A Deep Convolutional Neural Network-Based Approach to Detect False Data Injection Attacks on PV-Integrated Distribution Systems
<p dir="ltr">The integration of photovoltaic (PV) panels has allowed power distribution systems (PDSs) to regulate their voltage through the injection/absorption of reactive power. The deployment of information and communication technologies (ICTs), which is required for this scheme,...
Saved in:
| Main Author: | Masoud Ahmadzadeh (21633053) (author) |
|---|---|
| Other Authors: | Ahmadreza Abazari (21633056) (author), Mohsen Ghafouri (21633059) (author), Amir Ameli (12512083) (author), S. M. Muyeen (14778337) (author) |
| Published: |
2024
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
SPARQ: A Cyber-Resilient Voltage Regulation Using Soft Q-Learning Approach for Autonomous Grid Operations
by: Mohamed Massaoudi (16888710)
Published: (2025) -
A real-time automatic pothole detection system using convolution neural networks
by: Bharat, Ricardo
Published: (2023) -
Character convolutions for Arabic Named Entity Recognition with Long Short-Term Memory Networks
by: Khalifaa , Muhammad
Published: (2019) -
An Incentivized and Optimized Dynamic Mechanism for Demand Response for Managing Voltage in Distribution Networks
by: Md Moktadir Rahman (16904751)
Published: (2022) -
Improving the Resilience of Smart Distribution Networks against Cyber Attacks
by: ElYamani, Mohamed ElHusseiny Mohamed
Published: (2022)