Automatic Region-Based Layout Optimization of Substation Wiring Diagrams Via Improved Genetic Algorithms
This paper proposes an automatic region-based layout optimization method for substation main wiring diagrams using a improved genetic algorithm. The method addresses the problems of low space utilization and rigid region division caused by template-based layouts. A two-segment chromosome structure i...
Uložené v:
| Vydané v: | 2025 8th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) s. 237 - 241 |
|---|---|
| Hlavní autori: | , , , , , , |
| Médium: | Konferenčný príspevok.. |
| Jazyk: | English |
| Vydavateľské údaje: |
IEEE
09.05.2025
|
| Predmet: | |
| On-line prístup: | Získať plný text |
| Tagy: |
Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
|
| Abstract | This paper proposes an automatic region-based layout optimization method for substation main wiring diagrams using a improved genetic algorithm. The method addresses the problems of low space utilization and rigid region division caused by template-based layouts. A two-segment chromosome structure is designed to encode both region assignment and interval ordering. The algorithm includes repair mechanisms and enhanced crossover and mutation operations to improve search efficiency and solution stability. In the layout modeling phase, interval units are abstracted as rectangular blocks to enable unified spatial representation. A set of graph-structured constraints, including voltage isolation, region boundary rules, and transformer area merging logic, are incorporated into the objective function as penalty terms. A case study on a 220kV substation shows that the proposed method results in better-balanced occupancy across regions and a more compact and readable layout. Experimental results demonstrate improvements of 11.6 percent in optimal performance and 24.2 percent in average performance compared to the standard genetic algorithm. The method proves effective for handling constrained and dynamically changing layout tasks in intelligent substation design. |
|---|---|
| AbstractList | This paper proposes an automatic region-based layout optimization method for substation main wiring diagrams using a improved genetic algorithm. The method addresses the problems of low space utilization and rigid region division caused by template-based layouts. A two-segment chromosome structure is designed to encode both region assignment and interval ordering. The algorithm includes repair mechanisms and enhanced crossover and mutation operations to improve search efficiency and solution stability. In the layout modeling phase, interval units are abstracted as rectangular blocks to enable unified spatial representation. A set of graph-structured constraints, including voltage isolation, region boundary rules, and transformer area merging logic, are incorporated into the objective function as penalty terms. A case study on a 220kV substation shows that the proposed method results in better-balanced occupancy across regions and a more compact and readable layout. Experimental results demonstrate improvements of 11.6 percent in optimal performance and 24.2 percent in average performance compared to the standard genetic algorithm. The method proves effective for handling constrained and dynamically changing layout tasks in intelligent substation design. |
| Author | Ren, Hao Xu, Xiaofeng Shen, Zeliang Qin, Jun Liu, Junyi Peng, Cong Fan, Qing |
| Author_xml | – sequence: 1 givenname: Qing surname: Fan fullname: Fan, Qing email: fq@js.sgcc.com.cn organization: State Grid Jiangsu Electric Power Co., Ltd,Equipment Management Department,Nanjing,China – sequence: 2 givenname: Junyi surname: Liu fullname: Liu, Junyi email: liujunyi921@nuaa.edu.cn organization: Nanjing University of Aeronautics and Astronautics,School of Automation,Nanjing,China – sequence: 3 givenname: Hao surname: Ren fullname: Ren, Hao email: renhao@epri.sgcc.com.cn organization: Nanjing Branch China Electric Power Research Institute Co., Ltd,Nanjing,China – sequence: 4 givenname: Jun surname: Qin fullname: Qin, Jun email: qinjun@js.sgcc.com.cn organization: State Grid Wuxi Power Supply Company,Equipment Management Department,Wuxi,China – sequence: 5 givenname: Xiaofeng surname: Xu fullname: Xu, Xiaofeng email: xfxu@js.sgcc.com.cn organization: State Grid Wuxi Power Supply Company,Equipment Management Department,Wuxi,China – sequence: 6 givenname: Zeliang surname: Shen fullname: Shen, Zeliang email: zeliangsan@gmail.com organization: Nanjing Branch China Electric Power Research Institute Co., Ltd,Nanjing,China – sequence: 7 givenname: Cong surname: Peng fullname: Peng, Cong email: pengcong@nuaa.edu.cn organization: Nanjing University of Aeronautics and Astronautics,School of Astronautics,Nanjing,China |
