CN115392494A - Intelligent photovoltaic ash removal method and system - Google Patents
Intelligent photovoltaic ash removal method and system Download PDFInfo
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Abstract
The invention provides an intelligent photovoltaic ash removal method and system, relates to the technical field of data processing, and obtains a dust deposition property analysis result by performing dust deposition analysis on a photovoltaic panel array; optimizing the initial photovoltaic panel inclination angle according to the dust deposition property analysis result to obtain an optimal photovoltaic panel inclination angle; generating a dust accumulation power generation loss prediction curve according to the optimal photovoltaic panel inclination angle and the dust accumulation property analysis result; generating a dust deposition cleaning cost curve based on historical cleaning data; and carrying out normalization treatment on the accumulated dust cleaning cost curve and the accumulated dust power generation loss prediction curve to obtain the photovoltaic ash removal period. The technical problem of when carrying out photovoltaic board and setting up among the prior art, the grillage inclination set up the side and acquire in the irradiation volume, lead to that photovoltaic panel deposition clean cost is higher, reduce photovoltaic power generation economic efficiency and hinder photovoltaic trade development is solved. The technical effects that the surface dust deposition and the sunlight radiation quantity are considered at the inclination angle of the photovoltaic panel, the dust cleaning period of the photovoltaic panel is changed in real time along with the state of the photovoltaic panel, and the dust cleaning cost is reduced are achieved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an intelligent photovoltaic ash removal method and system.
Background
With the continuous improvement of the technology in the field of photovoltaic power generation, the scale of photovoltaic power generation is getting stronger and the photovoltaic power generation is outstanding in clean energy. Theoretically, the larger the irradiation amount received by the photovoltaic panel in unit time is, the larger the output power of the photovoltaic power generation device is, but in actual production operation, the photovoltaic power generation device receives solar radiation in open environments such as a field grassland, and meanwhile, environmental dust gradually displaces along with wind and air and adheres to or deposits on the photovoltaic panel, so that the photovoltaic panel receives diffuse reflection, and the solar radiation amount is reduced.
In order to realize the power generation operation of the photovoltaic panel by receiving radiation, workers need to clean the photovoltaic panel regularly, and the cleaning period of the photovoltaic panel is often determined by the economic loss and the plot cost of dust accumulation power generation.
When having among the prior art and carrying out photovoltaic board and erect, the grillage inclination is on the side of the irradiation volume and is acquireed, leads to the clean cost of photovoltaic panel deposition higher, reduces the technical problem that photovoltaic power generation economic efficiency hinders photovoltaic trade development.
Disclosure of Invention
The application provides an intelligent photovoltaic ash removal method and system, which are used for solving the technical problems that when a photovoltaic panel is erected, the inclination angle of a panel frame is higher than the irradiation amount, so that the cleaning cost of the deposited ash of a photovoltaic panel is higher, and the photovoltaic power generation economic efficiency is reduced to hinder the development of the photovoltaic industry in the prior art.
In view of the above problems, the present application provides an intelligent photovoltaic ash removal method and system.
In a first aspect of the application, an intelligent photovoltaic ash removal method is provided, and the method comprises the following steps: obtaining an initial photovoltaic panel inclination angle of the photovoltaic panel array; carrying out dust accumulation analysis on the photovoltaic panel array to obtain a dust accumulation property analysis result; optimizing the initial photovoltaic panel inclination angle according to the dust deposition property analysis result to obtain an optimal photovoltaic panel inclination angle; obtaining a prediction curve of accumulated dust power generation loss according to the optimal photovoltaic panel inclination angle and the accumulated dust property analysis result; collecting historical cleaning data of the photovoltaic panel array; performing data curve fitting analysis according to the historical cleaning data, and outputting a dust deposition cleaning cost curve; and carrying out normalization treatment on the accumulated dust cleaning cost curve and the accumulated dust power generation loss prediction curve to obtain a photovoltaic ash removal period.
In a second aspect of the present application, there is provided a photovoltaic intelligent cleaning management system, the system comprising: the photovoltaic inclination angle generation module is used for obtaining an initial photovoltaic panel inclination angle of the photovoltaic panel array; the dust accumulation property analysis module is used for carrying out dust accumulation analysis on the photovoltaic panel array to obtain a dust accumulation property analysis result; the photovoltaic inclination angle optimization module is used for optimizing the initial photovoltaic panel inclination angle according to the dust deposition property analysis result to obtain an optimal photovoltaic panel inclination angle; the power generation loss generation module is used for obtaining a prediction curve of accumulated dust power generation loss according to the optimal photovoltaic panel inclination angle and the accumulated dust property analysis result; the historical data acquisition module is used for acquiring historical cleaning data of the photovoltaic panel array; the ash cleaning cost analysis module is used for performing data curve fitting analysis according to the historical cleaning data and outputting a dust deposition cleaning cost curve; and the dust cleaning period obtaining module is used for carrying out normalization treatment on the dust deposition cleaning cost curve and the dust deposition power generation loss prediction curve to obtain a photovoltaic dust cleaning period.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
according to the method provided by the embodiment of the application, the initial photovoltaic panel inclination angle of the photovoltaic panel array is obtained and is used as a reference for designing the actual erection inclination angle of the photovoltaic panel, dust accumulation analysis is carried out on the photovoltaic panel array, and a dust accumulation property analysis result is obtained; optimizing the initial photovoltaic panel inclination angle according to the dust deposition property analysis result to obtain an optimal photovoltaic panel inclination angle, so that the requirements of the photovoltaic panel inclination angle on the properties of a photovoltaic panel, the dust deposition property and the irradiation are met; obtaining a prediction curve of accumulated dust power generation loss according to the optimal photovoltaic panel inclination angle and the accumulated dust property analysis result, and providing a calculation reference for subsequent ash removal period determination; collecting historical cleaning data of the photovoltaic panel array, performing data curve fitting analysis according to the historical cleaning data, outputting a dust deposition cleaning cost curve, performing normalization processing on the dust deposition cleaning cost curve and the dust deposition power generation loss prediction curve, achieving compatibility of dust deposition loss cost and cleaning consumption cost, and obtaining a photovoltaic ash removal period. The photovoltaic panel dust removing device has the advantages that the photovoltaic panel erection inclination angle is achieved, the requirements of surface dust deposition and power generation radiation quantity of the photovoltaic panel are met, the photovoltaic panel dust removing period changes in real time along with the state of the photovoltaic panel, and the photovoltaic dust removing cost is low.
