Publikationer av Kateryna Morozovska
Refereegranskade
Artiklar
[1]
I. Ramirez et al., "Residual-based attention Physics-informed Neural Networks for spatio-temporal ageing assessment of transformers operated in renewable power plants," Engineering applications of artificial intelligence, vol. 139, 2025.
[2]
F. Urban et al., "Decarbonizing maritime shipping and aviation: Disruption, regime resistance and breaking through carbon lock-in and path dependency in hard-to-abate transport sectors," Environmental Innovation and Societal Transitions, vol. 52, 2024.
[3]
W. V. Calil et al., "Determining total cost of ownership and peak efficiency index of dynamically rated transformer at the PV-power plant," Electric power systems research, vol. 229, 2024.
[4]
M. Hartmann, K. Morozovska och T. Laneryd, "Forecasting of wind farm power output based on dynamic loading of power transformer at the substation," Electric power systems research, vol. 234, 2024.
[5]
K. Morozovska et al., "Trade-offs of wind power production: A study on the environmental implications of raw materials mining in the life cycle of wind turbines," Journal of Cleaner Production, vol. 460, 2024.
[6]
A. Molina Gómez et al., "Optimal sizing of the wind farm and wind farm transformer using MILP and dynamic transformer rating," International Journal of Electrical Power & Energy Systems, vol. 136, s. 107645-107645, 2022.
[7]
F. Bragone et al., "Physics-informed neural networks for modelling power transformer’s dynamic thermal behaviour," Electric power systems research, vol. 211, s. 108447-108447, 2022.
[8]
K. Morozovska et al., "Including Dynamic Line Rating Into the Optimal Planning of Distributed Energy Resources," IEEE Transactions on Smart Grid, vol. 12, no. 6, s. 5052-5059, 2021.
[9]
K. Morozovska et al., "A framework for application of dynamic line rating to aluminum conductor steel reinforced cables based on mechanical strength and durability," International Journal of Electrical Power & Energy Systems, vol. 116, 2020.
[10]
O. D. Ariza Rocha et al., "Dynamic rating assists cost-effective expansion of wind farms by utilizing the hidden capacity of transformers," International Journal of Electrical Power & Energy Systems, vol. 123, 2020.
[11]
N. Viafora et al., "Day-ahead dispatch optimization with dynamic thermal rating of transformers and overhead lines," Electric power systems research, vol. 171, s. 194-208, 2019.
[12]
T. Zarei et al., "Reliability considerations and economic benefits of dynamic transformer rating for wind energy integration," International Journal of Electrical Power & Energy Systems, vol. 106, s. 598-606, 2019.
Konferensbidrag
[13]
F. Bragone et al., "Time Series Predictions Based on PCA and LSTM Networks : A Framework for Predicting Brownian Rotary Diffusion of Cellulose Nanofibrils," i Computational Science – ICCS 2024 - 24th International Conference, 2024, Proceedings, 2024, s. 209-223.
[14]
T. Laneryd et al., "Physics Informed Neural Networks for Power Transformer Dynamic Thermal Modelling," i IFAC Papersonline, 2022, s. 49-54.
[15]
F. Bragone et al., "Physics-Informed Neural Networks for Modeling Cellulose Degradation in Power Transformers," i 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), 2022.
[16]
K. Oueslati et al., "Physics-Informed Neural Networks for modelling insulation paper degradation in Power Transformers," i 2022 IEEE International Conference on Electrical Sciences and Technologies in Maghreb (CISTEM), 2022.
[17]
O. Welin Odeback et al., "Physics-Informed Neural Networks for prediction of transformer's temperature distribution," i 2022 21ST IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, ICMLA, 2022, s. 1579-1586.
[18]
O. Welin Odeback et al., "Physics-Informed Neural Networks for prediction of transformer’s temperature distribution," i 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), 2022.
[19]
D. Bogatov Wilkman et al., "Self-Supervised Transformer Networks for Error Classification of Tightening Traces," i 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), 2022.
