Open Access
| Issue |
ITM Web Conf.
Volume 47, 2022
2022 2nd International Conference on Computer, Communication, Control, Automation and Robotics (CCCAR2022)
|
|
|---|---|---|
| Article Number | 03020 | |
| Number of page(s) | 10 | |
| Section | Control Technology and Robotics Technology | |
| DOI | https://doi.org/10.1051/itmconf/20224703020 | |
| Published online | 23 June 2022 | |
- D L Alvarez, F F da Silva, E E Mombello, C L Bak and J A Rosero. Conductor temperature estimation and prediction at thermal transient state in dynamic line rating application IEEE Transactions on Power Delivery vol 33 no 5 pp 2236-2245 (2018) [CrossRef] [Google Scholar]
- N Viafora, K Morozovska, S H H Kazmi et al. Day-ahead dispatch optimization with Dynamic Thermal Rating of transformers and overhead lines Electric Power Systems Research vol 171 pp 194-208 (2019) [CrossRef] [Google Scholar]
- D. Douglass et al. Real-time overhead transmission-line monitoring for dynamic rating IEEE Transactions on Power Delivery vol 31 no 3 pp 921-927 (2016) [CrossRef] [Google Scholar]
- D M Greenwood and P C Taylor. Investigating the impact of real-time thermal ratings on power network reliability IEEE Transactions on Power Systems vol 29 no 5 pp 2460-2468 (2014) [CrossRef] [Google Scholar]
- R Fernandez Martinez, R Alberdi, E Fernandez, I Albizu and M T Bedialauneta. Improvement of safety operating conditions in overhead conductors based on ampacity modeling using artificial neural networks 2019 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) pp 1-5 (2019) [Google Scholar]
- S Madadi, B Mohammadi-Ivatloo, S Tohidi. Dynamic line rating forecasting based on integrated factorized Ornstein–Uhlenbeck processes IEEE Transactions on Power Delivery vol 35 no 2 pp 851-860 (2020) [CrossRef] [Google Scholar]
- Zhiqing Wei, Mengxia Wang, Xueshan Han, Haicheng Zhang and Qiang Zhang. Probabilistic forecasting for the ampacity of overhead transmission lines using quantile regression method 2016 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) pp 1632-1635 (2016) [Google Scholar]
- J L Aznarte and N Siebert. Dynamic line rating using Numerical Weather Predictions and machine learning: a case study IEEE Transactions on Power Delivery vol 32 no 1 pp 335-343 (2017) [CrossRef] [Google Scholar]
- Romain Dupin, George Kariniotakis and Andrea Michiorri. Overhead lines dynamic line rating based on probabilistic day-ahead forecasting and risk assessment International Journal of Electrical Power & Energy Systems vol 110 pp 565-578 (2019) [CrossRef] [Google Scholar]
- IEEE standard for calculating the current-temperature relationship of bare overhead conductors IEEE Std 738-2012 (Revision of IEEE Std 738-2006 - Incorporates IEEE Std 738-2012 Cor 1-2013) pp1-72. [Google Scholar]
- K V Mardia. Linear-circular correlation coefficients and rhythmometry Biometrika vol 63 no 2 pp 403-405 (1976) [CrossRef] [Google Scholar]
- X Jin, M Wang, M Cui, H Sun and M Yang. 2021 Joint Probability Density Prediction for Multiperiod Thermal Ratings of Overhead Conductors IEEE Transactions on Power Delivery vol 36 no 5 pp 3022-3032 (2021) [CrossRef] [Google Scholar]
- Ming Yang, Simeng Zhu, Xueshan Han and Hongtao Wang. Joint probability density forecast for wind farm output in multi-time-interval Automation of Electric Power Systems vol 37 pp 23-28 (2013) [MathSciNet] [Google Scholar]
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