A Hybrid Energy Management System for Reliable and Sustainable Microgrid Performance
Received: 7 May 2025 | Revised: 18 May 2025 and 1 June 2025 | Accepted: 5 June 2025 | Online: 2 August 2025
Corresponding author: Adi Soeprijanto
Abstract
This study develops a hybrid Energy Management System (EMS) that includes the primary grid power, a 10 kVA diesel generator, a 40 kW solar system, a 30 kW wind turbine, and a 66.6 kWh battery for optimal utilization of renewable energy and minimal utilization of fossil fuel. The introduced approach employs a fuzzy logic-based control technique, which is particularly proposed to negate the uncertainties, nonlinearity, and fluctuation characteristics in the renewable energy generation sources. Dynamic switching logic is created to tune the system response according to the operating modes, off-grid or on-grid, to maintain stability and performance under different conditions. The system is modeled and simulated in the MATLAB/Simulink environment. Three cases are simulated: static off-grid operation at a constant 50 kW load, static on-grid operation at a 200-kW load, and dynamic variations in solar irradiance between 0 and 1,000 W/m² and wind speed between 0 and 12 m/s. The results demonstrate the system's capacity to undergo seamless transitions between energy sources, ensure a continuous power supply, achieve more than 90% energy efficiency, and achieve an average renewable energy contribution of 65% for dynamic loads. The transition from off-grid to on-grid mode occurs within a period of 1 s without imposing a great load disturbance. The battery shows adaptive charging and discharging behavior for adapting to environmental changes in support of system robustness. The current study confirms the effectiveness of fuzzy logic as an intelligent and adaptive control technology for hybrid microgrid EMS, and it serves as a valuable reference for the application of sustainable energy in rural and remote areas.
Keywords:
controller, hybrid system, management energy, microgrid, optimizationDownloads
References
R. Delfianti, A. Soeprijanto, A. Priyadi, A. L. S. Budi, and I. Abadi, "Energy Management Efficiency and Stability Using Passive Filter in Standalone Photovoltaic Sudden Cloud Condition," in 3rd International Seminar on Research of Information Technology and Intelligent Systems, Yogyakarta, Indonesia, Sep. 2020, pp. 716–720. DOI: https://doi.org/10.1109/ISRITI51436.2020.9315434
Md. F. Ali, Md. R. I. Sheikh, R. Akter, K. M. N. Islam, and A. H. M. I. Ferdous, "Grid-connected hybrid microgrids with PV/wind/battery: Sustainable energy solutions for rural education in Bangladesh," Results in Engineering, vol. 25, Mar. 2025, Art. no. 103774. DOI: https://doi.org/10.1016/j.rineng.2024.103774
S. Almazrouei, A. Hamid, and A. Mehiri, "Energy Management for Large-Scale Grid Connected PV - Batteries System," in 2017 International Renewable and Sustainable Energy Conference, Tangier, Morocco, Sep. 2017, pp. 1–5. DOI: https://doi.org/10.1109/IRSEC.2017.8477260
K. Widarsono, A. Soeprijanto, and R. S. Wibowo, "Improved Whale Optimization Algorithm for Dynamic Optimal Power Flow with Renewable Energy Penetration," Engineering, Technology & Applied Science Research, vol. 15, no. 1, pp. 20379–20387. DOI: https://doi.org/10.48084/etasr.9662
E. Rovianto, R. Delfianti, B. W. Lenggana, and C. Harsito, "Dynamic Optimal Power Flow on Microgrid Incorporating Battery Energy Storage Considering Operational and Maintenance Cost," in Proceedings of the 9th International Conference and Exhibition on Sustainable Energy and Advanced Materials, Singapore, Singapore, Jun. 2024, pp. 265–270. DOI: https://doi.org/10.1007/978-981-97-0106-3_44
R. Delfianti, O. Penangsang, A. Soeprijanto, N. H. Rohiem, N. P. U. Putra, and T. Suheta, "Application of Particle Swarm Optimization Algorithm for Scheduling Of Capacitor Bank Switching To Improve Voltage," in 2021 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology, Amman, Jordan, Aug. 2021, pp. 245–249. DOI: https://doi.org/10.1109/JEEIT53412.2021.9634125
S. Ando, T. Gomi, A. Ishikawa, and S. Iwamoto, "System voltage control with PV output prediction considering PV output fluctuation," in 2016 IEEE Region 10 Conference, Singapore, Singapore, Aug. 2016, pp. 3324–3327. DOI: https://doi.org/10.1109/TENCON.2016.7848667
M. Abdillah et al., "Enhancement of frequency transient response using fuzzy-PID controller considering high penetration of doubly fed induction generators," Bulletin of Electrical Engineering and Informatics, vol. 13, no. 4, pp. 2260–2268, Aug. 2024. DOI: https://doi.org/10.11591/eei.v13i4.6481
