Research on an optimization algorithm based on distributed generation configuration

The location and capacity of distributed power sources in a distribution network affect the operation of the power system. The reasonable planning of the location and capacity of the sources in a distribution network improves system voltage stability and reduces network losses. In this paper an improved Harris Hawk algorithm is proposed to find an optimal scheme planning and configuring distributed generation which are connected to a distribution network. Chebyshev chaotic mapping combined with the search adjustment method of PID search algorithm is introduced to enhance the uniformity of the initialized population, to improve the diversity and optimization accuracy of the algorithm. Taking an IEEE33 distribution system as example, this algorithm is applied to simulating the optimization configuration of the distributed power sources. After analyzing the experimental data, comparing with the traditional particle swarm algorithm and the unimproved Harris Hawk algorithm, the convergence speed of the improved algorithm is faster, and the obtained configuration scheme of the distributed power sources reduces network losses.

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Publication Details

Published
2025-05-09
DOI
https://doi.org/10.1109/net-lc65482.2025.11070629
Primary Topic
Power Systems and Renewable Energy
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article
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article

Research on an optimization algorithm based on distributed generation configuration

Qun Ge, Qiushi Ye
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Power Systems and Renewable Energy
article

Research on an optimization algorithm based on distributed generation configuration

Qun Ge, Qiushi Ye
article en

Abstract

The location and capacity of distributed power sources in a distribution network affect the operation of the power system. The reasonable planning of the location and capacity of the sources in a distribution network improves system voltage stability and reduces network losses. In this paper an improved Harris Hawk algorithm is proposed to find an optimal scheme planning and configuring distributed generation which are connected to a distribution network. Chebyshev chaotic mapping combined with the search adjustment method of PID search algorithm is introduced to enhance the uniformity of the initialized population, to improve the diversity and optimization accuracy of the algorithm. Taking an IEEE33 distribution system as example, this algorithm is applied to simulating the optimization configuration of the distributed power sources. After analyzing the experimental data, comparing with the traditional particle swarm algorithm and the unimproved Harris Hawk algorithm, the convergence speed of the improved algorithm is faster, and the obtained configuration scheme of the distributed power sources reduces network losses.

Liaoning Technical University (CN)
Openalex Percentile: Top 83%
Power Systems and Renewable Energy
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Research on an optimization algorithm based on distributed generation configuration — Qun Ge, Qiushi Ye · (2025) | TGRS Research Map | TGRS