Floating type photovoltaic array data processing method and device and computer equipment

Abstract

The invention provides a data processing method and device of a floating type photovoltaic array and computer equipment, based on the method, before specific implementation, a motion sensor is arranged on a supporting floating body of a photovoltaic module of the floating type photovoltaic array in advance; a wave sensor is arranged outside the floating type photovoltaic array and at least in a reference position which is away from the floating type photovoltaic array by a specified distance in the direction opposite to the main wave direction. In specific implementation, a motion sensor is used for collecting motion parameters of a photovoltaic module at a current time point, and a wave sensor is used for collecting wave parameters of a reference position at the current time point; according to the wave parameters of the reference position at the current time point, determining the wave transmission delay of the reference position relative to the photovoltaic module, and constructing a current wave parameter change prediction model; by using the data and the model, the inclination angle change data of the photovoltaic module at the future target time point can be accurately predicted, so that the floating photovoltaic array can be timely and effectively adjusted in advance according to the inclination angle change data.

Description

Technical Field

[0001] This specification belongs to the technical field of new energy, and particularly relates to a data processing method, device, and computer equipment for a floating photovoltaic array. Background Art

[0002] In the technical field of new energy, compared with conventional photovoltaic power generation fields set on the ground, due to the vast area of the sea and usually no light occlusion around, floating photovoltaic power generation fields set on the sea have attracted more and more attention.

[0003] However, due to the action of sea waves, the actual pose state of the photovoltaic modules in the floating photovoltaic power generation field set on the sea will continuously change with the waves, which will in turn affect the overall power generation of the power generation field. Based on existing methods, it is often difficult to accurately predict and cooperate with the above changes to make targeted adjustments to the photovoltaic modules.

[0004] In response to the above problems, no effective solution has been proposed yet. Summary of the Invention

[0005] This specification provides a data processing method, device, and computer equipment for a floating photovoltaic array, which can accurately and efficiently predict in advance the inclination change data of the photovoltaic modules in the floating photovoltaic array, and timely make targeted adjustments to the photovoltaic modules according to the above inclination change data, thereby effectively improving the overall power generation of the floating photovoltaic array.

[0006] This specification provides a data processing method for a floating photovoltaic array, which is applied to a floating photovoltaic array. The floating photovoltaic array includes a plurality of photovoltaic modules, the photovoltaic modules are arranged on a support floating body, and a motion sensor is arranged on the support floating body; outside the floating photovoltaic array, a wave sensor is arranged at a reference position at least at a specified distance from the floating photovoltaic array along the reverse main wave direction. The method includes: Collecting the motion parameters of the photovoltaic modules at the current time point by using the motion sensor; collecting the wave parameters of the reference position at the current time point by using the wave sensor; Determining the wave transfer delay of the reference position relative to the photovoltaic modules according to the wave parameters of the reference position at the current time point; and constructing a matching current wave parameter change prediction model; Determining the target time point according to the current time point and the wave transfer delay; and determining the target wave parameters of the photovoltaic modules at the target time point by using the current wave parameter change prediction model; Predicting the inclination change data of the photovoltaic modules at the target time point according to the target wave parameters of the photovoltaic modules at the target time point and the motion parameters of the photovoltaic modules at the current time point; Adjust the floating photovoltaic array according to the inclination change data of the photovoltaic module at the target time point.

[0007] In one embodiment, determining the wave propagation delay of the reference position relative to the photovoltaic module according to the wave parameters of the reference position at the current time point includes: Determine the wave speed of the wave at the current time point according to the wave parameters of the reference position at the current time point; Obtain the layout parameters of the photovoltaic module with respect to the floating photovoltaic array; Calculate the wave propagation delay of the reference position relative to the photovoltaic module according to the specified distance, the wave speed of the wave at the current time point, and the layout parameters of the photovoltaic module with respect to the floating photovoltaic array.

[0008] In one embodiment, constructing a matching current wave parameter change prediction model includes: Obtain the environmental parameters of the floating photovoltaic array; wherein, the environmental parameters at least include the water depth of the area where the floating photovoltaic array is located; Calculate the wave attenuation coefficient of the area where the floating photovoltaic array is located relative to the reference position according to the wave parameters of the reference position at the current time point and the environmental parameters of the floating photovoltaic array; Construct a matching current wave parameter change prediction model according to the wave parameters of the reference position at the current time point and the wave attenuation coefficient of the area where the floating photovoltaic array is located relative to the reference position.

[0009] In one embodiment, predicting the inclination change data of the photovoltaic module at the target time point according to the target wave parameters of the photovoltaic module at the target time point and the motion parameters of the photovoltaic module at the current time point includes: Use the preset motion prediction model of the photovoltaic module to process the target wave parameters of the photovoltaic module at the target time point and the motion parameters of the photovoltaic module at the current time point to obtain the corresponding target prediction result; Determine the motion state data of the photovoltaic module at the target time point according to the target prediction result; Determine the inclination change data of the photovoltaic module at the target time point according to the motion state data of the photovoltaic module at the target time point and the motion parameters of the photovoltaic module at the current time point.

[0010] In one embodiment, after obtaining the corresponding target prediction result, the method further includes: Determine the motion response type of the photovoltaic module at the target time point according to the motion state data of the photovoltaic module at the target time point; Determine the matching target response type label according to the motion response type; Combine the target wave parameters of the photovoltaic module at the target time point, the motion parameters of the photovoltaic module at the current time point, and the target response type label to obtain target combined data; Use a preset motion prediction model of the photovoltaic module to process the target combined data to determine the motion state data of the photovoltaic module at the target time point.

[0011] In one embodiment, the motion response type includes at least one of the following: surge, sway, heave, roll, pitch, yaw.

[0012] In one embodiment, the method further includes: Obtain the temperature data at the current time point; Predict the temperature change data at the target time point according to the temperature data at the current time point; Adjust the floating photovoltaic array according to the inclination change data of the photovoltaic module at the target time point and the temperature change data at the target time point.

[0013] In one embodiment, outside the floating photovoltaic array, a plurality of wave sensors are arranged at reference positions at a specified distance from the floating photovoltaic array in multiple directions; Correspondingly, the method further includes: Obtain the wave parameters of the reference positions at multiple current time points collected by the plurality of wave sensors; Determine the main wave direction at the current time point according to the wave parameters of the reference positions at multiple current time points; Determine the effective wave parameters at the current time point from the wave parameters of the reference positions at multiple current time points according to the main wave direction at the current time point; wherein, the effective wave parameters at the current time point are used to determine the target wave parameters of the photovoltaic module at the target time point.

[0014] This specification also provides a data processing device for a floating photovoltaic array, which is applied to a floating photovoltaic array. The floating photovoltaic array includes a plurality of photovoltaic modules, the photovoltaic modules are arranged on a support floating body, and the support floating body is provided with motion sensors; outside the floating photovoltaic array, at least a wave sensor is arranged at a reference position at a specified distance from the floating photovoltaic array along the reverse main wave direction. The device includes: An acquisition module, configured to use the motion sensors to acquire the motion parameters of the photovoltaic modules at the current time point; use the wave sensors to acquire the wave parameters of the reference positions at the current time point; A processing module, configured to determine the wave transfer delay of the reference position relative to the photovoltaic module according to the wave parameters of the reference position at the current time point; and construct a matching current wave parameter change prediction model; A determination module, configured to determine a target time point according to the current time point and the wave propagation delay; and use the current wave parameter change prediction model to determine the target wave parameters of the photovoltaic module at the target time point; A prediction module, configured to predict the inclination change data of the photovoltaic module at the target time point according to the target wave parameters of the photovoltaic module at the target time point and the motion parameters of the photovoltaic module at the current time point; An adjustment module, configured to adjust the floating photovoltaic array according to the inclination change data of the photovoltaic module at the target time point.

[0015] This specification also provides a computer device, including a processor and a memory for storing processor-executable instructions. When the processor executes the instructions, the related steps of the data processing method of the floating photovoltaic array are implemented.

[0016] This specification also provides a computer program product, including a computer program. When the computer program is executed by a processor, the related steps of the data processing method of the floating photovoltaic array are implemented.

