Photovoltaic Electric Field Research Articles

Study on Fault Monitoring Technology of Photovoltaic Panel Based on Thermal Infrared and Optical Remote Sensing

Abstract. Rapid access to the operating status of Photovoltaic (PV) panels and troubleshooting can save management and maintenance costs for the development of PV power plants, which is important for PV power plant management and power generation capacity assurance. The use of remote sensing technology to identify the faults of photovoltaic panels has developed rapidly, however, current research usually relies only on a single optical data source to identify and count the area of PV panels in a PV electric field, although there are literature on PV panel fault detection, only the surface fault identification of PV panels is tested, while the internal faults (such as panel bad points or bad lines) cannot be identified because of the limitations of optical remote sensing. In this paper, a photovoltaic panel fault monitoring technology based on multi-source remote sensing is proposed. The optical and thermal infrared hybrid data combined with deep learning technology are used to achieve rapid and accurate fault identification and localization of PV panel arrays. It can not only automatically identify PV panels that are obscured by dust and foreign objects, but also locate PV panels that have bad dots or bad lines, which greatly improves the ability and effectiveness of remote sensing PV panel fault monitoring. The high-resolution unmanned air vehicle (UAV) optical image and thermal infrared image are applied in this experiment. The Mask RCNN algorithm is used to accurately locate and number the photovoltaic panel of the optical image. Then, the fault scene classification model is established for the multi-type fault characteristics of the optical image and thermal infrared image within the panel range, so as to identify five types of faults, such as dust cover, branch cover, bird droppings cover, internal bad points and bad lines of PV panel, which effectively solves the problem that the single optical remote sensing image cannot identify the internal component faults of the photovoltaic panel under normal conditions.

Photo‐Induced Electric Field Effects on Water Droplets Generated in a LiNbO3 Opto‐Microfluidic Platform

AbstractIn this work, droplets elongation as a result of the photo‐induced photovoltaic electric field is presented and modeled. Moving water droplets are generated in microfluidics channels by means of a droplet‐based opto‐microfluidic platform integrated in lithium niobate (LN). A cross‐junction is engraved on the substrate as droplets generator, on top of which a z‐cut iron‐doped lithium niobate (Fe:LN) crystal is placed in order to build up photo‐induced electric field as a result of photovoltaic effect promoted upon suitable illumination. Droplets detection is realized by optical waveguides, designed in a Mach‐Zehnder Interferometer (MZI) configuration on the same substrate. The dynamics of droplet elongation is investigated, highlighting the impact of the photovoltaic electric field on the droplet dimension and surface tension.

Effect of PV panel electric field on the wind speed required for dust removal from the PV panels

Abstract Methods to remove dust deposits by high-speed airflow have significant potential applications, with optimal design of flow velocity being the core technology. In this paper, we discuss the wind speed required for particle removal from photovoltaic (PV) panels by compressed air by analyzing the force exerted on the dust deposited on inclined photovoltaic panels, which also included different electrification mechanisms of dust while it is in contact with the PV panel. The results show that the effect of the particle charging mechanism in the electric field generated by the PV panel is greatly smaller than the effect of the Van der Waals force and gravity, but the effect of the particle charged by the contact electrification mechanism in the electrostatic field is very pronounced. The wind speed required for dust removal from the PV panel increases linearly with the PV panel electric field, so we suggest that the nighttime, when the PV electric field is relatively small, would be more appropriate time for dust removal. The above results are of great scientific importance for accurately grasping the dust distribution law and for achieving scientific removal of dust on PV panels.

Optimal Allocation of Energy Storage Capacity of High-Permeability Photovoltaic Power Generation System Based on Elastic Neural Network

The energy storage capacity configuration of high permeability photovoltaic power generation system is unreasonable and the cost is high. Taking the constant capacity of hybrid energy storage system (Hess) composed of high permeability wind frame and super capacitor as the standard, in order to ensure smooth and stable output of photovoltaic power equipment, this paper adopts the power suppression method based on empirical mode decomposition to decompose the original power into high and low frequency components, and uses super capacitor and energy storage battery to stabilize the high and low frequency components, Reduce output power fluctuation; Taking the minimum energy storage cost as the objective function, the optimal allocation of system energy storage capacity is realized by the recursive algorithm of elastic neural network. The experimental results show that when the supercapacitor capacity and photovoltaic electric field energy storage cell capacity are 0.262 mw· h and 2.889 mw· h respectively, the minimum cost is 16987 yuan, and the smoothness index is less than 5%; Compared with before the optimal configuration, the output power of the photovoltaic power generation system after the optimal configuration is smoother, the power peak valley difference is lower, and the loss can be reduced.

All-Biobased Hydrovoltaic-Photovoltaic Electricity Generators for All-Weather Energy Harvesting.

