Positioning Capacitors and Distributed Gen Units for Multi-Objective Optimization

The placement of distributed generation (DG), capacitors, and ULTC transformer tap settings can all be employed separately to lower loss, enhance the voltage profile, and raise the distribution network's available transfer capability (ATC). These devices will be more effective if they are placed and set simultaneously. This paper uses a multi-objective function to implement this strategy. Reducing loss, improving voltage, and raising ATC make up the objective function. The objective function is optimized through the application of Genetic Algorithm (GA) approach. The suggested approach is used on the IEEE 41 bus radial distribution network to demonstrate its efficacy. The outcomes demonstrate that this approach improves the objective functions more effectively.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-01
DOI
https://doi.org/10.5281/zenodo.14952695
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
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article

Positioning Capacitors and Distributed Gen Units for Multi-Objective Optimization

Zenodo (CERN European Organization for Nuclear Research)
Optimal Power Flow Distribution
article

Positioning Capacitors and Distributed Gen Units for Multi-Objective Optimization

article en

Abstract

The placement of distributed generation (DG), capacitors, and ULTC transformer tap settings can all be employed separately to lower loss, enhance the voltage profile, and raise the distribution network's available transfer capability (ATC). These devices will be more effective if they are placed and set simultaneously. This paper uses a multi-objective function to implement this strategy. Reducing loss, improving voltage, and raising ATC make up the objective function. The objective function is optimized through the application of Genetic Algorithm (GA) approach. The suggested approach is used on the IEEE 41 bus radial distribution network to demonstrate its efficacy. The outcomes demonstrate that this approach improves the objective functions more effectively.

Zenodo (CERN European Organization for Nuclear Research)
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Openalex Percentile: Top 55%
Optimal Power Flow Distribution
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