Energy management technique of hybrid energy storage system-based DC microgrid
Year 2025,
Volume: 9 Issue: 1, 36 - 51, 31.03.2025
Mohammed Abdulelah Albasheri
,
Ouahid Bouchhida
,
Youcef Soufı
,
Abderrezzak Cherifi
,
Mujammal Ahmed Hasan Mujammal
,
Abdelhafidh Moualdia
Abstract
The generation of variable energy from photovoltaic (PV) is significantly affected by unpredictable fluctuations due to weather changes. Additionally, the variability in load demand is a critical consideration for microgrid. Consequently, the implementation of an energy storage system is essential to address these challenges. This study presents a novel energy management technique (EMT) for hybrid energy storage systems (HESS). The innovative approach incorporates a low-pass filter (LPF) to optimize power distribution between batteries and supercapacitors (SC), thereby enhancing system stability and prolonging battery life. The proposed LPF-based EMT facilitates optimal power allocation, improves system stability by effectively filtering high-frequency power fluctuations, and extends battery life through reduced stress and optimized charge-discharge cycles. It developed a comprehensive system model to enable accurate simulation and analysis, supported by rigorous experimental validation that demonstrates the effectiveness of our method. This approach successfully redirects high-frequency power demands to the SC, stabilizing the DC link voltage. Comprehensive simulations indicate the system's capability, revealing quantitative improvements in battery performance and efficiency across various LPF time constants τ, representing a significant advancement in renewable energy control. The simulation results confirm that the proposed architecture and system representation achieve optimal DC link voltage stability. Furthermore, increasing the τ reduces the state of charge (SOC) of the battery, contributing to an overall increase in battery lifespan.
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Year 2025,
Volume: 9 Issue: 1, 36 - 51, 31.03.2025
Mohammed Abdulelah Albasheri
,
Ouahid Bouchhida
,
Youcef Soufı
,
Abderrezzak Cherifi
,
Mujammal Ahmed Hasan Mujammal
,
Abdelhafidh Moualdia
References
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- [2] Rezk H, Nassef AM, Abdelkareem MA, Alami AH, Fathy A. Comparison among various energy management strategies for reducing hydrogen consumption in a hybrid fuel cell/supercapacitor/battery system. Int J Hydrogen Energy. 2021 Jan;46(8):6110-26. doi: 10.1016/j.ijhydene.2019.11.195.
- [3] Jing W, Lai CH, Wong WSH, Wong MLD. A comprehensive study of battery-supercapacitor hybrid energy storage system for standalone PV power system in rural electrification. Appl Energy. 2018 Aug;224:340-56. doi: 10.1016/j.apenergy.2018.04.106.
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- [19] Zemirline N, Kabeche N, Moulahoum S. Artificial neural network controller for grid current quality improvement in solid-state transformers. J Power Electron. 2024 May;24(5):799-809. doi: 10.1007/s43236-023-00761-6.
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- [22] Yi Z, Dong W, Etemadi AH. A Unified Control and Power Management Scheme for PV-Battery-Based Hybrid Microgrids for Both Grid-Connected and Islanded Modes. IEEE Trans Smart Grid. 2018 Nov;9(6):5975-85. doi: 10.1109/TSG.2017.2700332.
- [23] Albasheri MA, Bouchhida O, Soufi Y, Cherifi A. Enhanced Vector Control of Induction Motor by Fuzzy Logic Controller. In: 2024 2nd International Conference on Electrical Engineering and Automatic Control (ICEEAC); 2024 May. p. 1-5. doi: 10.1109/ICEEAC61226.2024.10576217.
- [24] Qi W, Li Y, Li H, Wayne SW, Lin X. The development and numerical verification of a compromised real time optimal control algorithm for hybrid electric vehicle. J Power Sources. 2019 Dec;443:227272. doi: 10.1016/j.jpowsour.2019.227272.
- [25] Ghadbane HE, Barkat S, Houari A, Djerioui A, Abdelhak H, Mesbahi T. A Load Following Energy Management Strategy for a Battery-Supercapacitor Hybrid Power System Implemented with a PIL Co-Simulation Approach. Smart Grids Energy. 2024 Jul;9(2):32. doi: 10.1007/s40866-024-00214-4.
- [26] Dao HV, et al. Optimization-Based Fuzzy Energy Management Strategy for PEM Fuel Cell/Battery/Supercapacitor Hybrid Construction Excavator. Int J Precis Eng Manuf Green Tech. 2021 Jul;8(4):1267-85. doi: 10.1007/s40684-020-00262-y.
