Intelligent cleaning method and system for photovoltaic module of water area photovoltaic power station

Abstract

The invention discloses an intelligent cleaning method and system for a photovoltaic module of a water area photovoltaic power station. The intelligent cleaning method comprises the steps of obtaining and extracting characteristic parameters influencing pollution of the photovoltaic module in a current-voltage curve of the photovoltaic module; comprehensively evaluating the pollution degree evaluation value of the photovoltaic module based on the data value corresponding to each characteristic parameter; acquiring local irradiance and temperature to determine a theoretical power value of the photovoltaic module; determining the actual power value of the photovoltaic module, and determining the efficiency loss rate of the photovoltaic module based on the actual power value and the theoretical power value; and comprehensively determining a cleaning difficulty coefficient based on the pollution degree evaluation value and the efficiency loss rate of the photovoltaic module, and performing intelligent cleaning based on the determined cleaning mode. According to the invention, pollution degree quantification is realized by accurately extracting I-V curve parameters, theoretical power is calculated in combination with irradiance and temperature data, the efficiency loss rate is dynamically evaluated, and the cleaning difficulty coefficient is comprehensively generated to trigger intelligent decision, so that the power generation efficiency can be improved, the operation and maintenance cost can be reduced, and the water resource consumption can be reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic power generation, and in particular to an intelligent cleaning method and system for photovoltaic components of a water photovoltaic power station. Background Art

[0002] As the global energy structure shifts toward cleaner, lower-carbon energy, water-based photovoltaic power stations, owing to their "photovoltaic + water-based" hybrid utilization model, have become a key development direction in the renewable energy sector. Compared to traditional ground-based power stations, water-based photovoltaics can improve module power generation efficiency by approximately 5%-10% through the cooling effect of water bodies, while also reducing land resource occupation, making them particularly suitable for coastal and lake areas where land is scarce. However, photovoltaic modules exposed to aquatic environments for long periods of time face severe pollution challenges: pollutants such as algae adhesion, salt spray crystallization, plankton accumulation, and bird excrement form a shielding layer on the module surface, resulting in a decrease in light transmittance and hot spot effects, significantly reducing power generation efficiency (an average annual loss can reach 15%-25%) and accelerating module aging.

[0003] The limitations of traditional manual cleaning methods are highlighted in aquatic scenarios: on the one hand, the floating platform has a complex structure and sparsely distributed components, manual operation is inefficient and costly (accounting for more than 30% of the power station's operation and maintenance costs), and there are safety hazards of falling into the water; on the other hand, extensive cleaning can easily cause water resource waste and chemical cleaning agent pollution, threatening the ecological balance of the aquatic area. Summary of the Invention

[0004] In order to solve the above technical problems, the present invention provides a method and system for intelligent cleaning of photovoltaic modules of a water photovoltaic power station, comprising: Obtaining the current-voltage curve of the photovoltaic module and performing parameter extraction on the current-voltage curve of the photovoltaic module to obtain characteristic parameters that affect the pollution of the photovoltaic module; Determining a data value corresponding to each characteristic parameter, and comprehensively determining a contamination degree assessment value of the photovoltaic module based on the data value corresponding to each characteristic parameter; Obtain local irradiance and temperature, and determine the theoretical power value of the photovoltaic module based on the irradiance and temperature; Determine an actual power value of the photovoltaic module, and determine an efficiency loss rate of the photovoltaic module based on the actual power value and a theoretical power value of the photovoltaic module; The cleaning difficulty coefficient of the photovoltaic module is comprehensively determined based on the pollution degree assessment value and efficiency loss rate of the photovoltaic module, and the cleaning method is determined based on the cleaning difficulty coefficient for intelligent cleaning.

[0005] Furthermore, the current-voltage curve of the photovoltaic module is obtained, and parameters of the current-voltage curve of the photovoltaic module are extracted to obtain characteristic parameters that affect the pollution of the photovoltaic module, including: The current-voltage curve of the photovoltaic module is obtained, and parameters of the current-voltage curve of the photovoltaic module are extracted to obtain characteristic parameters affecting the pollution of the photovoltaic module, wherein the characteristic parameters affecting the pollution of the photovoltaic module include short-circuit current, fill factor and series resistance.

