A Survey of Machine Learning Techniques for Optimal Capacitor Placement and Sizing in Smart Distribution Networks
The increasing complexity of modern power distribution networks necessitates advanced strategies for reactive power compensation, particularly in capacitor placement and sizing. Traditional optimization techniques, while effective, often struggle with dynamic system behaviors, nonlinear loads, and r...
Saved in:
| Main Authors: | Kwabena Addo, Katleho Moloi, Musasa Kabeya, Evans Eshiemogie Ojo |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10982221/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Pareto Local Search Function for Optimal Placement of DG and Capacitors Banks in Distribution Systems
by: Abdolreza Sadighmanesh, et al.
Published: (2024-02-01) -
Optimizing Power System Performance: The Significance of Placement and Sizing of Battery Energy Storage Systems
by: Harith B. Hussien, et al.
Published: (2025-03-01) -
Simultaneous Optimal Network Reconfiguration, DG and Fixed/Switched Capacitor Banks Placement in Distribution Systems using Dedicated Genetic Algorithm
by: Davar Esmaeili, et al.
Published: (2024-02-01) -
Optimizing capacitor size and placement in radial distribution networks for maximum efficiency
by: R. Arunjothi, et al.
Published: (2024-12-01) -
A New 13-Level Flying Capacitor-based 1-φ Inverter with Full Reactive Power Support
by: Jaber Fallah Ardashir, et al.
Published: (2022-06-01)