A Hybrid Renewable Energy System Management Using an Artificial Intelligence MIMO-Fuzzy Controller
Received: 15 March 2025 | Revised: 22 April 2025 and 9 June 2025 | Accepted: 21 June 2025 | Online: 2 August 2025
Corresponding author: Ilham Aouaci
Abstract
The integration of clean energy sources into standalone power systems requires the selection of appropriate renewable resources based on the local weather conditions, geographic location, and installation costs. Photovoltaic (PV) panels and hydrogen-based systems, particularly those using Solid Oxide Fuel Cells (SOFCs), are often used in a complementary manner. The efficient operation of such hybrid systems necessitates an intelligent energy management capable of optimizing the power flow to the electrical loads and of storing the surplus energy. To achieve a high power quality and reduce the overall system costs, a suitable system architecture and advanced control strategies are essential. In this context, an intelligent supervisory control based on Multi-Input Multi-Output Fuzzy Logic Control (MIMO-FLC) is proposed. This controller addresses key challenges, such as enhancing the energy efficiency, ensuring a smooth production-consumption balance, and maintaining the service continuity and reliability. The proposed MIMO-FLC effectively manages the hybrid energy system by adapting to the changing weather conditions and load demands. The system was modeled and simulated using MATLAB/Simulink. The simulation results demonstrate that the fuzzy logic-based control significantly improves the system performance, ensuring high power quality and efficient energy usage. The controller successfully directs energy either to the load or to the battery storage without power loss or interruptions. This study emphasizes the simulation process and analyzes the evolution of key parameters—such as power, voltage, pressure, and current density—over time to estimate the electrical energy required for a 1 MW output load.
Keywords:
hybrid energy system management, Solid Oxide Fuel Cell (SOFC), PV, energy storage, grid on/off, MIMO-FLCDownloads
References
I. Laib, A. Hamidat, M. Haddadi, N. Ramzan, and A. G. Olabi, "Study and simulation of the energy performances of a grid-connected PV system supplying a residential house in north of Algeria," Energy, vol. 152, pp. 445–454, Jun. 2018. DOI: https://doi.org/10.1016/j.energy.2018.03.157
A. Alazazmeh, A. Ahmed, M. Siddiqui, and M. Asif, "Corrigendum to ‘Real-time data-based performance analysis of a large-scale building applied PV system’ [Energy Rep. 8 (2022) 15408–15420]," Energy Reports, vol. 10, Nov. 2023, Art. no. 2899. DOI: https://doi.org/10.1016/j.egyr.2023.09.083
I. Bendaas, K. Bouchouicha, S. Semaoui, A. Razagui, S. Bouchakour, and S. Boulahchiche, "Performance evaluation of large-scale photovoltaic power plant in Saharan climate of Algeria based on real data," Energy for Sustainable Development, vol. 76, Oct. 2023, Art. no. 101293. DOI: https://doi.org/10.1016/j.esd.2023.101293
M. M. Samy, S. Barakat, and H. S. Ramadan, "A flower pollination optimization algorithm for an off-grid PV-Fuel cell hybrid renewable system," International Journal of Hydrogen Energy, vol. 44, no. 4, pp. 2141–2152, Jan. 2019. DOI: https://doi.org/10.1016/j.ijhydene.2018.05.127
H. Wang, Z. Xie, L. Pu, Z. Ren, Y. Zhang, and Z. Tan, "Energy management strategy of hybrid energy storage based on Pareto optimality," Applied Energy, vol. 327, Dec. 2022, Art. no. 120095. DOI: https://doi.org/10.1016/j.apenergy.2022.120095
F. Saadaoui, K. Mammar, and M. Habbab, "Energy management of a hybrid energy system (PV / PEMFC and lithium-ion battery) based on hydrogen minimization modeled by macroscopic energy representation," International Journal of Hydrogen Energy, vol. 48, no. 53, pp. 20388–20405, Jun. 2023. DOI: https://doi.org/10.1016/j.ijhydene.2022.11.140
J. Luo, S. Gao, X. Wei, and Z. Tian, "Adaptive energy management strategy for high-speed railway hybrid energy storage system based on double-layer fuzzy logic control," International Journal of Electrical Power & Energy Systems, vol. 156, Feb. 2024, Art. no. 109739. DOI: https://doi.org/10.1016/j.ijepes.2023.109739
