Abstract
Due to the local optimum and the inaccurate fault location of distribution network when DG (distributed generation) access using the traditional BPSO (binary particle swarm optimization), an IBPSO (improved binary particle swarm optimization) to locate the fault places is proposed. Firstly, the locating model of distribution network fault is established, which mainly includes the improved coding mode, the improved switching function and the improved fitness function. Then, the BPSO is improved, in which the inertial weight in the algorithm has the adaptive ability, so that the particle can maintain better. At last, this algorithm is used to simulate and locate the fault of distribution network with DG. The results prove that the algorithm and the improved function can accurately locate fault places when the single point fault and multi point fault in the distribution network with DG.
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References
J. Sun, R. Chen, S. Cai, et al. A new fault location scheme for distribution system with distributed generations. Power Syst. Technol. 37(6), 1645–1650 (2013)
J. Liu, X. Dong, X. Chen, et al., Fault Location and Restoration for Distribution Systems (China Electric Power Press, Beijing, 2012), pp. 1–8
F. Hu, S. Sun, Fault location of distribution network by applying matrix algorithm based on graph theory. Electr. Power 49(3), 94–98 (2016)
S. Chen, Y. Ma, J. Fang, Application and analysis of genetic algorithm in fault location of intelligent distribution network. China Energy Environ. Prot. (12), 219–222 (2017)
C. Li, Z. He, H. Zhang, et al., Fault location for radicalized distribution networks based on BPSO algorithm. Power Syst. Prot. Control 37(7), 35–39 (2009)
X. Ruan, X. Zhang, Fault location of multi-sources power distribution network based on neural network. Coal Mine Mach. 35(2), 239–240 (2014)
Y. Wang, Application Study of Fault Location for Distribution Network Containing Distributed Generation (Taiyuan University of Technology, Taiyuan, 2017)
J. Zhao, Z. Tu, Y. Xie, Application of improved binary particle swarm optimization for fault location in distribution network with distributed generation. J. Heilongjiang Univ. Sci. Technol. 24(3), 277–281 (2014)
J. Kennedy, R.C. Eberhart, A discrete binary version of the particle swarm algorithm, in Proceeding of IEEE International Conference on Systems, Man, and Cybernetics, Orlando, USA (1997)
Y. Yao, Z. Wang, K. Guo, et al., Distribution network service restoration using a multi-objective binary particle swarm optimization based on e-dominance. Power Syst. Prot. Control (23), 76–81 (2014)
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© 2019 Springer Nature Singapore Pte Ltd.
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Meng, F., Zhao, S., Li, Z., Li, S. (2019). Distribution Network Fault Location Based on Improved Binary Particle Swarm Optimization. In: Jia, Y., Du, J., Zhang, W. (eds) Proceedings of 2018 Chinese Intelligent Systems Conference. Lecture Notes in Electrical Engineering, vol 528. Springer, Singapore. https://doi.org/10.1007/978-981-13-2288-4_19
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DOI: https://doi.org/10.1007/978-981-13-2288-4_19
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