[0006] Furthermore, determining the data value corresponding to each characteristic parameter and comprehensively determining the pollution degree assessment value of the photovoltaic module based on the data value corresponding to each characteristic parameter includes: Determining data values ​​corresponding to each characteristic parameter and standard data values ​​corresponding to each characteristic parameter when the photovoltaic module is in a clean state, and determining a current attenuation rate, a fill factor loss rate, and a series resistance growth rate based on the data values ​​and the standard data values; Determine corresponding preset values ​​for the current decay rate, fill factor loss rate, and series resistance growth rate, respectively; calculate the differences between the current decay rate, fill factor loss rate, and series resistance growth rate and the corresponding preset values; and evaluate these differences to obtain a current decay evaluation value, a fill factor loss evaluation value, and a series resistance growth evaluation value; The pollution degree assessment value of the photovoltaic module is calculated based on the current attenuation assessment value, the fill factor loss assessment value and the series resistance growth assessment value. The calculation formula of the pollution degree assessment value of the photovoltaic module is: S=a*ΔI+b*ΔFF+c*ΔR, Wherein, S is the pollution degree assessment value of the photovoltaic module, a is the first preset weight, ΔI is the current attenuation assessment value, b is the second preset weight, ΔFF is the fill factor loss assessment value, c is the third preset weight, and ΔR is the series resistance growth assessment value.

[0007] Furthermore, the obtaining of local irradiance and temperature and determining the theoretical power value of the photovoltaic module based on the irradiance and temperature includes: Obtain the local irradiance and temperature, and calculate the theoretical power value of the photovoltaic module based on the irradiance and temperature. The calculation formula for the theoretical power value of the photovoltaic module is: P0 = G / G S × P S × (1 - k(T - T S )), Among them, P0 is the theoretical power value of the photovoltaic module, G is the local irradiance, G S is the irradiance of photovoltaic modules under standard test conditions, P S is the nominal maximum power of the photovoltaic module under standard test conditions, k is the power temperature coefficient of the photovoltaic module, T is the local temperature, T S is the temperature of the photovoltaic module under standard test conditions.

[0008] Furthermore, determining the actual power value of the photovoltaic module and determining the efficiency loss rate of the photovoltaic module based on the actual power value and the theoretical power value of the photovoltaic module includes: Determine the actual power value of the photovoltaic module, and calculate the efficiency loss rate of the photovoltaic module based on the actual power value and the theoretical power value of the photovoltaic module. The calculation formula for the efficiency loss rate of the photovoltaic module is: N = (P0 - P1) / P0 × 100%, Among them, N is the efficiency loss rate of the photovoltaic module, P0 is the theoretical power value of the photovoltaic module, and P1 is the actual power value of the photovoltaic module.

[0009] Furthermore, the comprehensive determination of the cleaning difficulty coefficient of the photovoltaic module based on the pollution degree assessment value and efficiency loss rate of the photovoltaic module includes: Calculating the difference between the efficiency loss rate of the photovoltaic module and the preset loss rate, and evaluating the difference to obtain an efficiency loss evaluation value; The pollution degree assessment value and the efficiency loss assessment value are added together to obtain a comprehensive pollution value of the photovoltaic module, and a cleaning difficulty coefficient is determined based on the comprehensive pollution value of the photovoltaic module; A corresponding relationship between the cleaning difficulty coefficient and the comprehensive pollution value interval is pre-set, wherein the corresponding relationship between the cleaning difficulty coefficient and the comprehensive pollution value interval is associated with a corresponding cleaning difficulty coefficient for each comprehensive pollution value interval; The comprehensive pollution value of the photovoltaic component is obtained, and based on the mapping relationship between the comprehensive pollution value interval to which the comprehensive pollution value belongs and the corresponding relationship between the cleaning difficulty coefficient and the comprehensive pollution value interval, the cleaning difficulty coefficient corresponding to the comprehensive pollution value interval is selected as the cleaning difficulty coefficient of the photovoltaic component.

[0010] Furthermore, the intelligent cleaning method is determined based on the cleaning difficulty coefficient, including: Determine whether the cleaning difficulty coefficient exceeds a preset threshold, and determine the cleaning method based on the determination result; If the cleaning difficulty coefficient exceeds the preset threshold, mechanical cleaning is used for cleaning; If the cleaning difficulty coefficient does not exceed the preset threshold, water-based cleaning is used for cleaning.

