Research on Fault Location in DC Distribution Network Based on Adaptive Artificial Bee Colony Slime Mould Algorithm-Reference-Cited by-同舟云学术

Research on Fault Location in DC Distribution Network Based on Adaptive Artificial Bee Colony Slime Mould Algorithm

Published:2023 Issue: Volume:11 Page:62630-62638
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Ma Tian-Xiang¹^ORCID,Duan Xin¹,Xu Yan²,Wang Ruo-Lin²,Li Xiao-Yu¹

Affiliation:

1. State Grid Hebei Electric Power Research Institute, Shijiazhuang, China

2. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University (Baoding), Baoding, China

Funder

Science and Technology Project of State Grid Corporation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10155120.pdf?arnumber=10155120

Reference21 articles.

1. Chaos-opposition-enhanced slime mould algorithm for minimizing the cost of energy for the wind turbines on high-altitude sites

2. An efficient binary slime mould algorithm integrated with a novel attacking-feeding strategy for feature selection

3. EOSMA: An Equilibrium Optimizer Slime Mould Algorithm for Engineering Design Problems

4. Normalized square difference based multilevel thresholding technique for multispectral images using leader slime mould algorithm

5. Fault location method of active distribution network based on improved artificial bee colony algorithm

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