Hygroelectricity generators (HEGs) utilize the latent heat stored in environmental moisture for electricity generation, but nevertheless are showing relatively low power densities due to their weak energy harvesting capacities. Inspired by epiphytes that absorb ambient moisture and concurrently capture sunlight for dynamic photosynthesis, we propose herein a scenario of all-biobased hydrovoltaic-photovoltaic electricity generators (HPEGs) that integrate photosystem II (PSII) with Geobacter sulfurreducens (G.s) for simultaneous energy harvesting from both moisture and sunlight. This proof of concept illustrates that the all-biobased HPEG generates steady hygroelectricity induced by moisture absorption and meanwhile creates a photovoltaic electric field which further strengthens electricity generation under sunlight. Under environmental conditions, the synergic hydrovoltaic-photovoltaic effect in HPEGs has resulted in a continuous output power with a high density of 1.24 W/m2, surpassing all HEGs reported hitherto. This work thus provides a feasible strategy for boosting electricity generation via simultaneous energy harvesting from ambient moisture and sunlight.

Photorefractive Effect in NLC Cells Caused by Anomalous Electrical Properties of ITO Electrodes

In a pure nematic liquid crystal (NLC) cell, optically induced charge carriers followed by transports in double border interfaces of orientant/LC and indium-tin-oxide (ITO)/orientant (or LC) can cause removal of screening of the static electric field inside the LC film. This is called surface photorefractive effect (SPR), which induces director field reorientation at a low DC electric field beyond the threshold at a reduced Fréedericksz transition and, as a result, a modulation of the LC effective refractive index. The studies conducted on the photoinduced opto-electrical responses in pure nematic LC cells biased with uniform static DC electric fields support the SPR effect (attributed to the photoelectric activation of the double interfaces). The SPR effect was further studied in LC cells with photoresponsive substrates, which act as a source of a bell-shaped electric field distribution in the LC film if no ITO electrode was employed. In an equipped cell with ITO, the photovoltaic electric field induces charge carrier redistribution in the ITO film, hence the SPR effect. This paper is aimed at highlighting all the evidences supporting ITO film as one of the fundamental sources of the SPR effect in pure NLC cells under the condition of applying low optical power and low DC voltage. An optically induced fringe electric field stemming from inhomogeneous photo-charge profiles near the electrode surfaces is expected in the LC film due to the semiconducting behavior of the ITO layer.

Ultra-short-term prediction method of photovoltaic electric field power based on ground-based cloud image segmentation

As a large number of photovoltaic power stations are built and put into operation, the total amount of photovoltaic power generation accounts for an increasing proportion of the total electricity. The inability to accurately predict solar energy output has brought great uncertainty to the grid. Therefore, predicting the future power of photovoltaic fields is of great significance. According to different time scales, predictions are divided into long-term, medium-term and ultra-short-term predictions. The main difficulty of ultra-short-term forecasting lies in the power fluctuations caused by sudden and drastic changes in environmental factors. The shading of clouds is directly related to the irradiance received on the surface of the photovoltaic panel, which has become the main factor affecting the fluctuation of photovoltaic power generation. Therefore, sky images captured by conventional cameras installed near solar panels can be used to analyze cloud characteristics and improve the accuracy of ultra-short-term predictions. This paper uses historical power information of photovoltaic power plants and cloud image data, combined with machine learning methods, to provide ultra-short-term predictions of the power generation of photovoltaic power plants. First, the random forest method is used to use historical power generation data to establish a single time series prediction model to predict ultra-short-term power generation. Compared with the continuous model, the root mean square (RMSE) error of prediction is reduced by 28.38%. Secondly, the Unet network is used to segment the cloud image, and the cloud amount information is analyzed and input into the random forest prediction model to obtain the bivariate prediction model. The experimental results prove that, based on the cloud amount information contained in the cloud chart, the bivariate prediction model has an 11.56% increase in prediction accuracy compared with the single time series prediction model, and an increase of 36.66% compared with the continuous model.

Massive ordering and alignment of cylindrical micro-objects by photovoltaic optoelectronic tweezers.

Optical tools for manipulation and trapping of micro- and nano-objects are a fundamental issue for many applications in nano- and biotechnology. This work reports on the use of one such method, known as photovoltaic optoelectronics tweezers, to orientate and organize cylindrical microcrystals, specifically elongated zeolite L, on the surface of Fe-doped LiNbO3 crystal plates. Patterns of aligned zeolites have been achieved through the forces and torques generated by the bulk photovoltaic effect. The alignment patterns with zeolites parallel or perpendicular to the substrate surface are highly dependent on the features of light distribution and crystal configuration. Moreover, dielectrophoretic chains of zeolites with lengths up to 100μm have often been observed. The experimental results of zeolite trapping and alignment have been discussed and compared together with theoretical simulations of the evanescent photovoltaic electric field and the dielectrophoretic potential. They demonstrate the remarkable capabilities of the optoelectronic photovoltaic method to orientate and pattern anisotropic microcrystals. The combined action of patterning and alignment offers a unique tool to prepare functional nanostructures with potential applications in a variety of fields such as nonlinear optics or plasmonics.