[0011] The present invention also provides a photovoltaic module intelligent cleaning system for a water photovoltaic power station, comprising: An acquisition module is used to obtain the current-voltage curve of the photovoltaic module and perform parameter extraction on the current-voltage curve of the photovoltaic module to obtain characteristic parameters that affect the pollution of the photovoltaic module; An evaluation module, configured to determine a data value corresponding to each characteristic parameter, and comprehensively determine a contamination degree evaluation value of the photovoltaic module based on the data value corresponding to each characteristic parameter; A calculation module is used to obtain the local irradiance and temperature and determine the theoretical power value of the photovoltaic module based on the irradiance and temperature; A determination module is used to determine an actual power value of the photovoltaic module, and determine an efficiency loss rate of the photovoltaic module based on the actual power value and the theoretical power value of the photovoltaic module; The cleaning module is used to comprehensively determine the cleaning difficulty coefficient of the photovoltaic module based on the pollution degree assessment value and efficiency loss rate of the photovoltaic module, and determine the cleaning method based on the cleaning difficulty coefficient for intelligent cleaning.

[0012] Compared with the prior art, the intelligent cleaning method and system for photovoltaic modules of a water photovoltaic power station according to the embodiment of the present invention have the following beneficial effects: The present invention quantifies the degree of pollution by accurately extracting IV curve parameters, calculates theoretical power by combining irradiance and temperature data, dynamically evaluates efficiency loss rate, and comprehensively generates a cleaning difficulty coefficient to trigger intelligent decision-making. This can improve power generation efficiency, reduce operation and maintenance costs, and reduce water consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 1 is a schematic diagram of the process structure of the intelligent cleaning method for photovoltaic modules of a water photovoltaic power station according to an embodiment of the present invention; Figure 2 Schematic diagram of the composition of the intelligent cleaning system for photovoltaic modules of a water photovoltaic power station according to an embodiment of the present invention. DETAILED DESCRIPTION

[0014] The following embodiments are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0015] In the description of this application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the platform or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on this application.

[0016] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0017] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood broadly. For example, they can refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Persons of ordinary skill in the art will understand the specific meanings of the above terms in this application based on specific circumstances.

[0018] like Figure 1 As shown, in an embodiment of the present application, a method for intelligent cleaning of photovoltaic modules of a water photovoltaic power station is provided, including: S100: obtaining a current-voltage curve of the photovoltaic module, and performing parameter extraction on the current-voltage curve of the photovoltaic module to obtain characteristic parameters that affect the pollution of the photovoltaic module; S200: determining the data value corresponding to each characteristic parameter, and comprehensively determining the pollution degree assessment value of the photovoltaic module based on the data value corresponding to each characteristic parameter; S300: obtaining the local irradiance and temperature, and determining the theoretical power value of the photovoltaic module based on the irradiance and temperature; S400: determining the actual power value of the photovoltaic module, and determining the efficiency loss rate of the photovoltaic module based on the actual power value and the theoretical power value of the photovoltaic module; S500: comprehensively determining the cleaning difficulty coefficient of the photovoltaic module based on the pollution degree assessment value and the efficiency loss rate of the photovoltaic module, and determining the cleaning method based on the cleaning difficulty coefficient for intelligent cleaning.

[0019] Furthermore, the present invention quantifies the degree of pollution by accurately extracting IV curve parameters, calculates theoretical power by combining irradiance and temperature data, dynamically evaluates efficiency loss rate, and comprehensively generates a cleaning difficulty coefficient to trigger intelligent decision-making, which can improve power generation efficiency, reduce operation and maintenance costs, and reduce water consumption.

[0020] In an embodiment of the present application, a method for intelligent cleaning of photovoltaic modules of a water photovoltaic power station is provided, wherein the method obtains a current-voltage curve of the photovoltaic module and extracts parameters of the current-voltage curve of the photovoltaic module to obtain characteristic parameters that affect the contamination of the photovoltaic module, including: obtaining the current-voltage curve of the photovoltaic module and extracting parameters of the current-voltage curve of the photovoltaic module to obtain characteristic parameters that affect the contamination of the photovoltaic module, wherein the characteristic parameters that affect the contamination of the photovoltaic module include short-circuit current, fill factor and series resistance.

