Data processing method, device and computer equipment for floating photovoltaic array

Abstract

This specification provides a data processing method, apparatus, and computer equipment for a floating photovoltaic array. Based on this method, prior to implementation, a motion sensor is pre-installed on the supporting float of the photovoltaic modules of the floating photovoltaic array. A wave sensor is installed outside the floating photovoltaic array at a reference position at least a specified distance from the floating photovoltaic array in the opposite direction of the main wave. During implementation, the motion sensor is used to collect the motion parameters of the photovoltaic module at the current time point, and the wave sensor is used to collect the wave parameters of the reference position at the current time point. Based on the wave parameters at the reference position at the current time point, the wave transmission delay of the reference position relative to the photovoltaic module is determined, and a current wave parameter change prediction model is constructed. Using this data and model, the tilt angle change data of the photovoltaic module at a target future time point can be accurately predicted, and the floating photovoltaic array can be adjusted in a timely and effective manner based on this tilt angle change data.

Description

Technical Field

[0001] This specification belongs to the field of new energy technology, and in particular relates to data processing methods, devices, and computer equipment for floating photovoltaic arrays. Background Art

[0002] In the field of new energy technology, compared with conventional photovoltaic power plants installed on the ground, floating photovoltaic power plants installed at sea have attracted more and more attention due to the vast area at sea and the lack of light obstruction around them.

[0003] However, due to the effects of wind and waves at sea, the actual position of photovoltaic panels in floating photovoltaic power plants installed at sea is constantly changing with the waves, which in turn affects the overall power generation of the power plant. Existing methods often find it difficult to accurately predict and adapt to these changes and make targeted adjustments to the photovoltaic panels.

[0004] To address the above issues, no effective solutions have been proposed so far. 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 the tilt change data of photovoltaic modules in the floating photovoltaic array in advance, and make targeted adjustments to the photovoltaic modules in a timely and advance manner based on the above tilt 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 the floating photovoltaic array. The floating photovoltaic array includes a plurality of photovoltaic modules, each of which is disposed on a supporting float, and the supporting float is provided with a motion sensor. A wave sensor is provided outside the floating photovoltaic array at least at a reference position at a specified distance from the floating photovoltaic array in a direction opposite to the main wave. The method comprises:

[0007] The motion sensor is used to collect the motion parameters of the photovoltaic module at the current time point; the wave sensor is used to collect the wave parameters of the reference position at the current time point;

[0008] Based on the wave parameters at the reference position at the current time point, the wave transmission delay of the reference position relative to the photovoltaic module is determined; and a matching current wave parameter change prediction model is constructed;

[0009] Determine the target time point based on the current time point and the wave transmission 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;

[0010] Predicting 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;

[0011] The floating photovoltaic array is adjusted according to the tilt angle change data of the photovoltaic components at the target time point.

[0012] In one embodiment, determining the wave transmission delay of the reference position relative to the photovoltaic module based on the wave parameters of the reference position at the current time point includes:

[0013] Determine the wave speed of the wave at the current time point based on the wave parameters of the reference position at the current time point;

[0014] Obtaining layout parameters of photovoltaic modules with respect to a floating photovoltaic array;

[0015] The wave transmission delay of the reference position relative to the photovoltaic module is calculated based on the specified distance, the wave speed at the current time point, and the layout parameters of the photovoltaic module with respect to the floating photovoltaic array.

[0016] In one embodiment, building a matching current wave parameter change prediction model includes:

[0017] Acquiring 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;

[0018] Calculate the wave attenuation coefficient of the floating photovoltaic array relative to the reference position based on the wave parameters of the reference position at the current time point and the environmental parameters of the floating photovoltaic array;

[0019] 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, a matching current wave parameter change prediction model is constructed.

[0020] In one embodiment, the inclination angle change data of the photovoltaic assembly at the target time point is predicted based on the target wave parameters of the photovoltaic assembly at the target time point and the motion parameters of the photovoltaic assembly at the current time point, including:

[0021] Using a preset photovoltaic module motion prediction model 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, a corresponding target prediction result is obtained;

[0022] According to the target prediction results, the motion state data of the photovoltaic components at the target time point is determined;

[0023] According to the motion state data of the photovoltaic assembly at the target time point and the motion parameters of the photovoltaic assembly at the current time point, the tilt angle change data of the photovoltaic assembly at the target time point is determined.

