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Distributed wind-hybrid microgrids with autonomous controls and forecasting

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  • Anderson, Benjamin
  • Rane, Jayaraj
  • Khan, Rabia

Abstract

Distributed wind-hybrid microgrids have the potential to provide key resilience and economic benefits to both the customers they serve and the utility grids they are connected to. Such microgrids will likely be a key part of the grid of the future, whether connected to large utility grids or linked together in multi-microgrid systems. Through the hybridization of distributed wind and solar photovoltaics, autonomous device-level and system-level controls, battery energy storage systems with smart inverters, and forecasting, these microgrids could maintain local stability and provide grid services—all with renewable power. In the literature, these elements have been considered individually. However, they have not been combined and demonstrated at a high fidelity, which is essential to prove the concept’s operation before moving to hardware-in-the-loop and physical demonstrations. In this work, we develop a high-fidelity MATLAB-Simulink model of a real distributed wind-hybrid microgrid that includes all these elements. We demonstrate the microgrid maintaining stability and production in a variety of islanded, grid-connected, and transition scenarios. This includes riding through faults and grid transitions, handling resource variability, and providing grid services. The results demonstrate, at a high fidelity, how distributed wind-hybrid microgrids can operate in an economic and resilient fashion. Finally, we provide recommendations for future research to move advanced distributed wind-hybrid microgrids toward deployment.

Suggested Citation

  • Anderson, Benjamin & Rane, Jayaraj & Khan, Rabia, 2023. "Distributed wind-hybrid microgrids with autonomous controls and forecasting," Applied Energy, Elsevier, vol. 333(C).
  • Handle: RePEc:eee:appene:v:333:y:2023:i:c:s0306261922018141
    DOI: 10.1016/j.apenergy.2022.120557
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    References listed on IDEAS

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    1. Shuai, Zhikang & Sun, Yingyun & Shen, Z. John & Tian, Wei & Tu, Chunming & Li, Yan & Yin, Xin, 2016. "Microgrid stability: Classification and a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 167-179.
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    1. Jiyong Li & Ran Chen & Chengye Liu & Xiaoshuai Xu & Yasai Wang, 2023. "Capacity Optimization of Independent Microgrid with Electric Vehicles Based on Improved Pelican Optimization Algorithm," Energies, MDPI, vol. 16(6), pages 1-23, March.

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