[0017] Based on the data processing method, device and computer device of the floating photovoltaic array provided in this specification, before specific implementation, corresponding motion sensors can be pre-set on the support floats of the photovoltaic modules in the floating photovoltaic array; at the same time, outside the floating photovoltaic array, wave sensors are arranged at least at a reference position at a specified distance from the floating photovoltaic array along the reverse main wave direction. During specific implementation, the motion parameters of the photovoltaic module at the current time point can be collected by using the motion sensors, and at the same time, the wave parameters of the reference position at the current time point can be collected by using the wave sensors; according to the wave parameters of the reference position at the current time point, the wave propagation delay of the reference position relative to the photovoltaic module is determined, and a matching current wave parameter change prediction model is constructed; then, according to the current time point and the wave propagation delay, the target time point when the wave at the reference position reaches the photovoltaic module is determined; and the target wave parameters of the photovoltaic module at the target time point are predicted by using the current wave parameter change prediction model; then, by jointly using the target wave parameters of the photovoltaic module at the target time point and the motion parameters of the photovoltaic module at the current time point, the inclination change data of the photovoltaic module at the target time point is predicted; and the floating photovoltaic array is adjusted according to the inclination change data of the photovoltaic module at the target time point. Thus, the inclination change data of the photovoltaic module can be accurately and efficiently predicted in advance, and the photovoltaic module can be adjusted in a targeted manner in advance in a timely manner according to the above inclination change data, so as to ensure that the floating photovoltaic array can also reach a relatively optimal power generation efficiency at the target time point, and further effectively improve the overall power generation of the floating photovoltaic array. Description of the Drawings

[0018] To more clearly illustrate the embodiments of this specification, the accompanying drawings required for the embodiments will be briefly introduced below. The accompanying drawings in the following description are only some embodiments recorded in this specification. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0019] Figure 1 It is a schematic flowchart of a data processing method for a floating photovoltaic array provided by an embodiment of this specification; Figure 2 It is a schematic diagram of an embodiment applying the data processing method for a floating photovoltaic array provided by an embodiment of this specification in a scenario example; Figure 3 It is a schematic diagram of an embodiment applying the data processing method for a floating photovoltaic array provided by an embodiment of this specification in a scenario example; Figure 4 It is a schematic diagram of an embodiment applying the data processing method for a floating photovoltaic array provided by an embodiment of this specification in a scenario example; Figure 5 It is a schematic diagram of an embodiment applying the data processing method for a floating photovoltaic array provided by an embodiment of this specification in a scenario example; Figure 6 It is a schematic diagram of an embodiment applying the data processing method for a floating photovoltaic array provided by an embodiment of this specification in a scenario example; Figure 7 It is a schematic diagram of an embodiment applying the data processing method for a floating photovoltaic array provided by an embodiment of this specification in a scenario example; Figure 8 It is a schematic diagram of the structural composition of a computer device provided by an embodiment of this specification; Figure 9 It is a schematic diagram of the structural composition of a data processing device for a floating photovoltaic array provided by an embodiment of this specification; Figure 10 It is a schematic diagram of an embodiment applying the data processing method for a floating photovoltaic array provided by an embodiment of this specification in a scenario example; Figure 11 It is a schematic diagram of an embodiment applying the data processing method for a floating photovoltaic array provided by an embodiment of this specification in a scenario example. Detailed implementation manners

[0020] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all the embodiments. Based on the embodiments in this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this specification.

[0021] It should be noted that the information and data related to users involved in the embodiments of this specification are all information and data authorized by the users or fully authorized by the relevant parties. Moreover, the processing of relevant data, such as collection, storage, use, processing, transmission, provision, disclosure, and application, all comply with relevant laws, regulations, and standards, adopt necessary confidentiality measures, do not violate public order and good customs, and provide corresponding operation entrances for users or relevant parties to choose to authorize or refuse.

[0022] It should also be noted that in the embodiments of this specification, some existing industry solutions such as certain software, components, models, etc. may be mentioned. They should be regarded as exemplary, and their purpose is only to illustrate the feasibility in the implementation of the technical solutions of this application, but it does not mean that the applicant has already or necessarily used this solution.

[0023] Refer to Figure 1 As shown, the embodiments of this specification provide a data processing method for a floating photovoltaic array, where this method is specifically applied to a floating photovoltaic array. Refer to Figure 2 And Figure 3 As shown, the floating photovoltaic array may specifically include a plurality of photovoltaic modules, the photovoltaic modules are arranged on a support floating body, and the support floating body may specifically be provided with a motion sensor; outside the floating photovoltaic array, a wave sensor is further arranged at a reference position at least at a specified distance from the floating photovoltaic array along the reverse main wave direction. Specifically in implementation, this method may include the following content: S101: Use the motion sensor to collect the motion parameters of the photovoltaic modules at the current time point; use the wave sensor to collect the wave parameters of the reference position at the current time point; S102: Determine the wave transfer delay of the reference position relative to the photovoltaic modules according to the wave parameters of the reference position at the current time point; and construct a matching current wave parameter change prediction model; S103: Determine the target time point according to the current time point and the wave transfer delay; and use the current wave parameter change prediction model to determine the target wave parameters of the photovoltaic modules at the target time point; S104: Predict the tilt angle change data of the photovoltaic module at the target time point based on the target wave parameters of the photovoltaic module at the target time point and the motion parameters of the photovoltaic module at the current time point; S105: Adjust the floating photovoltaic array according to the tilt angle change data of the photovoltaic module at the target time point.

[0024] Refer to Figure 2 and Figure 3 As shown, the above floating photovoltaic array may include a plurality of independent photovoltaic modules. For example, the 1# photovoltaic module, 2# photovoltaic module, 3# photovoltaic module, 4# photovoltaic module, 5# photovoltaic module, etc. Among them, each photovoltaic module is also connected to a corresponding photovoltaic inverter. During specific implementation, parameters such as the current and voltage of the photovoltaic module can be adjusted through the photovoltaic inverter, so that the corresponding photovoltaic module can achieve a relatively optimal power generation efficiency. The above floating photovoltaic array can be specifically deployed in a floating photovoltaic power generation field on the sea or a large lake.

[0025] Specifically, the above photovoltaic modules can be respectively arranged on independent support floats (or floats). And, corresponding motion sensors are respectively arranged at the bottom ends of each support float. Among them, the above motion sensors can specifically be 6-degree-of-freedom motion sensors. Based on this motion sensor, motion parameters such as the tilt angle of the photovoltaic module linked to the support float can be accurately monitored and collected.

[0026] Refer to Figure 2 and Figure 3 As shown, outside the floating photovoltaic array, at a reference position along the reverse main wave direction and at least a specified distance (for example, L1) from the floating photovoltaic array, a wave sensor can be arranged. Among them, the above wave sensor can specifically be a floating wave sensor. Based on this wave sensor, corresponding wave parameters can be monitored and collected in advance before the waves are transmitted to the support floats of the photovoltaic modules in the floating photovoltaic array. The above specified distance is associated with the adjustment strategy of the floating photovoltaic array and specific wave parameters, which will be specifically described later.

[0027] Furthermore, the floating photovoltaic array further includes a processor (or a computer device), and this processor is respectively connected to the wave sensor, the motion sensor, the photovoltaic inverter, and the photovoltaic module.

[0028] The above-mentioned processor can specifically be used to execute the data processing method of the floating photovoltaic array proposed in this specification, control the wave sensor and the motion sensor to synchronously collect relevant data such as the motion parameters of the photovoltaic modules at the previous time point and the wave parameters of the reference position at the current time point; determine the target time point when the monitored wave reaches the support float of the photovoltaic modules in the floating photovoltaic array according to the above-mentioned relevant data, and construct a matching current wave parameter change prediction model; then use this current wave parameter change prediction model to predict the wave parameters when the wave reaches the floating photovoltaic array at the future target time point; and then accurately predict the inclination change data of the photovoltaic modules at the future target time point according to the wave parameters; furthermore, the corresponding adjustment strategy can be determined according to the inclination change data of the photovoltaic modules; and according to this adjustment strategy, the floating photovoltaic array can be adjusted in a targeted manner in advance through the corresponding photovoltaic inverter, so that the floating photovoltaic array can still achieve a relatively optimal power generation power at the future target time point.

