The large-scale access to the power grid by distributed power sources makes the complexity of the distribution network increase, and the direction of the line trend is complex, which causes the accuracy of the fault location algorithm to be greatly reduced. Aiming at this problem, based on the increasingly improved distribution network automation system, this paper proposes a fault location method for Beetle Antennae Search based on an improved particle swarm optimization algorithm. In order to improve the convergence speed of the algorithm, this paper firstly introduces the adaptive inertia weights and initialises the population by using Tent chaotic mapping to avoid falling into the local optimal solution; furthermore, the switching function and the fitness function are established in order to locate the faults of the distribution network containing the DG; finally, the algorithm optimization is verified by using the MATLAB simulation program with the IEEE-33 node as the model of the faults of the distribution network. The results show that: the algorithm has higher search speed and accuracy in locating faulty segments in DG-containing distribution networks, and has good fault tolerance in case of signal distortion. Therefore, the hybrid BAS-PSO algorithm can locate faulty segments in distribution networks in a more scientific and reasonable way, which provides an effective implementation path to improve the ability to capture fault information and rapidly locate faulty segments.
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Xuenan Zhang (2024) studied this question.
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