| BookMark | eNo1T91OwjAYrYleKPIGXtQHGHbf6LpeTkQkmSERopfk2_g6mtCVbJ0JPr0j6NXJ-U3OHbtufEOMPcZiEsdCP-Xz99l6nkrQMAEB8qxOYSrgio210lmSxHLIxekt2-d98A6DrfgH1dY30TN2tOMFnnwf-OoYrLM_g-8b7g1f92UXLuzLtrap-YvFukXX8U-LfOmOrf8e6gtq6LyZH2rf2rB33T27MXjoaPyHI7Z5nW9mb1GxWixneRFZnYQolTuglKRRhhBQaAkpKJWpqcFKSkFKaMAMM6VFaSTEld4JglKXMiMjqmTEHi6zloi2x9Y6bE_b___JL1EqV0M |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/AEMCSE65292.2025.11042402 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE Electronic Library (IEL) IEEE Proceedings Order Plans (POP All) 1998-Present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| EISBN | 9798331510916 |
| EndPage | 241 |
| ExternalDocumentID | 11042402 |
| Genre | orig-research |
| GrantInformation_xml | – fundername: Science and Technology Project of State Grid funderid: 10.13039/501100013096 |
| GroupedDBID | 6IE 6IL CBEJK RIE RIL |
| ID | FETCH-LOGICAL-i93t-65d2e6e5f7fea2a09526277874fac550e7092a8a8790bf521c9d0e2b9b58ef0c3 |
| IEDL.DBID | RIE |
| IngestDate | Wed Jul 02 05:55:41 EDT 2025 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i93t-65d2e6e5f7fea2a09526277874fac550e7092a8a8790bf521c9d0e2b9b58ef0c3 |
| PageCount | 5 |
| ParticipantIDs | ieee_primary_11042402 |
| PublicationCentury | 2000 |
| PublicationDate | 2025-May-9 |
| PublicationDateYYYYMMDD | 2025-05-09 |
| PublicationDate_xml | – month: 05 year: 2025 text: 2025-May-9 day: 09 |
| PublicationDecade | 2020 |
| PublicationTitle | 2025 8th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE) |
| PublicationTitleAbbrev | AEMCSE |
| PublicationYear | 2025 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| Score | 1.9078982 |
| Snippet | This paper proposes an automatic region-based layout optimization method for substation main wiring diagrams using a improved genetic algorithm. The method... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 237 |
| SubjectTerms | Biological cells Genetic algorithms graph-structured constraints improved genetic algorithm Layout layout optimization Software engineering Stability analysis substation main wiring diagrams Substations Transformers two-segment chromosome Voltage Wiring |
| Title | Automatic Region-Based Layout Optimization of Substation Wiring Diagrams Via Improved Genetic Algorithms |
| URI | https://ieeexplore.ieee.org/document/11042402 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3PT8IwFG6EGONJjRh_pyZeC6Pr1vWICPGASJQgN9J1r7IEmIHNxP_ethsaDx68NU1_JG3ar33vfd9D6JbJiDGuGEk86ROrX05EJNtEBW0tzYdIgUvJMhnw4TCaTsWoIqs7LgwAuOAzaNqi8-UnmSqsqaxloIpZb0AN1TgPS7LWHrqpdDNbnd5j96UXBlRYhhUNmtv2vzKnOODoH_xzykPU-KHg4dE3uByhHVgdo3mnyDOnsYqfwQYSkzsDQgkeyM-syPGTOf7LileJM43tpVB62vFrau13-D6VNhprgyepxKU9wXS30tN2zM7iLVun-Xy5aaBxvzfuPpAqVQJJhZ-TMEgohBBorkFSaZ5NNKTcnEWmpTJ_EOCeoDKSERderA1iK5F4QGMRBxFoT_knqL7KVnCKsBSS0yTQVHJgzPdjzyqSJcKPKY88n52hhl2l2XsphjHbLtD5H_UXaN_uhYsRFJeonq8LuEK76iNPN-trt4VfKc2eyQ |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3PT8MgFCY6jXpS44y_xcQrG1IY5Tjnlhm7uegyd1toC66JW83WmvjfC7TTePDgjZAACYT3wXvv-x4A11T6lPKIohhLD1n9ciR8eYMidqOl-RBFypVkGQW83_fHYzEoyeqOC6OUcslnqmabLpYfp1FuXWV1A1XURgPWwQajlOCCrrUFrkrlzHqz3Ws9txuMCMuxIqy2GvGrdoqDjs7uPxfdA9UfEh4cfMPLPlhT8wMwbeZZ6lRW4ZOyqcTo1sBQDAP5meYZfDQGYFYyK2GqoTULRawdviTWgwfvEmnzsZZwlEhYeBTMcCs-bedsvr2miySbzpZVMOy0h60uKosloER4GWqwmKiGYpprJYk0DyfSINzcRqplZH4himNBpC99LnCoDWZHIsaKhCJkvtI48g5BZZ7O1RGAUkhOYqaJ5IpSzwux1SSLhRcS7mOPHoOq3aXJeyGHMVlt0Mkf_ZdguzvsBZPgvv9wCnbsubiMQXEGKtkiV-dgM_rIkuXiwh3nF5jcohA |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2025+8th+International+Conference+on+Advanced+Electronic+Materials%2C+Computers+and+Software+Engineering+%28AEMCSE%29&rft.atitle=Automatic+Region-Based+Layout+Optimization+of+Substation+Wiring+Diagrams+Via+Improved+Genetic+Algorithms&rft.au=Fan%2C+Qing&rft.au=Liu%2C+Junyi&rft.au=Ren%2C+Hao&rft.au=Qin%2C+Jun&rft.date=2025-05-09&rft.pub=IEEE&rft.spage=237&rft.epage=241&rft_id=info:doi/10.1109%2FAEMCSE65292.2025.11042402&rft.externalDocID=11042402 |