ORIGINAL PAPER
Framework for managing day-ahead trading and storage scheduling in PV-based prosumer microgrids with islanding capability
1
Department of Modelling of Electrical Power Objects and Systems, Institute of Electrodynamics NASU, Ukraine
2
Management Department, AGH University of Krakow, Poland
3
Department of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics NASU; G.E. Pukhov Institute for Modelling in Energy Engineering of the NAS of Ukraine, Ukraine
4
G.E. Pukhov Institute for Modelling in Energy Engineering of the NAS of Ukraine; Center for Information-Analytical and Technical Support of Nuclear Power Facilities Monitoring of the NAS of Ukraine; Kyiv National Economic University Named After Vadym Hetman, Ukraine
5
Management Department, AGH University of Krakow; Institution of Social-Humanitarian Science, Dnipro University of Technology, Poland
Submission date: 2026-01-14
Final revision date: 2026-01-15
Acceptance date: 2026-01-15
Publication date: 2026-09-25
Corresponding author
Yuliya Pazynich
Management Department, AGH University of Krakow; Institution of Social-Humanitarian Science, Dnipro University of Technology, Krakow, Poland
Management Department, AGH University of Krakow; Institution of Social-Humanitarian Science, Dnipro University of Technology, Krakow, Poland
Polityka Energetyczna – Energy Policy Journal 2026;29(3):151-188
KEYWORDS
TOPICS
ABSTRACT
The integration of photovoltaic (PV) generation and energy storage systems in prosumer microgrids enables active participation in electricity markets. However, efficient management of day-ahead trading and storage scheduling remains challenging, particularly under forecast uncertainties and the need for islanding readiness. This study aims to develop a comprehensive framework for managing day-ahead electricity trading and energy storage scheduling in PV-based prosumer microgrids. The framework seeks to maximize economic profit while ensuring operational reliability and maintaining adequate reserves for potential islanded operation. The proposed approach employs day-ahead optimization based on forecasts of solar generation and critical load demand. These forecasts serve as input data for determining market transactions and optimal storage operation strategies. The framework was evaluated using historical operational and market data to assess its effectiveness in achieving profitability and reliability. Simulation results demonstrate that the framework enables efficient coordination of market participation and energy storage operation, achieving improved economic outcomes and maintaining sufficient energy reserves for islanded operation. The methodology effectively balances trading benefits with the technical constraints of prosumer systems under forecast uncertainty. The proposed management framework enhances the economic and operational performance of PV-based prosumer microgrids. It provides a practical tool for supporting intelligent decision-making in electricity markets and contributes to the development of resilient, self-sufficient energy communities.
CONFLICT OF INTEREST
The Authors have no conflicts of interest to declare.
METADATA IN OTHER LANGUAGES:
Polish
Struktura zarządzania handlem na dzień następny i harmonogramowaniem magazynowania w mikrosieciach prosumenckich opartych na energii fotowoltaicznej z możliwością pracy wyspowej
mikrosieci, dyspozycja ekonomiczna, handel energią elektryczną, zarządzanie handlem na dzień następny, planowanie na dzień następny
Integracja generacji fotowoltaicznej (PV) i systemów magazynowania energii w mikrosieciach prosumenckich umożliwia aktywny udział w rynkach energii elektrycznej. Jednak efektywne zarządzanie handlem na dzień następny i harmonogramowaniem magazynowania pozostaje wyzwaniem, szczególnie w warunkach niepewności prognoz i konieczności gotowości do pracy wyspowej. Niniejsze badanie ma na celu opracowanie kompleksowych ram zarządzania handlem energią elektryczną na dzień następny i harmonogramowaniem magazynowania energii w mikrosieciach prosumenckich opartych na energii fotowoltaicznej. Ramy te dążą do maksymalizacji zysku ekonomicznego przy jednoczesnym zapewnieniu niezawodności operacyjnej i utrzymaniu odpowiednich rezerw na potrzeby potencjalnej pracy wyspowej. Proponowane podejście wykorzystuje optymalizację na dzień następny w oparciu o prognozy generacji słonecznej i krytycznego zapotrzebowania na moc. Prognozy te służą jako dane wejściowe do określania transakcji rynkowych i optymalnych strategii działania magazynowania. Ramy zostały ocenione przy użyciu historycznych danych operacyjnych i rynkowych w celu oceny ich skuteczności w osiąganiu rentowności i niezawodności. Wyniki symulacji pokazują, że ramy umożliwiają efektywną koordynację udziału w rynku i operacji magazynowania energii, pozwalając na osiągnięcie lepszych wyników ekonomicznych i utrzymanie wystarczających rezerw energii na potrzeby pracy wyspowej. Metodologia skutecznie równoważy korzyści handlowe z ograniczeniami technicznymi systemów prosumenckich w warunkach niepewności prognoz. Proponowane ramy zarządzania poprawiają efektywność ekonomiczną i operacyjną mikrosieci prosumenckich opartych na fotowoltaice. Stanowią praktyczne narzędzie wspierające inteligentne podejmowanie decyzji na rynkach energii elektrycznej i przyczyniają się do rozwoju odpornych, samowystarczalnych społeczności energetycznych.
