Author
Listed:
- Zhaoyang, Kang
- Hongbin, Wu
- Guangdi, Yang
- Fuqiang, Ren
- Hongru, Zhang
- Kaining, Hou
- Ran, Zhu
- Peijin, Wang
- Hongshun, Liu
- Dongxin, He
- Qingquan, Li
Abstract
In response to the demand for compact design of 550 kV Gas-Insulated Transmission Lines (GIL), this paper proposes a compact design method for GIL based on multi-physics coupling and phased multi-objective optimization. By constructing a bi-directional coupling model of magnetic-thermal-fluid fields, the influence of bi-directional coupling on temperature prediction is revealed. Using parametric modeling and sensitivity analysis, key design variables affecting electric field strength and temperature rise are determined. For the first time, electric field strength, temperature rise, and cost are integrated into a unified optimization framework. This framework balances insulation safety, thermal stability, and economic practicality. Furthermore, this paper proposes a phased optimization strategy, utilizing the Response Surface Method (RSM), Non-dominated Sorting Genetic Algorithm II (NSGA-II), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to optimize global and local performance respectively. Results show that after optimization, the inner diameter of the GIL enclosure is reduced by 44.3 mm (from 290.0 mm to 245.7 mm), the cost is reduced by 12% (from 2178.9 CNY/m to 1918.3 CNY/m), and both electric field strength and temperature rise meet the design basis. Additionally, through lightning impulse tests, load-scan and steady-state thermal validation, and mechanical strength analysis, the engineering applicability of the optimized design is verified. This study provides a scientific method and engineering guidance for the compact design of GIL, holding significant application value.
Suggested Citation
Zhaoyang, Kang & Hongbin, Wu & Guangdi, Yang & Fuqiang, Ren & Hongru, Zhang & Kaining, Hou & Ran, Zhu & Peijin, Wang & Hongshun, Liu & Dongxin, He & Qingquan, Li, 2026.
"Compact design of 550 kV GIL based on multi-physics coupling and multi-objective optimization strategy,"
Energy, Elsevier, vol. 348(C).
Handle:
RePEc:eee:energy:v:348:y:2026:i:c:s0360544226005785
DOI: 10.1016/j.energy.2026.140475
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