Energy-saving optimal scheduling under multi-mode “source-network-load-storage” combined system in metro station based on modified GrayWolf Algorithm
Aiming to address power consumption issues of various equipment in metro stations and the inefficiency of peak shaving and valley filling in the power supply system, this study presents an economic optimization scheduling method for the multi-modal “source-network-load-storage” system in metro stati...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Polish Academy of Sciences
2024-03-01
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| Series: | Archives of Electrical Engineering |
| Subjects: | |
| Online Access: | https://journals.pan.pl/Content/130558/09_int.pdf |
| _version_ | 1827311412627636224 |
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| author | Jingjing Tian Yu Qian Feng Zhao Shenglin Mo Huaxuan Xiao Xiaotong Zhu Guangdi Liu |
| author_facet | Jingjing Tian Yu Qian Feng Zhao Shenglin Mo Huaxuan Xiao Xiaotong Zhu Guangdi Liu |
| author_sort | Jingjing Tian |
| collection | DOAJ |
| description | Aiming to address power consumption issues of various equipment in metro stations and the inefficiency of peak shaving and valley filling in the power supply system, this study presents an economic optimization scheduling method for the multi-modal “source-network-load-storage” system in metro stations. The proposed method, called the Improved Gray Wolf Optimization Algorithm (IGWO), utilizes objective evaluation criteria to achieve economic optimization. First, construct a mathematical model of the “sourcenetwork- load-storage” joint system with the metro station at its core. This model should consider the electricity consumption within the station. Secondly, a two-layer optimal scheduling model is established, with the upper model aiming to optimize peak elimination and valley filling, and the lower model aiming to minimize electricity consumption costs within a scheduling cycle. Finally, this paper introduces the IGWO optimization approach, which utilizes meta-models and the Improved Gray Wolf Optimization Algorithm to address the nonlinearity and computational complexity of the two-layer model. The analysis shows that the proposed model and algorithm can improve the solution speed and minimize the cost of electricity used by about 5.5% to 8.7% on the one hand, and on the other hand, it improves the solution accuracy, and at the same time effectively realizes the peak shaving and valley filling, which provides a proof of the effectiveness and feasibility of the new method. |
| first_indexed | 2024-04-24T20:18:35Z |
| format | Article |
| id | doaj.art-821fcceec2b94e12b1b1104fd8c71bd9 |
| institution | Directory Open Access Journal |
| issn | 2300-2506 |
| language | English |
| last_indexed | 2024-04-24T20:18:35Z |
| publishDate | 2024-03-01 |
| publisher | Polish Academy of Sciences |
| record_format | Article |
| series | Archives of Electrical Engineering |
| spelling | doaj.art-821fcceec2b94e12b1b1104fd8c71bd92024-03-22T12:48:01ZengPolish Academy of SciencesArchives of Electrical Engineering2300-25062024-03-01vol. 73No 1121141https://doi.org/10.24425/aee.2024.148861Energy-saving optimal scheduling under multi-mode “source-network-load-storage” combined system in metro station based on modified GrayWolf AlgorithmJingjing Tian0Yu Qian1Feng Zhao2Shenglin Mo3Huaxuan Xiao4Xiaotong Zhu5Guangdi Liu6School of Automation and Electrical Engineering, Lanzhou Jiaotong University Lanzhou, ChinaSchool of Automation and Electrical Engineering, Lanzhou Jiaotong University Lanzhou, ChinaSchool of Automation and Electrical Engineering, Lanzhou Jiaotong University Lanzhou, ChinaSchool of Automation and Electrical Engineering, Lanzhou Jiaotong University Lanzhou, ChinaSchool of Automation and Electrical Engineering, Lanzhou Jiaotong University Lanzhou, ChinaSchool of Automation and Electrical Engineering, Lanzhou Jiaotong University Lanzhou, ChinaSchool of Automation and Electrical Engineering, Lanzhou Jiaotong University Lanzhou, ChinaAiming to address power consumption issues of various equipment in metro stations and the inefficiency of peak shaving and valley filling in the power supply system, this study presents an economic optimization scheduling method for the multi-modal “source-network-load-storage” system in metro stations. The proposed method, called the Improved Gray Wolf Optimization Algorithm (IGWO), utilizes objective evaluation criteria to achieve economic optimization. First, construct a mathematical model of the “sourcenetwork- load-storage” joint system with the metro station at its core. This model should consider the electricity consumption within the station. Secondly, a two-layer optimal scheduling model is established, with the upper model aiming to optimize peak elimination and valley filling, and the lower model aiming to minimize electricity consumption costs within a scheduling cycle. Finally, this paper introduces the IGWO optimization approach, which utilizes meta-models and the Improved Gray Wolf Optimization Algorithm to address the nonlinearity and computational complexity of the two-layer model. The analysis shows that the proposed model and algorithm can improve the solution speed and minimize the cost of electricity used by about 5.5% to 8.7% on the one hand, and on the other hand, it improves the solution accuracy, and at the same time effectively realizes the peak shaving and valley filling, which provides a proof of the effectiveness and feasibility of the new method.https://journals.pan.pl/Content/130558/09_int.pdfbi-level optimizationgrey wolf optimization algorithmmulti-modepeakshaving and valley fillingsource-network -load-storage |
| spellingShingle | Jingjing Tian Yu Qian Feng Zhao Shenglin Mo Huaxuan Xiao Xiaotong Zhu Guangdi Liu Energy-saving optimal scheduling under multi-mode “source-network-load-storage” combined system in metro station based on modified GrayWolf Algorithm Archives of Electrical Engineering bi-level optimization grey wolf optimization algorithm multi-mode peakshaving and valley filling source-network -load-storage |
| title | Energy-saving optimal scheduling under multi-mode “source-network-load-storage” combined system in metro station based on modified GrayWolf Algorithm |
| title_full | Energy-saving optimal scheduling under multi-mode “source-network-load-storage” combined system in metro station based on modified GrayWolf Algorithm |
| title_fullStr | Energy-saving optimal scheduling under multi-mode “source-network-load-storage” combined system in metro station based on modified GrayWolf Algorithm |
| title_full_unstemmed | Energy-saving optimal scheduling under multi-mode “source-network-load-storage” combined system in metro station based on modified GrayWolf Algorithm |
| title_short | Energy-saving optimal scheduling under multi-mode “source-network-load-storage” combined system in metro station based on modified GrayWolf Algorithm |
| title_sort | energy saving optimal scheduling under multi mode source network load storage combined system in metro station based on modified graywolf algorithm |
| topic | bi-level optimization grey wolf optimization algorithm multi-mode peakshaving and valley filling source-network -load-storage |
| url | https://journals.pan.pl/Content/130558/09_int.pdf |
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