Drawings
FIG. 1 is a schematic flow diagram of an intelligent photovoltaic ash removal method provided herein;
FIG. 2 is a schematic flow chart of a dust deposition property analysis result obtained by the intelligent photovoltaic ash removal method provided by the present application;
FIG. 3 is a schematic flow chart of obtaining an optimal photovoltaic panel tilt angle in an intelligent photovoltaic ash removal method provided by the present application;
fig. 4 is a schematic structural diagram of a photovoltaic intelligent cleaning management system provided by the present application.
Description of reference numerals: the device comprises a photovoltaic inclination angle generation module 11, a dust deposition property analysis module 12, a photovoltaic inclination angle optimization module 13, a power generation loss generation module 14, a historical data acquisition module 15, a dust cleaning cost analysis module 16 and a dust cleaning period acquisition module 17.
Detailed Description
The application provides an intelligent photovoltaic ash removal method and system, which are used for solving the technical problems that when a photovoltaic panel is erected, the inclination angle of a panel frame is higher than the irradiation amount, so that the cleaning cost of the deposited ash of a photovoltaic panel is higher, and the photovoltaic power generation economic efficiency is reduced to hinder the development of the photovoltaic industry in the prior art.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
generating the optimal inclination angle of the photovoltaic panel based on the self attribute, the environmental dust deposition attribute and the power generation irradiation requirement of the photovoltaic panel, and calculating the power generation loss and the cleaning cost of the photovoltaic panel at the optimal inclination angle of the photovoltaic panel to generate a photovoltaic cleaning period with the lowest economic loss cost. The erection inclination angle of the photovoltaic panel is realized, the requirements of the surface dust accumulation and the power generation radiation quantity of the photovoltaic panel are met, the dust cleaning period of the photovoltaic panel is changed in real time along with the state of the photovoltaic panel, and the cost of the photovoltaic dust cleaning is low.
Example one
As shown in fig. 1, the application provides an intelligent photovoltaic ash removal method, which is applied to a photovoltaic intelligent cleaning management system, wherein the photovoltaic intelligent cleaning management system is in communication connection with a photovoltaic panel inclination angle adjusting device and a branch mutual inductor, and the method comprises the following steps:
s100, obtaining an initial photovoltaic panel inclination angle of the photovoltaic panel array;
further, an initial photovoltaic panel tilt angle of the photovoltaic panel array is obtained, and the step S100 of the method provided by the present application further includes:
s110, acquiring the geographical position information of the photovoltaic panel array;
s120, determining historical irradiation data according to the geographical position information;
and S130, determining an initial photovoltaic panel inclination angle according to the geographical position information and the historical irradiation data.
In particular, it should be understood that the inclination angle of the photovoltaic panel directly affects the amount of radiation that the photovoltaic panel can receive, and thus the amount of photovoltaic power generation. The historical irradiation data is a yearly radiant quantity data set generated by arranging a certain ground surface according to a time sequence.
In this embodiment, the latitude and longitude data of the photovoltaic panel array and the historical irradiation data are acquired according to the geographical position information of the photovoltaic panel array. And calculating and accumulating according to the historical irradiation data and the longitude and latitude data, and calculating to obtain a set of annual total radiation receiving quantity of the photovoltaic panel array under different photovoltaic panel inclination angles.
And sequencing the annual total radiant receiving quantity under different inclination angles of the photovoltaic panel to obtain the inclination angle of the photovoltaic panel corresponding to the maximum annual total radiant quantity as the initial inclination angle of the photovoltaic panel. The photovoltaic panel array receives the greatest amount of radiation at the initial photovoltaic panel tilt angle.
According to the embodiment, the calculation of the inclination angle of the photovoltaic panel corresponding to the annual maximum irradiation amount is carried out by combining the inclination angle of the photovoltaic panel through acquiring the geographic position information and the historical irradiation data of the photovoltaic panel array, so that the technical effect of providing an accurate inclination angle value for the adjustment of the inclination angle of the photovoltaic panel by combining the subsequent dust deposition cleaning is achieved.
S200, carrying out dust accumulation analysis on the photovoltaic panel array to obtain a dust accumulation property analysis result;
further, as shown in fig. 2, the method for analyzing the dust deposition of the photovoltaic panel array to obtain a result of analyzing the dust deposition property includes the following steps of:
s210, acquiring photovoltaic panel attribute information of the photovoltaic panel array;
s220, acquiring historical environment data according to the geographical position information;
s230, analyzing dust accumulation sources according to the historical environmental data to obtain a dust accumulation type information set consisting of a plurality of dust accumulation information;
s240, collecting the photovoltaic panel attribute information and the accumulated dust type information and inputting the collected information into a photovoltaic panel erosion damage analysis model to obtain an accumulated dust erosion damage result, wherein the accumulated dust erosion damage result is a plurality of groups of accumulated dust erosion scoring results;
s250, integrating the photovoltaic panel attribute information and the dust deposition type information into a photovoltaic panel adhesion analysis model to obtain a dust deposition adhesion analysis result, wherein the dust deposition adhesion analysis result is a plurality of groups of dust deposition adhesion scoring results;
and S260, carrying out weight assignment on the dust deposition erosion damage result and the dust deposition adhesion analysis result to generate a dust deposition property analysis result.
