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Application of Model Predictive Control to BESS for Microgrid Control

Author

Listed:
  • Thai-Thanh Nguyen

    (Department of Electrical Engineering, Incheon National University, 12-1 Songdo-dong, Yeonsu-gu, Incheon 406-840, Korea)

  • Hyeong-Jun Yoo

    (Department of Electrical Engineering, Incheon National University, 12-1 Songdo-dong, Yeonsu-gu, Incheon 406-840, Korea)

  • Hak-Man Kim

    (Department of Electrical Engineering, Incheon National University, 12-1 Songdo-dong, Yeonsu-gu, Incheon 406-840, Korea)

Abstract

Battery energy storage systems (BESSs) have been widely used for microgrid control. Generally, BESS control systems are based on proportional-integral (PI) control techniques with the outer and inner control loops based on PI regulators. Recently, model predictive control (MPC) has attracted attention for application to future energy processing and control systems because it can easily deal with multivariable cases, system constraints, and nonlinearities. This study considers the application of MPC-based BESSs to microgrid control. Two types of MPC are presented in this study: MPC based on predictive power control (PPC) and MPC based on PI control in the outer and predictive current control (PCC) in the inner control loops. In particular, the effective application of MPC for microgrids with multiple BESSs should be considered because of the differences in their control performance. In this study, microgrids with two BESSs based on two MPC techniques are considered as an example. The control performance of the MPC used for the control microgrid is compared to that of the PI control. The proposed control strategy is investigated through simulations using MATLAB/Simulink software. The simulation results show that the response time, power and voltage ripples, and frequency spectrum could be improved significantly by using MPC.

Suggested Citation

  • Thai-Thanh Nguyen & Hyeong-Jun Yoo & Hak-Man Kim, 2015. "Application of Model Predictive Control to BESS for Microgrid Control," Energies, MDPI, vol. 8(8), pages 1-16, August.
    • Handle: RePEc:gam:jeners:v:8:y:2015:i:8:p:8798-8813:d:54462
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    References listed on IDEAS

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    1. Thai-Thanh Nguyen & Hyeong-Jun Yoo & Hak-Man Kim, 2015. "A Flywheel Energy Storage System Based on a Doubly Fed Induction Machine and Battery for Microgrid Control," Energies, MDPI, vol. 8(6), pages 1-16, June.
    2. Hak-Man Kim & Yujin Lim & Tetsuo Kinoshita, 2012. "An Intelligent Multiagent System for Autonomous Microgrid Operation," Energies, MDPI, vol. 5(9), pages 1-16, September.
    3. Kim, Jaehoon & Kim, Sangsin, 2015. "2012년 국회법 개정의 효과 연구 [A Study on the Effect of the 2012 National Assembly Act Amendment]," KDI Research Monographs, Korea Development Institute (KDI), volume 127, number v:2015-03(k):y:2015:p:1-1.
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    1. Liuming Jing & Dae-Hee Son & Sang-Hee Kang & Soon-Ryul Nam, 2016. "A Novel Protection Method for Single Line-to-Ground Faults in Ungrounded Low-Inertia Microgrids," Energies, MDPI, vol. 9(6), pages 1-16, June.
    2. Daniele Mestriner & Alessandro Rosini & Iris Xhani & Andrea Bonfiglio & Renato Procopio, 2022. "Primary Voltage and Frequency Regulation in Inverter Based Islanded Microgrids through a Model Predictive Control Approach," Energies, MDPI, vol. 15(14), pages 1-19, July.
    3. Timur Yunusov & Maximilian J. Zangs & William Holderbaum, 2017. "Control of Energy Storage," Energies, MDPI, vol. 10(7), pages 1-5, July.
    4. Thijs Van der Klauw & Johann L. Hurink & Gerard J. M. Smit, 2016. "Scheduling of Electricity Storage for Peak Shaving with Minimal Device Wear," Energies, MDPI, vol. 9(6), pages 1-19, June.
    5. Thai-Thanh Nguyen & Hyeong-Jun Yoo & Hak-Man Kim & Huy Nguyen-Duc, 2018. "Direct Phase Angle and Voltage Amplitude Model Predictive Control of a Power Converter for Microgrid Applications," Energies, MDPI, vol. 11(9), pages 1-21, August.
    6. Mohamed Abdelrahem & Ralph Kennel, 2016. "Fault-Ride through Strategy for Permanent-Magnet Synchronous Generators in Variable-Speed Wind Turbines," Energies, MDPI, vol. 9(12), pages 1-15, December.
    7. Hussain Sarwar Khan & Muhammad Aamir & Muhammad Ali & Asad Waqar & Syed Umaid Ali & Junaid Imtiaz, 2019. "Finite Control Set Model Predictive Control for Parallel Connected Online UPS System under Unbalanced and Nonlinear Loads," Energies, MDPI, vol. 12(4), pages 1-20, February.
    8. Rosini, A. & Procopio, R. & Bonfiglio, A. & Incremona, G.P. & Ferrara, A., 2022. "A Decentralized Higher Order Sliding Mode Control for Islanded Photovoltaic-Storage Systems," Energy, Elsevier, vol. 255(C).
    9. Marvin Lema & Wilson Pavon & Leony Ortiz & Ama Baduba Asiedu-Asante & Silvio Simani, 2022. "Controller Coordination Strategy for DC Microgrid Using Distributed Predictive Control Improving Voltage Stability," Energies, MDPI, vol. 15(15), pages 1-15, July.
    10. Izaskun Garrido & Aitor J. Garrido & Stefano Coda & Hoang B. Le & Jean Marc Moret, 2016. "Real Time Hybrid Model Predictive Control for the Current Profile of the Tokamak à Configuration Variable (TCV)," Energies, MDPI, vol. 9(8), pages 1-14, August.
    11. Woo-Kyu Chae & Jong-Nam Won & Hak-Ju Lee & Jae-Eon Kim & Jaehong Kim, 2016. "Comparative Analysis of Voltage Control in Battery Power Converters for Inverter-Based AC Microgrids," Energies, MDPI, vol. 9(8), pages 1-18, July.
    12. Thai-Thanh Nguyen & Hyeong-Jun Yoo & Hak-Man Kim, 2017. "Analyzing the Impacts of System Parameters on MPC-Based Frequency Control for a Stand-Alone Microgrid," Energies, MDPI, vol. 10(4), pages 1-17, March.
    13. Feras Alasali & Stephen Haben & Victor Becerra & William Holderbaum, 2017. "Optimal Energy Management and MPC Strategies for Electrified RTG Cranes with Energy Storage Systems," Energies, MDPI, vol. 10(10), pages 1-18, October.

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