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Designing a High-Order Sliding Mode Controller for Photovoltaic- and Battery Energy Storage System-Based DC Microgrids with ANN-MPPT

Author

Listed:
  • Tushar Kanti Roy

    (School of Engineering, Deakin University, Melbourne, VIC 3216, Australia)

  • Amanullah Maung Than Oo

    (School of Engineering, Macquarie University, Sydney, NSW 2109, Australia)

  • Subarto Kumar Ghosh

    (Department of Electrical & Electronic Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh)

Abstract

This paper introduces a robust proportional integral derivative higher-order sliding mode controller (PID-HOSMC) based on a double power reaching law (DPRL) to enhance large-signal stability in DC microgrids. The microgrid integrates a solar photovoltaic (SPV) system, an energy storage system (ESS), and DC loads. Efficient DC-DC converters, including bidirectional and boost converters, are employed to maintain a constant voltage level despite the lower SPV output power. An artificial neural network (ANN) generates the optimal reference voltage for the SPV system. The dynamical model, which incorporates external disturbances, is initially developed and based on this model, and the PID-HOSMC is designed to control output power by generating switching gate pulses. Afterwards, Lyapunov stability theory is used to demonstrate the model’s closed-loop stability, and theoretical analysis indicates that the controller can converge tracking errors to zero within a finite time frame. Finally, a comparative numerical simulation result is presented, demonstrating that the proposed controller exhibits a 58% improvement in settling time and an 82% improvement in overshoot compared to the existing controller. Experimental validation using processor-in-the-loop (PIL) confirms the proposed controller’s performance on a real-time platform.

Suggested Citation

  • Tushar Kanti Roy & Amanullah Maung Than Oo & Subarto Kumar Ghosh, 2024. "Designing a High-Order Sliding Mode Controller for Photovoltaic- and Battery Energy Storage System-Based DC Microgrids with ANN-MPPT," Energies, MDPI, vol. 17(2), pages 1-22, January.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:2:p:532-:d:1323933
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    References listed on IDEAS

    as
    1. Armghan, Hammad & Yang, Ming & Ali, Naghmash & Armghan, Ammar & Alanazi, Abdulaziz, 2022. "Quick reaching law based global terminal sliding mode control for wind/hydrogen/battery DC microgrid," Applied Energy, Elsevier, vol. 316(C).
    2. Taimoor Ahmad Khan & Amjad Ullah & Ghulam Hafeez & Imran Khan & Sadia Murawwat & Faheem Ali & Sajjad Ali & Sheraz Khan & Khalid Rehman, 2022. "A Fractional Order Super Twisting Sliding Mode Controller for Energy Management in Smart Microgrid Using Dynamic Pricing Approach," Energies, MDPI, vol. 15(23), pages 1-14, November.
    3. Zhiye Lu & Lishu Wang & Panbao Wang, 2023. "Review of Voltage Control Strategies for DC Microgrids," Energies, MDPI, vol. 16(17), pages 1-19, August.
    4. Sabrina Yeasmin & Tushar Kanti Roy & Subarto Kumar Ghosh, 2022. "Design of Robust Integral Terminal Sliding Mode Controllers with Exponential Reaching Laws for Solar PV and BESS-Based DC Microgrids with Uncertainties," Sustainability, MDPI, vol. 14(13), pages 1-17, June.
    5. Jonathan Andrés Basantes & Daniela Estefanía Paredes & Jacqueline Rosario Llanos & Diego Edmundo Ortiz & Claudio Danilo Burgos, 2023. "Energy Management System (EMS) Based on Model Predictive Control (MPC) for an Isolated DC Microgrid," Energies, MDPI, vol. 16(6), pages 1-22, March.
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