REFERENCES (60)
1.
Ahmed et al. 2021 – Ahmed, M., Mohamed, Y.A.R.I. and El-Hag, A.H. 2021. Two-stage day-ahead and intraday microgrid scheduling for resilience under uncertainties. Electric Power Systems Research 194, https://doi.org/10.1016/j.epsr....
2.
An et al. 2020 – An, J., Lee, M., Yeom, S. and Hong, T. 2020. Determining the Peer-to-Peer electricity trading price and strategy for energy prosumers and consumers within a microgrid. Applied Energy 261, https://doi.org/10.1016/j.apen....
3.
Bashynska et al. 2024 – Bashynska, I., Niekrasova, L., Ivliev, D., Dudek, M., Kosenkov, V. and Yakimets, A. 2024. Justification for Transitioning Equipment to Direct Current for Smart Small Enterprises with Sustainable Solar Power Autonomy. 2024 IEEE 5th KhPI Week on Advanced Technology (KhPIWeek), pp. 1–6, https://doi.org/10.1109/khpiwe....
4.
Beridze et al. 2025 – Beridze, T., Mykhailenk, O., Sinchuk, I., Kotiakova, M., Rogoza, M. and Jamiński, M. 2025. The Multifactorial Approach to Power Quality Analysis in Underground Mining. Inżynieria Mineralna 1(1), https://doi.org/10.29227/im-20....
5.
Beshta et al. 2015a – Beshta, O., Albu, A., Balakhontsev, A. and Fedoreyko, V. 2015. Universal model of the galvanic battery as a tool for calculations of electric vehicles. [In:] Power Engineering, Control and Information Technologies in Geotechnical Systems, pp. 7–11, https://doi.org/10.1201/b18475....
6.
Beshta et al. 2015b – Beshta, O., Fedoreyko, V., Palchyk, A. and Burega, N. 2015. Independent power supply of menage objects based on biosolid oxide fuel systems. Power Engineering, Control and Information Technologies in Geotechnical Systems, pp. 33–39, https://doi.org/10.1201/b18475....
7.
Beshta et al. 2024 – Beshta, O.S., Beshta, O.O., Khudolii, S.S., Khalaimov, T.O. and Fedoreiko, V.S. 2024. Electric vehicle energy consumption taking into account the route topology. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu 2, pp. 104–112, https://doi.org/10.33271/nvngu....
8.
Bhattacharya, S. and Mishra, S. 2016. Coordinated decentralized control for PV-EV based Grid connected Microgrids. 2016 IEEE 6th International Conference on Power Systems (ICPS), pp. 1–6, https://doi.org/10.1109/icpes.....
9.
Blinov et al. 2021 – Blinov, I., Trach, I., Parus, Y., Khomenko, V., Kuchanskyy, V. and Shkarupylo, V. 2021. Evaluation of The Efficiency of The Use of Electricity Storage Systems in The Balancing Group and The Small Distribution System. 2021 IEEE 2nd KhPI Week on Advanced Technology (KhPIWeek), https://doi.org/10.1109/khpiwe....
10.
Blinov et al. 2024 – Blinov, I.V., Parus, Ye.V., Shymaniuk, P.V. and Vorushylo, A.O. 2024. Optimization model of microgrid functioning with solar power plant and energy storage system (Model’ optymizatsiyi funktsionuvannya mikromerezhi z ses ta ustanovkoyu zberihannya enerhiyi). Tekhnichna Elektrodynamika 5, pp. 69–78, https://doi.org/10.15407/techn... (in Ukrainian).
11.
Blinov et al. 2025 – Blinov, I., Radziukynas, V., Shymaniuk, P., Dyczko, A., Stecuła, K., Sychova, V., Miroshnyk, V. and Dychkovskyi, R. 2025. Smart Management of Energy Losses in Distribution Networks Using Deep Neural Networks. Energies 18(12), https://doi.org/10.3390/en1812....
12.
Brecl, K. and Topič, M. 2018. Photovoltaics (PV) System Energy Forecast on the Basis of the Local Weather Forecast: Problems, Uncertainties and Solutions. Energies 11(5), https://doi.org/10.3390/en1105....