[0029] Among them, the above-mentioned target time point can specifically be understood as the time point when the wave monitored at the reference position at the current time point (which can be denoted as t0) reaches the support float where the photovoltaic modules in the floating photovoltaic array are located.

[0030] The above-mentioned motion parameters of the photovoltaic modules can specifically be understood as parameter data that can describe the pose state of the photovoltaic modules. For example, the inclination angle α of the photovoltaic modules relative to the sea level, etc.

[0031] The above-mentioned wave parameters can specifically be understood as parameter data that can characterize the fluctuation attributes of the waves. Specifically, the above-mentioned wave parameters can include at least one of the following: wave number, wave amplitude, phase difference, angular frequency, period, etc. Of course, it should be noted that the above-listed wave parameters are only an illustrative description. In specific implementation, according to the specific situation and processing requirements, the above-mentioned wave parameters can also include other types of parameters. Regarding this, this specification does not make any limitations.

[0032] In specific implementation, the data directly collected by the wave sensor can be a kind of waveform data used to describe the wave; through analysis and processing of the above-mentioned waveform data, the required wave parameters can be extracted.

[0033] The above-mentioned matching current wave parameter change prediction model can specifically be understood as an algorithm model based on the fluctuation attributes of the current wave, combined with the wave transmission mechanism and the superposition mechanism, which can predict the wave change situation in the short term in the future.

[0034] Based on the above embodiments, by synchronously collecting the motion parameters of the photovoltaic modules at the current time point and the wave parameters at the reference position at the current time point of a reference position that is at a specified distance from the floating photovoltaic array along the reverse main wave direction; and jointly using the above two parameters, the inclination change data of the photovoltaic modules at a future target time point can be accurately predicted in advance, and then targeted adjustments can be made to the floating photovoltaic array in a timely manner to ensure that the photovoltaic modules can still obtain a relatively optimal power generation rate at the future target time point, thereby effectively improving the overall power generation of the floating photovoltaic array and enhancing the overall efficiency of the floating photovoltaic power plant.

[0035] In some embodiments, referring to Figure 4 as shown, based on the wave parameters at the reference position at the current time point, determining the wave transmission delay of the reference position relative to the photovoltaic modules. Specifically, in implementation, it may include the following content: S1: Based on the wave parameters at the reference position at the current time point, determining the wave speed of the wave at the current time point; S2: Obtaining the layout parameters of the photovoltaic modules with respect to the floating photovoltaic array; S3: Based on the specified distance, the wave speed of the wave at the current time point, and the layout parameters of the photovoltaic modules with respect to the floating photovoltaic array, calculating the wave transmission delay of the reference position relative to the photovoltaic modules.

[0036] Specifically, based on the wave parameters at the reference position at the current time point, through waveform analysis and parsing, the wave speed of the wave at the current time point can be extracted and denoted as c.

[0037] Meanwhile, based on the layout parameters of the photovoltaic modules with respect to the floating photovoltaic array (such as arrangement numbers, etc.) that are of concern, and in combination with the overall structural parameters of the floating photovoltaic array, the distance between the photovoltaic module and the edge of the floating photovoltaic array along the reverse main wave direction can be determined and denoted as: l1.

[0038] Correspondingly, the wave transmission delay of the reference position relative to the photovoltaic module can be calculated as: .

[0039] In the case of relatively low accuracy requirements, in order to simplify the calculation process and improve the overall calculation efficiency, the distance between the photovoltaic module and the reference position can also be approximated as L1, and the wave transmission delay can be directly calculated according to the following formula: .

[0040] After calculating the wave transmission delay, the target time point when the wave reaches the floating photovoltaic array can be determined by calculating the sum of the current time point and the wave transmission delay, that is: . Where t1 is the target time point after the current time point.

[0041] In some embodiments, referring to Figure 5 as shown, to construct a prediction model for the change of the current wave parameters that matches the above, in specific implementation, the following content may be included: S1: Obtain the environmental parameters of the floating photovoltaic array; wherein, the environmental parameters at least include the water depth of the area where the floating photovoltaic array is located; S2: Calculate the wave attenuation coefficient of the area where the floating photovoltaic array is located relative to the reference position according to the wave parameters of the reference position at the current time point and the environmental parameters of the floating photovoltaic array; S3: Construct a prediction model for the change of the current wave parameters that matches according to the wave parameters of the reference position at the current time point and the wave attenuation coefficient of the area where the floating photovoltaic array is located relative to the reference position.

[0042] In specific implementation, the required period (which can be denoted as T) and wave speed can be first extracted from the wave parameters of the reference position at the current time point; then, using the period and wave speed of the wave, as well as the water depth (which can be denoted as d) of the area where the floating photovoltaic array is located, the wave attenuation coefficient of the area where the floating photovoltaic array is located relative to the reference position is calculated (for example, ). Specifically, the corresponding wave attenuation coefficient can be calculated according to the following formula: .

[0043] In some embodiments, to construct a prediction model for the change of the current wave parameters that matches according to the wave parameters of the reference position at the current time point and the wave attenuation coefficient of the area where the floating photovoltaic array is located relative to the reference position, in specific implementation, the following content may be included: S1: Extract the waveform characteristics at the current time point according to the wave parameters of the reference position at the current time point; wherein, the waveform characteristics include at least one of the following: wave number (for example, k), wave amplitude (for example, A), phase angle (for example, ), angular frequency (for example, ω); S2: Construct an expression for the component of the wave according to the waveform characteristics at the current time point and the wave attenuation coefficient at the current time point; S3: Construct a prediction model for the change of the current wave parameters that matches through wave transmission and superposition processing according to the expression for the component of the wave.

[0044] In specific implementation, multiple sub-waveform data (e.g., N sub-waveform data), i.e., N constituent components of the wave, can be split through principal component analysis based on the waveform data directly collected by the wave sensor; then, according to the wave parameters of the reference position at the current time point extracted based on the above waveform data, combined with the N sub-waveform data, the waveform features corresponding to each sub-waveform data are extracted; according to the waveform features of the above sub-waveform data, the waveform expressions of each sub-waveform data are determined, which can be specifically expressed in the following form: , i = 1, 2... N. Wherein, i is the number of the sub-waveform data, with a value range of 1 to N; y i is the sub-waveform data numbered i, A i is the wave amplitude of the sub-waveform data numbered i, k i is the wave number of the sub-waveform data numbered i, ω i is the angular frequency of the sub-waveform data numbered i, is the phase angle of the sub-waveform data numbered i, x is the distance relative to the reference position, is the time interval relative to the current time point. When the wave reaches the area where the floating photovoltaic array is located, .

[0045] For the convenience of subsequent calculations, the waveform expressions of the above sub-waveform data can be further transformed and simplified to obtain the following form: , i = 1, 2... N. Wherein, A’ i is the equivalent wave amplitude for the sub-waveform data numbered i obtained after considering the attenuation coefficient . That is, the expression of the constituent components of the wave is obtained.

[0046] Furthermore, according to the wave transmission mechanism and superposition mechanism, corresponding wave transmission and superposition processing can be carried out based on the above expression of the constituent components of the wave, which can include: first, based on the wave superposition mechanism, the waveform expressions of multiple sub-waveform data are superposed to obtain the corresponding initial superposition expression, which can be denoted as: . Then, based on the wave transmission mechanism, the angular frequencies of different sub-waveform data are approximated to be equal, that is, ω1 = ω2 =... = ω i =... = ω N ; and the above initial superposition expression is converted into the corresponding complex form using trigonometric identities to obtain the corresponding intermediate superposition expression, which can be denoted as: . Based on the above intermediate superposition expression, it can be further transformed to obtain the final wave expression for characterizing the wave reaching the area where the floating photovoltaic array is located, which can be denoted as: . Wherein, |Y| represents the wave amplitude of the final wave, ; represents the phase of the final wave, . Convert the above expression of the final wave of the wave into a real number form, so as to obtain a matching prediction model for the change of the current wave parameters, denoted as: y = |Y| sin(kx - ωt + ).

