Abstract
The photovoltaic array can be used as a medium for carrier communication to realize monitoring of photovoltaic components. Photovoltaic array channel noise, especially the pulse-type noise therein, seriously interferes carrier communication, so it is necessary to grasp the characteristics of the photovoltaic array channel noise. Photovoltaic array channel noise modeling is a key process when conducting anti-noise immunity tests of monitoring equipment. Based on the time-domain waveform of photovoltaic series channel noise which is measured in a photovoltaic power station, this paper proposes a photovoltaic array noise modeling method of Wavelet Peak-Type Markov chain, and studies the influence on modeling accuracy when different mother wavelets are adopted for modeling. From the simulation results, root mean square errors of the predicted output for Haar, Biorthogonal and Daubechies wavelet-based function modeling case are 0.9614 V, 1.4915 V and 0.7928 V, respectively, validating that Daubechies wavelet-based function is the best wavelet-based function of modeling. In the case that the peak of original noise reaches 20 V, the predicted mean absolute error of this model is only 0.4926 V, which not only verifies the applicability of the Wavelet Peak-Type Markov chain model to the photovoltaic array channel noise, but also verifies the applicability to the pulse-type noise.
Highlights
With the rapid development of the photovoltaic industry, fault monitoring in photovoltaic power plants has become an important issue because the performance of photovoltaic modules affects the output characteristics of photovoltaic arrays directly, further affecting the stability of the photovoltaic generation system [1]
In [10], A single DC wire carrier communication mode is adopted among photovoltaic modules to transmit the operation status data of photovoltaic modules in a photovoltaic power station, which uses the photovoltaic array as a medium for carrier communication without adding extra wiring for communication
In order to solve the problem of modeling the mass pulse-type noise in photovoltaic array channel noise, this paper proposes a method of Wavelet Peak-Type Markov chain, and studies the influence on modeling accuracy when different mother wavelets are used for modeling, based on the time-domain waveform of photovoltaic array channel noise which is measured in photovoltaic power station
Summary
With the rapid development of the photovoltaic industry, fault monitoring in photovoltaic power plants has become an important issue because the performance of photovoltaic modules affects the output characteristics of photovoltaic arrays directly, further affecting the stability of the photovoltaic generation system [1]. In [18], an AR autoregressive model is established for low-voltage AC power line channel background noise, but AR models are not suitable for pulse-type noise analysis in photovoltaic array channels. In [20], a Peak-Type Markov chain modeling method is proposed, which is suitable for the modeling of background noise and impulse noise, but there is still a certain gap between the model output and the original noise in the frequency domain characteristics obtained by simulation; In another study [21], a low-voltage power line background noise Wavelet-Markov chain modeling method was proposed. The noise model can accurately fit the time-domain waveform of the periodic pulse-type noise and the background noise in the photovoltaic array channel, providing a theoretical basis for studying the noise characteristics of photovoltaic array channels
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