Enhancing Smart Grid Efficiency Through Innovative Data Management And Analytics For Demand Energy Management

The smart electrical grid allows data and power to flow in both directions, connecting generators and consumers. This allows for more efficient, reliable, and environmentally friendly power flow optimization. With this system in place, micro-energy producers and users may participate more actively in the power market and in DEM. Finding ways to get people involved so that smart grid (SG) users can help bring down electricity costs is the biggest obstacle. But accurate predictions of load and renewable generation are crucial for DEM to work. Because of this, there is a pressing need for smart approaches and solutions to harness the massive amounts of data produced by the proliferation of smart meters in real-time. To optimize the functioning of SGs, it is crucial to have strong data analytics, HPC, effective data network management, and cloud computing approaches. This study’s overarching goal is to provide insight on the difficulties encountered by the DEM used in SG networks due to huge data. Along with that, it lays out the most popular data processing techniques utilized in the literature and suggests a good path forward for study in the area.

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Publication Details

Published
2024-09-18
DOI
https://doi.org/10.1109/ic3i61595.2024.10829315
Citations
1
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
0.21
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article

Enhancing Smart Grid Efficiency Through Innovative Data Management And Analytics For Demand Energy Management

P. Subhashini, H Pal Thethi, Aravind Karrothu, G. Ramesh et al.
1 citations
Smart Grid Energy Management
0.21
article

Enhancing Smart Grid Efficiency Through Innovative Data Management And Analytics For Demand Energy Management

P. Subhashini, H Pal Thethi, Aravind Karrothu, G. Ramesh, C Praveen Kumar, Kanan Divetia
article en
1 citations

Abstract

The smart electrical grid allows data and power to flow in both directions, connecting generators and consumers. This allows for more efficient, reliable, and environmentally friendly power flow optimization. With this system in place, micro-energy producers and users may participate more actively in the power market and in DEM. Finding ways to get people involved so that smart grid (SG) users can help bring down electricity costs is the biggest obstacle. But accurate predictions of load and renewable generation are crucial for DEM to work. Because of this, there is a pressing need for smart approaches and solutions to harness the massive amounts of data produced by the proliferation of smart meters in real-time. To optimize the functioning of SGs, it is crucial to have strong data analytics, HPC, effective data network management, and cloud computing approaches. This study’s overarching goal is to provide insight on the difficulties encountered by the DEM used in SG networks due to huge data. Along with that, it lays out the most popular data processing techniques utilized in the literature and suggests a good path forward for study in the area.

Lovely Professional University (IN), Horizon College and Seminary (CA), Birla Institute of Technology and Science - Hyderabad Campus (IN)
Affordable and clean energy
Openalex Percentile: Top 44%
Smart Grid Energy Management
0.21
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Enhancing Smart Grid Efficiency Through Innovative Data Management And Analytics For Demand Energy Management — P. Subhashini, H Pal Thethi, et al. · (2024) | TGRS Research Map | TGRS