[0021] Specifically, in photovoltaic systems, the current-voltage (IV) curve is one of the important curves that describes the operating state of photovoltaic modules. Analyzing and extracting parameters from the IV curve of PV modules can reveal their performance under different operating conditions, including the impact of pollution. Using photovoltaic test instruments or data acquisition systems, PV modules can be tested on IV curves to obtain their current and voltage values ​​at different operating points. Parameter extraction also involves characteristic parameters that affect PV module pollution, including the short-circuit current (Isc): Under illuminated conditions, the maximum output current of a PV module in the short-circuit state represents the maximum output capacity of the PV module under sufficient sunlight. Pollution reduces light transmittance, resulting in a decrease in short-circuit current. Fill factor (FF): A key parameter reflecting the performance of PV module cells. It is the ratio of the output power at the maximum power point (MPP) to the product of the short-circuit current and the open-circuit voltage. A decrease in fill factor leads to a decrease in the output power of the PV module, affecting the overall efficiency of the PV system. Series resistance (Rs): A key parameter in the internal circuit of a PV module, series resistance represents the impact of the internal resistance of the PV module on current transmission. Pollution can reduce the surface reflectivity of the PV module, thereby affecting the magnitude of the series resistance. By extracting these characteristic parameters, this step can accurately assess the contamination level of PV modules, take timely cleaning or maintenance measures, and improve the power generation efficiency of the PV system. Understanding the changes in these characteristic parameters can help determine the optimal cleaning strategy to minimize the impact of contamination on the performance of PV modules and improve the system's ability to operate stably in the long term. By monitoring and maintaining the characteristic parameters of PV modules, problems can be discovered and measures can be taken in a timely manner, thereby improving the power generation efficiency and reliability of the PV system and extending the service life of PV modules.

[0022] In an embodiment of the present application, a method for intelligent cleaning of photovoltaic modules of a water photovoltaic power station is provided, wherein the method determines the data value corresponding to each characteristic parameter and comprehensively determines the pollution degree assessment value of the photovoltaic module based on the data value corresponding to each characteristic parameter, including: determining the data value corresponding to each characteristic parameter and the standard data value corresponding to each characteristic parameter when the photovoltaic module is in a clean state, and determining the current decay rate, fill factor loss rate and series resistance growth rate based on the data value and the standard data value; determining corresponding preset values ​​for the current decay rate, fill factor loss rate and series resistance growth rate respectively, taking the difference between the current decay rate, fill factor loss rate and series resistance growth rate and the corresponding preset values, and evaluating these differences to obtain a current decay assessment value, a fill factor loss assessment value and a series resistance growth assessment value; and calculating the pollution degree assessment value of the photovoltaic module based on the current decay assessment value, the fill factor loss assessment value and the series resistance growth assessment value, wherein the calculation formula for the pollution degree assessment value of the photovoltaic module is: S=a*ΔI+b*ΔFF+c*ΔR, Wherein, S is the pollution degree assessment value of the photovoltaic module, a is the first preset weight, ΔI is the current attenuation assessment value, b is the second preset weight, ΔFF is the fill factor loss assessment value, c is the third preset weight, and ΔR is the series resistance growth assessment value.

[0023] Specifically, determine the current short-circuit current, fill factor and series resistance values ​​of the PV module, and determine the standard short-circuit current, fill factor and series resistance values ​​of the PV module in a clean state; current decay rate: calculate the difference between the actual short-circuit current and the standard short-circuit current to reflect the degree of current decay of the PV module; fill factor loss rate: calculate the difference between the actual fill factor and the standard fill factor to evaluate the degree of fill factor loss of the PV module; series resistance growth rate: calculate the difference between the actual series resistance and the standard series resistance to characterize the growth of the series resistance of the PV module; according to the preset weights and the difference of each parameter, calculate the current decay evaluation value, fill factor loss evaluation value and series resistance growth evaluation value, which reflect the degree of loss in various aspects of the PV module under pollution conditions; use the current decay evaluation value, fill factor loss evaluation value and series resistance growth evaluation value, combined with the preset weights, to calculate the pollution degree evaluation value of the PV module, which can provide a basis for cleaning and maintenance decisions. This step, by comprehensively considering the changes in multiple characteristic parameters, can more accurately assess the degree of contamination of PV modules and formulate targeted cleaning and maintenance strategies. Based on the assessment value, cleaning measures can be taken in a timely manner to reduce the impact of contamination on PV module performance and improve system efficiency. Through scientific evaluation and maintenance, the life of PV modules can be extended and the long-term performance and stability of the system can be improved.

[0024] In an embodiment of the present application, a method for intelligently cleaning photovoltaic modules of a water photovoltaic power station is provided. The method of obtaining local irradiance and temperature and determining a theoretical power value of the photovoltaic module based on the irradiance and temperature includes: obtaining local irradiance and temperature, and calculating the theoretical power value of the photovoltaic module based on the irradiance and temperature. The calculation formula for the theoretical power value of the photovoltaic module is: P0 = G / G S × P S × (1 - k(T - T S )), Among them, P0 is the theoretical power value of the photovoltaic module, G is the local irradiance, G S is the irradiance of photovoltaic modules under standard test conditions, P S is the nominal maximum power of the photovoltaic module under standard test conditions, k is the power temperature coefficient of the photovoltaic module, T is the local temperature, T S is the temperature of the photovoltaic module under standard test conditions.