[20]
K. Morozovska, R. Karlsson och P. Hilber, "Dynamic rating of the wind farm transformer from the power system’s perspective," i 2021 IEEE Madrid PowerTech, PowerTech 2021 - Conference Proceedings, 2021.
[21]
Z. Li et al., "Sizing Transformer Considering Transformer Thermal Limits and Wind Farm Wake Effect," i 2021 IEEE PES Innovative Smart Grid Technologies - Asia, ISGT Asia 2021, 2021.
[22]
O. Kryvtsun, E. Tereschenko och K. Morozovska, "A few methods for construction of feasible labeling," i Combinatorial configurations and their applications, 2020.
[23]
V. Chakrapani Manakari et al., "Minimization of Wind Power Curtailment using Dynamic Line Rating," i 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), 2020.
[24]
W. Naim, K. Morozovska och P. Hilber, "Effects of Dynamic Line Rating on the Durability and Mechanical Strength of Aluminum Cable Steel Reinforced (ACSR) Conductors," i Innovative Solutions for Energy Transitions, 2019, s. 3164-3169.
[25]
A. Estanqueiro et al., "DLR use for optimization of network design withvery large wind (and VRE) penetration," i 17th Wind Integration Workshop, 2018.
[26]
A. Vieira Turnell et al., "Decentralized Secondary Frequency Control in an Optimized Diesel PV Hybrid System," i Proceedings of the 8th International Workshop on the Integration of Solar Power into Power Systems, 2018.
[27]
A. Vieira Turnell et al., "Decentralized Secondary Frequency Controlin an Optimized Diesel PV Hybrid System," i 8th International Workshop on the Integration of Solar Power into Power Systems | Stockholm, Sweden | 16 – 17 October 2018, 2018.
[28]
K. Morozovska och P. Hilber, "Risk analysis of wind farm connection to existing grids using dynamic line rating," i 2018 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2018 - Proceedings, 2018.
[29]
A. Vieira Turnell et al., "Risk and economic analysis of utilizing dynamic thermal rated transformer for wind farm connection," i 2018 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2018 - Proceedings, 2018.
[30]
K. Morozovska och P. Hilber, "Study of the Monitoring Systems for Dynamic Line Rating," i 8th International Conference on Applied Energy, ICAE 2016; Beijing; China; 8 October 2016 through 11 October 2016, 2017, s. 2557-2562.
[31]
O. Giesecke et al., "Reliability study of two offshore wind farm topologies : Radial and ring connection," i PROCEEDINGS 15th Wind Integration Workshop : International Workshop on Large-Scale Integration of Wind Power into Power Systems as well as on Transmission Networks for Offshore Wind Power Plants, 2016.
Icke refereegranskade
Avhandlingar
[32]
K. Morozovska, "Dynamic Rating with Applications to Renewable Energy," Doktorsavhandling Stockholm, : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2020:3, 2020.
[33]
K. Morozovska, "Dynamic Rating of Power Lines and Transformers for Wind Energy Integration," Licentiatavhandling Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2018:37, 2018.
Rapporter
[34]
D. Danylov et al., "An experimental assessment of the intermittent heating and cooling operation effect on power transformer insulation," , TRITA-EECS-RP, 2021.
Övriga
[35]
O. D. Ariza Rocha et al., "Dynamic rating assists cost-effective expansion of wind farms byutilizing hidden capacity of transformers," (Manuskript).
[36]
K. Morozovska et al., "Including Dynamic Line Rating into the Optimal Planning of Distributed Energy Resources," (Manuskript).
[37]
T. Zarei et al., "Reliability Considerations and Economic Benefits of Dynamic Transformer Rating for Wind Energy Integration," (Manuskript).
[38]
F. Bragone et al., "Unsupervised Learning Analysis of Flow-Induced Birefringence in Nanocellulose: Differentiating Materials and Concentrations," (Manuskript).
Senaste synkning med DiVA:
2024-11-21 00:06:51