Construction of a model for optimal scheduling of energy storage systems in the day-ahead market considering market strategies and technical constraints

Authors

DOI:

https://doi.org/10.15587/1729-4061.2026.355330

Keywords:

energy storage systems, price arbitrage, economic dispatch, day-ahead market

Abstract

This study investigates the process of optimal planning of energy storage system operating schedules in the day-ahead market. The task addressed is to prevent unprofitable operation of energy storage systems.

A comprehensive mathematical model of daily planning of energy storage operation modes has been built, which takes into account technological efficiency, hardware wear processes, as well as asymmetry of market payments. This forms an adaptive filter with cutting off cycles of economically inefficient arbitrage. The approach is based on separation of the vector of control variables into two independent charging and discharging flows. This has made it possible to take into account the asymmetry of tariffs and the structure of losses in a differentiated manner.

The study on the sensitivity of the model revealed the existence of areas of adaptive regulation and parametric insensitivity to fluctuations in price signals. In the area of parametric insensitivity, the model forms a stable cost-effective solution regardless of price fluctuations. In the area of adaptive regulation, the model changes the volumes of a separate operating cycle depending on a change in the market price spread. It has been established that ignoring the accompanying payments for the area of adaptive regulation leads to an overestimation of income by 35.6 percent and the formation of unprofitable operations. Under conditions of low market price spread, the deviation in the financial result reaches 91.6 percent; however, the parametric insensitivity of the model guarantees profitable operation.

The scope of model's practical implementation is decision support systems for operators of energy storage systems. The conditions of use assume the presence of deterministic forecasts of market price signals for the calculated operating day. Implementing the model contributes to the extension of the life cycle and increase in the operational profitability of energy storage systems

Author Biographies

Oleksandr Havva, G.E. Pukhov Institute for Modelling in Energy Engineering of the National Academy of Sciences of Ukraine

PhD Student

Laboratory of Mathematical Modelling of Energy Markets

Yevgene Parus, Institute of Electrodynamics of the National Academy of Sciences of Ukraine

Department of Modelling of Electrical Power Objects and Systems

Ihor Blinov, Institute of Electrodynamics of the National Academy of Sciences of Ukraine

Doctor of Technical Sciences

Department of Modelling of Electrical Power Objects and Systems

Volodymyr Evdokimov, G.E. Pukhov Institute for Modelling in Energy Engineering of the National Academy of Sciences of Ukraine

