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May 17, 2018IEEE Transactions on Power Systems126 citations

Robust Optimal Dispatch of AC/DC Hybrid Microgrids Considering Generation and Load Uncertainties and Energy Storage Loss

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BZBo ZhaoHQHaifeng QiuRQRuwen Qin

Key Points

  • This research aims to develop a robust model for optimal dispatch in microgrids facing generation and load uncertainties.
  • Developed a two-stage min-max-min dispatch model for AC/DC hybrid microgrids.
  • Created a linearized cost model accounting for energy storage degradation.
  • Applied a column-and-constraint generation algorithm to find optimal dispatch solutions.
  • Achieved minimized daily operating costs in worst-case scenarios.
  • Confirmed effectiveness through case studies and sensitivity analyses.

Abstract

Uncertainties from generation sources and loads have introduced tremendous challenges to the optimal dispatch of microgrids. This paper presents a novel two-stage min-max-min robust optimal dispatch model for a representative islanded ac/dc hybrid microgrid that faces uncertainties in renewable energy generation and customer loads. The first stage of the model determines the startup/shutdown state of the diesel engine generator and the operating state of the bidirectional converter of the microgrid. Then, the second stage optimizes the power dispatch of individual units in the microgrid. A new linearized equipment cost model is developed, counting for the degradation of energy storage. The use of this linear model helps maintain the linearity of the objective function without compromising solution accuracy. The column-and-constraint generation algorithm is implemented to efficiently obtain a robust dispatching plan for the microgrid, which minimizes the daily operating cost in the worst-case scenario. A case study and sensitivity analyses further demonstrate the rationale and the unique capability of the proposed model for the operation scheduling of ac/dc hybrid microgrids.

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Cite This Study

Zhao et al. (2018) studied this question.

synapsesocial.com/papers/6a19283dc27e07dcc0d950b1https://doi.org/10.1109/tpwrs.2018.2835464
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