[0047] Based on the above embodiments, the wave parameters at the current time point can be fully utilized, combined with the wave transmission mechanism and superposition mechanism, to construct a prediction model for the change of the current wave parameters with high prediction accuracy and good effect for a short period of time in the future starting from the current time point.

[0048] In some embodiments, the above-mentioned prediction model for the change of the current wave parameters is used to determine the target wave parameters of the photovoltaic module at the target time point. Specifically, in implementation, it may include: substituting the target time point into the prediction model for the change of the current wave parameters, and combining the wave parameters at the reference position at the current time point to determine the wave parameters at the position of the photovoltaic module in the floating photovoltaic array area at the target time point, that is, the target wave parameters.

[0049] In some embodiments, referring to Figure 6 as shown, the inclination angle change data of the photovoltaic module at the target time point is predicted according to the target wave parameters of the photovoltaic module at the target time point and the motion parameters of the photovoltaic module at the current time point. Specifically, in implementation, it may include the following contents: S1: Use the preset motion prediction model of the photovoltaic module to process the target wave parameters of the photovoltaic module at the target time point and the motion parameters of the photovoltaic module at the current time point to obtain the corresponding target prediction result; S2: Determine the motion state data of the photovoltaic module at the target time point according to the target prediction result; S3: Determine the inclination angle change data of the photovoltaic module at the target time point according to the motion state data of the photovoltaic module at the target time point and the motion parameters of the photovoltaic module at the current time point.

[0050] Among them, the preset motion prediction model of the photovoltaic module can be specifically understood as an algorithm model that is pre-trained by deep learning using a large amount of sample data and can predict the corresponding motion parameters of the photovoltaic module based on the wave parameters in the environment.

[0051] Before specific implementation, an experimental area can be set up at sea, and sample photovoltaic modules can be arranged in the experimental area. Among them, the sample photovoltaic modules are arranged on the supporting floating body, and a motion sensor is arranged at the bottom of the above-mentioned supporting floating body. A wave sensor is arranged in the adjacent area of the sample photovoltaic modules. During the implementation process, the wave parameters and motion parameters corresponding to the same time point are synchronously collected and combined to obtain multiple data sets. Among them, one data set corresponds to one time point and includes the wave parameters and motion parameters corresponding to that time point. From the above-mentioned multiple data sets, two data sets with a time interval within the effective duration range are extracted and combined to obtain multiple sample sets. The motion parameters corresponding to the prior time point are extracted from the multiple sample sets and combined with the motion parameters and wave parameters corresponding to the subsequent time point to obtain a sample data. In the above manner, multiple sample data can be constructed. The multiple sample data are subjected to data cleaning to obtain the cleaned sample data. An initial model based on FCOS (Fully Convolutional One-Stage) is constructed. By using the cleaned sample data, deep learning is performed on the initial model to obtain a motion prediction model of the preset photovoltaic module that meets the requirements.

[0052] Based on the above embodiments, the inclination change data of the photovoltaic module at the target time point after the current time point can be accurately and efficiently predicted by using the motion prediction model of the preset photovoltaic module.

[0053] In some embodiments, after obtaining the corresponding target prediction result, when the method is specifically implemented, the following content can also be included: S1: Determine the motion response type of the photovoltaic module at the target time point according to the motion state data of the photovoltaic module at the target time point. S2: Determine the target response type label that matches according to the motion response type. S3: Combine the target wave parameters of the photovoltaic module at the target time point, the motion parameters of the photovoltaic module at the current time point, and the target response type label to obtain target combined data. S4: Use the motion prediction model of the preset photovoltaic module to process the target combined data to determine the motion state data of the photovoltaic module at the target time point.

[0054] Specifically, it is found during the process of training the motion prediction model of the preset photovoltaic module that for different motion response types, there will be local differences in the variation law of the motion parameters of the photovoltaic module with the wave parameters. The preset motion prediction model of the photovoltaic module can more accurately predict the corresponding motion state of the photovoltaic module based on the variation law for this motion response type learned and mastered before when the motion response type is known.

[0055] Based on the above considerations, the motion prediction model of the preset photovoltaic module can be used to directly process the target wave parameters of the photovoltaic module at the target time point and the motion parameters of the photovoltaic module at the current time point for the first prediction to obtain the first prediction result. According to the first prediction result, the motion state data of the photovoltaic module at the target time point with relatively low accuracy can be determined. Furthermore, the motion state data can be used to match with the preset motion response template to determine the motion response type of the photovoltaic module at the target time point.

[0056] Among them, the above-mentioned preset motion response template is obtained by clustering a large number of motion state data of sample photovoltaic modules corresponding to different motion response types used in advance.

[0057] Furthermore, according to the motion response type, the target response type label that matches can be determined. Then, the above-mentioned target response type label is combined with the target wave parameters of the photovoltaic module at the target time point and the motion parameters of the photovoltaic module at the current time point to obtain the target combined data containing the motion response type information that the model can recognize.

[0058] Then, the preset motion prediction model of the photovoltaic module is used to process the above-mentioned target combined data. In the case of known motion response types, the change law of the motion parameters of the photovoltaic module with the wave parameters that matches and is targeted is used for the second prediction, so as to more accurately determine the motion state data of the photovoltaic module at the target time point.

[0059] Furthermore, the motion state data of the photovoltaic module at the target time point obtained by the second prediction can be used in combination with the motion parameters of the photovoltaic module at the current time point to determine the tilt angle change data of the photovoltaic module at the target time point with relatively higher accuracy and relatively smaller error.

[0060] In some embodiments, the motion response type may specifically include at least one of the following: surge, sway, heave, roll, pitch, yaw, etc.

[0061] During the deep learning process of the preset motion prediction model of the photovoltaic module, in addition to learning the basic change law of the motion parameters of the photovoltaic module with the wave parameters, it will also automatically identify and distinguish different motion response types, and learn and master the relatively more refined and targeted change laws for different motion response types.

[0062] In some embodiments, when the method is specifically implemented, it may further include the following content: S1: Obtain the temperature data at the current time point; S2: Predict the temperature change data at the target time point according to the temperature data at the current time point; S3: Adjust the floating photovoltaic array according to the inclination angle change data and temperature change data of the photovoltaic module at the target time point.

[0063] In specific implementation, in addition to obtaining the temperature data at the current time point, it may also be necessary to obtain the temperature record of the current time period and the condition information at the current time point. Among them, the above-mentioned condition information may include at least one of the following: weather information, season information, wind direction information, etc. Then, according to the preset splicing rule, splice the temperature data at the current time point, the temperature record of the current time period, the target time point, and the condition information at the current time point to obtain the combined temperature data. Then, use the preset temperature prediction model to process the combined temperature data to predict the temperature data at the target time point. Among them, the preset temperature prediction model is a neural network model obtained by pre-training with sample combined temperature data through deep learning. Then, determine the temperature change data at the target time point according to the temperature data at the target time point and the temperature data at the current time point.

[0064] Based on the above embodiments, by introducing the temperature change data, the temperature change data and the inclination angle change data can be combined to more comprehensively predict and analyze the situation characteristics of the floating photovoltaic array at the target time point, and can realize more effective and accurate adjustment of the floating photovoltaic array, so that the floating photovoltaic array can obtain relatively optimal power generation power at the target time point.

[0065] In specific implementation, according to the preset prompt word rule, the temperature change data at the target time point and the inclination angle change data of the photovoltaic module at the target time point can be jointly used to determine the corresponding target prompt word. Then, use the preset large language model to determine the matching target adjustment strategy according to the target prompt word. Among them, the preset large language model is connected to a preset adjustment strategy library, and the preset adjustment strategy library can store multiple preset adjustment strategies for different situations obtained by pre-combining expert experience and a large number of historical adjustment records. Furthermore, according to the target adjustment strategy, the photovoltaic inverter in the floating photovoltaic array can be specifically controlled to perform corresponding adjustments, so that the power generation power of the photovoltaic module at the target time point is relatively optimal, thereby ensuring that the overall power generation power of the floating photovoltaic array is relatively optimal at the target time point.

