Congestion Management in Italian HV grid using novel Dynamic Thermal Rating methods: first results of the H2020 European project Osmose
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Alfredo Vaccaro | Davide Poli | Paolo Pelacchi | Domenico Villacci | Giuseppe Lisciandrello | Fabia Gasparotto | Guido Coletta | Luca Orrú
[1] Anjan K. Deb. Powerline Ampacity System: Theory, Modeling and Applications , 2000 .
[2] Alfredo Vaccaro,et al. A Decentralized and Proactive Architecture based on the Cyber Physical System Paradigm for Smart Transmission Grids Modelling, Monitoring and Control , 2016 .
[3] Y. Motlis,et al. Application of the ruling span concept for overhead lines in mountainous terrain , 1998 .
[4] Konstantinos Kopsidas,et al. A probabilistic indicator of the optimal operator action time under short-time emergency line loadings , 2015, 2015 IEEE Eindhoven PowerTech.
[5] Giovanni Lutzemberger,et al. The possible impact of weather uncertainty on the Dynamic Thermal Rating of transmission power lines: A Monte Carlo error-based approach , 2019, Electric Power Systems Research.
[6] Claus Leth Bak,et al. An approach to dynamic line rating state estimation at thermal steady state using direct and indirect measurements , 2017, Electric Power Systems Research.
[7] Alfredo Vaccaro,et al. Dynamic loading of overhead lines by adaptive learning techniques and distributed temperature sensing , 2007 .
[8] Vitomir Komen,et al. Direct monitoring methods of overhead line conductor temperature , 2017 .
[9] Alfredo Vaccaro,et al. A cooperative smart sensor network for dynamic loading of overhead lines , 2011 .
[10] Marco Giuntoli,et al. Thermo-mechanical dynamic rating of OHTL: applications to Italian lines , 2014 .
[11] Jin-O Kim,et al. Prediction of transmission-line rating based on thermal overload probability using weather models , 2009 .
[12] Goran Andersson,et al. Probabilistic N−1 security assessment incorporating dynamic line ratings , 2013, 2013 IEEE Power & Energy Society General Meeting.
[13] Xueshan Han,et al. Probabilistic forecasting for the ampacity of overhead transmission lines using quantile regression method , 2016, 2016 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC).
[14] Vergerijeva Dp Elektroistra,et al. DIRECT MONITORING METHODS OF OVERHEAD LINE CONDUCTOR TEMPERATURE , 2017 .
[15] Davide Poli,et al. Thermo-mechanical model of multi-span overhead transmission lines equipped with high-temperature low-sag conductors , 2015 .
[16] H. B. White,et al. Limitations of the ruling span method for overhead line conductors at high operating temperatures , 1999 .
[17] Alfredo Vaccaro,et al. Experimental deployment of a self-organizing sensors network for dynamic thermal rating assessment of overhead lines , 2018 .
[18] Kuljit Singh. Cable monitoring solution — Predict with certainty , 2014 .
[19] R. Adapa,et al. Dynamic thermal ratings: monitors and calculation methods , 2005, 2005 IEEE Power Engineering Society Inaugural Conference and Exposition in Africa.