Study On The Microgrid Modeling Based On DIgSILENT And Harmonic And Inter-harmonic Analysis Methods

A microgrid is a single control unit consisted by distributed generator (DG) rated at tens of kilowatts, energy storage units, loads and control device. With the depth study and application of the microgrid, the quality problems caused by it have taken more and more people's attention, while one of the key indicators to measure power quality is the harmonics. Therefore, it is necessary for accurate detection and analysis the harmonics to achieve its governance.As there are many power electronic devices and nonlinear loads in the microgrid, which lead to harmonics and inter-harmonics pollution. Traditional FFT algorithm only can decompose integer harmonics. Because the presence of inter-harmonics and the changes of fundamental frequency, traditional FFT algorithm is difficult to achieve simultaneous sampling which will lead to spectral leakage and fence effect. For this situation, this paper presents a new harmonic and interharmonic analysis method based on cubic spline interpolation algorithm to reconstruct the waveform. Waveform reconstruction responses to the changes of fundamental frequency in microgrid, through the harmonic and interharmonic calculated step by step to reduce the interference between them, which will improve the inter-harmonic analysis accuracy.This paper modeled the main DG, including wind power systems, photovoltaic systems and energy storage batteries, and built low voltage distribution grid and microgrid model by DIgSILENT / Power Factory simulation software, which supplied the simulation basis for the harmonic analysis of the microgrid.To verify the cubic spline interpolation waveform reconstruction algorithm is effective, this paper used the algorithm to analysis the simulation current signal on different DG and different operating conditions (on-grid and island), and compared it with the traditional windowing two-line interpolation algorithm and the Newton interpolation waveform reconstruction algorithm. Through the results of analysis and comparison, the improved cubic spline interpolation waveform reconstruction algorithm has better analytical precision than plus Hanning window two-line interpolation algorithm, analytical precision of interharmonic improved greatly; has better analytical precision than Newton interpolation waveform reconstruction algorithm, and is easier to achieve. This algorithm takes more time than the windowing two-line interpolation algorithm. But taking into account the greatly increased analytical precision, it's not do more harm than good, and has good application prospects.