Grid Inverter Online Power Quality Analysis And Monitoring Module

Nowadays, the development of new energy likes a raging fire, and the prospect ofgrid-connected inverter market is broad. It is essential to guarantee indicators of inverterpower in line with the national utility grid quality standards and into the grid smoothly.Power quality is complex and changeable, the conditions of evoked accident are alsocomplex, and the quality decline will cause damage to the electrical equipment of thesystem, which sometimes is not apparent immediately, leaving a hidden danger for safeoperation.In this thesis, relying on the research topic of detection systems for lithium-ionbatteries, study the problem of lithium-ion battery charge and discharge module andpower feedback to grid. The inverter is the main object of the research, based onin-depth analysis of the theory and technology of today’s power quality testing,designing grid inverter online power quality analysis and monitoring module. Mainly asfollows:1. Proposed an adaptive algorithm for detection of harmonics and inter-harmonics.FFT transform on the sampled data to obtain signal spectral characteristics, calculatingthe harmonic content, at the same time Lagrange interpolation the signal spectrum.Introduce the concept of energy slider estimates. Estimating band and re-sampling,accurately detect inter-harmonics2. Comprehensive analysis of the IEC the recommended filter Design principle ofthe algorithm and the dynamic independent component analysis algorithm of blindsignal separation technology, selected the appropriate detection algorithms, separationflicker package, statistical assessment flicker value for the detection of voltagefluctuation and flicker.3. According to the time-frequency characteristics of wavelet transforms and thesingularity of modulus maxima of wavelet coefficients, Mallat algorithm is used todecompose signal. The beginning and ending times of disturbance signal are located bydetermining the singular points of the modulus maxima of the band at all levels. Thismethod can accurately and quickly locate the transient disturbances of inverter output signal. Taking into account the impact of noise on the results, before the waveletanalysis, the signal should carry out threshold de-noising.4. Combined with the grid-connected inverter structure, ARM+PC-based powerquality monitoring module is designed. In accordance with the actual situation andalgorithm requirements, the STM32family of ARM chips is selected as data acquisitionand control unit to complete the hardware design. The ARM peripheral design includesA/D5590acquisition circuit, clock, and power supply design. CAN bus is used to sendthe grid inverter output data to the PC side.