Specifically, the photovoltaic panel attribute information is a material attribute of the light-transmitting protective layer on the surface of the photovoltaic panel, for example, an organic-inorganic material having high light-transmitting property such as glass. The historical environmental data includes, but is not limited to, industrial plant information, soil acidity and alkalinity information, land desertification condition, land water content information and other environmental information related to the surface dust deposition condition of the geographical location.
The photovoltaic panel corrosion damage analysis model is a model capable of analyzing and determining whether the accumulated dust has corrosion interference on the photovoltaic panel material or not according to the material property of the photovoltaic panel and the chemical property of the accumulated dust deposited on the photovoltaic panel to cause diffuse reflection to reduce the radiation receiving capacity of the photovoltaic panel. The photovoltaic panel erosion damage model is provided with a plurality of dust accumulation erosion loss submodels, and each kind of dust accumulation corresponds to one dust accumulation erosion damage submodel.
The photovoltaic panel adhesion analysis model is a model capable of analyzing and determining displacement sliding or incapability of stagnation of accumulated dust under a specific photovoltaic panel inclination angle according to photovoltaic panel material properties and accumulated dust physical adhesion properties deposited on the photovoltaic panel. The photovoltaic panel erosion damage model is provided with a plurality of dust accumulation adhesion analysis submodels, and each kind of dust accumulation corresponds to one dust accumulation adhesion analysis submodel. And generating a dust adhesion scoring result based on the slip inclination angle data of the dust on the photovoltaic panel.
In this embodiment, by obtaining photovoltaic panel attribute information of the photovoltaic panel array, obtaining historical environmental data according to the geographic position information, and performing dust accumulation source analysis according to the historical environmental data, a dust accumulation type information set composed of a plurality of types of dust accumulation information is obtained, such as acid dust, alkaline dust, dry dust, sand, and the like.
And inputting the photovoltaic panel attribute information and the accumulated dust type information into a photovoltaic panel erosion damage analysis model in a gathering manner, and obtaining a plurality of groups of accumulated dust erosion scoring results to form accumulated dust erosion damage results. And integrating the photovoltaic panel attribute information and the dust accumulation type information into a photovoltaic panel adhesion analysis model, and obtaining a plurality of groups of dust accumulation adhesion scoring results to form a dust accumulation adhesion analysis result.
And summing a plurality of groups of accumulated dust erosion scoring results of the plurality of accumulated dust to obtain an accumulated dust erosion total score, and performing weight assignment on each accumulated dust erosion capacity based on the accumulated dust erosion total score. And summing a plurality of groups of dust adhesion analysis results of the plurality of kinds of dust to obtain a dust adhesion total score, and performing weight assignment on the adhesion capacity of each dust based on the dust adhesion total score. And adding and averaging the weight assignment of the adhesion capacity and the weight assignment of the erosion capacity of each dust deposit to generate a dust deposit property analysis result, wherein the dust deposit property analysis result reflects the erosion capacity of the photovoltaic panel and the adhesion capacity of the photovoltaic panel of the dust deposit.
The embodiment does not limit the training and construction method of the photovoltaic panel erosion damage analysis model and the photovoltaic panel adhesion analysis model. Optionally, in actual operation, model construction and training can be performed according to historical photovoltaic panel erosion and dust slip conditions.
According to the method, through constructing the photovoltaic panel erosion damage analysis model and the photovoltaic panel adhesion analysis model, the irradiation interference analysis of the physical properties and the chemical properties of the accumulated dust on the surface of the photovoltaic panel on the photovoltaic panel is carried out, the accumulated dust property analysis result with the correlation of the photovoltaic panel attributes is accurately obtained, the photovoltaic panel inclination angle is optimized for follow-up, and the technical effect of providing the accumulated dust property reference information for the photovoltaic panel inclination angle optimization with the overall consideration on the power generation irradiation requirement and the accumulated dust deposition requirement is achieved.
S300, optimizing the initial photovoltaic panel inclination angle according to the dust deposition property analysis result to obtain an optimal photovoltaic panel inclination angle;
further, as shown in fig. 3, the initial photovoltaic panel tilt angle is optimized according to the dust deposition property analysis result to obtain an optimal photovoltaic panel tilt angle, and the step S300 of the method provided by the present application further includes:
s310, acquiring the surface dust density based on the geographical position information;
s320, constructing a photovoltaic inclination angle optimization model;
s330, inputting the surface dust density, the dust deposition property analysis result and the initialized photovoltaic panel inclination angle into the photovoltaic inclination angle optimization model, and outputting an inclination angle adjusting coefficient;
s340, obtaining the optimal photovoltaic panel inclination angle according to the inclination angle adjusting coefficient and the initial photovoltaic panel inclination angle;
and S350, the inclination angle adjusting device of the photovoltaic panel adjusts the inclination angle of the photovoltaic panel array according to the inclination angle adjusting coefficient.
