Open Access
| Issue |
ITM Web Conf.
Volume 47, 2022
2022 2nd International Conference on Computer, Communication, Control, Automation and Robotics (CCCAR2022)
|
|
|---|---|---|
| Article Number | 03014 | |
| Number of page(s) | 10 | |
| Section | Control Technology and Robotics Technology | |
| DOI | https://doi.org/10.1051/itmconf/20224703014 | |
| Published online | 23 June 2022 | |
- Davis M W. A new thermal rating approach: the real time thermal rating system for strategic overhead conductor transmission lines–Part I: General description and justification of the real time thermal rating system IEEE Trans Power Appar Syst 96 pp 803–809 (1977) [CrossRef] [Google Scholar]
- Seppa O Clements M Damsgaard-Mikkelsen S et al. Application of real time thermal ratings for optimizing transmission line investment and operating decisions CIGRE Paper 22–301 (2000) [Google Scholar]
- Cigre Brouchure. Increasing Capacity of Overhead Transmission Lines: Needs and Solutions (2010) [Google Scholar]
- M W Davis A new thermal rating approach: the real time thermal rating system for strategic overhead conductor transmission lines Part I IEEE Transactions on Power Apparatus and Systems vol PAS-96 803–825 (1977) [CrossRef] [Google Scholar]
- M W Davis. A new thermal rating approach: the real time thermal rating system for strategic overhead conductor transmission lines Part II IEEE Transactions on Power Apparatus and Systems vol PAS-97:810–824 (1978) [Google Scholar]
- M W Davis. A new thermal rating approach: the real time thermal rating system for strategic overhead conductor transmission lines Part III IEEE Transactions on Power Apparatus and Systems vol PAS-97:444–452 (1978) [CrossRef] [Google Scholar]
- Bishnu P Bhattarai, Jake P Gentle, Timothy McJunkin et al. Improvement of transmission line ampacity utilization by weather-based dynamic line rating IEEE Trans Power Del vol 33 no 4 pp 1853–1863 Aug (2018) [CrossRef] [Google Scholar]
- Hamid Shaker Mahmud Fotuhi-Firuzabad and Farrokh Aminifar. Fuzzy dynamic thermal rating of transmission lines IEEE Trans Power Del vol 27 no 4 pp 1885–1892 Oct (2012) [Google Scholar]
- Z Huiping, M Jinbi, H Xiaoqing, B Liming, M Dongjuan and H Jie. A Critical Line Identification Method Based on Probabilistic Load Flow 2018 IEEE International Power Electronics and Application Conference and Exposition (PEAC) pp 1–6 (2018) [Google Scholar]
- Min Li, Lixiong Xu, Hui Gong, Zhaoou Song, Lijie Ding and Junyong Liu. Study on critical lines identification Proceedings 2013 International Conference on Mechatronic Sciences Electric Engineering and Computer (MEC) pp 3132–3135 (2013) [CrossRef] [Google Scholar]
- Y Cao, Y Zhang, C Guo, B Zhu and L Xu. Identification of power grid critical lines based on comprehensive transmission betweenness 2017 IEEE Power & Energy Society General Meeting pp 1–5 (2017) [Google Scholar]
- J Wan et al. Determination of critical span in real time using proper orthogonal decomposition 2013 Seventh International Conference on Sensing Technology (ICST) pp 816–821 (2013) [Google Scholar]
- M Matus et al Identification of Critical Spans for Monitoring Systems in Dynamic Thermal Rating IEEE Transactions on Power Delivery vol 27 no 2 pp 1002–1009 [Google Scholar]
- Cotton I and Teh J. Critical span identification model for dynamic thermal rating system placement Iet Generation Transmission & Distribution 9(16):2644–2652 (2015) [CrossRef] [Google Scholar]
- CIGRE. Guide for thermal rating calculations of overhead lines CIGRE WG B2 43 Technical brochures 601 Dec (2014) [Google Scholar]
- Kiessling F. Overhead power lines: planning, design, construction (2003) [Google Scholar]
- X Jin, M Wang, M Cui, H Sun and M Yang Joint Probability Density Prediction for Multiperiod Thermal Ratings of Overhead Conductors IEEE Transactions on Power Delivery vol 36 no 5 pp 3022–3032 [Google Scholar]
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