Application of fuzzy control harmonic suppression and reactive power compensation technology for power electronic equipment based on cloud computing

2020 ◽  
pp. 1-11
Author(s):  
Zhimei Duan ◽  
Xiaojin Yuan ◽  
Rongfei Zhu

Harmonic pollution and reactive power consumption are the two most important factors affecting power quality. Power electronics, as the largest harmonic source, will produce a large number of harmonics while running, and will also lose reactive power, reduce the power factor of the system and affect power quality. Firstly, the current situation of reactive power and harmonic suppression based on fuzzy control is briefly introduced. Then, the harmonic component and power factor of the power grid are taken as two objective functions to model the power grid. The improved particle swarm optimization (PSO) genetic algorithm is used to establish the harmonic suppression and reactive power compensation model. To improve the design efficiency, aiming at the complexity of the algorithm and the field measurement data, the reactive power compensation device is quickly solved on the Hadoop cloud computing platform to achieve the global optimal compensation effect, to improve the convergence speed and global search ability of the particle swarm optimization algorithm. Thus, based on ensuring the power factor, the harmonic component is restrained and the safety and reliability of power grid operation are improved.

2012 ◽  
Vol 229-231 ◽  
pp. 1030-1033
Author(s):  
Wei Cui ◽  
Lin Chuan Li ◽  
Lei Zhang ◽  
Qian Sun

The reactive power compensation optimization in distribution network has the important meaning in maintaining system voltage stability, decreasing network loss and reducing operation costs. In order to meet factual conditions, we assume the system operates in minimum, normal and maximum three load modes and the objective function of problem includes the costs of power loss and the dynamic reactive power compensation devices allocated. In this paper we use Artificial Immune Algorithm(AIA) and Particle Swarm Optimization Algorithm(PSO) to determine compensate nodes and use the back/forward sweep algorithm calculate load flows. After applied into 28-nodes system, the result demonstrates the method is feasible and effective.


2018 ◽  
Vol 1087 ◽  
pp. 042084
Author(s):  
Jingjing Yang ◽  
Song Wang ◽  
Tian Yan ◽  
Ruining He ◽  
Pengtao Dong ◽  
...  

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