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Stream/Area:
-
Subject:
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Paper ID:
IJSREM65263
Volume:
10 |
6 |
Jun 2026
Pages:
1-8
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Electrical Engineering
RSR Rungta College of Engineering and Technology, Kurud, Bhilai, Chhattishgarh, INDIA
Department of Electrical Engineering
RSR Rungta College of Engineering and Technology, Kurud, Bhilai, Chhattishgarh, INDIA
Department of Electrical Engineering
RSR Rungta College of Engineering and Technology, Kurud, Bhilai, Chhattishgarh, INDIA
This paper provides a critical, systematic evaluation of recent advancements in supervisory energy management systems (EMS) designed for islanded hybrid DC microgrids. Specifically, this review synthesizes contemporary literature focusing on the co-optimization of multi-asset configurations that couple intermittent solar photovoltaics with hydrogen-based proton exchange membrane fuel cells (PEMFC) and secondary lithium-ion battery energy storage systems (BESS). A primary analytical focus is directed toward comparing the structural efficacy of rule-based state machines against artificial intelligence-driven frameworks, with particular emphasis on Mamdani versus Takagi-Sugeno-Kang (TSK) fuzzy logic inference engines. This survey exposes critical gaps in current literature regarding the real-time execution bounds of these supervisors under strict fixed-step discrete integration constraints. Furthermore, we evaluate the industry adoption of protective physical constraints, such as clamping electrochemical current ramp rates to stabilize the (di/dt) derivative and configuring parallel resistor-capacitor (RC) snubber networks to eliminate numerical Jacobian singularities during high-frequency pulse-width modulation (PWM) switching. The paper concludes by mapping the operational barriers hindering the transition from continuous software-defined simulations to low-latency, hard-deterministic Hardware-in-the-Loop (HIL) microprocessing deployment. Ultimately, this comprehensive review provides a structured roadmap identifying the exact parametric thresholds required to balance transient power quality metrics against multi-asset degradation constraints in decentralised distribution networks.
KEYWORDS
This review has systematically evaluated the operational paradigms governing supervisory energy management architectures for islanded DC microgrids. The literature clearly demonstrates that while classical linear loops and deterministic state machines offer low computational overhead, they are fundamentally limited by operating point sensitivity and severe boundary threshold chattering. Intelligent soft-computing frameworks, specifically fuzzy logic controllers, successfully eliminate threshold chattering and provide superior multi-asset coordination. However, existing Mamdani-based fuzzy implementations introduce severe computational burdens that jeopardise numerical stability and real-time execution viability when transitioned into strict, fixed-step discrete hardware-in-the-loop environments.
[1] A. K. Singh, P. Kumar, and V. Das, "Levelized cost of energy-based economic analysis of microgrid equipped with multi-energy storage system," Distributed Generation & Alternative Energy Journal, vol. 38, no. 4, pp. 1156–1182, May 2023. [2] N. A. Jasim and M. N. Hawas, "Modelling and simulation of microgrid power system including a hybrid energy storage system," Journal of Renewable Energy and Sustainable Development, vol. 11, no. 1, pp. 141–153, Jun. 2025. [3] M. Upadhya, A. K. Singh, and P. Thakur, "Evaluation of alternative control strategies of hybrid microgrid under islanded operational conditions: A review," Journal of Energy Storage, vol. 49, p. 104068, May 2022. [4] S. Choudhury, "Power management strategies in a hybrid energy storage system integrated AC/DC microgrid: A comprehensive review," Energies, vol. 15, no. 19, p. 7176, Oct. 2022. [5] N. Rawat, P. Thakur, and A. K. Singh, "Performance analysis of solar PV parameter estimation techniques using single-diode mathematical models," Optik, vol. 279, p. 170785, May 2023. [6] L. A. Zadeh, "Fuzzy sets," Information and Control, vol. 8, no. 3, pp. 338–353, Jun. 1965. (Foundational Paper) [7] T. Takagi and M. Sugeno, "Fuzzy identification of systems and its applications to modelling and control," IEEE Transactions on Systems, Man, and Cybernetics, vol. SMC-15, no. 1, pp. 116–132, Jan. 1985. (Foundational Paper) [8] M. Sugeno and G. T. Kang, "Structure identification of fuzzy model," Fuzzy Sets and Systems, vol. 28, no. 1, pp. 15–33, Oct. 1988. [9] H. S. Das, A. K. Chakrabarty, and S. R. Mohanty, "State-of-charge tracking loops and optimization of isolated hybrid microgrid systems," IEEE Transactions on Smart Grid, vol. 14, no. 2, pp. 982–995, Mar. 2023. [10] F. Blaabjerg, Y. Yang, and D. Wang, "Power electronics interfaces for distributed generation units and microgrids: An overview," IEEE Transactions on Industrial Electronics, vol. 70, no. 5, pp. 4312–4326, May 2023.
Publication Date
6/22/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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