Keywords
How to Cite
Abstract
Introduction. The paper develops the previously justified power supply scheme of an industrial refrigeration enterprise with a 297 kW grid-connected PV plant by integrating LiFePO₄ battery storage and predictive SCADA/MPC control of the refrigeration load. The proposed approach considers the PV plant, grid, BESS, and cold rooms as a single energy-technological system.
Materials and methods. The study was carried out using simulation modeling. Five scenarios were compared: S0 — grid only, S1 — PV, S2 — PV+BESS, S3 — PV+MPC, and S4 — PV+BESS+MPC. The calculations used a 297 kW PV plant, a 400–650 kWh LiFePO₄ BESS, the refrigeration load profile, BESS state of charge, thermal inertia of cold rooms, and apple storage constraints.
Results. In the integrated S4 scenario, local PV utilization increased to 419.9 MWh/year, while grid import decreased to 968.2 MWh/year. Compared with S1, grid import was reduced by 94.4 MWh/year, giving an estimated annual saving of about 94.4 million UZS at an electricity tariff of 1,000 UZS/kWh. The evening grid peak was also reduced, and PV self-consumption increased.
Conclusion. The combined use of a PV plant, LiFePO₄ BESS, and SCADA/MPC control provides a higher system-level effect than separate storage or load control. For the considered facility, a BESS configuration of approximately 500 kWh / 200 kW is technically reasonable, providing backup for the critical refrigeration load, evening-import smoothing, and a digital control loop for the refrigeration enterprise.
References
[1] Avezova N. R., Rakhimov E. Yu., Frid S. E., et al. Assessment of the technical potential of photovoltaic convertors: The case of the Fergana Valley. Part I: Dynamics of climate data changes in the region // Applied Solar Energy. 2022. Vol. 58. P. 697–707. DOI: 10.3103/S0003701X22600977.
[2] Matchanov N. A., Kulmatov Kh. Kh., Muminov Sh. A., Dekhkonova M. Kh., Shodiev B. T. Power supply of an industrial refrigeration enterprise based on a grid-connected photovoltaic power plant (Fergana Valley). Part 1. Schematic solutions and operational assessment // Alternative Energy. 2026. Vol. 2(23). P. 101–111.
[3] International Energy Agency Photovoltaic Power Systems Programme. A methodology for the analysis of PV self-consumption policies. IEA PVPS, 2016.
[4] FAO. Small-scale postharvest handling practices: A manual for horticultural crops. Food and Agriculture Organization of the United Nations, 2004.
[5] Ghafoor A., Munir A. Worldwide overview of solar thermal cooling technologies // Renewable and Sustainable Energy Reviews. 2015. Vol. 43. P. 763–774. DOI: 10.1016/j.rser.2014.11.073.
[6] Otanicar T., Taylor R. A., Phelan P. E. Prospects for solar cooling: An economic and environmental assessment // Solar Energy. 2012. Vol. 86(5). P. 1287–1299. DOI: 10.1016/j.solener.2012.01.020.
[7] Han Y., Li M., Wang Y., Li G., Ma X., Wang R. Impedance matching control strategy for a solar cooling system directly driven by distributed photovoltaics // Energy. 2019. Vol. 168. P. 953–965. DOI: 10.1016/j.energy.2018.11.160.
[8] Seyednezhad M., Najafi H. Solar-powered thermoelectric-based cooling and heating system for building applications: A parametric study // Energies. 2021. Vol. 14. DOI: 10.3390/en14175573.
[9] Bozorgi M., Tasnim S. H., Mahmud S. Enhancing indoor thermal comfort and sustainability: A solar-driven desiccant cooling and adsorption chiller system with environmental impact assessment // Solar Energy. 2024. Vol. 271. Article 112440.
[10] Belyaev A., Ivanova T. Integration of photovoltaic systems with industrial refrigeration loads: Control strategies and power quality issues // Journal of Renewable and Sustainable Energy. 2022. Vol. 14(6). Article 062302.
[11] Mirzabaev A. M., Shodiev B. T., Kulmatov Kh. Kh. Assessment of economic and ecological effectiveness of solar cooling systems under conditions of Uzbekistan // Informatika va energetika muammolari. 2025. No. 4. P. 57–70.
[12] International Electrotechnical Commission. IEC 61724-1:2017 Photovoltaic system performance — Part 1: Monitoring. IEC, 2017.
[13] IEEE. IEEE Std 1547-2018: Standard for interconnection and interoperability of distributed energy resources with associated electric power systems interfaces. IEEE Standards Association, 2018.
[14] Rybakov I. P., Nikiforov S. A. Energy consumption and management of refrigeration loads at industrial enterprises // Izvestiya vuzov. Elektromekhanics. 2021. Vol. 64(3). P. 42–49.
[15] NASA Langley Research Center. NASA POWER: Hourly API documentation. 2026.
[16] UzHydromet. Climatic data summary 2005–2024. Hydrometeorological Service of Uzbekistan, 2024.
[17] Ahmed N., Patel M. Energy management algorithms for PV integrated industrial microgrids using SCADA systems // Renewable Energy and Power Quality Journal. 2021. Vol. 19(1). P. 185–192.
[18] Lund H., Østergaard P. A., Connolly D., et al. Smart Energy Systems and the transition to 100% renewable energy systems // Energy. 2017. Vol. 137. P. 556–565. DOI: 10.1016/j.energy.2017.05.123.
[19] U.S. Department of Energy. Energy storage grand challenge: Energy storage market report. U.S. DOE, 2020.
