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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Maximizing Efficiency in Energy Trading Operations through IoT-Integrated Digital Twins.

Faiza Qayyum1, Reem Alkanhel2, Ammar Muthanna3

  • 1Department of Computer Engineering, Jeju National University, Jeju-si 63243, Republic of Korea.

Sensors (Basel, Switzerland)
|December 23, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a digital twin framework for optimizing energy storage systems (ESSs) in peer-to-peer (P2P) nano-grid trading. The approach enhances energy utilization and reduces costs through intelligent power management and IoT task orchestration.

Keywords:
Internet of Thingscomplex problem solvingcritical IoT systemsnano-gridoptimizationtask modelingtask orchestration

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Area of Science:

  • Energy Systems Engineering
  • Computer Science
  • Artificial Intelligence

Background:

  • The energy industry is exploring Internet of Things (IoT) applications beyond traditional sectors.
  • Distributed energy systems require advanced frameworks like digital twins for improved performance.
  • Energy storage systems (ESSs) are vital for nano-grids to enhance sustainability and resilience.

Purpose of the Study:

  • To propose a novel conceptual framework for IoT-enabled nano-grid energy trading.
  • To optimize power management of ESSs within a peer-to-peer (P2P) trading environment.
  • To enhance P2P energy trading efficiency through digital twin-based IoT task orchestration.

Main Methods:

  • Particle Swarm Optimization (PSO) for ESS power optimization.
  • Digital twin technology for IoT task orchestration (generation, virtualization, mapping, scheduling, allocation, deployment).
  • IoT sensors and Raspberry Pi edge technology for virtual nano-grid operation.

Main Results:

  • The proposed framework effectively manages surplus ESS energy and meets nano-grid demands.
  • PSO techniques demonstrated efficacy in reducing energy trading costs.
  • Digital twin-based orchestration improved power utilization and overall system efficiency in simulated nano-grids.

Conclusions:

  • The integration of digital twins and IoT is crucial for efficient nano-grid energy trading.
  • Optimized ESS power management significantly reduces operational costs.
  • The framework offers a scalable solution for enhancing distributed energy system performance.