Abstract
A new method for fault location of a power distribution network based on Improved Cuckoo Search Algorithm is proposed. Cuckoo Search Algorithm uses Levy flight to simulate the global parasitic propagation mechanism of the cuckoo population. Therefore, the algorithm avoids falling into local optimum easily. According to the requirements of quickness and accuracy for fault location, the algorithm is improved by combining the search step size of the algorithm and the number of iterations. It improves the algorithm's early iteration speed and subsequent search accuracy. In this paper, the improved Cuckoo Search Algorithm is used to generate random status for all line segments. Then, convert it to the expected status for each switch. And next, update the line segment status by iteration of the algorithm, which makes the expected status of the switches approach to status uploaded by the FTU. Finally, the model outputs the fault location. In this way, a new generic switching function is proposed. It is suitable for single or multiple faults under single and multiple power conditions, which greatly extends the range of applications and versatility. In the evaluation function, the anti-false positive factor and the assumed fault number are introduced. Both of them improve effectiveness and adaptability. And, the validity of these ideas was proved by simulation. Compared with Cuckoo Search Algorithm, Binary Particle Swarm Optimization Algorithm and Genetic Algorithm, Improved Cuckoo Search Algorithm turns out to be good at finding an optimal solution to multiple faults location problems with a faster convergence speed and higher accuracy.
Highlights
The distribution network plays a very important role in delivering power to users
Compared with Cuckoo Search Algorithm, Binary Particle Swarm Optimization Algorithm and Genetic Algorithm, the Improved Cuckoo Search Algorithm has the advantages of fast convergence speed and high accuracy, and can well solve the problem of multiple fault location
In (11): r is the search step size; iter is the current number of iterations; NG is the maximum number of iterations; Ub is the upper bound of the variable; Lb is the lower bound of the variable; t indicates that the optimal solution has not changed for continuous t iterations
Summary
The distribution network plays a very important role in delivering power to users. Due to a huge number of various devices are used, the network architecture tends to be complex. They use the already-trained artificial neural networks to judge the fault location [8]–[10] X. Huang et al.: Fault Location of Distribution Network Base on Improved CS Algorithm single-power radiation-type distribution networks. Huang et al.: Fault Location of Distribution Network Base on Improved CS Algorithm single-power radiation-type distribution networks This idea greatly improves the effectiveness of judging the fault location. This paper applies the Cuckoo Search Algorithm(CS) to the fault location in power distribution networks. CS uses Lévy flight to simulate the global parasitic propagation mechanism of the cuckoo population In this way, the algorithm avoids falling into local optimum . The anti-false positive factor and the assumed fault number are introduced Both of them improve their effectiveness and adaptability. Compared with Cuckoo Search Algorithm, Binary Particle Swarm Optimization Algorithm and Genetic Algorithm, the Improved Cuckoo Search Algorithm has the advantages of fast convergence speed and high accuracy, and can well solve the problem of multiple fault location
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