- [27] Zemirline N, Kabeche N, Moulahoum S. Grid current quality improvement for solid state transformer with an improved current controller. Electr Power Syst Res. 2024 Nov;236:110921. doi: 10.1016/j.epsr.2024.110921.
- [28] Ma Z, et al. Optimal SOC Control and Rule-Based Energy Management Strategy for Fuel-Cell-Based Hybrid Vessel including Batteries and Supercapacitors. J Mar Sci Eng. 2023 Feb;11(2):398. doi: 10.3390/jmse11020398.
- [29] Atif. Fuzzy logic controller for solar power smoothing based on controlled battery energy storage and varying low pass filter. IET Renew Power Gener. 2020. doi: 10.1049/iet-rpg.2020.0459.
- [30] Ramos GA, Costa-Castelló R. Energy Management Strategies for Hybrid Energy Storage Systems Based on Filter Control: Analysis and Comparison. Electronics. 2022 Jan;11(10):1631. doi: 10.3390/electronics11101631.
- [31] Cabrane Z, Ouassaid M, Maaroufi M. Analysis and evaluation of battery-supercapacitor hybrid energy storage system for photovoltaic installation. Int J Hydrogen Energy. 2016 Dec;41(45):20897-907. doi: 10.1016/j.ijhydene.2016.06.141.
- [32] Cabrane Z, Kim J, Yoo K, Ouassaid M. HESS-based photovoltaic/batteries/supercapacitors: Energy management strategy and DC bus voltage stabilization. Sol Energy. 2021 Mar;216:551-63. doi: 10.1016/j.solener.2021.01.048.
- [33] Li H, Kang J, Li C. Energy Management Strategy Based on Reinforcement Learning and Frequency Decoupling for Fuel Cell Hybrid Powertrain. Energies. 2024 Jan;17(8):1929. doi: 10.3390/en17081929.
- [34] Tao F, Zhu L, Fu Z, Si P, Sun L. Frequency Decoupling-Based Energy Management Strategy for Fuel Cell/Battery/Ultracapacitor Hybrid Vehicle Using Fuzzy Control Method. IEEE Access. 2020;8:166491-502. doi: 10.1109/ACCESS.2020.3023470.
- [35] Worku MY, Hassan MA, Abido MA. Real Time-Based under Frequency Control and Energy Management of Microgrids. Electronics. 2020 Sep;9(9):1487. doi: 10.3390/electronics9091487.
- [36] Mujammal MAH, Moualdia A, Boulkhrachef S, Wira P, Boudana D, Albasheri MA. Advancing wind energy conversion: smart maximum power point based on M5-Pruned algorithm for enhanced wind energy production. Prod Eng Res Devel. 2024 Oct. doi: 10.1007/s11740-024-01315-w.
- [37] Mujammal MAH, Moualdia A, Boulkhrachef S, Boudana D, Wira P, Albasheri MA. Next-Generation MPPT: neural network-driven optimization for superior solar performance. Stud Eng Exact Sci. 2024 Sep;5(2):e7338. doi: 10.54021/seesv5n2-150.
- [38] Mujammal MAH, Moualdia A, Bouchhida O, Albasheri MA. Upgrade Perturbation and Observation of MPPT Strategy via Fuzzy Logic Controller. In: 2023 2nd International Conference on Electronics, Energy and Measurement (IC2EM); 2023 Nov. p. 1-7. doi: 10.1109/IC2EM59347.2023.10419670.
- [39] Albasheri MA, Bouchhida O, Soufi Y, Moualdia A, Mujammal M. Control and Power Management of DC Microgrid Based Wind/Battery/Supercapacitor. In: 2022 IEEE 2nd International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA); 2022 May. p. 680-5. doi: 10.1109/MI-STA54861.2022.9837665.
- [40] Truong HVA, et al. Mapping Fuzzy Energy Management Strategy for PEM Fuel Cell–Battery–Supercapacitor Hybrid Excavator. Energies. 2020 Jan;13(13):3387. doi: 10.3390/en13133387.
- [41] Abdulelah AM, Ouahid B, Youcef S, Abderrezzak C, Abdelhafidh M, Ahmed M. Improve Lifespan of Battery Energy Storage in Remote Area Power System. In: 2023 2nd International Conference on Electronics, Energy and Measurement (IC2EM); 2023 Nov. p. 1-6. doi: 10.1109/IC2EM59347.2023.10419419.
- [42] Cau G, Cocco D, Petrollese M, Kær SK, Milan C. Energy management strategy based on short-term generation scheduling for a renewable microgrid using a hydrogen storage system. Energy Convers Manag. 2014 Nov;87:820-31. doi: 10.1016/j.enconman.2014.07.078.
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