A Novel Method for Islanding in Active Distribution Network Considering Distributed Generation

  • Jun Wang Shenyang Agricultural University
  • Xinran Wang Shenyang Agricultural University
  • Bart Di Emanden Technical Solutions Pty Ltd.
  • Chao Sun Yingkou Power Supply Company, Liaoning Electric Power Co. Ltd, State Grid Co. Ltd.
  • Wei Zheng Yingkou Power Supply Company, Liaoning Electric Power Co. Ltd, State Grid Co. Ltd.


The output of distributed generation (DG) has strong randomness, and its randomness has a great influence on the division of islands. To simulate the impact of DG output on island division when dividing islands, this study proposed an island division method that considers the randomness of DG output. The basic idea of this method is as follows. First, Monte Carlo sampling was used to obtain the output power of DG under different confidence levels to simulate the randomness of DG output. Furthermore, a multi-objective and multi-constraint considering the randomness of DG output were established. The niche genetic algorithm was used to solve the model, and the effectiveness of the proposed model and algorithm was verified through the analysis of examples. The results show that the risk reserve power introduced by simulating the randomness of DG output is inversely proportional to the confidence level. The minimum value of the system node voltage level after islanding is 0.9495 pu, which meets the requirements of the constraint. Under the same conditions, compared with the island division method of not considering the random DG, the method proposed in this study not only has a larger total load recovery and a higher priority load recovery rate but also has a higher DG utilization rate, which can meet the needs of practical applications. This study provides a certain reference for the establishment and solution method of the islanding model of the distribution network with DG.


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How to Cite
WANG, Jun et al. A Novel Method for Islanding in Active Distribution Network Considering Distributed Generation. Journal of Power Technologies, [S.l.], v. 101, n. 1, p. 11-21, feb. 2021. ISSN 2083-4195. Available at: <https://papers.itc.pw.edu.pl/index.php/JPT/article/view/1735>. Date accessed: 14 july 2024.
Energy Engineering and Technology

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