[20] National Renewable Energy Laboratory. Understanding solar photovoltaic system performance: An assessment of 75 federal photovoltaic systems. NREL, 2022.
[21] Hafez F. S., Safa-Gamal M., Taufiq-Yap Y. H., Alfiabey M., Seyedmahmoudian M., Stojcevski A., Horan B., Mekhilef S. Energy efficiency in sustainable buildings: A systematic review // Energy Strategy Reviews. 2023. Vol. 45. Article 101013. DOI: 10.1016/j.esr.2022.101013.
[22] Simonetti R., Moretti L., Molinaroli L., Manzolini G. Energetic and economic optimization of the yearly performance of solar-assisted heat pump systems // Energy Conversion and Management. 2020. Vol. 206. Article 112446. DOI: 10.1016/j.enconman.2019.112446.
[23] Salata F., Falasca S., Ciancio V., Curci G., Gignaffini S., de Wilde P. Estimating building cooling energy demand through the Cooling Degree Hours in a changing climate: A modeling study // Sustainable Cities and Society. 2022. Vol. 76. Article 103518. DOI: 10.1016/j.scs.2021.103518.
[24] Tian S., Shao S., Liu B. Investigation on transient energy consumption of cold storages: Modeling and a case study // Energy. 2019. Vol. 180. P. 1–9. DOI: 10.1016/j.energy.2019.04.217.
[25] Parisio A., Rikos E., Glielmo L. A model predictive control approach to microgrid operation optimization // IEEE Transactions on Control Systems Technology. 2014. Vol. 22(5). P. 1813–1827. DOI: 10.1109/TCST.2013.2295737.
[26] Luthander R., Widén J., Nilsson D., Palm J. Photovoltaic self-consumption in buildings: A review // Applied Energy. 2015. Vol. 142. P. 80–94. DOI: 10.1016/j.apenergy.2014.12.028.
[27] Quoilin S., Kavvadias K., Mercier A., Pappone I., Zucker A. Quantifying self-consumption linked to solar home battery systems: Statistical analysis and economic assessment // Applied Energy. 2016. Vol. 182. P. 58–67. DOI: 10.1016/j.apenergy.2016.08.077.
[28] Hannan M. A., Lipu M. S. H., Hussain A., Mohamed A. A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations // Renewable and Sustainable Energy Reviews. 2017. Vol. 78. P. 834–854. DOI: 10.1016/j.rser.2017.05.001.
[29] Schimpe M., Naumann M., Truong N., Hesse H. C., Santhanagopalan S., Saxon A., Jossen A. Energy efficiency evaluation of a stationary lithium-ion battery container storage system via electro-thermal modeling and detailed component analysis // Applied Energy. 2018. Vol. 210. P. 211–229. DOI: 10.1016/j.apenergy.2017.10.129.
[30] Hu X., Li S., Peng H. A comparative study of equivalent circuit models for Li-ion batteries // Journal of Power Sources. 2012. Vol. 198. P. 359–367. DOI: 10.1016/j.jpowsour.2011.10.013.
[31] Barré A., Deguilhem B., Grolleau S., Gérard M., Suard F., Riu D. A review on lithium-ion battery ageing mechanisms and estimations for automotive applications // Journal of Power Sources. 2013. Vol. 241. P. 680–689. DOI: 10.1016/j.jpowsour.2013.05.040.
[32] East A. R., Smale N. J., Trujillo F. J. Potential for energy cost savings by utilising alternative temperature control strategies for controlled atmosphere stored apples // International Journal of Refrigeration. 2013. Vol. 36(3). P. 1109–1117. DOI: 10.1016/j.ijrefrig.2012.10.028.
[33] Leducq D., Vende P. E., Hoang H. M. Demand response in refrigerated warehouses and thermal energy storage // 4th IIR International Conference on Sustainability and the Cold Chain. 2016. DOI: 10.18462/iir.iccc.2016.0038.
[34] Khorsandnejad E., Malzahn R., Oldenburg A.-K., Mittreiter A., Doetsch C. Analysis of flexibility potential of a cold warehouse with different refrigeration compressors // Energies. 2024. Vol. 17(1). Article 85. DOI: 10.3390/en17010085.
[35] Hovgaard T. G., Larsen L. F. S., Jørgensen J. B., Boyd S. Fast nonconvex model predictive control for commercial refrigeration // IFAC Proceedings Volumes. 2012. Vol. 45(17). P. 514–521. DOI: 10.3182/20120823-5-NL-3013.00082.
[36] Oldewurtel F., Parisio A., Jones C. N., Gyalistras D., Gwerder M., Stauch V., Lehmann B., Morari M. Use of model predictive control and weather forecasts for energy efficient building climate control // Energy and Buildings. 2012. Vol. 45. P. 15–27. DOI: 10.1016/j.enbuild.2011.09.022.
[37] Bejarano G., Lemos J. M., Rico-Azagra J., Rubio F. R., Ortega M. G. Energy management of refrigeration systems with thermal energy storage based on non-linear model predictive control // Mathematics. 2022. Vol. 10(17). Article 3167. DOI: 10.3390/math10173167.
[38] Tang R., Wang S. Model predictive control for thermal energy storage and thermal comfort optimization of building demand response in smart grids // Applied Energy. 2019. Vol. 242. P. 873–882. DOI: 10.1016/j.apenergy.2019.03.038.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright (c) 2026 Mirzabayev, A.M., Matchanov, N.A., Kulmatov, X.X., Muminov, S.A., Dekhkonova, M.X., Shodiev, B.T. (Muallif)