• "SMART GRIDS AND IOT: REVOLUTIONIZING ENERGY DISTRIBUTION" Zoltan GALA University Zeged, Hungary Csanak Edit Dla
  • Keywords
  • Key Components of Smart Grids and IoT Advanced Metering Infrastructure (AMI)
  • IoT Sensors and Devices
  • Namangan Institute of Engineering and Technology




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    Namangan Institute of Engineering and Technology 
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    10.25.2023
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    ENERGIYA ISHLAB CHIQARISH, UZATISH VA TAQSIMLASH SOHASIDAGI 
    DOLZARB MUAMMOLAR VA YECHIMLAR
     
     
    "SMART GRIDS AND IOT: REVOLUTIONIZING ENERGY DISTRIBUTION" 
     Zoltan GALA
    University Zeged, Hungary 
    Csanak Edit Dla
    University Obuda, Hungary 
     
    Introduction. The integration of Smart Grids and the Internet of Things (IoT) is revolutionizing 
    the energy sector by enhancing efficiency, reliability, and sustainability in energy distribution. This 
    technological synergy is creating a more adaptive and intelligent energy network. This article 
    explores how Smart Grids and IoT are working together to transform the energy distribution 
    landscape. 
    Keywords: Smart Grids, Internet of Things, IoT, Energy Distribution, Renewable Energy, Grid 
    Efficiency.
     
    The Evolution of Energy Distribution. Traditional energy grids are often inefficient and 
    incapable of handling the complexities of modern energy demands and the integration of renewable 
    energy sources. Smart Grids, enhanced with IoT technology, represent a paradigm shift, offering a 
    more dynamic and interactive system for energy distribution. 
    Key Components of Smart Grids and IoT 
    Advanced Metering Infrastructure (AMI): AMI, consisting of smart meters, communication 
    networks, and data management systems, allows for real-time monitoring and management of 
    energy usage, enhancing efficiency and facilitating demand response programs. 
    IoT Sensors and Devices: Sensors and IoT devices placed throughout the grid can monitor 
    various aspects of the energy system, including voltage, current, and temperature, providing critical 
    data for optimizing grid performance. 

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