[0025] Specifically, the theoretical power value of the photovoltaic module is calculated, where irradiance (G) represents the light energy flux density per unit area, which is the solar radiation energy received by the photovoltaic module; the irradiance of the photovoltaic module under rated conditions; the nominal maximum power under standard test conditions (P S ) represents the rated maximum output power of the photovoltaic module under standard test conditions; the power temperature coefficient (k) represents the rate of change of the photovoltaic module power with temperature; temperature (T) represents the local ambient temperature; temperature under standard test conditions (T S ) represents the rated temperature of the PV module. The theoretical power value (P0) of a PV module is calculated by considering the effects of local irradiance and temperature on PV module performance. Temperature significantly affects the output power of a PV module, so a temperature correction factor must be considered when calculating the theoretical power. When the temperature exceeds the standard test conditions, the value of the power temperature coefficient k will cause the theoretical power value to decrease. This step calculates the theoretical power value of the PV module by considering the local irradiance and temperature, providing a more accurate assessment of the actual output capacity of the PV module. Understanding the theoretical power value of PV modules under different environmental conditions helps optimize system design and operation strategies, improving the power generation efficiency of the PV system. By calculating the theoretical power of PV modules, the power generation potential of the PV system can be better utilized, improving energy utilization efficiency and reducing energy costs.

[0026] In an embodiment of the present application, a method for intelligent cleaning of photovoltaic modules of a water photovoltaic power station is provided. The method of determining the actual power value of the photovoltaic module and determining the efficiency loss rate of the photovoltaic module based on the actual power value and the theoretical power value of the photovoltaic module includes: determining the actual power value of the photovoltaic module and calculating the efficiency loss rate of the photovoltaic module based on the actual power value and the theoretical power value of the photovoltaic module. The calculation formula of the efficiency loss rate of the photovoltaic module is: N = (P0 - P1) / P0 × 100%, Among them, N is the efficiency loss rate of the photovoltaic module, P0 is the theoretical power value of the photovoltaic module, and P1 is the actual power value of the photovoltaic module.

[0027] Specifically, the current output power of the PV module obtained through actual testing or monitoring; the theoretical power value of the PV module calculated according to the formula mentioned above; the efficiency loss rate (N) represents the difference between the actual output power of the PV module and the theoretical output power, expressed as a percentage; the efficiency loss rate (N) of the PV module is calculated by the difference between the actual power value and the theoretical power value. This value reflects the performance loss of the PV module due to various factors during actual operation. By calculating the efficiency loss rate, this step can accurately evaluate the actual performance of the PV module and help monitor the operating status of the PV system. The efficiency loss rate can help identify the reasons for the decline in PV module performance, and then take appropriate measures to optimize system performance and improve power generation efficiency. Promptly discovering and resolving PV module performance issues helps maintain system stability and long-term efficient operation.

[0028] In an embodiment of the present application, a method for intelligent cleaning of photovoltaic modules of a water photovoltaic power station is provided, wherein the cleaning difficulty coefficient of the photovoltaic module is comprehensively determined based on the pollution degree assessment value and efficiency loss rate of the photovoltaic module, including: calculating the difference between the efficiency loss rate of the photovoltaic module and a preset loss rate, and evaluating the difference to obtain an efficiency loss assessment value; adding the pollution degree assessment value and the efficiency loss assessment value to obtain a comprehensive pollution value of the photovoltaic module, and determining the cleaning difficulty coefficient based on the comprehensive pollution value of the photovoltaic module; presetting a corresponding relationship between the cleaning difficulty coefficient and the comprehensive pollution value interval, wherein the corresponding relationship between the cleaning difficulty coefficient and the comprehensive pollution value interval is associated with a corresponding cleaning difficulty coefficient for each comprehensive pollution value interval; obtaining the comprehensive pollution value of the photovoltaic module, and based on the mapping relationship between the comprehensive pollution value interval to which the comprehensive pollution value belongs within the corresponding relationship between the cleaning difficulty coefficient and the comprehensive pollution value interval, selecting the cleaning difficulty coefficient corresponding to the comprehensive pollution value interval as the cleaning difficulty coefficient of the photovoltaic module.