[0066] During specific adjustment, according to the target adjustment strategy, the photovoltaic inverter can be used to specifically adjust the electrical parameters such as current and voltage of the corresponding photovoltaic module by means of the small perturbation method.

[0067] In some embodiments, outside the floating photovoltaic array, a plurality of wave sensors may be specifically arranged at reference positions at a specified distance from the floating photovoltaic array in multiple directions. Correspondingly, when the method is specifically implemented, it may further include the following content: S1: Obtain wave parameters of reference positions at multiple current time points collected by multiple wave sensors; S2: Determine the main wave direction at the current time point according to the wave parameters of reference positions at multiple current time points; S3: Determine the effective wave parameters at the current time point from the wave parameters of reference positions at multiple current time points according to the main wave direction at the current time point; wherein, the effective wave parameters at the current time point are used to determine the target wave parameters of the photovoltaic module at the target time point.

[0068] Specifically, for example, historical wave monitoring records of the area where the floating photovoltaic array is located can be obtained and processed through big data to determine 4 relatively common wave directions; and along the above 4 wave directions, 4 different wave sensors are set at 4 reference positions at a specified distance from the floating photovoltaic array, see Figure 7 As shown, for example, wave sensor 1, wave sensor 2, wave sensor 3, and wave sensor 4.

[0069] In specific implementation, wave parameters of reference positions at multiple current time points corresponding to multiple reference positions can be collected by multiple wave sensors; furthermore, the wave parameters of reference positions at multiple current time points can be jointly used for cross-verification to determine the main wave direction at the current time point; then, reference positions that belong to the positions at a specified distance from the floating photovoltaic array along the main wave direction or the reference positions closest to that position are selected from multiple reference positions as effective reference positions; and the wave parameters of reference positions at the current time point collected based on the effective reference positions are used as the effective wave parameters at the current time point. Furthermore, the effective wave parameters at the current time point can be used later as the wave parameters of the reference positions at the current time point used this time to determine the wave transmission delay of the reference position relative to the photovoltaic module; and a matching current wave parameter change prediction model is constructed to determine the target wave parameters of the photovoltaic module at the target time point. Thereby, the error can be further reduced and the data processing accuracy can be improved.

[0070] In some embodiments, when the method is specifically implemented, the following content can also be included: Determine other wave parameters other than the effective wave parameters at the current time point among the wave parameters of reference positions at multiple current time points as the reference wave parameters at the current time point; Correspondingly, after determining the target wave parameters of the photovoltaic module at the target time point by using the current wave parameter change prediction model, the following content can also be included when the method is specifically implemented: S1: Use the reference wave parameters at the current time point as auxiliary verification to detect whether there are errors in the target wave parameters of the photovoltaic module at the target time point; S2: When it is determined that there is an error, use the reference wave parameters at the current time point to correct the target wave parameters of the photovoltaic module at the target time point.

[0071] In addition, the effective wave parameters at the current time point can also be corrected with reference to the wave parameters to eliminate the error of the effective wave parameters at the current time point and improve the accuracy of the parameters.

[0072] In some embodiments, when the method is specifically implemented, the following content may further be included: S1: At every preset time interval, obtain the wave parameters at the reference position in the current time period; S2: According to the wave parameters at the reference position in the current time period, determine whether the wave fluctuation amplitude in the current time period is greater than the preset amplitude threshold; S3: When it is determined that the wave fluctuation amplitude in the current time period is greater than the preset amplitude threshold, trigger the acquisition of the motion parameters of the photovoltaic module at the current time point by using a motion sensor; use a wave sensor to acquire the wave parameters at the reference position at the current time point.

[0073] Based on the above embodiments, at every preset time interval, by obtaining and evaluating the wave fluctuation amplitude in the current time period according to the wave parameters at the reference position in the current time period, it can be determined whether the wave fluctuation in the current time period will have an obvious impact on the floating photovoltaic array. When it is determined that there will be an obvious impact, the data processing method of the floating photovoltaic array provided in this specification can be triggered in a timely and automatic manner. On the contrary, when it is not certain that there will be an obvious impact, the data processing of the floating photovoltaic array provided in this specification is not triggered, and the monitoring of the next time period continues.

[0074] In some embodiments, after the wave parameters at the reference position in the current time period, when the method is specifically implemented, the following content may further be included: S1: According to the wave parameters at the reference position in the current time period, determine the wave transmission delay in the current time period; S2: According to the wave transmission delay in the current time period and the preset reference adjustment duration, determine whether the specified distance is valid currently; S3: When it is determined that the specified distance is invalid currently, generate an adjustment instruction regarding the reference position.

[0075] Among them, the above preset reference adjustment duration can be specifically determined according to the overall operation data processing time-consuming and the overall adjustment effective time-consuming.

[0076] In specific implementation, the wave speed of the wave will continuously change. When the wave speed is relatively fast, the corresponding wave transmission delay will be relatively short. At this time, the actual wave transmission delay may be less than the preset reference adjustment duration, that is, when the wave reaches the area where the floating photovoltaic array is located from the reference position, the relevant adjustment cannot be completed yet. In this case, it can be considered that the specified distance currently used is invalid. In such a situation, it is necessary to extend the specified distance to have enough time to complete the relevant data processing and adjustment in advance. On the contrary, if the specified distance is too long, or during the actual wave transmission delay process, the process of the wave transmitting from the reference position to the area where the floating photovoltaic array is located may be affected by relatively more unpredictable factors, resulting in relatively large errors and low credibility of the wave parameters of the photovoltaic modules at the determined target time point. In this case, it can also be considered that the specified distance currently used is invalid.

[0077] Therefore, it is possible to monitor in real time or at regular intervals and judge whether the specified distance used is valid according to the actual situation in the above manner; and when it is found that the specified distance is invalid, an adjustment instruction regarding the reference position is generated in a timely manner; and in response to this adjustment instruction, a suitable reference position is re-determined according to the actual situation, and then the wave sensor can be deployed at the new reference position to collect the corresponding wave parameters.

[0078] Specifically, an underwater mobile module can be set at the bottom of the wave sensor. Correspondingly, it can receive and respond to the adjustment instruction, combine the current wave speed and the main wave direction, perform planning and solution, and determine the updated reference position; then control the underwater mobile module to drive the wave sensor to move to and stay at the updated reference position. Thus, it is possible to more intelligently and efficiently complete the re-determination of the reference position and the automatic deployment of the wave sensor.

[0079] As can be seen from the above, for the data processing method of the floating photovoltaic array provided by the embodiments of this specification, before specific implementation, corresponding motion sensors can be pre-set on the support floats of the photovoltaic modules of the floating photovoltaic array; at the same time, outside the floating photovoltaic array, wave sensors are set at least at a reference position along the reverse main wave direction at a specified distance from the floating photovoltaic array. During specific implementation, the motion parameters of the photovoltaic modules at the current time point can be collected by using the motion sensors, and at the same time, the wave parameters of the reference position at the current time point can be collected by using the wave sensors; according to the wave parameters of the reference position at the current time point, the wave transmission delay of the reference position relative to the photovoltaic modules is determined, and a matching current wave parameter change prediction model is constructed; then according to the current time point and the wave transmission delay, the target time point is determined; and the target wave parameters of the photovoltaic modules at the target time point are determined by using the current wave parameter change prediction model; according to the target wave parameters of the photovoltaic modules at the target time point and the motion parameters of the photovoltaic modules at the current time point, the inclination change data of the photovoltaic modules at the target time point are predicted; according to the inclination change data of the photovoltaic modules at the target time point, the floating photovoltaic array is adjusted. Thus, the inclination change data of the photovoltaic modules can be accurately and efficiently predicted in advance, and the photovoltaic modules can be adjusted in a targeted manner in advance in a timely manner according to the above inclination change data, thereby effectively improving the overall power generation of the floating photovoltaic array.