[0024] In one embodiment, after obtaining the corresponding target prediction result, the method further includes:

[0025] determining a motion response type of the photovoltaic assembly at the target time point based on the motion state data of the photovoltaic assembly at the target time point;

[0026] According to the motion response type, a matching target response type label is determined;

[0027] combining the target wave parameters of the photovoltaic assembly at the target time point, the motion parameters of the photovoltaic assembly at the current time point, and the target response type label to obtain target combination data;

[0028] The target combination data is processed using a preset photovoltaic assembly motion prediction model to determine motion state data of the photovoltaic assembly at a target time point.

[0029] In one embodiment, the motion response type includes at least one of the following: surge, sway, heave, roll, pitch, and yaw.

[0030] In one embodiment, the method further comprises:

[0031] Get the temperature data at the current time point;

[0032] Based on the temperature data at the current time point, predict the temperature change data at the target time point;

[0033] The floating photovoltaic array is adjusted 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.

[0034] In one embodiment, a plurality of wave sensors are provided outside the floating photovoltaic array at reference positions at specified distances from the floating photovoltaic array in multiple directions;

[0035] Accordingly, the method further includes:

[0036] Acquire wave parameters of multiple reference positions at current time points collected by multiple wave sensors;

[0037] Determine the main wave direction at the current time point based on the wave parameters of multiple reference positions at the current time point;

[0038] According to the main wave direction at the current time point, the effective wave parameters at the current time point are determined from the wave parameters of multiple reference positions 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 components at the target time point.

[0039] This specification also provides a data processing device for a floating photovoltaic array, which is applied to the floating photovoltaic array. The floating photovoltaic array includes a plurality of photovoltaic modules, each of which is disposed on a supporting float, and the supporting float is provided with a motion sensor. A wave sensor is provided outside the floating photovoltaic array at least at a reference position at a specified distance from the floating photovoltaic array in a direction opposite to the main wave. The device includes:

[0040] An acquisition module is used to acquire motion parameters of the photovoltaic module at the current time point using a motion sensor; and to acquire wave parameters of a reference position at the current time point using a wave sensor;

[0041] A processing module is used to determine the wave transmission delay of the reference position relative to the photovoltaic module based on the wave parameters of the reference position at the current time point; and to construct a matching current wave parameter change prediction model;

[0042] A determination module is used to determine a target time point based on the current time point and the wave transmission delay; and to determine the target wave parameters of the photovoltaic module at the target time point using the current wave parameter change prediction model;

[0043] A prediction module is used to 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;

[0044] The adjustment module is used to adjust the floating photovoltaic array according to the inclination change data of the photovoltaic components at the target time point.

[0045] This specification also provides a computer device, including a processor and a memory for storing processor-executable instructions, wherein the processor implements relevant steps of the data processing method for the floating photovoltaic array when executing the instructions.

[0046] This specification also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the computer program implements the relevant steps of the data processing method for the floating photovoltaic array.

[0047] Based on the data processing method, device, and computer equipment for a floating photovoltaic array provided in this specification, prior to implementation, corresponding motion sensors can be pre-installed on the supporting floats of the photovoltaic modules in the floating photovoltaic array; at the same time, wave sensors can be installed outside the floating photovoltaic array at least at a reference position at a specified distance from the floating photovoltaic array along the opposite direction of the main wave. During implementation, the motion sensors can be used to collect motion parameters of the photovoltaic modules at the current time point, and the wave sensors can be used to collect wave parameters at the reference position at the current time point. Based on the wave parameters at the reference position at the current time point, the wave propagation delay from the reference position to the photovoltaic module is determined, and a matching current wave parameter change prediction model is constructed. Based on the current time point and the wave propagation delay, a target time point for the wave at the reference position to reach the photovoltaic module is determined. The current wave parameter change prediction model is used to predict the target wave parameters of the photovoltaic module at the target time point. 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 are then combined to predict the tilt angle change data of the photovoltaic module at the target time point. Based on the tilt angle change data of the photovoltaic module at the target time point, the floating photovoltaic array is adjusted. This allows for accurate and efficient prediction of the PV module's tilt angle change data in advance, and timely and targeted adjustments to the PV modules based on the tilt angle change data, to ensure that the floating PV array can achieve a relatively optimal power generation at the target time point, thereby effectively increasing the overall power generation of the floating PV array. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of this specification, the following is a brief introduction to the drawings required for use in the embodiments. The drawings described below are only some of the embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0049] Figure 1 This is a flow chart of a data processing method for a floating photovoltaic array provided by one embodiment of this specification;