[0029] Specifically, a loss rate is pre-set for evaluating the performance of photovoltaic modules. The difference between the efficiency loss rate and the pre-set loss rate is calculated to evaluate the performance loss of the photovoltaic modules. The pollution level assessment value represents the degree of pollution suffered by the photovoltaic modules. The value obtained by adding the efficiency loss assessment value and the pollution level assessment value is used to comprehensively evaluate the pollution of the photovoltaic modules. The cleaning difficulty coefficients corresponding to different comprehensive pollution value intervals are pre-set. The comprehensive pollution value interval to which the photovoltaic module belongs is determined based on the comprehensive pollution value of the photovoltaic module, and the corresponding cleaning difficulty coefficient is found within the corresponding relationship between the cleaning difficulty coefficient and the comprehensive pollution value interval as the cleaning difficulty coefficient of the photovoltaic module. This step can quickly determine the cleaning difficulty coefficient of the photovoltaic module and guide the cleaning work by comprehensively considering the efficiency loss rate, the pollution level assessment value, and the pre-set cleaning difficulty coefficient. By determining the cleaning difficulty coefficient based on different comprehensive pollution values, a customized cleaning solution can be provided for the photovoltaic module to improve the cleaning efficiency and maintenance effect. Timely cleaning and maintenance can effectively reduce the performance loss of the photovoltaic module, extend the service life of the photovoltaic module, and improve the power generation efficiency of the system.

[0030] In an embodiment of the present application, a method for intelligent cleaning of photovoltaic components of a water photovoltaic power station is provided, wherein the intelligent cleaning is performed by determining a cleaning method based on a cleaning difficulty coefficient, including: judging whether the cleaning difficulty coefficient exceeds a preset threshold, and determining a cleaning method based on the judgment result; if the cleaning difficulty coefficient exceeds the preset threshold, mechanical cleaning is used for cleaning; if the cleaning difficulty coefficient does not exceed the preset threshold, water-based cleaning is used for cleaning.

[0031] Specifically, the coefficient used to assess the difficulty of cleaning photovoltaic modules is calculated previously; a threshold is set to determine whether the cleaning difficulty coefficient exceeds an acceptable range; mechanical cleaning is used for cleaning in situations where the cleaning difficulty is higher; water or aqueous cleaning is used for cleaning in situations where the cleaning difficulty is lower. This step selects mechanical or aqueous cleaning methods based on the cleaning difficulty coefficient to most effectively clean the photovoltaic modules. Based on the cleaning difficulty coefficient, the appropriate cleaning method can improve cleaning efficiency and ensure that the photovoltaic modules are thoroughly cleaned. Regular cleaning can reduce contamination and performance loss of photovoltaic modules, extend their service life, and improve the power generation efficiency of the system. Selecting the appropriate cleaning method can avoid unnecessary waste of cleaning equipment and materials, saving cleaning costs.

[0032] like Figure 2As shown, in an embodiment of the present application, an intelligent cleaning system for photovoltaic modules of a water photovoltaic power station is provided, including: an acquisition module for acquiring a current-voltage curve of a photovoltaic module, and performing parameter extraction on the current-voltage curve of the photovoltaic module to obtain characteristic parameters that affect the pollution of the photovoltaic module; an evaluation module for determining a data value corresponding to each characteristic parameter, and comprehensively determining an evaluation value of the degree of pollution of the photovoltaic module based on the data value corresponding to each characteristic parameter; a calculation module for acquiring local irradiance and temperature, and determining a theoretical power value of the photovoltaic module based on the irradiance and temperature; a determination module for determining an actual power value of the photovoltaic module, and determining an efficiency loss rate of the photovoltaic module based on the actual power value and the theoretical power value of the photovoltaic module; a cleaning module for comprehensively determining a cleaning difficulty coefficient of the photovoltaic module based on the pollution degree evaluation value and the efficiency loss rate of the photovoltaic module, and determining a cleaning method for intelligent cleaning based on the cleaning difficulty coefficient.

[0033] In summary, an embodiment of the present invention provides a method and system for intelligent cleaning of photovoltaic modules of a photovoltaic power station in a water area, which includes: obtaining and extracting characteristic parameters that affect the pollution of photovoltaic modules from the current-voltage curve of the photovoltaic modules; comprehensively evaluating the pollution degree evaluation value of the photovoltaic modules based on the data values ​​corresponding to each characteristic parameter; obtaining the local irradiance and temperature to determine the theoretical power value of the photovoltaic modules; determining the actual power value of the photovoltaic modules, and determining the efficiency loss rate of the photovoltaic modules based on the actual power value and the theoretical power value; comprehensively determining the cleaning difficulty coefficient based on the pollution degree evaluation value and the efficiency loss rate of the photovoltaic modules, and performing intelligent cleaning based on the cleaning method. The present invention quantifies the pollution degree by accurately extracting IV curve parameters, calculates the theoretical power by combining irradiance and temperature data, dynamically evaluates the efficiency loss rate, and comprehensively generates a cleaning difficulty coefficient to trigger intelligent decision-making, which can improve power generation efficiency, reduce operation and maintenance costs, and reduce water resource consumption.

