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Optimal sizing, operation strategy and case study of a grid-connected solid oxide fuel cell microgrid

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Listed:
  • Jiang, Jianhua
  • Zhou, Renjie
  • Xu, Hao
  • Wang, Hao
  • Wu, Ping
  • Wang, Zhuo
  • Li, Jian

Abstract

The microgrid (MG) system based on renewable energy generators plays a significant role in sustainable development and environmental protection, which has been developed rapidly. As a promising clean energy conversion technology, solid oxide fuel cell (SOFC) is a clean, efficient and controllable power generator, which is very suitable to be integrated in a distributed MG system. Finding the optimal size configuration and the beneficial operation strategy of the Grid-connected MG under different operation modes are critical issues for MG application. In this work, a single-dwelling MG incorporating solar photovoltaic (PV), wind turbine generator (WTG), SOFC and battery energy storage system (BESS) is studied by minimizing the system levelized cost of energy (LCOE) on the basis of system multi-constraints. The dispatching problem of MG is modeled as a quadratic programming problem and an improved GA-PSO algorithm is employed to explore the optimal configuration. Then, sensitivity analysis is carried out to identify the impact of different distributed energy resource size on the performance of MG. Based on the optimal configuration, the operation strategy of the proposed MG under both off-grid mode and grid-connected mode, as well as the influence of electricity price and fuel price on the operation of the MG are investigated. Finally, the economic and environmental benefits of the MG are studied and compared. The results show that, in Shanghai, Beijing, Wuhan and Hulunbuir, the costs of the MG in both off-grid mode and grid-connected mode are lower than the grid-supplied price by up to 13%-28% and 28%-37% separately.

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  • Jiang, Jianhua & Zhou, Renjie & Xu, Hao & Wang, Hao & Wu, Ping & Wang, Zhuo & Li, Jian, 2022. "Optimal sizing, operation strategy and case study of a grid-connected solid oxide fuel cell microgrid," Applied Energy, Elsevier, vol. 307(C).
  • Handle: RePEc:eee:appene:v:307:y:2022:i:c:s0306261921014811
    DOI: 10.1016/j.apenergy.2021.118214
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    Cited by:

    1. Wang, Yijian & Cui, Yang & Li, Yang & Xu, Yang, 2023. "Collaborative optimization of multi-microgrids system with shared energy storage based on multi-agent stochastic game and reinforcement learning," Energy, Elsevier, vol. 280(C).
    2. Gong, Chengyuan & Tu, Zhengkai & Hwa Chan, Siew, 2023. "A novel flow field design with flow re-distribution for advanced thermal management in Solid oxide fuel cell," Applied Energy, Elsevier, vol. 331(C).

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