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Internet of Things-Based Robust Green Smart Grid
Faculty
Engineering
Year:
2024
Type of Publication:
ZU Hosted
Pages:
Authors:
Rania Ahmed Elsayed Ahmed Mansour Khalifa
Staff Zu Site
Abstract In Staff Site
Journal:
computers MDPI
Volume:
Keywords :
Internet , Things-Based Robust Green Smart Grid
Abstract:
Renewable energy sources play a critical role in all governments’ and organizations’ energy management and sustainability plans. The solar cell represents one such renewable energy resource, generating power in a population-free circumference. Integrating these renewable sources with the smart grids leads to the generation of green smart grids. Smart grids are critical for modernizing electricity distribution by using new communication technologies that improve power system efficiency, reliability, and sustainability. Smart grids assist in balancing supply and demand by allowing for real-time monitoring and administration, as well as accommodating renewable energy sources and reducing outages. However, their execution presents considerable problems. High upfront expenditures and the need for substantial and reliable infrastructure changes present challenges. Despite these challenges, shifting to green smart grids is critical for a resilient and adaptable energy future that can fulfill changing consumer demands and environmental aims. To this end, this work considers developing a reliable Internet of Things (IoT)-based green smart grid. The proposed green grid integrates traditional grids with solar energy and provides a control unit between the generation and consumption parts of the grid. The work deploys intelligent IoT units to control energy demands and manage energy consumption effectively. The proposed framework deploys the paradigm of distributed edge computing in four levels to provide efficient data offloading and power management. The developed green grid outperformed traditional grids in terms of its reliability and energy efficiency. The proposed green grid reduces energy consumption over the distribution area by an average of 24.3% compared to traditional grids.
Author Related Publications
Rania Ahmed Elsayed Ahmed Mansour Khalifa, "Speech Compression Techniques based on Gaussian Mixture Model and Wavelet Analysis", Ain Shams University, Faculty of Engineering, 2009
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Rania Ahmed Elsayed Ahmed Mansour Khalifa, "Hybrid Method based on Multi-Feature Descriptor for Static Sign Language Recognition", (Institute of Electrical and Electronics Engineers (IEEE, 2017
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Rania Ahmed Elsayed Ahmed Mansour Khalifa, "Skin-based Adaptive Background Subtraction for Hand Gesture Segmentation", (Institute of Electrical and Electronics Engineers (IEEE, 2015
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Rania Ahmed Elsayed Ahmed Mansour Khalifa, "Hand Gesture Recognition Based on Dimensionality Reduction of Histogram of Oriented Gradients", (Institute of Electrical and Electronics Engineers (IEEE, 2017
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Rania Ahmed Elsayed Ahmed Mansour Khalifa, "Performance Enhancement of Indoor Cellular Visible Light Communication through Cell Size and Wavelength Reuse Pattern", Springer Nature, 2023
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Department Related Publications
Mohammed Ayesh Muhammad Hanafi, "Compressed sensing for reliable body area propagation with efficient signal reconstruction", IEEE, 2018
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Saleh Ibrahiem Saied Saleh, "Rate Splitting Multiple Access Scheme for Cognitive Radio Network", The Egyptian International Journal of Engineering Sciences and Technology, 2021
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Saleh Ibrahiem Saied Saleh, "Performance Evaluation of 5G Modulation Techniques", Springer US, 2021
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Nabila Alsawy Elsayed Elsawy, "Mode Skipping for Screen Content Coding Based On Neural Network Classifier", Springer, 2021
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Nabila Alsawy Elsayed Elsawy, "Efficient Coding Unit Classifier for HEVC Screen Content Coding Based on Machine Learning", Springer, 2022
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