[0050] Figure 2 This is a schematic diagram of an embodiment of a data processing method for a floating photovoltaic array provided by an embodiment of this specification, in a scenario example;

[0051] Figure 3 This is a schematic diagram of an embodiment of a data processing method for a floating photovoltaic array provided by an embodiment of this specification, in a scenario example;

[0052] Figure 4This is a schematic diagram of an embodiment of a data processing method for a floating photovoltaic array provided by an embodiment of this specification, in a scenario example;

[0053] Figure 5 This is a schematic diagram of an embodiment of a data processing method for a floating photovoltaic array provided by an embodiment of this specification, in a scenario example;

[0054] Figure 6 This is a schematic diagram of an embodiment of a data processing method for a floating photovoltaic array provided by an embodiment of this specification, in a scenario example;

[0055] Figure 7 This is a schematic diagram of an embodiment of a data processing method for a floating photovoltaic array provided by an embodiment of this specification, in a scenario example;

[0056] Figure 8 This is a schematic diagram of the structure of a computer device provided by one embodiment of this specification;

[0057] Figure 9 This is a schematic diagram of the structure of a data processing device for a floating photovoltaic array provided by one embodiment of this specification;

[0058] Figure 10 This is a schematic diagram of an embodiment of a data processing method for a floating photovoltaic array provided by an embodiment of this specification, in a scenario example;

[0059] Figure 11 This is a schematic diagram of an embodiment of a data processing method for a floating photovoltaic array provided by an embodiment of this specification, in a scenario example. DETAILED DESCRIPTION

[0060] To help those skilled in the art better understand the technical solutions in this specification, the following will provide a clear and complete description of the technical solutions in the embodiments of this specification, in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. All other embodiments derived by those skilled in the art based on the embodiments in this specification without creative effort shall fall within the scope of protection of this specification.

[0061] It should be noted that the user-related information and data involved in the embodiments of this specification are all information and data authorized by the user or fully authorized by relevant parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with relevant laws, regulations and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users or relevant parties to choose to authorize or refuse.

[0062] It should also be noted that in the embodiments of this specification, certain software, components, models and other existing solutions in the industry may be mentioned. They should be regarded as exemplary and their purpose is only to illustrate the feasibility of implementing the technical solution of this application, but it does not mean that the applicant has or will necessarily use the solution.

[0063] See Figure 1 As shown, the embodiment of this specification provides a data processing method for a floating photovoltaic array, wherein the method is specifically applied to a floating photovoltaic array. Figure 2 and Figure 3 As shown, the floating photovoltaic array may include multiple photovoltaic modules, which are arranged on a supporting float. The supporting float may be provided with a motion sensor. A wave sensor is also provided outside the floating photovoltaic array at least at a reference position along the opposite direction of the main wave and at a specified distance from the floating photovoltaic array. In specific implementation, the method may include the following:

[0064] S101: using a motion sensor to collect motion parameters of the photovoltaic module at the current time point; using a wave sensor to collect wave parameters of a reference position at the current time point;

[0065] S102: Determine the wave transmission delay of the reference position relative to the photovoltaic module based on the wave parameters of the reference position at the current time point; and construct a matching current wave parameter change prediction model;

[0066] S103: Determine a target time point based on the current time point and the wave transmission delay; and determine target wave parameters for the photovoltaic module at the target time point using the current wave parameter change prediction model;

[0067] S104: predicting 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;

[0068] S105: Adjusting the floating photovoltaic array according to the tilt angle change data of the photovoltaic components at the target time point.

[0069] See Figure 2 and Figure 3As shown, the floating photovoltaic array can include multiple independent photovoltaic modules, such as photovoltaic module 1#, photovoltaic module 2#, photovoltaic module 3#, photovoltaic module 4#, and photovoltaic module 5#. Each photovoltaic module is also connected to a corresponding photovoltaic inverter. In specific implementations, the photovoltaic inverter can adjust parameters such as the current and voltage of the photovoltaic module to achieve a relatively optimal power generation output for the corresponding photovoltaic module. The floating photovoltaic array can be deployed in a floating photovoltaic power plant at sea or on a large lake.

