough analysis of the taxonomy of emerging EEWS approaches using IoT and cloud facilities and the verification and validation methods required for such systems. Our findings suggest that the use of IoT and cloud infrastructure in early earthquake detection can significantly improve the speed and effectiveness of disaster response efforts, thereby saving lives and reducing the economic impact of earthquakes. Finally, we identify research gaps in this domain and suggest future directions toward achieving a sustainable EEWS. Overall, this study provides valuable insights into the use of IoT and cloud infrastructure in earthquake disaster early detection and emphasizes the importance of sustainability in designing such systems.

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Section: Iot Systemsmentioning

confidence: 99%

Early Detection of Earthquakes Using IoT and Cloud Infrastructure: A Survey

Abdalzaher,

Krichen,

Yiltas-Kaplan

et al. 2023

Sustainability

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“…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]. LoRa uses spread spectrum technology which employs a low-complicity receiver, making it a suitable choice for machine-to-machine (M2M) communication, IoT, wireless sensor networks, and many other applications.…”

Section: Design Of the Iot Communication Networkmentioning

confidence: 99%

“…In many applications, communication latency is a crucial element in any actuator-type or control-type application. The latency requirements for implementing the DR program have been studied in research and industrial trends [62][63][64]. However, in the context of smart grids, there have been limited efforts devoted to using them in isolated-mode microgrids.…”

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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