Congestion Management Using an Optimized Deep Convolution Neural Network in Deregulated Environment
The technical issue of congestion, which is predominantly found in deregulated power systems, is caused by the failure of transmission networks to satisfy load power demands. This failure is primarily caused due to an increase in loads or loss of transmission lines or generators in modern restructur...
Saved in:
| Main Authors: | Dhanadeepika B., Vanithasri M., Chakravarthi M. |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Academy of Sciences of Moldova
2023-08-01
|
| Series: | Problems of the Regional Energetics |
| Subjects: | |
| Online Access: | https://journal.ie.asm.md/assets/files/11_03_59_2023.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Generator Rescheduling Based Congestion Management in Power System Deregulation Using the Cheetah Optimization
by: Sajal Debbarma, et al.
Published: (2025-03-01) -
Real-time congestion control using cascaded LSTM deep neural networks for deregulated power markets
by: G. Madhu Mohan, et al.
Published: (2025-08-01) -
FACTS Controllers’ Contribution for Load Frequency Control, Voltage Stability and Congestion Management in Deregulated Power Systems over Time: A Comprehensive Review
by: Muhammad Asad, et al.
Published: (2025-07-01) -
Deregulation as an Effort to Improve Public Services in Indonesia
by: Marlan Hutahaean, et al.
Published: (2024-01-01) -
Voltage and frequency regulation in wind penetrated deregulated power system using an electric vehicle and IPFC assisted model predictive controller
by: Vineet Kumar, et al.
Published: (2025-08-01)