[0070] Specifically, the photovoltaic modules can be mounted on independent supporting floats (or floating bodies). Furthermore, a corresponding motion sensor is installed at the bottom of each supporting float. Specifically, the motion sensor can be a six-degree-of-freedom motion sensor. This motion sensor can accurately monitor and collect motion parameters, such as the tilt angle, of the photovoltaic modules linked to the supporting floats.

[0071] See Figure 2 and Figure 3 As shown, a wave sensor can be installed outside the floating photovoltaic array at a reference location at least a specified distance (e.g., L1) from the floating photovoltaic array along the opposite direction of the main wave. Specifically, the wave sensor can be a floating wave sensor. This wave sensor can monitor and collect relevant wave parameters before waves reach the supporting buoys of the photovoltaic modules in the floating photovoltaic array. This specified distance is associated with the adjustment strategy of the floating photovoltaic array and the specific wave parameters, which will be explained in detail later.

[0072] Furthermore, the floating photovoltaic array further includes a processor (or computer device), which is connected to the wave sensor, the motion sensor, the photovoltaic inverter, and the photovoltaic module respectively.

[0073] The above-mentioned processor can be specifically used to execute the data processing method for 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 components at the previous time point and the wave parameters of the reference position at the current time point; based on the above-mentioned relevant data, determine the target time point when the monitored wave reaches the supporting float of the photovoltaic components of the floating photovoltaic array, and construct a matching current wave parameter change prediction model; then use the 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; then, based on the wave parameters, accurately predict the inclination change data of the photovoltaic components at the future target time point; and then, based on the inclination change data of the photovoltaic components, determine a matching adjustment strategy; and based on the adjustment strategy, perform targeted adjustments to the floating photovoltaic array 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.

[0074] The target time point may be specifically understood as the time point when the wave monitored at the reference position at the current time point (which may be recorded as t0) reaches the supporting float where the photovoltaic components in the floating photovoltaic array are located.

[0075] The motion parameters of the photovoltaic assembly mentioned above can be specifically understood as parameter data that can describe the posture state of the photovoltaic assembly, for example, the inclination angle α of the photovoltaic assembly relative to the sea level.

[0076] The aforementioned wave parameters can be understood as parameter data that can characterize the wave properties. Specifically, these wave parameters may include at least one of the following: wave number, amplitude, phase difference, angular frequency, period, and so on. Of course, it should be noted that the wave parameters listed above are merely illustrative. During implementation, depending on specific circumstances and processing requirements, the aforementioned wave parameters may also include other types of parameters. This specification does not limit this.

[0077] In a specific implementation, the data directly collected by the wave sensor can be a waveform data for describing the waves; by analyzing and processing the above waveform data, the required wave parameters can be extracted.

[0078] The above-mentioned matching current wave parameter change prediction model can be specifically understood as an algorithm model that is constructed based on the fluctuation properties of the current wave, combined with the transmission mechanism and superposition mechanism of the wave, and can predict the wave changes in a short period of time in the future.

[0079] Based on the above embodiment, by synchronously collecting the motion parameters of the photovoltaic components at the current time point and the wave parameters of the reference position at the current time point at a specified distance from the floating photovoltaic array along the opposite direction of the main wave; and jointly utilizing the above two parameters, the inclination change data of the photovoltaic components at the future target time point can be accurately predicted in advance, so that targeted adjustments can be made to the floating photovoltaic array in time to ensure that the photovoltaic components can still obtain a relatively good power generation rate at the future target time point, thereby effectively improving the overall power generation of the floating photovoltaic array and improving the overall efficiency of the floating photovoltaic power plant.

[0080] In some embodiments, see Figure 4 As shown, the wave transmission delay of the reference position relative to the photovoltaic module is determined based on the wave parameters of the reference position at the current time point. The specific implementation may include the following:

[0081] S1: Determine the wave speed of the wave at the current time point based on the wave parameters of the reference position at the current time point;

[0082] S2: Obtaining the layout parameters of the photovoltaic components with respect to the floating photovoltaic array;

[0083] S3: Calculate the wave transmission delay of the reference position relative to the photovoltaic module according to the specified distance, the wave speed at the current time point, and the layout parameters of the photovoltaic module with respect to the floating photovoltaic array.

