Hunan Electric Power ›› 2022, Vol. 42 ›› Issue (6): 83-89.doi: 10.3969/j.issn.1008-0198.2022.06.014

• New technology and Application • Previous Articles     Next Articles

Equivalent Modeling of AC/DC Microgrid Connection Based on Improved Extreme Learning Machine

XI Mengrui1,2, CAI Changchun1,2, WANG Bin3   

  1. 1. Jiangsu Key Laboratory of Power Transmission & Distribution Equipment Technology(Hohai University), Changzhou 213022, China;
    2. College of The IOT Engineering, Hohai University, Changzhou 213022, China;
    3. State Grid Taicang Electric Power Supply Company, Taicang 215400, China
  • Received:2022-08-20 Revised:2022-10-13 Online:2022-12-25 Published:2023-01-13

Abstract: With the increasing number of microgrid connected to distribution network, it brings challenges to the stable operation of distribution network. The equivalent modeling of microgrid is the basis for analyzing the impact of microgrid access and dynamic simulation of distribution network. Based on the theory of non-mechanistic modeling, this paper establishes an AC/DC microgrid grid-connected equivalent model of extreme learning machine with real and imaginary parts of voltage and current as input and power as output. The sparrow search algorithm is used to optimize the input weight and threshold of extreme learning machine to reduce the model accuracy problem caused by the lack of unity of input weight and threshold. Finally, the AC/DC hybrid microgrid model is built on DIgSILENT platform for verification. The simulation results show the effectiveness and accuracy of the proposed equivalent model.

Key words: microgrid, sparrow search algorithm, improved extreme learning machine, AC/DC microgrid, equivalent modeling

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