[0080] Embodiments of this specification provide a computer device, refer to Figure 8 as shown. Among them, the computer device includes a network communication port 801, a processor 802, and a memory 803. The above structures are connected by internal cables so that each structure can perform specific data interactions.

[0081] Among them, the network communication port 801 can specifically be used to receive a trigger instruction.

[0082] The processor 802 can specifically be used to respond to the trigger instruction, collect the motion parameters of the photovoltaic modules at the current time point by using the motion sensors; collect the wave parameters of the reference position at the current time point by using the wave sensors; determine the wave transmission delay of the reference position relative to the photovoltaic modules according to the wave parameters of the reference position at the current time point; and construct a matching current wave parameter change prediction model; determine the target time point according to the current time point and the wave transmission delay; and determine the target wave parameters of the photovoltaic modules at the target time point by using the current wave parameter change prediction model; predict the inclination change data of the photovoltaic modules at the target time point according to the target wave parameters of the photovoltaic modules at the target time point and the motion parameters of the photovoltaic modules at the current time point; adjust the floating photovoltaic array according to the inclination change data of the photovoltaic modules at the target time point.

[0083] The memory 803 can specifically be used to store corresponding instruction programs, as well as relevant data such as the motion parameters of the photovoltaic module at the current time point and the wave parameters of the reference position at the current time point.

[0084] Based on the above method, the relevant structural performance of the computer device can be effectively utilized, the data processing speed of the electronic device can be improved, and the data processing of the floating photovoltaic array can be efficiently achieved.

[0085] In this embodiment, the network communication port 801 can be bound to different communication protocols, so as to send or receive different data. For example, the network communication port can be a port responsible for web data communication, or a port responsible for FTP data communication, or a port responsible for mail data communication. In addition, the network communication port can also be a physical communication interface or a communication chip. For example, it can be a wireless mobile network communication chip, such as GSM, CDMA, etc.; it can also be a Wifi chip; it can also be a Bluetooth chip.

[0086] In this embodiment, the processor 802 can be implemented in any suitable manner. For example, the processor can take the form of, for example, a microprocessor or a processor and a computer-readable medium storing computer-readable program code (such as software or firmware) executable by the (micro)processor, logic gates, switches, application specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers, etc. This specification does not make any limitations.

[0087] In this embodiment, the memory 803 can include multiple levels. In a digital system, anything that can store binary data can be a memory; in an integrated circuit, a circuit with a storage function without a physical form is also called a memory, such as RAM, FIFO, etc.; in a system, a storage device with a physical form is also called a memory, such as a memory module, a TF card, etc.

[0088] The embodiments of this specification also provide a computer-readable storage medium for the data processing method of the above floating photovoltaic array. The computer-readable storage medium stores computer program instructions, which when executed, implement the following steps: using a motion sensor to collect the motion parameters of the photovoltaic module at the current time point; using a wave sensor to collect the wave parameters of the reference position at the current time point; determining the wave propagation delay of the reference position relative to the photovoltaic module according to the wave parameters of the reference position at the current time point; and constructing a matching current wave parameter change prediction model; determining the target time point according to the current time point and the wave propagation delay; and using the current wave parameter change prediction model to determine the target wave parameters of the photovoltaic module at the target time point; predicting the inclination change data of the photovoltaic module at the target time point according to the target wave parameters of the photovoltaic module at the target time point and the motion parameters of the photovoltaic module at the current time point; and adjusting the floating photovoltaic array according to the inclination change data of the photovoltaic module at the target time point.

[0089] In this embodiment, the above storage medium includes but is not limited to Random Access Memory (RAM), Read-Only Memory (ROM), Cache, Hard Disk Drive (HDD), or Memory Card. The memory can be used to store computer program instructions. The network communication unit can be set according to the standards specified by the communication protocol and is used for the interface of network connection communication.

[0090] In this embodiment, the functions and effects specifically implemented by the program instructions stored in the computer-readable storage medium can be explained in comparison with other embodiments and will not be elaborated here.

[0091] The embodiments of this specification also provide a computer program product, which at least includes a computer program. When the computer program is executed by a processor, the following method steps are implemented: using a motion sensor to collect the motion parameters of the photovoltaic module at the current time point; using a wave sensor to collect the wave parameters of the reference position at the current time point; determining the wave propagation delay of the reference position relative to the photovoltaic module according to the wave parameters of the reference position at the current time point; and constructing a matching current wave parameter change prediction model; determining the target time point according to the current time point and the wave propagation delay; and using the current wave parameter change prediction model to determine the target wave parameters of the photovoltaic module at the target time point; predicting the inclination change data of the photovoltaic module at the target time point according to the target wave parameters of the photovoltaic module at the target time point and the motion parameters of the photovoltaic module at the current time point; and adjusting the floating photovoltaic array according to the inclination change data of the photovoltaic module at the target time point.

[0092] Refer to Figure 9 As shown, the embodiment of the present specification also provides a data processing device for a floating photovoltaic array, which is applied to a floating photovoltaic array. The floating photovoltaic array includes a plurality of photovoltaic modules, the photovoltaic modules are arranged on a supporting floating body, and a motion sensor is arranged on the supporting floating body; outside the floating photovoltaic array, a wave sensor is arranged at a reference position at least at a specified distance from the floating photovoltaic array along the reverse main wave direction. The device may specifically include the following structural modules: An acquisition module 901, which can specifically be used to collect the motion parameters of the photovoltaic modules at the current time point by using the motion sensor; and collect the wave parameters of the reference position at the current time point by using the wave sensor; A processing module 902, which can specifically be used to determine the wave propagation delay of the reference position relative to the photovoltaic modules according to the wave parameters of the reference position at the current time point; and construct a matching current wave parameter change prediction model; A determination module 903, which can specifically be used to determine the target time point according to the current time point and the wave propagation delay; and determine the target wave parameters of the photovoltaic modules at the target time point by using the current wave parameter change prediction model; A prediction module 904, which can specifically be used to predict the inclination change data of the photovoltaic modules at the target time point according to the target wave parameters of the photovoltaic modules at the target time point and the motion parameters of the photovoltaic modules at the current time point; An adjustment module 905, which can specifically be used to adjust the floating photovoltaic array according to the inclination change data of the photovoltaic modules at the target time point.

[0093] In some embodiments, when the above-mentioned processing module 902 is specifically implemented, the wave propagation delay of the reference position relative to the photovoltaic modules can be determined in the following manner according to the wave parameters of the reference position at the current time point: determine the wave speed of the wave at the current time point according to the wave parameters of the reference position at the current time point; obtain the layout parameters of the photovoltaic modules with respect to the floating photovoltaic array; calculate the wave propagation delay of the reference position relative to the photovoltaic modules according to the specified distance, the wave speed of the wave at the current time point, and the layout parameters of the photovoltaic modules with respect to the floating photovoltaic array.

[0094] In some embodiments, when the above-mentioned processing module 902 is specifically implemented, the corresponding current wave parameter change prediction model can be constructed in the following manner: Obtain the environmental parameters of the floating photovoltaic array; wherein, the environmental parameters at least include the water depth of the area where the floating photovoltaic array is located; According to the wave parameters at the reference position at the current time point and the environmental parameters of the floating photovoltaic array, calculate the wave attenuation coefficient of the area where the floating photovoltaic array is located relative to the reference position; According to the wave parameters at the reference position at the current time point and the wave attenuation coefficient of the area where the floating photovoltaic array is located relative to the reference position, construct the corresponding current wave parameter change prediction model.

[0095] In some embodiments, when the above-mentioned prediction module 904 is specifically implemented, the inclination angle change data of the photovoltaic module at the target time point can be predicted in the following manner: Use the preset motion prediction model of the photovoltaic module to process the target wave parameters of the photovoltaic module at the target time point and the motion parameters of the photovoltaic module at the current time point to obtain the corresponding target prediction result; According to the target prediction result, determine the motion state data of the photovoltaic module at the target time point; According to the motion state data of the photovoltaic module at the target time point and the motion parameters of the photovoltaic module at the current time point, determine the inclination angle change data of the photovoltaic module at the target time point.