Specifically, it should be understood that there is no practical feasibility in the actual operation of the surface dust collection performed according to a short-term time sequence such as a month or a week, and therefore the present embodiment collects the rain erosion amount to calculate the surface dust density based on the natural dust collection amount of the geographical location where the large data is obtained. The ground dust density is the integral dust situation of the geographical position of the photovoltaic panel array.
The photovoltaic inclination angle optimization model is a generation optimization model which is used for carrying out coordination generation on an inclination angle adjusting coefficient according to the dust deposition property analysis result, the dust deposition amount and the power generation radiation amount to guide the standard inclination angle adjustment of the photovoltaic panel. The inclination angle adjusting coefficient is an angle value for adjusting the inclination angle of the initial photovoltaic panel, and comprises a positive number and a negative number, when the angle value is the positive number, the inclination angle is adjusted clockwise, and when the angle value is the negative number, the inclination angle is adjusted anticlockwise.
The embodiment does not set any limit to the construction of the photovoltaic inclination angle optimization model. Illustratively, the photovoltaic inclination angle optimization model can be composed of a master control Agent, a dust deposition adjusting Agent, an irradiation adjusting Agent and an inclination angle dust deposition changing Agent. The main control Agent is used for coordinating the dust deposition adjusting Agent, the irradiation adjusting Agent and the inclination angle dust deposition changing Agent; and outputting the inclination angle adjusting coefficient based on the coordination action among a plurality of agents.
In this embodiment, the optimal photovoltaic panel inclination angle is obtained by inputting the surface dust accumulation density, the dust accumulation property analysis result, and the initialized photovoltaic panel inclination angle into the photovoltaic inclination angle optimization model, outputting an inclination angle adjustment coefficient, and using the inclination angle adjustment coefficient and the initial photovoltaic panel inclination angle, and the photovoltaic panel inclination angle adjustment device adjusts the inclination angle of the photovoltaic panel array according to the inclination angle adjustment coefficient.
This embodiment is through combining the accumulation and the erosion situation of electricity generation irradiation intensity demand and laying dust on photovoltaic board surface, and is intended initial photovoltaic board inclination improves, has reached and has obtained the laying dust degree of difficulty and has risen, does not influence the photovoltaic board inclination that the normal electricity generation irradiation of photovoltaic board needs simultaneously, reduces the technical effect of the power generation loss that the laying dust caused, compares in that traditional photovoltaic board inclination confirms that the mode is more comprehensive to the consideration of various environmental factors to photovoltaic board electricity generation influence.
S400, obtaining a prediction curve of accumulated dust power generation loss according to the optimal photovoltaic panel inclination angle and the accumulated dust property analysis result;
further, according to the optimal photovoltaic panel inclination angle and the accumulated dust property analysis result, an accumulated dust power generation loss prediction curve is obtained, and the method provided by the application further comprises the following steps of S400:
s410, carrying out output power change analysis according to the accumulated dust and the output power of the photovoltaic panel array to obtain a power time sequence change curve;
s420, obtaining the highest output power according to the power time sequence variation curve to be used as the dust-free output power of the photovoltaic panel;
s430, carrying out de-diversification treatment according to the power time sequence change curve to generate a power change correction curve;
s440, generating an ideal power output curve according to the dustless output power of the photovoltaic panel;
s450, calculating to obtain comprehensive electricity price information based on big data;
and S460, generating the accumulated dust power generation loss prediction curve according to the power change correction curve and the ideal power output curve and by combining the comprehensive electricity price information.
Specifically, it should be understood that no matter the inclination angle of the photovoltaic panel is geometric, deposition of ambient dust on the surface of the photovoltaic panel cannot be avoided, and therefore the calculation of the dust deposition power generation loss is performed based on the theoretical photovoltaic panel power generation power and the actual photovoltaic panel power generation power in the embodiment.
In this embodiment, output power change analysis is performed according to the accumulated dust and the output power of the photovoltaic panel array, photovoltaic panel power change data of the accumulated dust on the surface of the photovoltaic panel along with time change are obtained, and the power time sequence change curve is generated according to the photovoltaic panel power change data and the corresponding recording time sequence, and is a curve scatter diagram.
And obtaining the highest output power as the dust-free output power of the photovoltaic panel according to the power time sequence variation curve, wherein the dust-free output power of the photovoltaic panel is the power generation power of the photovoltaic panel under an ideal state, and generating an ideal power output curve based on the dust-free output power of the photovoltaic panel.
And carrying out de-differentiation treatment according to the power time sequence change curve, removing abnormal scattered points deviating from the curve, and generating a power change correction curve, wherein the power change correction curve can accurately reflect the influence degree of the deposited dust on the generating power of the photovoltaic panel.
And calculating to obtain comprehensive electricity price information based on big data, subtracting the power change correction curve and the ideal power output curve, calculating a processing result and the comprehensive electricity price information according to a time sequence to generate a dust accumulation electricity generation loss prediction curve, wherein the dust accumulation electricity generation loss curve is an electricity generation economic loss curve caused by dust accumulation under the time sequence.
According to the embodiment, the market electricity price is obtained, and the comprehensive calculation is carried out by combining the power generation loss caused by the dust deposition, so that the technical effect of accurately knowing the power generation economic loss information of the photovoltaic panel array which is installed at a specific geographic position under the influence of the dust deposition is achieved under the condition that the dust deposition is not carried out.