13.
Bulińska et al. 2025 – Bulińska, S., Sujak, A. and Pyzalski, M. 2025. Sustainable Management of Photovoltaic Waste Through Recycling and Material Use in the Construction Industry. Materials 18(2), https://doi.org/10.3390/ma1802....
14.
Chen et al. 2022 – Chen, L., Wang, Q., Li, F., Lu, X. and Liu, Q. 2022. Multi-criteria optimization of demand response and energy storage considering cost and reliability. Sustainable Energy, Grids and Networks 29, https://doi.org/10.1016/j.sega....
15.
Denysiuk, S. and Derevianko, D. 2020. Optimisation features of energy processes in energy systems with Distributed Generation. 2020 IEEE 7th International Conference on Energy Smart Systems (ESS), pp. 211–214, https://doi.org/10.1109/ess503....
16.
Diachenko et al. 2025 – Diachenko, G., Laktionov, I., Sala, D., Pyzalski, M., Balakhontsev, O. and Pazynich, Y. 2025. Substantiation of a Rational Model of an Induction Motor in a Predictive Energy-Efficient Control System. Energies 18(17), https://doi.org/10.3390/en1817....
17.
Dąbek et al. 2023 – Dąbek, J., Gaweł, R., Pyzalski, M. and Brylewski, T. (2023). Oxidation and Electrical Property Studies on Ferritic Steels as Potential Interconnects in Electrochemical Devices for Energy Conversion. Crystals 13(6), https://doi.org/10.3390/cryst1....
18.
EC SRD 62913-2-1:2019. Generic smart grid requirements. Part 2-1: Grid related domains [Electronic resource].
19.
Faraji et al. 2020 – Faraji, J., Abazari, A., Babaei, M., Muyeen, S. M. and Benbouzid, M. 2020. Day-Ahead Optimization of Prosumer Considering Battery Depreciation and Weather Prediction for Renewable Energy Sources. Applied Sciences 10(8), https://doi.org/10.3390/app100....
20.
García et al. 2023 – García, R., Ordiano, F. and Giraldo, G. 2023. Simulation of PV-ESS co-optimized microgrid operation with islanding reserve. Solar Energy 254, pp. 67–78, https://doi.org/10.1016/j.sole....
21.
Gbadega et al. 2024 – Gbadega, P. A., Sun, Y. and Abolaji Balogun, O. 2024. Advanced Control Technique for Optimal Power Management of a Prosumer-Centric Residential Microgrid. IEEE Access 12, pp. 163819–163855, https://doi.org/10.1109/access....
22.
Gitelman et al. 2019 – Gitelman, L., Magaril, E., Kozhevnikov, M. and Rada, E.C. 2019. Rational Behavior of an Enterprise in the Energy Market in a Circular Economy. Resources 8, https://doi.org/10.3390/resour....
23.
Gurobi Optimization LLC, Gurobi Optimizer Reference Manual 2025. [Online:] https://docs.gurobi.com/projec... [Accessed: 2025-09-09].
24.
Hennadii et al. 2019 – Hennadii, I., Ihor, B. and Yevhen, P. 2019. Simulation Model of New Electricity Market in Ukraine. 2019 IEEE 6th International Conference on Energy Smart Systems (ESS), pp. 339–342, https://doi.org/10.1109/ess.20....
25.
IEC TS 62898-1:2017/Amd.1:2023 Microgrids — Part 1: Guidelines for microgrid projects planning and specification. Geneva: IEC, 2023. 72 р.
26.
IEC TS 62898-3-2:2024 Microgrids – Part 3 2: Technical requirements – Energy management systems. – International Electrotechnical Commission, 2024. – 94 с.
27.
IEEE 2019. IEEE Guide for Design, Operation, and Maintenance of Battery Energy Storage Systems, Both Stationary and Mobile, and Applications Integrated with Electric Power Systems: IEEE Std 2030.2.1-2019; IEEE: New York, NY, USA, https://doi.org/10.1109/IEEEST....
28.
IEEE 2030.72017 IEEE Standard for the Specification of Microgrid Controllers. – Institute of Electrical and Electronics Engineers, 2017. 78 р.
29.
IEEE Std 2030.9™-2019 IEEE Recommended Practice for the Planning and Design of the Microgrid, 2019. 45 с.
30.
Jani et al. 2023 – Jani, A., Shah, N., Latha, K. and Jani, A.B. 2023. Shared-ESS coordinated day-ahead and real-time trading among microgrids. Renewable Energy 205, pp. 1039–1051, https://doi.org/10.1016/j.rene....