Doctor of Technical Sciences

Laboratory of Mathematical Modelling of Energy Markets

References

  1. Kyrylenko, O., Denysiuk, S., Bielokha, H., Dyczko, A., Stecuła, B., Pazynich, Y. (2025). Smart Monitoring and Management of Local Electricity Systems with Renewable Energy Sources. Energies, 18 (16), 4434. https://doi.org/10.3390/en18164434
  2. Faia, R., Lezama, F., Soares, J., Pinto, T., Vale, Z. (2024). Local electricity markets: A review on benefits, barriers, current trends and future perspectives. Renewable and Sustainable Energy Reviews, 190, 114006. https://doi.org/10.1016/j.rser.2023.114006
  3. Parus, E., Blinov, I., Rybina, O., Olefir, D., Sala, D., Tora, B., Dychkovskyi, R. (2025). Improving the Electricity Market Participation Management of Hydropower Plants in Ukraine. Inżynieria Mineralna, 1 (1). https://doi.org/10.29227/im-2025-01-26
  4. Blinov, I., Zaitsev, I., Bajaj, M., Miroshnyk, V., Sychova, V., Shymaniuk, P., Blazek, V., Prokop, L. (2025). Advanced long short-term memory-based forecasting of electricity imbalances in the Ukrainian power system: Enhancing accuracy and stability with comparative model analysis. Energy Exploration & Exploitation. https://doi.org/10.1177/01445987251360272
  5. Hannan, M. A., Faisal, M., Ker, P. J., Mun, L. H., Parvin, K., Mahlia, T. M. I., Blaabjerg, F. (2018). A Review of Internet of Energy Based Building Energy Management Systems: Issues and Recommendations. IEEE Access, 6, 38997–39014. https://doi.org/10.1109/access.2018.2852811
  6. Krishnamurthy, D., Uckun, C., Zhou, Z., Thimmapuram, P. R., Botterud, A. (2018). Energy Storage Arbitrage Under Day-Ahead and Real-Time Price Uncertainty. IEEE Transactions on Power Systems, 33 (1), 84–93. https://doi.org/10.1109/tpwrs.2017.2685347
  7. Zachmann, G., Meissner, F., Riepin, I. (2025). Mitigating Ukraine’s looming electricity crisis. Energy Strategy Reviews, 59, 101724. https://doi.org/10.1016/j.esr.2025.101724
  8. Metz, D., Saraiva, J. T. (2018). Use of battery storage systems for price arbitrage operations in the 15- and 60-min German intraday markets. Electric Power Systems Research, 160, 27–36. https://doi.org/10.1016/j.epsr.2018.01.020
  9. Xu, B., Zhao, J., Zheng, T., Litvinov, E., Kirschen, D. S. (2018). Factoring the Cycle Aging Cost of Batteries Participating in Electricity Markets. IEEE Transactions on Power Systems, 33 (2), 2248–2259. https://doi.org/10.1109/tpwrs.2017.2733339
  10. Blinov, I. V., Parus, Ye. V., Shymaniuk, P. V., Vorushylo, A. O. (2024). Optimization model of microgrid functioning with solar power plant and energy storage system. Tekhnichna Elektrodynamika, 5, 69–78. https://doi.org/10.15407/techned2024.05.069
  11. He, G., Chen, Q., Kang, C., Pinson, P., Xia, Q. (2016). Optimal Bidding Strategy of Battery Storage in Power Markets Considering Performance-Based Regulation and Battery Cycle Life. IEEE Transactions on Smart Grid, 7 (5), 2359–2367. https://doi.org/10.1109/tsg.2015.2424314
  12. Vetter, J., Novák, P., Wagner, M. R., Veit, C., Möller, K.-C., Besenhard, J. O. et al. (2005). Ageing mechanisms in lithium-ion batteries. Journal of Power Sources, 147 (1-2), 269–281. https://doi.org/10.1016/j.jpowsour.2005.01.006
  13. Preto, M., Lucas, A., Benedicto, P. (2024). Hybrid Energy Storage System Dispatch Optimization for Cost and Environmental Impact Analysis. Energies, 17 (12), 2987. https://doi.org/10.3390/en17122987
  14. Christen, T. (2018). Efficiency and Power in Energy Conversion and Storage. CRC Press. https://doi.org/10.1201/9780429454288
  15. Chazarra, M., García-González, J., Pérez-Díaz, J. I., Arteseros, M. (2016). Stochastic optimization model for the weekly scheduling of a hydropower system in day-ahead and secondary regulation reserve markets. Electric Power Systems Research, 130, 67–77. https://doi.org/10.1016/j.epsr.2015.08.014
  16. Blinov, I., Radziukynas, V., Shymaniuk, P., Dyczko, A., Stecuła, K., Sychova, V. et al. (2025). Smart Management of Energy Losses in Distribution Networks Using Deep Neural Networks. Energies, 18 (12), 3156. https://doi.org/10.3390/en18123156
  17. Bradbury, K., Pratson, L., Patiño-Echeverri, D. (2014). Economic viability of energy storage systems based on price arbitrage potential in real-time U.S. electricity markets. Applied Energy, 114, 512–519. https://doi.org/10.1016/j.apenergy.2013.10.010
  18. Migliari, L., Cocco, D., Petrollese, M. (2025). Levelized Cost of Storage (LCOS) of Battery Energy Storage Systems (BESS) Deployed for Photovoltaic Curtailment Mitigation. Energies, 18 (14), 3602. https://doi.org/10.3390/en18143602
  19. Boyd, S., Vandenberghe, L. (2004). Convex Optimization. Cambridge: Cambridge University Press. https://doi.org/10.1017/cbo9780511804441
  20. Parus, Ye. V., Blinov, I. V. (2025). Optimization of the use of available energy resources of the microgrid under the condition of supporting readiness for isolated mode. Tekhnichna Elektrodynamika, 5, 56–69. https://doi.org/10.15407/techned2025.05.056
Construction of a model for optimal scheduling of energy storage systems in the day-ahead market considering market strategies and technical constraints

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Published

2026-04-30

How to Cite

Havva, O., Parus, Y., Blinov, I., & Evdokimov, V. (2026). Construction of a model for optimal scheduling of energy storage systems in the day-ahead market considering market strategies and technical constraints. Eastern-European Journal of Enterprise Technologies, 2(2 (140), 94–101. https://doi.org/10.15587/1729-4061.2026.355330

Issue

Vol. 2 No. 2 (140) (2026): Information technology. Industry control systems

Section

Industry control systems

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Copyright (c) 2026 Oleksandr Havva, Yevgene Parus, Ihor Blinov, Volodymyr Evdokimov

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