R. Delfianti, B. Mustaqim, F. Nusyura, A. Priyadi, I. Abadi, and A. Soeprijanto, "Implementation design of energy trading monitoring application for blockchain technology-based wheeling cases," International Journal of Electrical and Computer Engineering, vol. 13, no. 3, pp. 2931–2941, Jun. 2023. DOI: https://doi.org/10.11591/ijece.v13i3.pp2931-2941
R. Delfianti, B. Mustaqim, and Y. Afif, "Standalone Photovoltaic Power Stabilizer Using Double Series Connected Converter in Sudden Cloud Condition," International Journal of Integrated Engineering, vol. 15, no. 4, pp. 281–291, Aug. 2023. DOI: https://doi.org/10.30880/ijie.2023.15.04.024
R. Umar, Sunardi, and Y. B. Fitriana, "Taxonomy of Fuzzy Multi-Attribute Decision Making Systems in Terms of Model, Inventor and Data Type," Engineering, Technology & Applied Science Research, vol. 8, no. 1, pp. 2568–2571, Feb. 2018. DOI: https://doi.org/10.48084/etasr.1747
F. Ullah et al., "A comprehensive review of wind power integration and energy storage technologies for modern grid frequency regulation," Heliyon, vol. 10, no. 9, May 2024, Art. no. e30466. DOI: https://doi.org/10.1016/j.heliyon.2024.e30466
K. binti Hanifulkhair, A. Priyadi, V. Lystianingrum, and R. Delfianti, "One Day Ahead Prediction of PV Power Plant for Energy Management System Using Neural Network," in 2020 International Seminar on Intelligent Technology and Its Applications (ISITIA), Surabaya, Indonesia, Jul. 2020, pp. 107–112. DOI: https://doi.org/10.1109/ISITIA49792.2020.9163783
S. Algarni, V. Tirth, T. Alqahtani, S. Alshehery, and P. Kshirsagar, "Contribution of renewable energy sources to the environmental impacts and economic benefits for sustainable development," Sustainable Energy Technologies and Assessments, vol. 56, Mar. 2023, Art. no. 103098. DOI: https://doi.org/10.1016/j.seta.2023.103098
Z. Li, G. Dewantoro, T. Xiao, and A. Swain, "A Comparative Analysis of Fuzzy Logic Control and Model Predictive Control in Photovoltaic Maximum Power Point Tracking," Electronics, vol. 14, no. 5, Mar. 2025, Art. no. 1009. DOI: https://doi.org/10.3390/electronics14051009
I. Abadi, R. Delfianti, and M. Ihwani, "Design of an Active Dual-Axis Solar Tracking System Using Fuzzy Ant Colony Controller," International Review on Modelling and Simulations, vol. 16, no. 2, pp. 62–73, 2023. DOI: https://doi.org/10.15866/iremos.v16i2.23315
D. Erazo-Caicedo, E. Mojica-Nava, and J. Revelo-Fuelagán, "Model predictive control for optimal power flow in grid-connected unbalanced microgrids," Electric Power Systems Research, vol. 209, Aug. 2022, Art. no. 108000. DOI: https://doi.org/10.1016/j.epsr.2022.108000
J. Arroyo, C. Manna, F. Spiessens, and L. Helsen, "Reinforced model predictive control (RL-MPC) for building energy management," Applied Energy, vol. 309, Mar. 2022, Art. no. 118346. DOI: https://doi.org/10.1016/j.apenergy.2021.118346
I. M. Cabral, J. S. Pereira, and J. B. Ribeiro, "Performance evaluation of PID and Fuzzy Logic controllers for residential ORC-based cogeneration systems," Energy Conversion and Management: X, vol. 23, Jul. 2024, Art. no. 100622. DOI: https://doi.org/10.1016/j.ecmx.2024.100622
G. Bujgoi and D. Sendrescu, "Tuning of PID Controllers Using Reinforcement Learning for Nonlinear System Control," Processes, vol. 13, no. 3, Mar. 2025, Art. no. 735. DOI: https://doi.org/10.3390/pr13030735
S. Boubaker and K. Jouili, "Fuzzy Logic Energy Management System-based Nonlinear Sliding Mode Controller for the Stabilization of DC Microgrids," Engineering, Technology & Applied Science Research, vol. 14, no. 4, pp. 15408–15414, Aug. 2024. DOI: https://doi.org/10.48084/etasr.7658
N.-K. Nguyen and D.-V. Doan, "Designing a Novel Hybrid Fuzzy~GWO~PID Load-Frequency Controller for a complicated Large-Scale Four-Area interconnected Power Grid with RES and SMES," Engineering, Technology & Applied Science Research, vol. 15, no. 3, pp. 23217–23223, Jun. 2025. DOI: https://doi.org/10.48084/etasr.10964
D. V. Doan, K. Nguyen, and Q. V. Thai, "A Novel Fuzzy Logic Based Load Frequency Control for Multi-Area Interconnected Power Systems," Engineering, Technology & Applied Science Research, vol. 11, no. 4, pp. 7522–7529, Aug. 2021. DOI: https://doi.org/10.48084/etasr.4320
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Copyright (c) 2025 Sudirman Palaloi, Andhika Prastawa, Adi Soeprijanto

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