31.
Kolb et al. 2020 – Kolb, A., Pazynich, Y., Mirek, A. and Petinova, O. 2020. Influence of voltage reserve on the parameters of parallel power active compensators in mining. E3S Web of Conferences 201, https://doi.org/10.1051/e3scon....
32.
Kumar et al. 2023 – Kumar, S., Singh, M., Sahoo, N.C. and Kumar, R. 2023. Degradation-aware scheduling of battery energy storage systems in microgrid operations. Journal of Energy Storage 66, https://doi.org/10.1016/j.est.....
33.
Kyrylenko et al. 2025 – Kyrylenko, O., Denysiuk, S., Bielokha, H., Dyczko, A., Stecuła, B. and Pazynich, Y. 2025. Smart Monitoring and Management of Local Electricity Systems with Renewable Energy Sources. Energies 18(16), https://doi.org/10.3390/en1816....
34.
Lapshyn, Y. 2025. Feasibility of Fine Classification in Processing Watered Coal Sludge from Storage: A Case Study of the Dnipro Coke Chemical Plant. Acta Montanistica Slovaca 100, https://doi.org/10.46544/ams.v....
35.
Lewicka, D. 2020. Employee institutional trust as an antecedent of diverse dimensions of organisational commitment. Argumenta Oeconomica 2019(1), pp. 321–340, https://doi.org/10.15611/aoe.2....
36.
Liu et al. 2017 – Liu, G., Liu, J. and Guo, Q. 2017. Optimal day-ahead scheduling of islanded microgrid considering risk-based reserve decision. IEEE Transactions on Smart Grid 8(1), pp. 164–173, https://doi.org/10.1109/TSG.20....
37.
Liu et al. 2017 – Liu, G., Starke, M., Xiao, B. and Tomsovic, K. 2017. Robust optimisation‐based microgrid scheduling with islanding constraints. IET Generation, Transmission and Distribution 11(7), pp. 1820–1828, https://doi.org/10.1049/iet-gt....
38.
Market Operator. Official website of the State Enterprise «Market Operator». [Online:] https://www.oree.com.ua [Accessed: 2025-09-09].
39.
NERC Resolution № 2200 from 19.12.2024. [Online:] https://zakon.rada.gov.ua/rada... [Accessed: 2025-09-09].
40.
NERC Resolution № 2209 from 19.12.2024. [Online:] https://zakon.rada.gov.ua/rada... [Accessed: 2025-09-09].
41.
NERC Resolution № 2103, from 10.12.2024. [Online:] https://www.nerc.gov.ua/acts/p... [Accessed: 2025-09-09].
42.
Nikolsky et al. 2022 – Nikolsky, V., Dychkovskyi, R., Cabana, E. C., Howaniec, N., Jura, B., Widera, K. and Smoliński, A. 2022. The Hydrodynamics of Translational−Rotational Motion of Incompressible Gas Flow within the Working Space of a Vortex Heat Generator. Energies 15(4), https://doi.org/10.3390/en1504....
43.
Nikolsky et al. 2022 – Nikolsky, V., Dychkovskyi, R., Lobodenko, A., Ivanova, H., Cabana E.C. and Shavarskyi, Ja. 2022. Thermodynamics of the developing contact heating of a process liquid. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu 2, pp. 48–53, https://doi.org/10.33271/nvngu....
44.
Parus, Ye.V. and 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 2025(5), pp. 56–69, https://doi.org/10.15407/techn....
45.
Parus et al. 2025 – Parus, E., Blinov, I., Rybina, O., Olefir, D., Sala, D., Tora, B. and Dychkovskyi, R. 2025. Improving the Electricity Market Participation Management of Hydropower Plants in Ukraine. Inżynieria Mineralna 2025 1(1), pp. 195–204, https://doi.org/10.29227/im-20....
46.
Pavlychenko et al. 2025 – Pavlychenko, A., Sala, D., Pyzalski, M., Dybrin, S., Antoniuk, O. and Dychkovskyi, R. 2025. Utilizing Fuel and Energy Sector Waste as Thermal Insulation Materials for Technical Buildings. Energies 18(9), https://doi.org/10.3390/en1809....
47.
Pazynich et al. 2024 – Pazynich, Y., Kolb, A., Korcyl, A., Buketov, V. and Petinova, O. 2024. Mathematical model and characteristics of dynamic modes for managing the asynchronous motors at voltage asymmetry. Polityka Energetyczna – Energy Policy Journal 27(4), pp. 39–58, https://doi.org/10.33223/epj/1....
48.