Z. Yang, F. Zhu, and F. Lin, "Deep-Reinforcement-Learning-Based Energy Management Strategy for Supercapacitor Energy Storage Systems in Urban Rail Transit," IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 2, pp. 1150–1160, Feb. 2021. DOI: https://doi.org/10.1109/TITS.2019.2963785
F. Calise, F. L. Cappiello, L. Cimmino, and M. Vicidomini, “Dynamic simulation modelling of reversible solid oxide fuel cells for energy storage purpose,” Energy, vol. 260, Dec. 2022, Art. no. 124893. DOI: https://doi.org/10.1016/j.energy.2022.124893
A. S. Al-Khayyat, M. J. Hameed, and A. A. Ridha, "Optimized power flow control for PV with hybrid energy storage system HESS in low voltage DC microgrid," e-Prime - Advances in Electrical Engineering, Electronics and Energy, vol. 6, Dec. 2023, Art. no. 100388. DOI: https://doi.org/10.1016/j.prime.2023.100388
L. Yin and D. Liu, "Adaptive multistep model predictive control for tubular grid-connected solid oxide fuel cells," Renewable Energy, vol. 216, Nov. 2023, Art. no. 119062. DOI: https://doi.org/10.1016/j.renene.2023.119062
J. Zhang et al., "Optimal operation of energy storage system in photovoltaic-storage charging station based on intelligent reinforcement learning," Energy and Buildings, vol. 299, Nov. 2023, Art. no. 113570. DOI: https://doi.org/10.1016/j.enbuild.2023.113570
H. Wang, L. Mao, H. Zhang, and Q. Wu, "Multi-prediction of electric load and photovoltaic solar power in grid-connected photovoltaic system using state transition method," Applied Energy, vol. 353, Jan. 2024, Art. no. 122138. DOI: https://doi.org/10.1016/j.apenergy.2023.122138
E. O. Prado, P. C. Bolsi, H. C. Sartori, and J. R. Pinheiro, "Design and management of photovoltaic energy in uninterruptible power supplies," Energy Conversion and Management, vol. 301, Feb. 2024, Art. no. 118038. DOI: https://doi.org/10.1016/j.enconman.2023.118038
X. Zhang, Y. Zhang, C. Zheng, and F. Chen, "Model construction and performance investigation of compound parabolic concentrator based on satellite solar wing photovoltaic arrays," Energy, vol. 285, Dec. 2023, Art. no. 129398. DOI: https://doi.org/10.1016/j.energy.2023.129398
L. Cassayre, B. Guzhov, M. Zielinski, and B. Biscans, "Chemical processes for the recovery of valuable metals from spent nickel metal hydride batteries: A review," Renewable and Sustainable Energy Reviews, vol. 170, Dec. 2022, Art. no. 112983. DOI: https://doi.org/10.1016/j.rser.2022.112983
B. Allaoua, K. Asnoune, and B. Mebarki, "Energy management of PEM fuel cell/ supercapacitor hybrid power sources for an electric vehicle," International Journal of Hydrogen Energy, vol. 42, no. 33, pp. 21158–21166, Aug. 2017. DOI: https://doi.org/10.1016/j.ijhydene.2017.06.209
M. A. Hartani, M. Hamouda, O. Abdelkhalek, and S. Mekhilef, "Sustainable energy assessment of multi-type energy storage system in direct-current-microgrids adopting Mamdani with Sugeno fuzzy logic-based energy management strategy," Journal of Energy Storage, vol. 56, Dec. 2022, Art. no. 106037. DOI: https://doi.org/10.1016/j.est.2022.106037
Z. Kang, Y. Zhao, and D. Kim, "Investigation of enterprise economic management model based on fuzzy logic algorithm," Heliyon, vol. 9, no. 8, Aug. 2023, Art. no. e19016. DOI: https://doi.org/10.1016/j.heliyon.2023.e19016
M. Ali, Y. Haitao, Z. Che, and Z. Din, "Control of Free Piston Stirling Linear Generator system connected with dc/dc converter for energy storage applications based on SVPWM Rectification Method," Energy Reports, vol. 8, pp. 15421–15435, Nov. 2022. DOI: https://doi.org/10.1016/j.egyr.2022.11.095
J. Ingilala and I. Vairavasundaram, "Investigation of high gain DC/DC converter for solar PV applications," e-Prime - Advances in Electrical Engineering, Electronics and Energy, vol. 5, Sep. 2023, Art. no. 100264. DOI: https://doi.org/10.1016/j.prime.2023.100264
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