Improving the efficiency of secondary load frequency control in a power system considering internal tie-line power exchanges
DOI:
https://doi.org/10.15587/1729-4061.2025.336113Keywords:
frequency control, power flow limitation, model predictive control, power system stabilityAbstract
This study's object is the processes of frequency and power adjustment in the power system of Ukraine, which is connected to parallel operation with a neighboring power system.
The current issues related to increasing the efficiency of secondary frequency and power adjustment in the unified power system of Ukraine, which operates in parallel with the European power system (ENTSO-E), have been considered. The factors associated with the introduction of renewable energy sources, the growing role of decentralized generation, and the need to take into account the limitations of internal tie-lines in the power system when distributing the load have been analyzed.
An analysis of approaches to automatic frequency and power adjustment was conducted; the shortcomings of existing solutions were identified, including simplification of the network topology, failure to take into account the technical limitations of power units and reserves, as well as limitations in internal controlled tie-lines.
An improved approach to secondary adjustment based on the method of predictive models has been proposed, which makes it possible to take into account these limitations and improve the efficiency of secondary frequency and power adjustment in the power system. The study of the processes was performed on a dynamic model of the power system with real parameters; the effectiveness of the proposed approach was confirmed by comparison with the conventional proportional-integral control law of the automatic frequency and power control system.
It has been shown that the implementation of the devised approach provides a reduction in frequency recovery time by 8% and prevents overloading of controlled sections, increasing the stability and reliability of the power system under the conditions of modern challenges. The has proposed approach made it possible to increase the efficiency of secondary frequency and power control in the power system
References
- Liu, Y., Qu, Z., Xin, H., Gan, D. (2017). Distributed Real-Time Optimal Power Flow Control in Smart Grid. IEEE Transactions on Power Systems, 32 (5), 3403–3414. https://doi.org/10.1109/tpwrs.2016.2635683
- Ohanu, C. P., Rufai, S. A., Oluchi, U. C. (2024). A comprehensive review of recent developments in smart grid through renewable energy resources integration. Heliyon, 10 (3), e25705. https://doi.org/10.1016/j.heliyon.2024.e25705
- Fan, W., Hu, Z., Veerasamy, V. (2022). PSO-Based Model Predictive Control for Load Frequency Regulation with Wind Turbines. Energies, 15 (21), 8219. https://doi.org/10.3390/en15218219
- Qi, X., Zheng, J., Mei, F. (2022). Model Predictive Control–Based Load-Frequency Regulation of Grid-Forming Inverter–Based Power Systems. Frontiers in Energy Research, 10. https://doi.org/10.3389/fenrg.2022.932788
- Zhao, D., Sun, S., Mohammadzadeh, A., Mosavi, A. (2022). Adaptive Intelligent Model Predictive Control for Microgrid Load Frequency. Sustainability, 14 (18), 11772. https://doi.org/10.3390/su141811772
- Ersdal, A. M., Imsland, L., Uhlen, K. (2016). Model Predictive Load-Frequency Control. IEEE Transactions on Power Systems, 31 (1), 777–785. https://doi.org/10.1109/tpwrs.2015.2412614
- Dangeti, L. satya nagasri, R., M. (2025). Distributed model predictive control strategy for microgrid frequency regulation. Energy Reports, 13, 1158–1170. https://doi.org/10.1016/j.egyr.2024.12.071
- Zheng, Y., Zhou, J., Xu, Y., Zhang, Y., Qian, Z. (2017). A distributed model predictive control based load frequency control scheme for multi-area interconnected power system using discrete-time Laguerre functions. ISA Transactions, 68, 127–140. https://doi.org/10.1016/j.isatra.2017.03.009
- Yang, J., Sun, X., Liao, K., He, Z., Cai, L. (2019). Model predictive control‐based load frequency control for power systems with wind‐turbine generators. IET Renewable Power Generation, 13 (15), 2871–2879. https://doi.org/10.1049/iet-rpg.2018.6179
- Yandulskyi, O., Marchenko, A., Hulyi, V. (2018). Analysis of Efficiency Of Primary Load-Frequency Control of Integrated Power System of Ukraine. 2018 IEEE 3rd International Conference on Intelligent Energy and Power Systems (IEPS), 244–247. https://doi.org/10.1109/ieps.2018.8559567
- Yandulskyy, O. S., Nesterko, A. B. (2015). Power system model identification using synchronized measurements of transient modes. Tekhnichna elektrodynamika, 5, 59–62. Available at: http://nbuv.gov.ua/UJRN/TED_2015_5_12
- Kunya, A. B., Argin, M., Jibril, Y., Shaaban, Y. A. (2020). Improved model predictive load frequency control of interconnected power system with synchronized automatic generation control loops. Beni-Suef University Journal of Basic and Applied Sciences, 9 (1). https://doi.org/10.1186/s43088-020-00072-w
- Stanojev, O., Markovic, U., Aristidou, P., Hug, G., Callaway, D., Vrettos, E. (2022). MPC-Based Fast Frequency Control of Voltage Source Converters in Low-Inertia Power Systems. IEEE Transactions on Power Systems, 37 (4), 3209–3220. https://doi.org/10.1109/tpwrs.2020.2999652
- Liu, J., Yao, Q., Hu, Y. (2019). Model predictive control for load frequency of hybrid power system with wind power and thermal power. Energy, 172, 555–565. https://doi.org/10.1016/j.energy.2019.01.071
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Oleksandr Yandulskiy, Volodymyr Hulyi, Artem Nesterko, Mykhailo Kovalenko, Oleksandr Tymokhin

This work is licensed under a Creative Commons Attribution 4.0 International License.
The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.
A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.