[0034] Finally, it should be noted that it is apparent that various modifications and variations may be made by those skilled in the art without departing from the spirit and scope of the present invention. Thus, the present invention is intended to include such modifications and variations as long as they fall within the scope of the present invention and its equivalents.

[0035] The above description is only an example of an embodiment of the present invention, but it does not limit the scope of the present invention. Any structural changes made according to the present invention, as long as they do not lose the essence of the present invention, should be considered to fall within the scope of protection of the present invention and be subject to restrictions. Technical personnel in the relevant technical field can clearly understand that for the convenience and simplicity of description, the specific working process and related instructions of the platform described above can refer to the corresponding process in the aforementioned platform embodiment, and will not be repeated here.

[0036] The term "comprise," "comprising," or any other similar term is intended to cover a non-exclusive inclusion such that a process, platform, article, or apparatus / platform that comprises a list of elements includes not only those elements but also other elements not expressly listed or inherent to such process, platform, article, or apparatus / platform.

[0037] Thus far, the technical solutions of the present invention have been described in conjunction with the further embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to closely related technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

[0038] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention.

Claims

1. A method for intelligent cleaning of photovoltaic modules of a water photovoltaic power station, characterized in that: include: Obtaining the current-voltage curve of the photovoltaic module and performing parameter extraction on the current-voltage curve of the photovoltaic module to obtain characteristic parameters that affect the pollution of the photovoltaic module; Determining a data value corresponding to each characteristic parameter, and comprehensively determining a contamination degree assessment value of the photovoltaic module based on the data value corresponding to each characteristic parameter; Obtain local irradiance and temperature, and determine the theoretical power value of the photovoltaic module based on the irradiance and temperature; Determine an actual power value of the photovoltaic module, and determine an efficiency loss rate of the photovoltaic module based on the actual power value and a theoretical power value of the photovoltaic module; The cleaning difficulty coefficient of the photovoltaic module is comprehensively determined based on the pollution degree assessment value and efficiency loss rate of the photovoltaic module, and the cleaning method is determined based on the cleaning difficulty coefficient for intelligent cleaning.

2. The method for intelligently cleaning photovoltaic modules of a water photovoltaic power station according to claim 1, characterized in that: The step of obtaining the current-voltage curve of the photovoltaic module and extracting parameters of the current-voltage curve of the photovoltaic module to obtain characteristic parameters affecting the pollution of the photovoltaic module includes: The current-voltage curve of the photovoltaic module is obtained, and parameters of the current-voltage curve of the photovoltaic module are extracted to obtain characteristic parameters affecting the pollution of the photovoltaic module, wherein the characteristic parameters affecting the pollution of the photovoltaic module include short-circuit current, fill factor and series resistance.

3. The method for intelligently cleaning photovoltaic modules of a water photovoltaic power station according to claim 2, characterized in that: Determining the data value corresponding to each characteristic parameter, and comprehensively determining the pollution degree assessment value of the photovoltaic module based on the data value corresponding to each characteristic parameter, includes: Determining data values ​​corresponding to each characteristic parameter and standard data values ​​corresponding to each characteristic parameter when the photovoltaic module is in a clean state, and determining a current attenuation rate, a fill factor loss rate, and a series resistance growth rate based on the data values ​​and the standard data values; Determine corresponding preset values ​​for the current decay rate, fill factor loss rate, and series resistance growth rate, respectively; calculate the differences between the current decay rate, fill factor loss rate, and series resistance growth rate and the corresponding preset values; and evaluate these differences to obtain a current decay evaluation value, a fill factor loss evaluation value, and a series resistance growth evaluation value; The pollution degree assessment value of the photovoltaic module is calculated based on the current attenuation assessment value, the fill factor loss assessment value and the series resistance growth assessment value. The calculation formula of the pollution degree assessment value of the photovoltaic module is: S=a*ΔI+b*ΔFF+c*ΔR, Wherein, S is the pollution degree assessment value of the photovoltaic module, a is the first preset weight, ΔI is the current attenuation assessment value, b is the second preset weight, ΔFF is the fill factor loss assessment value, c is the third preset weight, and ΔR is the series resistance growth assessment value.