S500, collecting historical cleaning data of the photovoltaic panel array;
s600, performing data curve fitting analysis according to the historical cleaning data, and outputting a dust deposition cleaning cost curve;
in particular, it will be appreciated that as the residence time of the dirt on the photovoltaic panel increases, the difficulty of cleaning it on the photovoltaic panel increases. The historical cleaning data is cleaning cost information of a unit area when the photovoltaic panel array is cleaned historically, cleaning cost is in an ascending trend along with different deposition and adhesion time of deposited dust on the photovoltaic panel, and data curve fitting analysis is performed based on the historical plot data to obtain the dust deposition cleaning cost curve.
S700, carrying out normalization treatment on the accumulated dust cleaning cost curve and the accumulated dust power generation loss prediction curve to obtain a photovoltaic ash removal period.
Further, the accumulated dust cleaning cost curve and the accumulated dust power generation loss prediction curve are normalized to obtain a photovoltaic ash removal period, and the step S700 of the method provided by the application further includes:
s710, carrying out normalization processing on the accumulated dust cleaning cost curve and the accumulated dust power generation loss prediction curve to obtain an image intersection point of the accumulated dust cleaning cost curve and the accumulated dust power generation loss prediction curve;
s720, tracing to obtain the photovoltaic ash removal period according to the image intersection point;
s730, obtaining predicted precipitation information in the photovoltaic ash removal period;
s740, inputting the predicted precipitation information, the dust deposition property analysis result and the optimal photovoltaic panel inclination angle into a cleaning effect prediction model, wherein the cleaning effect prediction model is used for judging whether the photovoltaic panel array is cleaned according to the photovoltaic ash removal period;
s750, when the output result of the cleaning effect prediction model is 1, cleaning the photovoltaic panel array according to the photovoltaic ash removal period;
and S760, when the output result of the cleaning effect prediction model is 0, generating a photovoltaic panel ash cleaning optimization cycle according to the predicted precipitation information, and cleaning the photovoltaic panel array.
Specifically, in this embodiment, the dust deposition cleaning cost curve and the dust deposition power generation loss prediction curve are normalized and included in the same curve image, an image intersection point of the dust deposition cleaning cost curve and the dust deposition power generation loss prediction curve is obtained, a power reduction time sequence is obtained according to the image intersection point, and the photovoltaic ash removal period is generated according to the power reduction time sequence and the power initial recording time sequence.
The cleaning effect prediction model is used for analyzing and outputting the cleaning effect of the photovoltaic panel based on the inclination angle, the dust deposition property and the precipitation information of the photovoltaic panel. The embodiment does not limit the construction of the cleaning effect prediction model, and the construction and training of the model can be performed according to the needs in practical implementation.
It should be understood that, when environmental rainfall occurs, rainwater may also clean the photovoltaic panel, so to further reduce the plot, in this embodiment, predicted rainfall information in the photovoltaic ash removal period is obtained, where the predicted rainfall information includes predicted rainfall time and rainfall intensity information, the predicted rainfall information, the dust deposition property analysis result, and the optimal photovoltaic panel inclination angle are input into a cleaning effect prediction model, and it is determined whether to clean the photovoltaic panel array according to the photovoltaic ash removal period, and when an output result of the cleaning effect prediction model is 1, it is indicated that the cleaning effect does not meet the photovoltaic panel cleaning requirement, and the photovoltaic panel array is cleaned according to the photovoltaic ash removal period; and when the output result of the cleaning effect prediction model is 0, the surface cleaning effect meets the cleaning requirement of the photovoltaic panel, and a photovoltaic panel ash cleaning optimization period is generated according to the predicted precipitation information to clean the photovoltaic panel array. The "1" and "0" have no practical meaning, i.e. represent whether the data result is qualified or not.
The clean effect prediction model is built, the original clean period is adjusted by combining natural environment precipitation, the clean cost is further reduced, and the technical effect of improving the economic benefit of photovoltaic power generation is achieved.
According to the method provided by the embodiment, the initial photovoltaic panel inclination angle of the photovoltaic panel array is obtained and is used as the reference for designing the actual erection inclination angle of the photovoltaic panel, and the photovoltaic panel array is subjected to dust accumulation analysis to obtain a dust accumulation property analysis result; optimizing the initial photovoltaic panel inclination angle according to the dust deposition property analysis result to obtain an optimal photovoltaic panel inclination angle, so that the requirements of the photovoltaic panel inclination angle on the properties of a photovoltaic panel, the dust deposition property and the irradiation are met; obtaining a prediction curve of accumulated dust power generation loss according to the optimal photovoltaic panel inclination angle and the accumulated dust property analysis result, and providing a calculation reference for subsequent ash removal period determination; collecting historical cleaning data of the photovoltaic panel array, performing data curve fitting analysis according to the historical cleaning data, outputting a dust deposition cleaning cost curve, performing normalization processing on the dust deposition cleaning cost curve and the dust deposition power generation loss prediction curve, achieving compatibility of dust deposition loss cost and cleaning consumption cost, and obtaining a photovoltaic ash removal period. The photovoltaic panel dust removal device has the advantages that the erection inclination angle of the photovoltaic panel is achieved, the requirements of the surface dust deposition and the power generation radiation quantity of the photovoltaic panel are met, the dust removal period of the photovoltaic panel is changed in real time along with the state of the photovoltaic panel, and the photovoltaic dust removal cost is low.
Further, the method provided by the present application further includes:
s810, acquiring historical monitoring data of the photovoltaic panel array;
s820, acquiring photovoltaic branch surface temperature data of the photovoltaic panel array according to the branch mutual inductor;
s830, comparing the photovoltaic branch surface temperature data with the historical monitoring data, and outputting abnormal detection data;
s840, judging whether the photovoltaic panel array has hot spot phenomenon or not according to the abnormal detection data;
and S850, when the photovoltaic array is judged to have the hot spot phenomenon, carrying out hot spot photovoltaic panel positioning on the photovoltaic panel array according to the abnormal detection data.
