Dual-weight decay mechanism and Nelder-Mead simplex boosted RIME algorithm for optimal power flow

The increasing demand for electricity presents substantial challenges in power system planning, particularly optimizing the Optimal Power Flow (OPF) problem. The OPF problem entails establishing the best settings for control variables in a power system to reduce objectives such as generating cost and transmission losses while meeting operational restrictions. This research introduces an upgraded RIME optimization algorithm (WDNMRIME) to address these challenges. WDNMRIME integrates a dual-weight decay mechanism and the Nelder-Mead simplex (NMs), enhancing population diversity and mitigating the risk of local optima. Additionally, NMs expedites convergence by refining the population's optimal solution set. Experimental validation on the IEEE 30-bus test system demonstrates that WDNMRIME achieves a generation cost of $806.00298 per hour and reduces total power loss from 1.43 MW to 1.39 MW. These results surpass the performance of the original RIME algorithm, showcasing a 15% improvement in convergence speed. The algorithm effectively optimizes multiple concurrent Flexible Alternating Current Transmission Systems (FACTS) devices, even under the uncertain nature of wind energy resources modeled using the Weibull probability density function. These findings highlight WDNMRIME's significant contribution to improving OPF optimization in dynamic power systems.

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Publication Details

Journal
Journal Of Big Data
Published
2024-12-04
DOI
https://doi.org/10.1186/s40537-024-01034-0
Citations
7
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
1.46

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article

Dual-weight decay mechanism and Nelder-Mead simplex boosted RIME algorithm for optimal power flow

Zhennao Cai, Ali Asghar Heidari, Guoxi Liang, Yi Chen et al.
7 citations
Journal Of Big Data
Optimal Power Flow Distribution
1.46
article

Dual-weight decay mechanism and Nelder-Mead simplex boosted RIME algorithm for optimal power flow

Zhennao Cai, Ali Asghar Heidari, Guoxi Liang, Yi Chen, Huiling Chen, Huangying Wu
article en
7 citations

Abstract

The increasing demand for electricity presents substantial challenges in power system planning, particularly optimizing the Optimal Power Flow (OPF) problem. The OPF problem entails establishing the best settings for control variables in a power system to reduce objectives such as generating cost and transmission losses while meeting operational restrictions. This research introduces an upgraded RIME optimization algorithm (WDNMRIME) to address these challenges. WDNMRIME integrates a dual-weight decay mechanism and the Nelder-Mead simplex (NMs), enhancing population diversity and mitigating the risk of local optima. Additionally, NMs expedites convergence by refining the population's optimal solution set. Experimental validation on the IEEE 30-bus test system demonstrates that WDNMRIME achieves a generation cost of $806.00298 per hour and reduces total power loss from 1.43 MW to 1.39 MW. These results surpass the performance of the original RIME algorithm, showcasing a 15% improvement in convergence speed. The algorithm effectively optimizes multiple concurrent Flexible Alternating Current Transmission Systems (FACTS) devices, even under the uncertain nature of wind energy resources modeled using the Weibull probability density function. These findings highlight WDNMRIME's significant contribution to improving OPF optimization in dynamic power systems.

Journal Of Big DataVol. 11(1)
Wenzhou University (CN), University of Tehran (IR), Wenzhou Polytechnic (CN)
National Natural Science Foundation of China, Wenzhou University, Natural Science Foundation of Zhejiang Province
Affordable and clean energy
Openalex Percentile: Top 17%
Optimal Power Flow Distribution
1.46
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