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Improved Linear Active Disturbance Rejection Control for Microgrid Frequency Regulation

Author

Listed:
  • Xiao Qi

    (School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China)

  • Yan Bai

    (School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China)

Abstract

The frequency regulation has become one of the major subjects in microgrid power system due to the complexity structure of microgrid. In order to solve this problem, this paper proposes an improved linear active disturbance rejection control algorithm (ILADRC) that can significantly improve system performances through changing feedback control law to reduce the disturbance estimation error of extended state observer. Then, the proposed algorithm is employed in microgrid power system frequency regulation problem, which demonstrates its effectiveness. The parameters of controllers are optimized by particle swarm optimization (PSO) algorithm improved by genetic algorithm (GA). Simulations with different disturbances including sudden and stochastic change of load demand and wind turbine generation are carried out in comparison with previous studies. And robustness testing based on Monte-Carlo approach also shows better performance. So frequency stability of microgrid power system can be well guaranteed by proposed control algorithm.

Suggested Citation

  • Xiao Qi & Yan Bai, 2017. "Improved Linear Active Disturbance Rejection Control for Microgrid Frequency Regulation," Energies, MDPI, vol. 10(7), pages 1-20, July.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:7:p:1047-:d:105303
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    References listed on IDEAS

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    1. Palizban, Omid & Kauhaniemi, Kimmo & Guerrero, Josep M., 2014. "Microgrids in active network management – part II: System operation, power quality and protection," Renewable and Sustainable Energy Reviews, Elsevier, vol. 36(C), pages 440-451.
    2. Pandey, Shashi Kant & Mohanty, Soumya R. & Kishor, Nand, 2013. "A literature survey on load–frequency control for conventional and distribution generation power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 25(C), pages 318-334.
    3. Andrea Bonfiglio & Federico Delfino & Marco Invernizzi & Renato Procopio, 2017. "Modeling and Maximum Power Point Tracking Control of Wind Generating Units Equipped with Permanent Magnet Synchronous Generators in Presence of Losses," Energies, MDPI, vol. 10(1), pages 1-24, January.
    4. Dreidy, Mohammad & Mokhlis, H. & Mekhilef, Saad, 2017. "Inertia response and frequency control techniques for renewable energy sources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 144-155.
    5. Kaur, Amandeep & Kaushal, Jitender & Basak, Prasenjit, 2016. "A review on microgrid central controller," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 338-345.
    6. Nayeripour, Majid & Hoseintabar, Mohammad & Niknam, Taher, 2011. "Frequency deviation control by coordination control of FC and double-layer capacitor in an autonomous hybrid renewable energy power generation system," Renewable Energy, Elsevier, vol. 36(6), pages 1741-1746.
    7. Bhatt, Praghnesh & Ghoshal, S.P. & Roy, Ranjit, 2012. "Coordinated control of TCPS and SMES for frequency regulation of interconnected restructured power systems with dynamic participation from DFIG based wind farm," Renewable Energy, Elsevier, vol. 40(1), pages 40-50.
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    Citations

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    Cited by:

    1. Xiao Qi & Yan Bai & Huanhuan Luo & Yiqing Zhang & Guiping Zhou & Zhonghua Wei, 2018. "Novel Distributed Optimal Control of Battery Energy Storage System in an Islanded Microgrid with Fast Frequency Recovery," Energies, MDPI, vol. 11(8), pages 1-18, July.
    2. 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.
    3. Md Mijanur Rahman & A. Hasib Chowdhury & Md Alamgir Hossain, 2017. "Improved Load Frequency Control Using a Fast Acting Active Disturbance Rejection Controller," Energies, MDPI, vol. 10(11), pages 1-18, October.
    4. Muhammad Majid Gulzar & Muhammad Iqbal & Sulman Shahzad & Hafiz Abdul Muqeet & Muhammad Shahzad & Muhammad Majid Hussain, 2022. "Load Frequency Control (LFC) Strategies in Renewable Energy-Based Hybrid Power Systems: A Review," Energies, MDPI, vol. 15(10), pages 1-23, May.
    5. Raja M. Imran & D. M. Akbar Hussain & Bhawani Shanker Chowdhry, 2018. "Parameterized Disturbance Observer Based Controller to Reduce Cyclic Loads of Wind Turbine," Energies, MDPI, vol. 11(5), pages 1-13, May.
    6. Raul-Cristian Roman & Radu-Emil Precup & Emil M. Petriu & Florin Dragan, 2019. "Combination of Data-Driven Active Disturbance Rejection and Takagi-Sugeno Fuzzy Control with Experimental Validation on Tower Crane Systems," Energies, MDPI, vol. 12(8), pages 1-19, April.
    7. Xiao Qi & Yan Bai & Huanhuan Luo & Yiqing Zhang & Guiping Zhou & Zhonghua Wei, 2018. "Fully-distributed Load Frequency Control Strategy in an Islanded Microgrid Considering Plug-In Electric Vehicles," Energies, MDPI, vol. 11(6), pages 1-18, June.

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