In particular, it is understood that the hot spot effect can produce the result of directly damaging the photovoltaic panel, as compared to the interference of the photovoltaic panel deposition on the generation irradiance. Therefore, when the photovoltaic panel array is cleaned by the periodical dust deposition, the photovoltaic panel array is monitored in real time and early-warning treatment is carried out in time, and the photovoltaic panel is prevented from being irreversibly damaged by the hot spot effect.
In this embodiment, the branch mutual inductor is assembled based on the photovoltaic panel array, and the branch mutual inductor is a sensing device for monitoring and recording the current, voltage, power and surface temperature data of the photovoltaic module generated by each photovoltaic branch of the photovoltaic panel array in real time.
And traversing the branch mutual inductor to detect the obtained historical monitoring data of each photovoltaic branch, and generating an abnormal comparison reference data set. And acquiring surface temperature data of each photovoltaic branch of the photovoltaic panel array according to the branch mutual inductor.
And acquiring instant temperature data according to the photovoltaic branch surface temperature data, traversing the historical monitoring data by combining with the environmental weather information, acquiring historical monitoring photovoltaic panel branch data consistent with the environmental weather information, comparing the historical monitoring photovoltaic panel branch data with the environmental weather information, and outputting abnormal detection data.
And according to the abnormal detection data, carrying out photovoltaic branch circuits corresponding to the abnormal detection data, and judging whether the photovoltaic panel array has partial photovoltaic panel hot spot phenomenon or not by combining an image acquisition device. When the abnormal detection data and the image acquisition device display that the corresponding photovoltaic panel has the hot spot phenomenon, the working personnel clean the photovoltaic panel quickly and accurately according to the hot spot phenomenon.
This embodiment combines image acquisition device to carry out quick analysis to the photovoltaic board hot spot phenomenon of contingency through introducing branch sensor and handles, has reached the technological cleanness to photovoltaic board contingency pollution, eliminates the single technological effect who relies on the clean hidden danger that produces of periodicity.
Example two
Based on the same inventive concept as the intelligent photovoltaic ash removal method in the foregoing embodiment, as shown in fig. 4, the present application provides a photovoltaic intelligent cleaning management system, wherein the system includes:
a photovoltaic inclination angle generation module 11, configured to obtain an initial photovoltaic panel inclination angle of the photovoltaic panel array;
the dust accumulation property analysis module 12 is used for analyzing dust accumulation of the photovoltaic panel array to obtain a dust accumulation property analysis result;
the photovoltaic inclination angle optimization module 13 is configured to perform initial photovoltaic panel inclination angle optimization according to the dust deposition property analysis result to obtain an optimal photovoltaic panel inclination angle;
a power generation loss generation module 14, configured to obtain a prediction curve of power generation loss due to dust deposition according to the optimal photovoltaic panel inclination angle and the analysis result of the dust deposition property;
the historical data acquisition module 15 is used for acquiring historical cleaning data of the photovoltaic panel array;
the ash cleaning cost analysis module 16 is used for performing data curve fitting analysis according to the historical cleaning data and outputting a dust deposition cleaning cost curve;
and the ash cleaning period obtaining module 17 is used for carrying out normalization processing on the accumulated dust cleaning cost curve and the accumulated dust power generation loss prediction curve to obtain a photovoltaic ash cleaning period.
Further, the photovoltaic tilt angle generation module 11 further includes:
the azimuth information retrieval unit is used for acquiring the geographic position information of the photovoltaic panel array;
the irradiation data acquisition unit is used for determining historical irradiation data according to the geographical position information;
and the photovoltaic inclination angle calculation unit is used for determining an initial photovoltaic panel inclination angle according to the geographical position information and the historical irradiation data.
Further, the dust deposition property analysis module 12 further includes:
the panel attribute obtaining unit is used for obtaining photovoltaic panel attribute information of the photovoltaic panel array;
the environment data retrieval unit is used for acquiring historical environment data according to the geographical position information;
a dust type obtaining unit, configured to perform dust source analysis according to the historical environment data to obtain a dust type information set including a plurality of types of dust information;
the accumulated dust erosion analysis unit is used for inputting the photovoltaic panel attribute information and the accumulated dust type information into a photovoltaic panel erosion damage analysis model in a gathering manner to obtain an accumulated dust erosion damage result, wherein the accumulated dust erosion damage result is a plurality of groups of accumulated dust erosion scoring results;
the dust adhesion analysis unit is used for inputting the photovoltaic panel attribute information and the dust type information into a photovoltaic panel adhesion analysis model in a set mode to obtain a dust adhesion analysis result, and the dust adhesion analysis result is a plurality of groups of dust adhesion scoring results;
and the dust deposition property analysis unit is used for carrying out weight assignment on the dust deposition corrosion damage result and the dust deposition adhesion analysis result to generate a dust deposition property analysis result.
Further, the photovoltaic tilt angle optimization module 13 further includes:
the earth surface dust search unit is used for obtaining earth surface dust density based on the geographical position information;
the optimization model construction unit is used for constructing a photovoltaic inclination angle optimization model;
the adjusting coefficient calculating unit is used for inputting the surface dust density, the dust deposition property analysis result and the initialized photovoltaic panel inclination angle into the photovoltaic inclination angle optimization model and outputting an inclination angle adjusting coefficient;
the optimal inclination angle calculation unit is used for obtaining the optimal inclination angle of the photovoltaic panel according to the inclination angle adjustment coefficient and the initial inclination angle of the photovoltaic panel;
and the inclination angle adjusting execution unit is used for adjusting the inclination angle of the photovoltaic panel array by the photovoltaic panel inclination angle adjusting device according to the inclination angle adjusting coefficient.