[0096] In some embodiments, after obtaining the corresponding target prediction result, when the device is specifically implemented, it can also be used for: According to the motion state data of the photovoltaic module at the target time point, determine the motion response type of the photovoltaic module at the target time point; According to the motion response type, determine the corresponding target response type label; Combine the target wave parameters of the photovoltaic module at the target time point, the motion parameters of the photovoltaic module at the current time point, and the target response type label to obtain the target combined data; Use the preset motion prediction model of the photovoltaic module to process the target combined data to determine the motion state data of the photovoltaic module at the target time point.

[0097] In some embodiments, the motion response type may specifically include at least one of the following: surge, sway, heave, roll, pitch, yaw, etc.

[0098] In some embodiments, when the device is specifically implemented, it can also be used for: Obtain the temperature data at the current time point; According to the temperature data at the current time point, predict the temperature change data at the target time point; According to the inclination angle change data of the photovoltaic module at the target time point and the temperature change data at the target time point, adjust the floating photovoltaic array.

[0099] In some embodiments, outside the floating photovoltaic array, a plurality of wave sensors are arranged at reference positions at a specified distance from the floating photovoltaic array in a plurality of directions; Correspondingly, when the device is specifically implemented, it can also be used to: obtain wave parameters at the reference positions at a plurality of current time points collected by the plurality of wave sensors; determine the main wave direction at the current time point according to the wave parameters at the reference positions at the plurality of current time points; determine the effective wave parameters at the current time point from the wave parameters at the reference positions at the plurality of current time points according to the main wave direction at the current time point; wherein, the effective wave parameters at the current time point are used to determine the target wave parameters of the photovoltaic modules at the target time point.

[0100] It should be noted that the units, devices, modules, etc. described in the above embodiments can be specifically implemented by computer chips or entities, or by products with certain functions. For the convenience of description, when describing the above devices, they are divided into various modules according to functions and described separately. Of course, when implementing this specification, the functions of each module can be implemented in the same or multiple software and / or hardware, or the modules implementing the same function can be realized by a combination of multiple sub-modules or sub-units, etc. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical or other forms.

[0101] As can be seen from the above, based on the data processing device for the floating photovoltaic array provided in the embodiments of this specification, the inclination change data of the photovoltaic modules can be accurately and efficiently predicted in advance, and the photovoltaic modules can be adjusted timely and specifically according to the above inclination change data, thereby effectively improving the overall power generation of the floating photovoltaic array.

[0102] In a specific scenario example, the data processing method for the floating photovoltaic array provided in this specification can be applied to realize the optimal power prediction and adjustment of the array floating photovoltaic based on the incident waves.

[0103] In this scenario example, considering that for fixed photovoltaic power generation, the influencing factors of maximum power are solar irradiance, temperature, and resistance, and solar irradiance is mainly affected by various external environmental factors such as the angle of sunlight irradiation, clouds, and shadows. For floating offshore photovoltaic power generation, in addition to the influencing factors encountered in fixed photovoltaic power generation, the floating body base supporting the photovoltaic modules will perform reciprocating motion under the action of waves, resulting in a change in the inclination angle of the floating photovoltaic modules at any given moment. At present, for floating offshore photovoltaic power generation, no corresponding appropriate maximum power tracking strategy has been clearly formulated, resulting in a reduction in the output power of the photovoltaic modules and affecting the power generation amount.

[0104] To address the above problems, this scenario example further considers a method for predicting the motion of the floating body of a floating photovoltaic based on incident wave data, which can predict the motion response law of the floating body of the photovoltaic module through the parameters of the incident wave; and a method for predicting the maximum power of a floating photovoltaic, which obtains the motion response law of the floating body of the floating photovoltaic base through the incident wave and predicts the maximum power according to the predicted inclination angle. Specifically, as shown in Figure 10 it may include the following content.

[0105] As shown in Figure 2 and Figure 3 The array-type floating photovoltaic (or floating photovoltaic array) consists of 20 photovoltaic modules, arranged in a 5*4 layout. The main wave direction is incident from north to south. The floating bodies supporting the 1-5# modules are located on the leftmost side, and the floating wave sensor is located in the main wave direction.

[0106] Among them, the photovoltaic modules are placed on the floating bodies, and the floating bodies are connected through a connection structure. The array-type photovoltaic is connected to the seabed through four mooring chains.

[0107] Using the floating wave sensor, obtain the wave parameters (e.g., the wave parameters at the reference position at the current time point) of the array-type floating photovoltaic periphery at time t0 (e.g., the current time point).

[0108] According to the distance L1 from the floating wave sensor to the floating body supporting the 1# photovoltaic module and the wave speed c, calculate the time for the wave to travel from the floating wave sensor to the floating body supporting the 1# photovoltaic module (e.g., wave propagation delay).

[0109] Calculate and predict the wave parameters (e.g., the target wave parameters of the photovoltaic module at the target time point) of the wave that reaches the floating body supporting the 1# photovoltaic module at a transmission distance of L1 at time t0 + △t1 (e.g., the target time point) in the photovoltaic field area of the array.

[0110] When performing specific calculations and predictions, the attenuation coefficient of the wave in the array photovoltaic field can be calculated first after the wave passes through the array photovoltaic field from the periphery for a time transfer of Δt1; then, considering the above attenuation coefficient, according to the wave transfer and superposition principle, the wave parameters at the position of the target support floating body in the array photovoltaic field at the moment of t0 + Δt1 can be obtained.

[0111] Among them, the above wave transfer and superposition principle can specifically include the following content.

[0112] For N waves superimposed at the same point, the displacement of each wave can be expressed as:

[0113] where i ranges from 1 to N, representing the i-th wave, A i is the amplitude of the i-th wave, k i is the wave number, ω i is the angular frequency, is the phase difference, x is the position, and t is the time.

[0114] The total displacement y after the superposition of N waves is the sum of the displacements of all single waves: .

[0115] If the frequencies of each wave are the same, that is, ω1 = ω2 =... = ω N , then the above sum is converted into a single sine function for processing using trigonometric identities, that is: (1) Expand the sine function of each term into the complex exponential form: .

[0116] (2) Add all the terms: .

[0117] (3) Convert the sum into the modulus and phase of the complex form: .

[0118] , .

[0119] (4) Convert the complex form back to the real form: . Among them, |Y| is the amplitude of the final wave, is the phase of the final wave.

[0120] Using the parameters of the support floating bodies and mooring systems of the 5*4 arranged array floating photovoltaic, through numerical calculations, the motion responses of each floating body in the array floating photovoltaic in all working conditions in each direction are obtained in advance, such as Figure 11As shown in the figure. In the figure, the partial images indicated by 1#, 2#, 3#, 4#, and 5# respectively represent the motion responses of the 1# photovoltaic module, the 2# photovoltaic module, the 3# photovoltaic module, the 4# photovoltaic module, and the 5# photovoltaic module. The vertical axis (T) represents the period of the wave in seconds; the gray value characterizes the inclination angle in the motion response in radians.

[0121] Compare the wave conditions at the target wind turbine position in the array photovoltaic field area at a certain moment with the pre-obtained pre-wave conditions required for the array floating photovoltaic response data under all working conditions in the information processing center to obtain the motion states of the support floats of the 1-5# components in the array photovoltaic field area under the current working conditions. The motion responses of the component support floats in each direction include: one or more of surge, sway, heave, roll, pitch, and yaw.

[0122] According to the six-degree-of-freedom motion sensor, obtain the motion state of the 1# component support float at time t0 and the inclination angle α0 at time t0. According to the predicted

[0123] motion of the support float at a certain moment, obtain the inclination angle at a certain moment as a certain moment, obtain the inclination angle at a certain moment is .

[0124] According to the change in the inclination angle within a certain time, the maximum power can be predicted and adjusted in advance by a certain time, adjust the I-V curve to achieve the maximum power.

[0125] Through the above scenario example, it is verified that the data processing method for the floating photovoltaic array provided in this specification can indeed accurately and efficiently predict the inclination angle change data of the photovoltaic module in advance, and timely and specifically adjust the photovoltaic module according to the above inclination angle change data, thereby effectively improving the overall power generation of the floating photovoltaic array.

