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A Generalized Droop Strategy for Interlinking Converter in a Standalone Hybrid Microgrid

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  • Malik, Sarmad Majeed
  • Sun, Yingyun
  • Huang, Wen
  • Ai, Xin
  • Shuai, Zhikang

Abstract

The existence of ac and dc grid leads to a new concept of hybrid microgrid in which both grids are tied by an interlinking converter (ILC). Various control schemes of ILC have been discussed in literature but there is a lack of a generalized, autonomous control which considers the tie line capacity between ac and dc grids. In addition, the majority of schemes involve switching between control modes which increases power losses. To address these issues, this paper presents a generalized droop scheme of ILC for power sharing and control in a standalone hybrid ac/dc microgrid. A 3-dimensional plane is proposed where the axis correspond to dc voltage, ac frequency and converter power. The converter utilizes frequency droop at ac terminal and voltage droop at dc terminal so any change in voltage or frequency results in active power flow from an underloaded to overloaded grid. A corresponding mathematical model is also presented which determines the impact of load change on frequency and dc voltage. The proposed scheme enables autonomous power transfer in both directions without any form of communication. A comparison between the traditional normalization scheme and proposed scheme is also presented where it is observed that this method reduces the frequency deviations and transient response time, thereby giving a better performance. Both the simulations and experimental results confirm the validity of the proposed model.

Suggested Citation

  • Malik, Sarmad Majeed & Sun, Yingyun & Huang, Wen & Ai, Xin & Shuai, Zhikang, 2018. "A Generalized Droop Strategy for Interlinking Converter in a Standalone Hybrid Microgrid," Applied Energy, Elsevier, vol. 226(C), pages 1056-1063.
    • Handle: RePEc:eee:appene:v:226:y:2018:i:c:p:1056-1063
    DOI: 10.1016/j.apenergy.2018.06.002
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    References listed on IDEAS

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    1. Craparo, Emily & Karatas, Mumtaz & Singham, Dashi I., 2017. "A robust optimization approach to hybrid microgrid operation using ensemble weather forecasts," Applied Energy, Elsevier, vol. 201(C), pages 135-147.
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    4. Ding, Tao & Lin, Yanling & Bie, Zhaohong & Chen, Chen, 2017. "A resilient microgrid formation strategy for load restoration considering master-slave distributed generators and topology reconfiguration," Applied Energy, Elsevier, vol. 199(C), pages 205-216.
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    Cited by:

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    2. Mageswaran Rengasamy & Sivasankar Gangatharan & Rajvikram Madurai Elavarasan & Lucian Mihet-Popa, 2020. "The Motivation for Incorporation of Microgrid Technology in Rooftop Solar Photovoltaic Deployment to Enhance Energy Economics," Sustainability, MDPI, vol. 12(24), pages 1-27, December.
    3. Yu, Hang & Niu, Songyan & Zhang, Yumeng & Jian, Linni, 2020. "An integrated and reconfigurable hybrid AC/DC microgrid architecture with autonomous power flow control for nearly/net zero energy buildings," Applied Energy, Elsevier, vol. 263(C).
    4. Ferahtia, Seydali & Rezk, Hegazy & Abdelkareem, Mohammad Ali & Olabi, A.G., 2022. "Optimal techno-economic energy management strategy for building’s microgrids based bald eagle search optimization algorithm," Applied Energy, Elsevier, vol. 306(PB).
    5. Sohail Sarwar & Desen Kirli & Michael M. C. Merlin & Aristides E. Kiprakis, 2022. "Major Challenges towards Energy Management and Power Sharing in a Hybrid AC/DC Microgrid: A Review," Energies, MDPI, vol. 15(23), pages 1-30, November.
    6. Muhammad Awais & Laiq Khan & Said Ghani Khan & Qasim Awais & Mohsin Jamil, 2023. "Adaptive Neural Network Q-Learning-Based Full Recurrent Adaptive NeuroFuzzy Nonlinear Control Paradigms for Bidirectional-Interlinking Converter in a Grid-Connected Hybrid AC-DC Microgrid," Energies, MDPI, vol. 16(4), pages 1-40, February.

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