2022
DOI: 10.1088/1742-6596/2158/1/012011
|View full text |Cite
|
Sign up to set email alerts
|

Reactive Power Optimization Based on AVC Time-division Control Strategy

Abstract: In order to avoid frequent actions of transformer taps and capacitor banks caused by reactive power optimization, this paper proposes a reactive power optimization based on AVC time division control strategy. The time division control strategy is used to segment the load curve of the next day, and the reactive power optimization process of each period is calculated by genetic algorithm. The strategy and algorithm are applied to the reactive power and voltage optimization of IEEE 30 bus system. The simulation r… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2022
2022
2022
2022

Publication Types

Select...
1
1

Relationship

0
2

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 3 publications
0
1
0
Order By: Relevance
“…When faced with large-scale reactive power compensation of the power grid, the calculation is complicated, the calculation amount is large, and the oscillation divergence phenomenon occurs, making it difficult to find the optimal solution [2]. In Literature [3], the AVC time-division control strategy is adopted to perform time-division reactive power optimization by segmenting analysis of the power grid load curve and combining it with a genetic algorithm. Literature [4] combined the advantages of TS, GA, and COA algorithms to obtain the genetic Tabu hybrid algorithm (TTGA) with optimized tent mapping.…”
Section: Introductionmentioning
confidence: 99%
“…When faced with large-scale reactive power compensation of the power grid, the calculation is complicated, the calculation amount is large, and the oscillation divergence phenomenon occurs, making it difficult to find the optimal solution [2]. In Literature [3], the AVC time-division control strategy is adopted to perform time-division reactive power optimization by segmenting analysis of the power grid load curve and combining it with a genetic algorithm. Literature [4] combined the advantages of TS, GA, and COA algorithms to obtain the genetic Tabu hybrid algorithm (TTGA) with optimized tent mapping.…”
Section: Introductionmentioning
confidence: 99%