Further, the power generation loss generation module 14 further includes:
the interference curve generating unit is used for carrying out output power change analysis according to the accumulated dust and the output power of the photovoltaic panel array to obtain a power time sequence change curve;
the ideal power obtaining unit is used for obtaining the highest output power according to the power time sequence variation curve and using the highest output power as the dust-free output power of the photovoltaic panel;
the curve correction execution unit is used for carrying out de-differentiation processing according to the power time sequence change curve to generate a power change correction curve;
the ideal power drawing unit is used for generating an ideal power output curve according to the dustless output power of the photovoltaic panel;
the electricity price information retrieval unit is used for calculating and obtaining comprehensive electricity price information based on the big data;
and the loss curve generating unit is used for generating the accumulated dust power generation loss prediction curve according to the power change correction curve and the ideal power output curve and by combining the comprehensive electricity price information.
Further, the ash removal period obtaining module 17 further includes:
a curve intersection point generating unit, configured to perform normalization processing on the accumulated dust cleaning cost curve and the accumulated dust power generation loss prediction curve to obtain an image intersection point of the accumulated dust cleaning cost curve and the accumulated dust power generation loss prediction curve;
the ash removal period generation unit is used for tracing and obtaining the photovoltaic ash removal period according to the image intersection point;
the prediction information obtaining unit is used for obtaining predicted precipitation information in the photovoltaic ash removal period;
the dust cleaning period judging unit is used for inputting the predicted precipitation information, the dust deposition property analysis result and the optimal photovoltaic panel inclination angle into a cleaning effect prediction model, and the cleaning effect prediction model is used for judging whether the photovoltaic panel array is cleaned according to the photovoltaic dust cleaning period;
a judgment result execution unit, configured to, when an output result of the cleaning effect prediction model is 1, perform cleaning of the photovoltaic panel array according to the photovoltaic ash removal cycle;
and the ash cleaning period changing unit is used for generating an ash cleaning optimization period of the photovoltaic panel according to the predicted precipitation information when the output result of the cleaning effect prediction model is 0, and cleaning the photovoltaic panel array.
Further, the method provided by the present application further includes:
the monitoring data acquisition unit is used for acquiring historical monitoring data of the photovoltaic panel array;
the photovoltaic temperature acquisition unit is used for acquiring photovoltaic branch surface temperature data of the photovoltaic panel array according to the branch mutual inductor;
the abnormal data comparison unit is used for comparing the photovoltaic branch surface temperature data with the historical monitoring data and outputting abnormal detection data;
the hot spot phenomenon judging unit is used for judging whether the photovoltaic panel array has a hot spot phenomenon or not according to the abnormal detection data;
and the photovoltaic hot spot positioning unit is used for positioning the hot spot photovoltaic panel of the photovoltaic panel array according to the abnormal detection data after judging that the photovoltaic array has the hot spot phenomenon.
Any of the methods or steps described above may be stored as computer instructions or programs in various non-limiting types of computer memory and identified by various non-limiting types of computer processors to implement any of the methods or steps described above.
Based on the above embodiments of the present invention, those skilled in the art should make any improvements and modifications to the present invention without departing from the principle of the present invention, and therefore, the present invention should fall into the protection scope of the present invention.
Claims (8)
1. An intelligent photovoltaic ash removal method is applied to a photovoltaic intelligent cleaning management system, the photovoltaic intelligent cleaning management system is in communication connection with a photovoltaic panel inclination angle adjusting device and a branch mutual inductor, and the method comprises the following steps:
obtaining an initial photovoltaic panel inclination angle of the photovoltaic panel array;
carrying out dust accumulation analysis on the photovoltaic panel array to obtain a dust accumulation property analysis result;
optimizing the initial photovoltaic panel inclination angle according to the dust deposition property analysis result to obtain an optimal photovoltaic panel inclination angle;
obtaining a prediction curve of accumulated dust power generation loss according to the optimal photovoltaic panel inclination angle and the accumulated dust property analysis result;
collecting historical cleaning data of the photovoltaic panel array;
performing data curve fitting analysis according to the historical cleaning data, and outputting a dust deposition cleaning cost curve;
and carrying out normalization treatment on the accumulated dust cleaning cost curve and the accumulated dust power generation loss prediction curve to obtain a photovoltaic ash removal period.
2. The method of claim 1, wherein obtaining an initial photovoltaic panel tilt angle for the array of photovoltaic panels comprises:
obtaining geographic location information of the photovoltaic panel array;
determining historical irradiation data according to the geographical position information;
and determining an initial photovoltaic panel inclination angle according to the geographical position information and the historical irradiation data.
3. The method of claim 2, wherein performing a dust deposition analysis on the array of photovoltaic panels to obtain a dust deposition property analysis result comprises:
acquiring photovoltaic panel attribute information of the photovoltaic panel array;
obtaining historical environment data according to the geographical position information;
performing dust accumulation source analysis according to the historical environmental data to obtain a dust accumulation type information set consisting of a plurality of kinds of dust accumulation information;
the photovoltaic panel attribute information and the dust accumulation type information are input into a photovoltaic panel erosion damage analysis model in a gathering mode, and a dust accumulation erosion damage result is obtained and is a plurality of groups of dust accumulation erosion scoring results;
the photovoltaic panel attribute information and the dust accumulation type information are input into a photovoltaic panel adhesion analysis model in a gathering mode, and dust accumulation adhesion analysis results are obtained and are multiple groups of dust accumulation adhesion scoring results;
and carrying out weight assignment on the accumulated dust erosion damage result and the accumulated dust adhesion analysis result to generate an accumulated dust property analysis result.
