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Analyzing the Impacts of System Parameters on MPC-Based Frequency Control for a Stand-Alone Microgrid

Author

Listed:
  • Thai-Thanh Nguyen

    (Department of Electrical Engineering, Incheon National University, Songdo-dong, 119 Academy-ro, Yeonsu-gu, Incheon 22012, Korea)

  • Hyeong-Jun Yoo

    (Department of Electrical Engineering, Incheon National University, Songdo-dong, 119 Academy-ro, Yeonsu-gu, Incheon 22012, Korea)

  • Hak-Man Kim

    (Department of Electrical Engineering, Incheon National University, Songdo-dong, 119 Academy-ro, Yeonsu-gu, Incheon 22012, Korea)

Abstract

Model predictive control (MPC) has been widely studied for regulating frequency in stand-alone microgrids (MGs), owing to the advantages of MPC such as fast response and robustness against the parameter uncertainties. Understanding the impacts of system parameters on the control performance of MPC could be useful for the designing process of the controller to achieve better performance. This study analyzes the impact of system parameters on the control performance of MPC for frequency regulation in a stand-alone MG. The typical stand-alone MG, which consists of a diesel engine generator, an energy storage system (ESS), a wind turbine generator, and a load, is considered in this study. The diesel engine generator is in charge of primary frequency control whereas the ESS is responsible for secondary frequency control. The stand-alone MG is linearized to obtain the dynamic model that is used for designing MPC-based secondary frequency control. The robustness of MPC against the variation of system parameters is also analyzed in this study. A comparison study of MPC and proportional–integral (PI) control is presented. Simulation results show that MPC has a faster response time and lower overshoot compared to PI control. In addition, the robustness of MPC against the system uncertainties is stronger than conventional PI control.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:4:p:417-:d:93821
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    References listed on IDEAS

    as
    1. 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.
    2. Xiaoling Su & Minxiao Han & Josep M. Guerrero & Hai Sun, 2015. "Microgrid Stability Controller Based on Adaptive Robust Total SMC," Energies, MDPI, vol. 8(3), pages 1-18, March.
    3. Yun-Su Kim & Chul-Sang Hwang & Eung-Sang Kim & Changhee Cho, 2016. "State of Charge-Based Active Power Sharing Method in a Standalone Microgrid with High Penetration Level of Renewable Energy Sources," Energies, MDPI, vol. 9(7), pages 1-13, June.
    4. Eneko Unamuno & Jon Andoni Barrena, 2017. "Equivalence of Primary Control Strategies for AC and DC Microgrids," Energies, MDPI, vol. 10(1), pages 1-13, January.
    5. Jong-Yul Kim & Hak-Man Kim & Seul-Ki Kim & Jin-Hong Jeon & Heung-Kwan Choi, 2011. "Designing an Energy Storage System Fuzzy PID Controller for Microgrid Islanded Operation," Energies, MDPI, vol. 4(9), pages 1-18, September.
    6. Mohammed Elsayed Lotfy & Tomonobu Senjyu & Mohammed Abdel-Fattah Farahat & Amal Farouq Abdel-Gawad & Atsuhi Yona, 2017. "A Frequency Control Approach for Hybrid Power System Using Multi-Objective Optimization," Energies, MDPI, vol. 10(1), pages 1-22, January.
    7. Jun Yang & Zhili Zeng & Yufei Tang & Jun Yan & Haibo He & Yunliang Wu, 2015. "Load Frequency Control in Isolated Micro-Grids with Electrical Vehicles Based on Multivariable Generalized Predictive Theory," Energies, MDPI, vol. 8(3), pages 1-20, March.
    8. Young-Sik Jang & JoonHyung Park & Yong Tae Yoon, 2015. "Designing Structure-Dependent MPC-Based AGC Schemes Considering Network Topology," Energies, MDPI, vol. 8(5), pages 1-18, April.
    9. Wei Gu & Wei Liu & Zhi Wu & Bo Zhao & Wu Chen, 2013. "Cooperative Control to Enhance the Frequency Stability of Islanded Microgrids with DFIG-SMES," Energies, MDPI, vol. 6(8), pages 1-21, August.
    10. Jin-Sun Yang & Jin-Young Choi & Geon-Ho An & Young-Jun Choi & Myoung-Hoe Kim & Dong-Jun Won, 2016. "Optimal Scheduling and Real-Time State-of-Charge Management of Energy Storage System for Frequency Regulation," Energies, MDPI, vol. 9(12), pages 1-13, November.
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    5. Andrea Bonfiglio & Massimo Brignone & Marco Invernizzi & Alessandro Labella & Daniele Mestriner & Renato Procopio, 2017. "A Simplified Microgrid Model for the Validation of Islanded Control Logics," Energies, MDPI, vol. 10(8), pages 1-28, August.
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    8. Tiago Lukasievicz & Ricardo Oliveira & César Torrico, 2018. "A Control Approach and Supplementary Controllers for a Stand-Alone System with Predominance of Wind Generation," Energies, MDPI, vol. 11(2), pages 1-17, February.
    9. José Antonio Cortajarena & Oscar Barambones & Patxi Alkorta & Jon Cortajarena, 2021. "Grid Frequency and Amplitude Control Using DFIG Wind Turbines in a Smart Grid," Mathematics, MDPI, vol. 9(2), pages 1-18, January.
    10. Guo-Qiang Zeng & Xiao-Qing Xie & Min-Rong Chen, 2017. "An Adaptive Model Predictive Load Frequency Control Method for Multi-Area Interconnected Power Systems with Photovoltaic Generations," Energies, MDPI, vol. 10(11), pages 1-23, November.
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