Publications by Kateryna Morozovska
Peer reviewed
Articles
[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 and 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, pp. 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, pp. 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, pp. 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, pp. 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, pp. 598-606, 2019.
Conference papers
[13]
F. Bragone et al., "Time Series Predictions Based on PCA and LSTM Networks : A Framework for Predicting Brownian Rotary Diffusion of Cellulose Nanofibrils," in Computational Science – ICCS 2024 - 24th International Conference, 2024, Proceedings, 2024, pp. 209-223.
[14]
T. Laneryd et al., "Physics Informed Neural Networks for Power Transformer Dynamic Thermal Modelling," in IFAC Papersonline, 2022, pp. 49-54.
[15]
F. Bragone et al., "Physics-Informed Neural Networks for Modeling Cellulose Degradation in Power Transformers," in 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," in 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," in 2022 21ST IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, ICMLA, 2022, pp. 1579-1586.
[18]
O. Welin Odeback et al., "Physics-Informed Neural Networks for prediction of transformer’s temperature distribution," in 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," in 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA), 2022.
[20]
K. Morozovska, R. Karlsson and P. Hilber, "Dynamic rating of the wind farm transformer from the power system’s perspective," in 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," in 2021 IEEE PES Innovative Smart Grid Technologies - Asia, ISGT Asia 2021, 2021.
[22]
O. Kryvtsun, E. Tereschenko and K. Morozovska, "A few methods for construction of feasible labeling," in Combinatorial configurations and their applications, 2020.
[23]
V. Chakrapani Manakari et al., "Minimization of Wind Power Curtailment using Dynamic Line Rating," in 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), 2020.
[24]
W. Naim, K. Morozovska and P. Hilber, "Effects of Dynamic Line Rating on the Durability and Mechanical Strength of Aluminum Cable Steel Reinforced (ACSR) Conductors," in Innovative Solutions for Energy Transitions, 2019, pp. 3164-3169.
[25]
A. Estanqueiro et al., "DLR use for optimization of network design withvery large wind (and VRE) penetration," in 17th Wind Integration Workshop, 2018.
[26]
A. Vieira Turnell et al., "Decentralized Secondary Frequency Control in an Optimized Diesel PV Hybrid System," in 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," in 8th International Workshop on the Integration of Solar Power into Power Systems | Stockholm, Sweden | 16 – 17 October 2018, 2018.
[28]
K. Morozovska and P. Hilber, "Risk analysis of wind farm connection to existing grids using dynamic line rating," in 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," in 2018 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2018 - Proceedings, 2018.
[30]
K. Morozovska and P. Hilber, "Study of the Monitoring Systems for Dynamic Line Rating," in 8th International Conference on Applied Energy, ICAE 2016; Beijing; China; 8 October 2016 through 11 October 2016, 2017, pp. 2557-2562.
[31]
O. Giesecke et al., "Reliability study of two offshore wind farm topologies : Radial and ring connection," in 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.
Non-peer reviewed
Theses
[32]
K. Morozovska, "Dynamic Rating with Applications to Renewable Energy," Doctoral thesis 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," Licentiate thesis Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2018:37, 2018.
Reports
[34]
D. Danylov et al., "An experimental assessment of the intermittent heating and cooling operation effect on power transformer insulation," , TRITA-EECS-RP, 2021.
Other
[35]
O. D. Ariza Rocha et al., "Dynamic rating assists cost-effective expansion of wind farms byutilizing hidden capacity of transformers," (Manuscript).
[36]
K. Morozovska et al., "Including Dynamic Line Rating into the Optimal Planning of Distributed Energy Resources," (Manuscript).
[37]
T. Zarei et al., "Reliability Considerations and Economic Benefits of Dynamic Transformer Rating for Wind Energy Integration," (Manuscript).
[38]
F. Bragone et al., "Unsupervised Learning Analysis of Flow-Induced Birefringence in Nanocellulose: Differentiating Materials and Concentrations," (Manuscript).
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2024-11-21 00:06:51