Light controlled phase shifter for optofluidics.

We report the light-induced control of optical phase shift by a liquid crystal cell made with LiNbO3:Fe crystals as substrates. We show that a phase shift of a few πs can be easily reached for two orthogonal polarizations due to liquid crystal reorientation driven by the photovoltaic electric field originated in the substrates. This effect is exploited to get all-optical switching with a contrast of about 80%, by 2 s pump pulse.

Short-Term Output Forecasting Model of Photovoltaic Electric Field Based on Wavelet Transform

As the meteorological parameter of numeric weather forecast model has systematic error, which leads to the restriction of forecast precision for photovoltaic electric field, the paper put forward a short-term output forecasting model of photovoltaic electric field based on wavelet transform. Wavelet transform algorithm that using 4 series of sym6 wavelet decomposition conducts a dynamic correction to the wind speed data outputted by numerical weather forecasting. Through combining other meteorological data, it formed a new amended meteorological data collection used to forecast the photovoltaic power; according to the two training set of both the original and the amended meteorological data, two prediction model based on original and amended neural network outputted by photovoltaic plant power are established. By comparing the measured data and model analysis data within a same period, it shows that the amended model can significantly reduce the RMSE of predict results and decrease the error from 70.66% to 70.66%, and increase the relative accuracy from 70.66% to 70.66%.

Universal theory of incoherently coupled spatial solitons families in photorefractive crystals

The incoherently coupled soliton families are predicted in photovoltaic photorefractive crystals illuminated by E-polarized incoherent uniform back-ground irradiation with a divider resistance under steady-state conditions. These soliton families can be established provided that the incident optical beams share the same polarization and wavelength, and are mutually incoherent. When these incoherent coupled soliton families propagate together, all components can propagate stably in photorefractive crystal. Moreover, such soliton families reduce into spatial soliton or incoherently coupled soliton pairs when they contain only one or two components. The 14 kinds of incoherently coupled spatial soliton families can be obtained from this theory by adjusting the value of the divider resistance, E-polarized back-ground irradiation, the biased electric field and photovoltaic electric field. Previous theories advanced individually elsewhere for these soliton families can be obtained by simplifying this theory under appropriate conditions.

Incoherently coupled screening photovoltaic spatial soliton pairs with a divider resistance

Steady-state incoherently coupled screening photovoltaic spatial soliton pairs are predicted for biased photorefractive crystal circuit with a divider resistance. All kinds of the incoherently coupled spatial soliton pairs can be obtained from this theory by adjusting the values of the divider resistance, the biased electric field and photovoltaic electric field, such as the incoherently coupled screening spatial soliton pairs in biased photorefractive crystal with or without a divider resistance, the photovoltaic spatial soliton pairs in open-circuit, the photovoltaic spatial soliton pairs in close-circuit with or without a divider resistance, the screening-photovoltaic spatial soliton pairs in biased photovoltaic-photorefractive crystal with or without a divider resistance. Previous theories advanced individually elsewhere for these soliton pairs can be obtained by simplifying this theory under appropriate conditions.

Anisotropic photorefraction in congruent magnesium-doped lithium niobate

A remarkable dependence of photorefractive response on c-axis orientation for lithium niobate samples at several magnesium contents has been observed. Above the well-known threshold concentration of magnesium, around 4.6 mol% MgO in congruent melt, the photorefraction almost disappears when the polar axis is parallel to the incidence plane of light beams in the two-wave mixing configuration. However, if the c-axis is perpendicular to the incidence plane the photorefractive effect persists even above threshold and it is strongly diminished below threshold. An explanation for this anisotropic behavior along with an estimation of bulk photovoltaic electric field through a proposed model has also been carried out.

Refractive-index profile and physical process determination in thick gratings in electrooptic crystals

A method for determining the refractive index profile of thick phase gratings in linear electrooptic crystals is presented. This method also determines the effective photovoltaic electric field and the relative contributions of diffusion and drift during hologram recording. The method requires only a knowledge of the modulation ratio during hologram recording and the fundamental and the higher-order diffraction efficiencies of the grating. As an illustration of the method, the refractive index profile, the effective photovoltaic field, and the relative contributions of diffusion and drift are determined from experimental measurements for a lithium niobate holographic grating.