.png){kind=icon}
Return
Optimal reactive power planning using evolutionary algorithms: A comparative study for evolutionary programming, evolutionary strategy, genetic algorithm, and linear programming
.png){kind=icon}
PRE
AI
DOI：10.1109/59.651620.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper presents a comparative study for three evolutionary algorithms (EAs) to the Optimal Reactive Power Planning (ORPP) problem: evolutionary programming, evolutionary strategy, and genetic algorithm. The ORPP problem is decomposed into P- and Q-optimization modules, and each module is optimized by the EAs in an iterative manner to obtain the global solution. The EA methods for the ORPP problem are evaluated against the IEEE 30-bus system as a common testbed, and the results are compared against each other and with those of linear programming.
Keywords:
optimal reactive power planning
evolutionary algorithms
genetic algorithm
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
7.2
Papers:
1.1W
Citations:
5.0W
Organization
No organization information available
Cited Papers
ShareSaveShareSaveShareSave
ShareSaveGeochemistry and behavior of REE in stream sediments close to an old Sn-W mine, Ribeira, Northeast Portugal.png)
Geochemistry
GeochemistryIF0
PREAI
ShareSaveShareSave
View more