Open AccessResearch on Detect of Power Quality Problems in DC Distribution Network
Author(s) -
XiaopingYang,
Chendi Wang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1639/1/012034
Subject(s) - realization (probability) , computer science , matlab , power (physics) , sparse approximation , algorithm , nondeterministic algorithm , field (mathematics) , matching (statistics) , decomposition , component (thermodynamics) , matching pursuit , representation (politics) , mathematical optimization , mathematics , compressed sensing , ecology , statistics , physics , thermodynamics , quantum mechanics , politics , political science , pure mathematics , law , biology , operating system
In recent years, sparseness-based representation methods have been studied in the field of signal processing. Among them, sparse decomposition based on Matching Pursuit is the most commonly used, but it is a NP difficult (Nondeterministic poly-nominal) problem essentially. The concept of infinity will increase the difficulty, affects its practicability. Aiming at the problem of the computational efficiency above, Matching Pursuit algorithm based on genetic algorithm is proposed to achieve sparse decomposition of signals. Then build a simulation model through MATLAB, simulate the actual DC distribution network, obtain power quality data, and use the algorithm proposed in this paper to verify, the results show that the algorithm is applied to the DC power distribution system power quality detection, in the realization of disturbance classification. At the same time, the characteristic parameters of the disturbance component can be obtained. This method not only can obtain the optimal atom with higher precision, but also can greatly reduce the calculation amount and improve the efficiency, which has certain practical value in engineering