Study on power transformer protection based on chaos particle swarm optimization

2011 ◽  
Author(s):  
Han Han ◽  
Wang Houjun
Keyword(s):  
Particle Swarm Optimization ◽  
Power Transformer ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Transformer Protection

Power Transform Fault Diagnosis Based on the Adaptive Mutation Particle Swarm Optimization

2013 ◽  
Vol 756-759 ◽  
pp. 3804-3808
Author(s):  
Zhi Mei Duan ◽  
Jia Tang Cheng
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Fault Diagnosis ◽  
Power Transformer ◽  
Recognition Rate ◽  
Particle Swarm ◽  
Adaptive Mutation ◽  
Bp Network ◽  
Swarm Optimization ◽  
Fault Recognition

In order to improve the accuracy of fault diagnosis of power transformer, in this paper, a method is proposed that optimize the weight of BP neural network by adaptive mutation particle swarm optimization (AMPSO). According to the characteristic of transformer fault, the optimized neural network is used to diagnose fault of the power transformer. Individual particles action is amended by this algorithm and local minima problems of the standard PSO and BP network are overcooked. The experimental results show that, the method can classify transformer faults, and effectively improve the fault recognition rate.

Application of BP Neural Network Based on Immune Particle Swarm Optimization for Fault Diagnosis of Power Transformer

2013 ◽  
Vol 448-453 ◽  
pp. 3605-3609
Author(s):  
Yu Xin Zhang ◽  
Yu Liu
Keyword(s):  
Neural Network ◽  
Particle Swarm Optimization ◽  
Fault Diagnosis ◽  
Bp Neural Network ◽  
Power Transformer ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Network Training ◽  
Gradient Descent Algorithm ◽  
Ipso Algorithm

Cloing and hypermutation of immune theory were used in optimization on particle swarm optimization (PSO), an immune particle swarm optimization (IPSO) algorithm was proposed , which overcome the problem of premature convergence on PSO. IPSO was used in BP Neural Network training to overcome slow convergence speed and easily getting into local dinky value of gradient descent algorithm. BP Neural Network trained by IPSO was used to fault diagnosis of power transformer, it has high accuracy after experimental verification and to meet the power transformer diagnosis engineering requirements.

A Particle Swarm Optimization for Optimal Tolerance Design of Power Transformer Core Column Cross-Section

2010 ◽  
Vol 439-440 ◽  
pp. 74-79
Author(s):  
Jia Di Wan ◽  
Yuan Biao Zhang ◽  
Lei Cai ◽  
Chuan He
Keyword(s):  
Particle Swarm Optimization ◽  
Power Transformer ◽  
Sheet Material ◽  
Particle Swarm ◽  
Probabilistic Methods ◽  
Power Transformers ◽  
Utilization Rate ◽  
Tolerance Design ◽  
Swarm Optimization ◽  
Passing Rate

This paper presents a solution of the Optimal Tolerance Design Problems for the production of power transformers. Based on statistical and probabilistic methods, it establishes a multi-objective and multi-constraint mathematical model. We then present a solution that maximizes the effective utilization rate of sheet material, for producing core columns of power transformers, and the passing rate of quality controls of matching coils and cores. It also minimizes the Tolerance cost of the product. The solution uses Particle Swarm Optimization (PSO), which is very effective as shown by simulation results.

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