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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM63892

Adaptive Sliding Mode Control with Fuzzy Logic for a Microgrid System Using Renewable Energy Sources

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM63892

Volume:

10 |

5 |

May 2026

Pages:

1-6

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM63892

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.

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Authors

KVVB

K V V Bapiraju

eee

SRINIVASA ENGG COLLEGE

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BS

B Srinavya

eee

SRINIVASA ENGG COLLEGE

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NM

N Meghana

eee

SRINIVASA ENGG COLLEGE

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NSG

N Sriya Geethika

eee

SRINIVASA ENGG COLLEGE

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PPSH

P P S Hanuma

eee

SRINIVASA ENGG COLLEGE

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Abstract

This paper presents sophisticated control architecture for standalone single phase micro grid system to enhance the power quality and frequency stability under the different operating conditions. The proposed system enables smooth integration of a governor-less micro-hydro turbine supplied by a two-winding self-excited induction generator (SEIG) with a wind-driven permanent magnet brushless DC (PMBLDC) generator, a solar photovoltaic (PV) array, and a battery energy storage system (BESS). An Adaptive Sliding Mode Control (ASMC) algorithm is applied for the estimation of reference source currents, which enables accurate regulation of micro grid voltage and frequency, and effective suppression of harmonic distortion. Moreover, a secondary sliding mode control scheme is applied to maintain the real time energy balance by estimating the reference real power of the system, such that the BESS compensates the fluctuation of wind, hydro and solar generation. To overcome the non-linear load disturbances and to improve the power quality the fuzzy logic controller is integrated to suppress the harmonic currents. The robustness of the grid voltage and frequency during sudden load changes and variable intermittent power penetration are established through extensive simulation studies in the MATLAB/Simulink environment confirming the effectiveness of the proposed control strategy.

KEYWORDS

KEYWORDS: Adaptive Sliding mode controller(ASMC) microgrid Renewable energy source(RES) Fuzzy logic controller.

Cite This Article

K V V Bapiraju, B Srinavya, N Meghana, N Sriya Geethika, P P S Hanuma, "Adaptive Sliding Mode Control with Fuzzy Logic for a Microgrid System Using Renewable Energy Sources," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 5, pp. 1-6, May 2026. https://doi.org/10.55041/IJSREM63892

Full Article/Conclusion

Adaptive sliding mode control algorithm is used for voltage and frequency control of stand-alone single phase micro grid. The proposed SEIG based standalone micro grid has incorporated the three main renewable sources including micro-hydro, solar PV and wind energy. The test results have shown that the ASMC algorithm has been effective and has good control of Microgrid voltage and frequency. The proposed control algorithm has also enhanced the power quality of the microgrid under linear and nonlinear loads and also ensures the optimal utilization of BESS and renewable energy sources. Fuzzy Logic Controller is used to reduce the harmonics of the system and the results are analyzed through MATLAB/SIMULINK environment.

References

[1].Ujjwal Kumar Kalla, Senior Member, IEEE, Bhim Singh, Fellow, IEEE, S. S. Murthy, Life Fellow, IEEE, Chinmay Jain AndKrishan Kant       “Adaptive Sliding Mode Control of Standalone Single-Phase Microgrid Using Hydro, Wind and Solar PV Array Based Generation” @ 2017 IEEE. [2]. P. Dondi, D. Bayoumi, C. Haederli, D. Julian, and M. Suter, “Network integration of distributed power generation,” J. of Power Sources, vol.106, no. 1–2, pp. 1–9, 2002.  [3]. J. P. Lopes, N. Hatziargyriou, J. Mutale, P. Djapic, and N. Jenkins, “Integrating distributed generation into electric power systems: A reviewof drivers, challenges and opportunities,” Electric Power Syst. Research, vol. 77, no. 9, pp. 1189–1203, 2007.  [4]. N. Hatziargyriou, H. Asano, R. Iravani, and C. Marnay, “Microgrids, “IEEE Power Energy Mag.,” vol. 5, no. 4, pp. 78–94, Jul./Aug. 2007.  [5]. N. Ruiz, I. Cobelo, and J. Oyarzabal, “A direct load control model for virtual power plant management,” IEEE Trans. Power Syst., vol. 24,no. 2, pp. 959–966, May 2009.  [6]. H. Morais, P. Kádár, M. Cardoso, Z. A. Vale, and H. Khodr, “VPP operating in the isolated grid,” in Proc. IEEE Power and Energy Soc. General Meet., 2008, pp. 16.  [7]. D. Pudjianto, C. Ramsay, and G. Strbac, “Virtual power plant and system integration of distributed energy resources,” IET Renew. Power Gener., vol. 1, no. 1, pp. 10–16, Mar. 2007.  [8]. D. Pudjianto, C. Ramsay, and G. Starbac, “Microgrids and virtual power plants: Concepts to support the integration of distributed energy resources,” in Proc. Inst. Mech. Engineers, Part A: J. Power and Energy (IMechE), 2008, vol. 222, pp. 731741.  [9]. H. Karimi, H. Nikkhajoei, and M. R. Iravani, “Control of an electronically-coupled distributed resource unit subsequent to an islanding event,” IEEE Trans. Power Del., vol. 23, no. 1, pp. 493–501, Jan.2008.  [10]. F. Katiraei, M. R. Iravani, and P. W. Lehn, “Micro-grid autonomous operation during and subsequent to islanding process,” IEEE Trans. Power Del., vol. 20, no. 1, pp. 248–257, Jan. 2005.

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Publication Date

5/24/2026

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