Pivnyak et al. 2025 – Pivnyak, G., Stepanenko, Y., Stecuła, K., Kyrychenko, M., Lysenko, O. and Dychkovskyi, R. 2025. Management of Zero-Sequence Parameters for Earth Faults on the Power Receiver’s Side in IT-Type Networks. Energies 18(24), https://doi.org/10.3390/en1824....
49.
Polyanska et al. 2022 – Polyanska, A., Savchuk, S., Dudek, M., Sala, D., Pazynich, Y. and Cicho, D. 2022. Impact of digital maturity on sustainable development effects in energy sector in the condition of Industry 4.0. Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu 6, pp. 97–103, https://doi.org/10.33271/nvngu....
50.
Polyanska et al. 2024 – Polyanska, A., Pazynich, Y., Petinova, O., Nesterova, O., Mykytiuk, N. and Bodnar, G. 2024. Formation of a Culture of Frugal Energy Consumption in the Context of Social Security. The Journal of the International Committee for the History of Technology 29(2), pp. 60–87, https://doi.org/10.11590/icon.....
51.
Procedure for the sale and accounting of electricity generated by active consumers, and payments for it. NERC Resolution № 2651 of 29.12.2023. [Online:] https://zakon.rada.gov.ua/rada... [Accessed: 2025-07-04] (in Ukrainian).
52.
Pyzalski et al. 2025 – Pyzalski, M., Juszczyk, M., Durczak, K., Sala, D., Duda, J., Dudek, M. and Ustinovičius, L. 2025. Cement Carbonation Under Fermentation Conditions as a Tool for CO2 Emission Management – Technological, Environmental and Economic Analysis. Energies 18(17), https://doi.org/10.3390/en1817....
53.
Rules of the market. NERC Resolution № 307 from 14.03.2018. [Online:] https://zakon.rada.gov.ua/laws... [Accessed: 2025-06-20] (in Ukrainian).
54.
Seheda et al. 2024 – Seheda, M.S., Beshta, O.S., Gogolyuk, P.F., Blyznak, Yu.V., Dychkovskyi, R.D. and Smoliński, A. 2024. Mathematical model for the management of the wave processes in three-winding transformers with consideration of the main magnetic flux in mining industry. Journal of Sustainable Mining 23(1), pp. 20–39, https://doi.org/10.46873/2300-....
55.
Shcherba et al. 2025a – Shcherba, A., Podoltsev, O., Kucheriava, І., Hutorova, M., Petryshyn, L. and Pazynich, Y. 2025. Computer simulation and management of partial discharges in XLPE insulation of high-voltage power cable. Polityka Energetyczna – Energy Policy Journal 28(3), pp. 5–26, https://doi.org/10.33223/epj/2....
56.
Shcherba et al. 2025b – Shcherba, A., Vinnychenko, D., Suprunovska, N., Roziskulov, S., Dyczko, A. and Dychkovskyi, R. 2025. Management of Mobile Resonant Electrical Systems for High-Voltage Generation in Non-Destructive Diagnostics of Power Equipment Insulation. Preprints.org, https://doi.org/10.20944/prepr....
57.
Silva et al. 2020 – Silva, V.A., Aoki, A.R. and Lambert-Torres, G. 2020. Optimal Day-Ahead Scheduling of Microgrids with Battery Energy Storage System. Energies 13(19), https://doi.org/10.3390/en1319....
58.
Vladyko et al. 2025 – Vladyko, O., Maltsev, D., Gliwiński, Ł., Dychkovskyi, R., Stecuła, K. and Dyczko, A. 2025. Enhancing Mining Enterprise Energy Resource Extraction Efficiency Through Technology Synthesis and Performance Indicator Development. Energies 18(7), https://doi.org/10.3390/en1807....
59.
Woźniak et al. 2024 – Woźniak, G., Bryś, W., Dychkovskyi, R., Dyczko, A., Nowak, T., Piekarska-Stachowiak, A., Trząski, L., Molenda, T. and Hutniczak, A. 2024. Modelling ecosystem services – a tool for assessing novel ecosystems functioning in the urban-industrial landscape. Journal of Water and Land Development, pp. 168–168, https://doi.org/10.24425/jwld.....
60.
Yang et al. 2018 – Yang, X., Li, X., Wu, X. and Sun, C. 2018. Data-driven robust day-ahead scheduling of microgrid under uncertainty. Energy 151, pp. 596–608, https://doi.org/10.1016/j.ener....
Share
RELATED ARTICLE
| eISSN: | 2720-569X |
| ISSN: | 1429-6675 |
© 2006-2026 Journal hosting platform by Bentus
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
