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An Algorithm for Short-Circuit Current Interval in Distribution Networks with Inverter Type Distributed Generation Based on Affine Arithmetic

Yan Zhang1, Bowen Du2,*, Benren Pan1, Guannan Wang1, Guoqiang Xie1, Tong Jiang2

1 Electric Power Research Institute, State Grid Jiangxi Electric Power Co., Ltd., Nanchang, 330096, China
2 School of Electrical and Electronic Engineering, North China Electric Power University, Beijing, 102206, China

* Corresponding Author: Bowen Du. Email: email

Energy Engineering 2024, 121(7), 1903-1920. https://doi.org/10.32604/ee.2024.048718

Abstract

During faults in a distribution network, the output power of a distributed generation (DG) may be uncertain. Moreover, the output currents of distributed power sources are also affected by the output power, resulting in uncertainties in the calculation of the short-circuit current at the time of a fault. Additionally, the impacts of such uncertainties around short-circuit currents will increase with the increase of distributed power sources. Thus, it is very important to develop a method for calculating the short-circuit current while considering the uncertainties in a distribution network. In this study, an affine arithmetic algorithm for calculating short-circuit current intervals in distribution networks with distributed power sources while considering power fluctuations is presented. The proposed algorithm includes two stages. In the first stage, normal operations are considered to establish a conservative interval affine optimization model of injection currents in distributed power sources. Constrained by the fluctuation range of distributed generation power at the moment of fault occurrence, the model can then be used to solve for the fluctuation range of injected current amplitudes in distributed power sources. The second stage is implemented after a malfunction occurs. In this stage, an affine optimization model is first established. This model is developed to characterizes the short-circuit current interval of a transmission line, and is constrained by the fluctuation range of the injected current amplitude of DG during normal operations. Finally, the range of the short-circuit current amplitudes of distribution network lines after a short-circuit fault occurs is predicted. The algorithm proposed in this article obtains an interval range containing accurate results through interval operation. Compared with traditional point value calculation methods, interval calculation methods can provide more reliable analysis and calculation results. The range of short-circuit current amplitude obtained by this algorithm is slightly larger than those obtained using the Monte Carlo algorithm and the Latin hypercube sampling algorithm. Therefore, the proposed algorithm has good suitability and does not require iterative calculations, resulting in a significant improvement in computational speed compared to the Monte Carlo algorithm and the Latin hypercube sampling algorithm. Furthermore, the proposed algorithm can provide more reliable analysis and calculation results, improving the safety and stability of power systems.

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Cite This Article

APA Style
Zhang, Y., Du, B., Pan, B., Wang, G., Xie, G. et al. (2024). An algorithm for short-circuit current interval in distribution networks with inverter type distributed generation based on affine arithmetic. Energy Engineering, 121(7), 1903-1920. https://doi.org/10.32604/ee.2024.048718
Vancouver Style
Zhang Y, Du B, Pan B, Wang G, Xie G, Jiang T. An algorithm for short-circuit current interval in distribution networks with inverter type distributed generation based on affine arithmetic. Energ Eng. 2024;121(7):1903-1920 https://doi.org/10.32604/ee.2024.048718
IEEE Style
Y. Zhang, B. Du, B. Pan, G. Wang, G. Xie, and T. Jiang, “An Algorithm for Short-Circuit Current Interval in Distribution Networks with Inverter Type Distributed Generation Based on Affine Arithmetic,” Energ. Eng., vol. 121, no. 7, pp. 1903-1920, 2024. https://doi.org/10.32604/ee.2024.048718



cc Copyright © 2024 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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