Dual-weight decay mechanism and Nelder-Mead simplex boosted RIME algorithm for optimal power flow
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 generatin...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2024-12-01
|
| Series: | Journal of Big Data |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40537-024-01034-0 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846137002538303488 |
|---|---|
| author | Huangying Wu Yi Chen Zhennao Cai Ali Asghar Heidari Huiling Chen Guoxi Liang |
| author_facet | Huangying Wu Yi Chen Zhennao Cai Ali Asghar Heidari Huiling Chen Guoxi Liang |
| author_sort | Huangying Wu |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-9f92b0c3e3bf4212bcddb935a2d63536 |
| institution | Kabale University |
| issn | 2196-1115 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Big Data |
| spelling | doaj-art-9f92b0c3e3bf4212bcddb935a2d635362024-12-08T12:33:24ZengSpringerOpenJournal of Big Data2196-11152024-12-0111113310.1186/s40537-024-01034-0Dual-weight decay mechanism and Nelder-Mead simplex boosted RIME algorithm for optimal power flowHuangying Wu0Yi Chen1Zhennao Cai2Ali Asghar Heidari3Huiling Chen4Guoxi Liang5Department of Computer Science and Artificial Intelligence, Wenzhou UniversityDepartment of Computer Science and Artificial Intelligence, Wenzhou UniversityDepartment of Computer Science and Artificial Intelligence, Wenzhou UniversitySchool of Surveying and Geospatial Engineering, College of Engineering, University of TehranDepartment of Computer Science and Artificial Intelligence, Wenzhou UniversityDepartment of Artificial Intelligence, Wenzhou PolytechnicAbstract 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.https://doi.org/10.1186/s40537-024-01034-0FACTS devicesRIMEOptimal power flowGlobal optimization |
| spellingShingle | Huangying Wu Yi Chen Zhennao Cai Ali Asghar Heidari Huiling Chen Guoxi Liang Dual-weight decay mechanism and Nelder-Mead simplex boosted RIME algorithm for optimal power flow Journal of Big Data FACTS devices RIME Optimal power flow Global optimization |
| title | Dual-weight decay mechanism and Nelder-Mead simplex boosted RIME algorithm for optimal power flow |
| title_full | Dual-weight decay mechanism and Nelder-Mead simplex boosted RIME algorithm for optimal power flow |
| title_fullStr | Dual-weight decay mechanism and Nelder-Mead simplex boosted RIME algorithm for optimal power flow |
| title_full_unstemmed | Dual-weight decay mechanism and Nelder-Mead simplex boosted RIME algorithm for optimal power flow |
| title_short | Dual-weight decay mechanism and Nelder-Mead simplex boosted RIME algorithm for optimal power flow |
| title_sort | dual weight decay mechanism and nelder mead simplex boosted rime algorithm for optimal power flow |
| topic | FACTS devices RIME Optimal power flow Global optimization |
| url | https://doi.org/10.1186/s40537-024-01034-0 |
| work_keys_str_mv | AT huangyingwu dualweightdecaymechanismandneldermeadsimplexboostedrimealgorithmforoptimalpowerflow AT yichen dualweightdecaymechanismandneldermeadsimplexboostedrimealgorithmforoptimalpowerflow AT zhennaocai dualweightdecaymechanismandneldermeadsimplexboostedrimealgorithmforoptimalpowerflow AT aliasgharheidari dualweightdecaymechanismandneldermeadsimplexboostedrimealgorithmforoptimalpowerflow AT huilingchen dualweightdecaymechanismandneldermeadsimplexboostedrimealgorithmforoptimalpowerflow AT guoxiliang dualweightdecaymechanismandneldermeadsimplexboostedrimealgorithmforoptimalpowerflow |