4. The method for intelligently cleaning photovoltaic modules of a water photovoltaic power station according to claim 3, characterized in that: The obtaining of local irradiance and temperature and determining the theoretical power value of the photovoltaic module based on the irradiance and temperature includes: Obtain the local irradiance and temperature, and calculate the theoretical power value of the photovoltaic module based on the irradiance and temperature. The calculation formula for the theoretical power value of the photovoltaic module is: P0 = G / G S × P S × (1 - k(T - T S )), Among them, P0 is the theoretical power value of the photovoltaic module, G is the local irradiance, G S is the irradiance of photovoltaic modules under standard test conditions, P S is the nominal maximum power of the photovoltaic module under standard test conditions, k is the power temperature coefficient of the photovoltaic module, T is the local temperature, T S is the temperature of the photovoltaic module under standard test conditions.

5. The method for intelligently cleaning photovoltaic modules of a water photovoltaic power station according to claim 4, characterized in that: Determining the actual power value of the photovoltaic module and determining the efficiency loss rate of the photovoltaic module based on the actual power value and the theoretical power value of the photovoltaic module includes: Determine the actual power value of the photovoltaic module, and calculate the efficiency loss rate of the photovoltaic module based on the actual power value and the theoretical power value of the photovoltaic module. The calculation formula for the efficiency loss rate of the photovoltaic module is: N = (P0 - P1) / P0 × 100%, Among them, N is the efficiency loss rate of the photovoltaic module, P0 is the theoretical power value of the photovoltaic module, and P1 is the actual power value of the photovoltaic module.

6. The method for intelligently cleaning photovoltaic modules of a water photovoltaic power station according to claim 5, characterized in that: The comprehensive determination of the cleaning difficulty coefficient of the photovoltaic module based on the pollution degree assessment value and efficiency loss rate of the photovoltaic module includes: Calculating the difference between the efficiency loss rate of the photovoltaic module and the preset loss rate, and evaluating the difference to obtain an efficiency loss evaluation value; The pollution degree assessment value and the efficiency loss assessment value are added together to obtain a comprehensive pollution value of the photovoltaic module, and a cleaning difficulty coefficient is determined based on the comprehensive pollution value of the photovoltaic module; A corresponding relationship between the cleaning difficulty coefficient and the comprehensive pollution value interval is pre-set, wherein the corresponding relationship between the cleaning difficulty coefficient and the comprehensive pollution value interval is associated with a corresponding cleaning difficulty coefficient for each comprehensive pollution value interval; The comprehensive pollution value of the photovoltaic component is obtained, and based on the mapping relationship between the comprehensive pollution value interval to which the comprehensive pollution value belongs and the corresponding relationship between the cleaning difficulty coefficient and the comprehensive pollution value interval, the cleaning difficulty coefficient corresponding to the comprehensive pollution value interval is selected as the cleaning difficulty coefficient of the photovoltaic component.

7. A method for intelligently cleaning photovoltaic modules of a water photovoltaic power station according to claim 6, characterized in that: The intelligent cleaning method is determined based on the cleaning difficulty coefficient, including: Determine whether the cleaning difficulty coefficient exceeds a preset threshold, and determine the cleaning method based on the determination result; If the cleaning difficulty coefficient exceeds the preset threshold, mechanical cleaning is used for cleaning; If the cleaning difficulty coefficient does not exceed the preset threshold, water-based cleaning is used for cleaning.

8. An intelligent cleaning system for photovoltaic modules of a water photovoltaic power station, characterized in that: include: An acquisition module is used to obtain the current-voltage curve of the photovoltaic module and perform parameter extraction on the current-voltage curve of the photovoltaic module to obtain characteristic parameters that affect the pollution of the photovoltaic module; An evaluation module, configured to determine a data value corresponding to each characteristic parameter, and comprehensively determine a contamination degree evaluation value of the photovoltaic module based on the data value corresponding to each characteristic parameter; A calculation module is used to obtain the local irradiance and temperature and determine the theoretical power value of the photovoltaic module based on the irradiance and temperature; A determination module is used to determine an actual power value of the photovoltaic module, and determine an efficiency loss rate of the photovoltaic module based on the actual power value and the theoretical power value of the photovoltaic module; The cleaning module is used to comprehensively determine the cleaning difficulty coefficient of the photovoltaic module based on the pollution degree assessment value and efficiency loss rate of the photovoltaic module, and determine the cleaning method based on the cleaning difficulty coefficient for intelligent cleaning.

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