Application of improved ant-lion algorithm for power systems

An improved ant-lion algorithm is proposed to solve the load allocation problem to improve the efficiency of load allocation in the power system. The global search capability and optimization performance of the algorithm have been significantly improved by introducing elite weights and chaotic search mechanisms. The innovation of the research lies in not only optimizing economic goals, but also considering environmental goals, achieving dual optimization of economy and environment. The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s, respectively. The required number of iterations was significantly better than other algorithms. In the verification of solving economic load dispatch, the improved ant-lion optimizer achieved a total fuel cost reduction of 0.10% -2.39% and 6% in both 3-unit and 6-unit simulations, respectively, compared to the other three algorithms. In the verification of solving environmental and economic load dispatch, considering the valve point effect, this proposed optimization scheme had a total fuel cost of 622.46 $/hr and a total emission of 0.20 tons/h. The total objective function was 1542.54 $/hr, which was an average reduction of 53.55 $/hr compared to the other five algorithms. Therefore, improving the ant-lion optimizer can enhance its optimization performance. The improved ant-lion optimizer has positive application significance in power system load dispatch and can achieve superior load dispatch results.

Authors

Publication Details

Journal
PLoS ONE
Published
2024-12-04
DOI
https://doi.org/10.1371/journal.pone.0311563
Citations
1
Primary Topic
Electric Power System Optimization
Type
article
Field-Weighted Citation Impact
0.21
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article

Application of improved ant-lion algorithm for power systems

Renjun Zhou, Weitao Wang
1 citations
PLoS ONE
Electric Power System Optimization
0.21
article

Application of improved ant-lion algorithm for power systems

Renjun Zhou, Weitao Wang
article en
1 citations

Abstract

An improved ant-lion algorithm is proposed to solve the load allocation problem to improve the efficiency of load allocation in the power system. The global search capability and optimization performance of the algorithm have been significantly improved by introducing elite weights and chaotic search mechanisms. The innovation of the research lies in not only optimizing economic goals, but also considering environmental goals, achieving dual optimization of economy and environment. The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s, respectively. The required number of iterations was significantly better than other algorithms. In the verification of solving economic load dispatch, the improved ant-lion optimizer achieved a total fuel cost reduction of 0.10% -2.39% and 6% in both 3-unit and 6-unit simulations, respectively, compared to the other three algorithms. In the verification of solving environmental and economic load dispatch, considering the valve point effect, this proposed optimization scheme had a total fuel cost of 622.46 $/hr and a total emission of 0.20 tons/h. The total objective function was 1542.54 $/hr, which was an average reduction of 53.55 $/hr compared to the other five algorithms. Therefore, improving the ant-lion optimizer can enhance its optimization performance. The improved ant-lion optimizer has positive application significance in power system load dispatch and can achieve superior load dispatch results.

PLoS ONEVol. 19(12)
Openalex Percentile: Top 45%
Electric Power System Optimization
0.21
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