[0126] Although this specification provides method operation steps as described in the embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-creative means. The order of steps listed in the embodiments is only one way among many orders of step execution and does not represent the only order of execution. When the actual device or client product is executed, it may be executed in the order of the method shown in the embodiments or the drawings or executed in parallel (for example, in a parallel processor or multi-threaded processing environment, or even in a distributed data processing environment). The terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, such that a process, method, product or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, product or device. Without further limitation, there is no exclusion of additional identical or equivalent elements in the process, method, product or device comprising the said elements. The terms such as first, second, etc. are used to denote names and do not denote any particular order.

[0127] Those skilled in the art also know that in addition to implementing the controller in the form of pure computer-readable program code, the method steps can be logically programmed to enable the controller to implement the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Therefore, such a controller can be regarded as a hardware component, and the devices included therein for implementing various functions can also be regarded as the structures within the hardware component. Or even, the devices for implementing various functions can be regarded as either software modules for implementing the method or structures within the hardware component.

[0128] This specification can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, classes, etc. that perform specific tasks or implement specific abstract data types. This specification can also be practiced in a distributed computing environment where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer-readable storage media including storage devices.

[0129] As can be seen from the description of the above embodiments, those skilled in the art can clearly understand that this specification can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of this specification can essentially be embodied in the form of a software product, and this computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions for causing a computer device (which can be a personal computer, a mobile terminal, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments of this specification.

[0130] The various embodiments in this specification are described in a progressive manner. For the same or similar parts between the various embodiments, reference can be made to each other. The key point of each embodiment is to illustrate the differences from other embodiments. This specification can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multi-processor systems, microprocessor-based systems, set-top boxes, programmable electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and so on.

[0131] Although this specification is depicted through embodiments, those of ordinary skill in the art know that this specification has many variations and changes without departing from the spirit of this specification. It is hoped that the appended claims will cover these variations and changes without departing from the spirit of this specification.

Claims

1. A data processing method for a floating photovoltaic array, characterized in that, Applied to a floating photovoltaic array, wherein the floating photovoltaic array includes a plurality of photovoltaic modules, the photovoltaic modules are arranged on a support floating body, and the support floating body is provided with a motion sensor; outside the floating photovoltaic array, a wave sensor is arranged at a reference position at least at a specified distance from the floating photovoltaic array along the reverse main wave direction. The method includes: Collecting the motion parameters of the photovoltaic modules at the current time point by using the motion sensor; collecting the wave parameters of the reference position at the current time point by using the wave sensor; Determining the wave propagation delay of the reference position relative to the photovoltaic modules according to the wave parameters of the reference position at the current time point; and constructing a matching current wave parameter change prediction model; Determining the target time point according to the current time point and the wave propagation delay; and determining the target wave parameters of the photovoltaic modules at the target time point by using the current wave parameter change prediction model; Predicting the inclination change data of the photovoltaic modules at the target time point according to the target wave parameters of the photovoltaic modules at the target time point and the motion parameters of the photovoltaic modules at the current time point; Adjusting the floating photovoltaic array according to the inclination change data of the photovoltaic modules at the target time point.

2. The method according to claim 1, characterized in that Determining the wave propagation delay of the reference position relative to the photovoltaic modules according to the wave parameters of the reference position at the current time point, including: Determining the wave speed of the wave at the current time point according to the wave parameters of the reference position at the current time point; Obtaining the layout parameters of the photovoltaic modules with respect to the floating photovoltaic array; Calculating the wave propagation delay of the reference position relative to the photovoltaic modules according to the specified distance, the wave speed of the wave at the current time point, and the layout parameters of the photovoltaic modules with respect to the floating photovoltaic array.

3. The method according to claim 1, characterized in that, Constructing a matching current wave parameter change prediction model, including: Obtaining the environmental parameters of the floating photovoltaic array; wherein the environmental parameters at least include the water depth of the area where the floating photovoltaic array is located; Calculating the wave attenuation coefficient of the area where the floating photovoltaic array is located relative to the reference position according to the wave parameters of the reference position at the current time point and the environmental parameters of the floating photovoltaic array; Constructing a matching current wave parameter change prediction model according to the wave parameters of the reference position at the current time point and the wave attenuation coefficient of the area where the floating photovoltaic array is located relative to the reference position.

4. The method according to claim 1, wherein Predicting the inclination change data of the photovoltaic modules at the target time point according to the target wave parameters of the photovoltaic modules at the target time point and the motion parameters of the photovoltaic modules at the current time point, including: Processing the target wave parameters of the photovoltaic modules at the target time point and the motion parameters of the photovoltaic modules at the current time point by using a preset motion prediction model of the photovoltaic modules to obtain a corresponding target prediction result; Determining the motion state data of the photovoltaic modules at the target time point according to the target prediction result; Determining the inclination change data of the photovoltaic modules at the target time point according to the motion state data of the photovoltaic modules at the target time point and the motion parameters of the photovoltaic modules at the current time point.

5. The method according to claim 4, wherein After obtaining the corresponding target prediction result, the method further includes: Determining the motion response type of the photovoltaic modules at the target time point according to the motion state data of the photovoltaic modules at the target time point; Determine the matching target response type label according to the motion response type; Combine the target wave parameters of the photovoltaic module at the target time point, the motion parameters of the photovoltaic module at the current time point, and the target response type label to obtain target combined data; Use the preset motion prediction model of the photovoltaic module to determine the motion state data of the photovoltaic module at the target time point by processing the target combined data.

6. The method according to claim 5, characterized in that, The motion response type includes at least one of the following: surge, sway, heave, roll, pitch, yaw.

7. The method according to claim 1, characterized in that, The method further includes: Obtain the temperature data at the current time point; Predict the temperature change data at the target time point according to the temperature data at the current time point; Adjust the floating photovoltaic array according to the inclination change data of the photovoltaic module at the target time point and the temperature change data at the target time point.

8. The method according to claim 1, characterized in that, Outside the floating photovoltaic array, a plurality of wave sensors are arranged at reference positions at a specified distance from the floating photovoltaic array in multiple directions; Correspondingly, the method further includes: Obtain the wave parameters of the reference positions at multiple current time points collected by the plurality of wave sensors; Determine the main wave direction at the current time point according to the wave parameters of the reference positions at multiple current time points; Determine the effective wave parameters at the current time point from the wave parameters of the reference positions at multiple current time points according to the main wave direction at the current time point; wherein, the effective wave parameters at the current time point are used to determine the target wave parameters of the photovoltaic module at the target time point.

9. A data processing device for a floating photovoltaic array, characterized in that, Applied to a floating photovoltaic array, wherein the floating photovoltaic array includes a plurality of photovoltaic modules, the photovoltaic modules are arranged on a support floating body, and the support floating body is provided with a motion sensor; outside the floating photovoltaic array, at least a wave sensor is arranged at a reference position at a specified distance from the floating photovoltaic array along the reverse main wave direction, and the device includes: An acquisition module, configured to use the motion sensor to acquire the motion parameters of the photovoltaic module at the current time point; use the wave sensor to acquire the wave parameters of the reference position at the current time point; A processing module, configured to determine the wave transfer delay of the reference position relative to the photovoltaic module according to the wave parameters of the reference position at the current time point; and construct a matching current wave parameter change prediction model; A determination module, configured to determine the target time point according to the current time point and the wave transfer delay; and use the current wave parameter change prediction model to determine the target wave parameters of the photovoltaic module at the target time point; A prediction module, configured to predict the inclination change data of the photovoltaic module at the target time point according to the target wave parameters of the photovoltaic module at the target time point and the motion parameters of the photovoltaic module at the current time point; An adjustment module, configured to adjust the floating photovoltaic array according to the inclination change data of the photovoltaic module at the target time point.

10. A computer device, characterized in that, Includes a processor and a memory for storing processor-executable instructions, and when the processor executes the instructions, the steps of the method according to any one of claims 1 to 8 are implemented.

11. A computer program product, characterized in that, Contains a computer program, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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