4. The method of claim 3, wherein performing the initial photovoltaic panel tilt angle optimization based on the dust deposition property analysis results to obtain an optimal photovoltaic panel tilt angle comprises:
obtaining the earth surface dust density based on the geographical position information;
constructing a photovoltaic inclination angle optimization model;
inputting the surface dust density, the dust deposition property analysis result and the initialized photovoltaic panel inclination angle into the photovoltaic inclination angle optimization model, and outputting an inclination angle adjusting coefficient;
obtaining the optimal photovoltaic panel inclination angle according to the inclination angle adjusting coefficient and the initial photovoltaic panel inclination angle;
and the photovoltaic panel inclination angle adjusting device adjusts the inclination angle of the photovoltaic panel array according to the inclination angle adjusting coefficient.
5. The method of claim 1, wherein obtaining a dust deposition power generation loss prediction curve based on the optimal photovoltaic panel tilt angle and the dust deposition property analysis result comprises:
carrying out output power change analysis according to the accumulated dust and the output power of the photovoltaic panel array to obtain a power time sequence change curve;
obtaining the highest output power according to the power time sequence variation curve and using the highest output power as the dust-free output power of the photovoltaic panel;
carrying out de-differentiation processing according to the power time sequence change curve to generate a power change correction curve;
generating an ideal power output curve according to the dustless output power of the photovoltaic panel;
calculating to obtain comprehensive electricity price information based on big data;
and generating the accumulated dust power generation loss prediction curve according to the power change correction curve and the ideal power output curve and by combining the comprehensive electricity price information.
6. The method of claim 1, wherein normalizing the accumulated dust cleaning cost curve and the accumulated dust power generation loss prediction curve to obtain a photovoltaic ash removal cycle comprises:
normalizing the accumulated dust cleaning cost curve and the accumulated dust power generation loss prediction curve to obtain an image intersection point of the accumulated dust cleaning cost curve and the accumulated dust power generation loss prediction curve;
tracing to obtain the photovoltaic ash removal period according to the image intersection point;
obtaining predicted precipitation information in the photovoltaic ash removal period;
inputting the predicted precipitation information, the dust deposition property analysis result and the optimal photovoltaic panel inclination angle into a cleaning effect prediction model, wherein the cleaning effect prediction model is used for judging whether the photovoltaic panel array is cleaned according to the photovoltaic ash removal period;
when the output result of the cleaning effect prediction model is 1, cleaning the photovoltaic panel array according to the photovoltaic ash removal period;
and when the output result of the cleaning effect prediction model is 0, generating a photovoltaic panel deashing optimization cycle according to the predicted precipitation information, and cleaning the photovoltaic panel array.
7. The method of claim 1, comprising:
acquiring historical monitoring data of the photovoltaic panel array;
acquiring photovoltaic branch surface temperature data of the photovoltaic panel array according to the branch mutual inductor;
comparing the photovoltaic branch surface temperature data with the historical monitoring data, and outputting abnormal detection data;
judging whether the photovoltaic panel array has a hot spot phenomenon or not according to the abnormal detection data;
and when the photovoltaic array is judged to have the hot spot phenomenon, positioning the hot spot photovoltaic panel of the photovoltaic panel array according to the abnormal detection data.
8. A photovoltaic intelligent cleaning management system, characterized in that the system comprises:
the photovoltaic inclination angle generation module is used for obtaining an initial photovoltaic panel inclination angle of the photovoltaic panel array;
the dust accumulation property analysis module is used for carrying out dust accumulation analysis on the photovoltaic panel array to obtain a dust accumulation property analysis result;
the photovoltaic inclination angle optimization module is used for optimizing the initial photovoltaic panel inclination angle according to the dust deposition property analysis result to obtain an optimal photovoltaic panel inclination angle;
the power generation loss generation module is used for obtaining a prediction curve of accumulated dust power generation loss according to the optimal photovoltaic panel inclination angle and the accumulated dust property analysis result;
the historical data acquisition module is used for acquiring historical cleaning data of the photovoltaic panel array;
the ash cleaning cost analysis module is used for performing data curve fitting analysis according to the historical cleaning data and outputting a dust deposition cleaning cost curve;
and the dust cleaning period obtaining module is used for carrying out normalization treatment on the dust deposition cleaning cost curve and the dust deposition power generation loss prediction curve to obtain a photovoltaic dust cleaning period.
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| CN116232222A (en) * | 2023-05-10 | 2023-06-06 | 山东科技大学 | Cloud edge cooperative dust accumulation degree monitoring method and system for distributed photovoltaic system |
| CN117522156A (en) * | 2023-10-17 | 2024-02-06 | 江苏尚诚能源科技有限公司 | Distributed photovoltaic prediction evaluation method and system based on big data analysis |
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| CN116232222A (en) * | 2023-05-10 | 2023-06-06 | 山东科技大学 | Cloud edge cooperative dust accumulation degree monitoring method and system for distributed photovoltaic system |
| CN116232222B (en) * | 2023-05-10 | 2023-09-08 | 山东科技大学 | Cloud edge cooperative dust accumulation degree monitoring method and system for distributed photovoltaic system |
| CN117522156A (en) * | 2023-10-17 | 2024-02-06 | 江苏尚诚能源科技有限公司 | Distributed photovoltaic prediction evaluation method and system based on big data analysis |
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