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Microgrid Harmonic Mitigation Strategy Based on the Optimal Allocation of Active Power and Harmonic Mitigation Capacities of Multi-Functional Grid-Connected Inverters

Author

Listed:
  • Ning Wang

    (Key Lab of Power Electronics for Energy Conservation and Motor Drive of Hebei Province, Yanshan University, Qinhuangdao 066004, China)

  • Shuai Zheng

    (Key Lab of Power Electronics for Energy Conservation and Motor Drive of Hebei Province, Yanshan University, Qinhuangdao 066004, China)

  • Weiqiang Gao

    (Key Lab of Power Electronics for Energy Conservation and Motor Drive of Hebei Province, Yanshan University, Qinhuangdao 066004, China)

Abstract

Harmonic pollution sources in microgrids have the characteristics of high penetration and decentralization, as well as forming a full network. Local harmonic mitigation is a traditional harmonic mitigation method, which has the disadvantages of complexity and costly operation. Based on the idea of the decentralized autonomy of power quality, this paper establishes a comprehensive optimization model of the active power and harmonic mitigation capacities of grid-connected inverters based on two-layer optimization and realizes harmonic mitigation. Firstly, based on the harmonic sensitivity analysis, the calculation method of harmonic mitigation capacity is given. Secondly, a two-layer model of harmonic mitigation optimization is established. The upper-layer optimization model takes the minimum operation cost of the microgrid as the objective and the active power reduction in the multi-functional grid-connected inverter (MFGCI) as the optimization variable. The lower-layer optimization model offers the best harmonic mitigation effect as the objective and the harmonic current compensation as the optimization variable. According to the relationship between the total remaining capacity of MFGCI and the capacity required for harmonic mitigation, there are three different objective functions in the lower-layer optimization model. Then, the model solving steps are provided. Finally, an example shows that the proposed optimization model can achieve harmonic mitigation at different times. Compared with the case without active power optimization, the operation cost of the whole system can be reduced by up to 14.6%, while ensuring the harmonic mitigation effect. The proposed method has the advantages of a harmonic mitigation effect and economical system operation.

Suggested Citation

  • Ning Wang & Shuai Zheng & Weiqiang Gao, 2022. "Microgrid Harmonic Mitigation Strategy Based on the Optimal Allocation of Active Power and Harmonic Mitigation Capacities of Multi-Functional Grid-Connected Inverters," Energies, MDPI, vol. 15(17), pages 1-20, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6109-:d:895353
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    References listed on IDEAS

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    1. Łukasz Michalec & Michał Jasiński & Tomasz Sikorski & Zbigniew Leonowicz & Łukasz Jasiński & Vishnu Suresh, 2021. "Impact of Harmonic Currents of Nonlinear Loads on Power Quality of a Low Voltage Network–Review and Case Study," Energies, MDPI, vol. 14(12), pages 1-19, June.
    2. Masoud Babaei & Ahmadreza Abazari & S. M. Muyeen, 2020. "Coordination between Demand Response Programming and Learning-Based FOPID Controller for Alleviation of Frequency Excursion of Hybrid Microgrid," Energies, MDPI, vol. 13(2), pages 1-23, January.
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    1. Manuel Martínez-Gómez & Claudio Burgos-Mellado & Helmo Kelis Morales-Paredes & Juan Sebastián Gómez & Anant Kumar Verma & Jakson Paulo Bonaldo, 2023. "Distributed Control Scheme for Clusters of Power Quality Compensators in Grid-Tied AC Microgrids," Sustainability, MDPI, vol. 15(22), pages 1-23, November.
    2. Emmanuel Hernández-Mayoral & Manuel Madrigal-Martínez & Jesús D. Mina-Antonio & Reynaldo Iracheta-Cortez & Jesús A. Enríquez-Santiago & Omar Rodríguez-Rivera & Gregorio Martínez-Reyes & Edwin Mendoza-, 2023. "A Comprehensive Review on Power-Quality Issues, Optimization Techniques, and Control Strategies of Microgrid Based on Renewable Energy Sources," Sustainability, MDPI, vol. 15(12), pages 1-53, June.
    3. Jingyi Zhang & Tongtian Sheng & Pan Gu & Miao Yu & Honghao Wu & Jianqun Sun & Jinming Bao, 2024. "Comprehensive Power Quality Assessment Based on a Data-Driven Determinant-Valued Extension Hierarchical Analysis Approach," Energies, MDPI, vol. 17(13), pages 1-14, June.
    4. Anna Ostrowska & Łukasz Michalec & Marek Skarupski & Michał Jasiński & Tomasz Sikorski & Paweł Kostyła & Robert Lis & Grzegorz Mudrak & Tomasz Rodziewicz, 2022. "Power Quality Assessment in a Real Microgrid-Statistical Assessment of Different Long-Term Working Conditions," Energies, MDPI, vol. 15(21), pages 1-26, October.

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