Surface Cleanliness Identification of Photovoltaic Modules Based on Non-Linear Signals
The process of analyzing the surface cleanliness of photovoltaic modules is easily affected by nonlinear signals,leading to inaccurate identification results.In order to solve this problem,a nonlinear autoregressive identification technique for PV module surface cleanliness is proposed.The influence of dirt and hot spot effect on the power generation of PV modules is analyzed to obtain the time-domain response nonlinear signals on the surface of PV modules.Simulate the time-domain nonlinear unclean liness problem on the surface of PV modules,analyze the nonlinear signal units,extract the corresponding nonlinear features from the time-range re-sponse,and abate the interference of environmental uncertainties.Filter the time-range response linear signal by linear function,cal-culate probabilistic conditional variance,and determine the nonlinear autoregressive identification index.The nonlinear autoregressive dirty and hot spot effect recognition structure is constructed,and the dirty is recognized by the nonlinear autoregressive I-V curve,and the hot spot effect is recognized using the nonlinear autoregressive loss function.As can be seen from the experimental results,the dirty I-V characteristics identified using the studied technique show that when the voltage is 0,the short-circuit current is 0.41 A,and when the current is 0,the open-circuit voltage is 19.5 V;the identified hot spot effect I-V characteristics show that compared with the normal components,the open-circuit voltage and the short-circuit current affected by the hot spot effect have decreased,and the maximum open-circuit voltages are respectively 100,80 and 55 V,which is consistent with the actual data and has an accurate rec-ognition effect.
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