Improving efficiency in smart grid monitoring using hybrid classification and dimensionality reduction
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View abstract on PubMed
Summary
This summary is machine-generated.This study introduces a Smart Grid Monitoring System (SGMS) using IoT for efficient data handling. The system achieves high accuracy and low energy consumption for smart grids.
Area Of Science
- Electrical Engineering
- Computer Science
- Renewable Energy Systems
Background
- Smart grids and renewable energy integration require efficient monitoring and data communication.
- Traditional methods face challenges with adaptability, path selection, communication overhead, and latency.
- Internet of Things (IoT) offers potential for enhanced smart grid management.
Purpose Of The Study
- To develop an intelligent Smart Grid Monitoring System (SGMS) for improved data collection, processing, and transmission in IoT-based smart grids.
- To address inefficiencies in path selection, communication overhead, and latency associated with traditional monitoring techniques.
- To enhance the responsiveness and scalability of smart grid operations through efficient data management.
Main Methods
- Utilized sensors to gather data from photovoltaic (PV) systems, wind systems, the grid, and battery systems.
- Employed ESP8266 NodeMCU for data processing and storage, with preprocessing including one-hot encoding and Linear Discriminant Analysis (LDA).
- Introduced a Hybrid Updated Gazelle-Random Forest (HUG-RF) classifier for shortest path identification to an IoT webpage, optimizing data transmission.
Main Results
- Achieved 96.8% accuracy in monitoring critical smart grid parameters.
- Demonstrated a low energy consumption rate of 0.36%.
- Successfully reduced computational complexity and improved data transmission efficiency and latency.
Conclusions
- The developed SGMS provides comprehensive monitoring and efficient data processing for smart grids.
- The system enhances remote accessibility and control through an integrated IoT platform.
- The proposed approach offers a robust and intelligent solution for modern smart grid challenges.
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