[0084] Specifically, the wave speed of the wave at the current time point can be extracted through waveform analysis based on the wave parameters of the reference position at the current time point, which is recorded as c.

[0085] At the same time, based on the layout parameters of the PV module of interest relative to the floating PV array (for example, the arrangement number, etc.) and the overall structural parameters of the floating PV array, the distance between the PV module and the edge of the floating PV array along the direction opposite to the main wave can be determined, which is recorded as: l1.

[0086] Accordingly, the wave transmission delay of the reference position relative to the photovoltaic module can be calculated as: .

[0087] When the accuracy requirement is relatively low, in order to simplify the calculation process and improve the overall calculation efficiency, the distance between the photovoltaic module and the reference position can be directly approximated as L1, and the wave transmission delay can be directly calculated according to the following formula: .

[0088] 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.

[0089] In some embodiments, see Figure 5 As shown, the above-mentioned construction matches the current wave parameter change prediction model, and when implemented specifically, it may include the following contents:

[0090] S1: Obtaining environmental parameters of a floating photovoltaic array; wherein the environmental parameters at least include a water depth in an area where the floating photovoltaic array is located;

[0091] S2: Calculate the wave attenuation coefficient of the area where the floating photovoltaic array is located relative to the reference position based on the wave parameters of the reference position at the current time point and the environmental parameters of the floating photovoltaic array;

[0092] S3: Based on 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, a matching current wave parameter change prediction model is constructed.

[0093] In specific implementation, the required period (which can be recorded 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 wave period, wave speed, and the water depth (which can be recorded 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 can be calculated (for example, ). Specifically, the corresponding wave attenuation coefficient can be calculated according to the following formula: .

[0094] In some embodiments, the above-mentioned current wave parameter change prediction model is constructed based on 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. When implemented, it may include the following:

[0095] S1: extracting the waveform characteristics of 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), amplitude (for example, A), phase angle (for example, ), angular frequency (e.g., ω);

[0096] S2: Construct the wave component expression based on the waveform characteristics and wave attenuation coefficient at the current time point;

[0097] S3: Based on the expression of wave components, a matching current wave parameter change prediction model is constructed through wave transfer and superposition processing.

[0098] In a specific implementation, the waveform data directly collected by the wave sensor can be first split into multiple sub-waveform data (for example, N sub-waveform data) through principal component analysis, that is, N components of the wave; then, based on the wave parameters of the reference position at the current time point extracted based on the above waveform data, the waveform characteristics corresponding to each sub-waveform data are extracted in combination with the N sub-waveform data; based on the waveform characteristics of the above sub-waveform data, the waveform expression of each sub-waveform data is determined, which can be specifically expressed as follows: , i=1,2……N. Among them, i is the number of the sub-waveform data, ranging from 1 to N; y i is the sub-waveform data numbered i, A i is the 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 interval length relative to the current time point. When the wave reaches the area where the floating photovoltaic array is located, .

[0099] To facilitate subsequent calculations, the waveform expression of the above sub-waveform data can be further converted and simplified to obtain the following form: , i=1,2...N. Among them, A' i The attenuation coefficient is taken into account After that, the equivalent amplitude of the sub-waveform data numbered i is obtained. That is, the component expression of the wave is obtained.

[0100] Then, according to the wave transmission mechanism and superposition mechanism, corresponding wave transmission and superposition processing can be performed according to the above wave component expressions, which can include: first, based on the wave superposition mechanism, superposition processing is performed on the waveform expressions of multiple sub-waveform data to obtain the corresponding initial superposition expression, which can be recorded as: 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 use the trigonometric identity to convert the above initial superposition expression into the corresponding complex form to obtain the corresponding intermediate superposition expression, which can be written as: Based on the above intermediate superposition expression, we can further convert it to obtain the final wave expression used to characterize the waves reaching the area where the floating photovoltaic array is located, which can be expressed as: Among them, |Y| represents the amplitude of the terminal wave, ; represents the phase of the final wave, Convert the terminal wave expression of the above wave into real number form, so as to obtain the matching current wave parameter change prediction model, which is recorded as: y=|Y| sin(kx-ωt+ ).

[0101] Based on the above embodiment, the wave parameters at the current time point can be fully utilized, combined with the wave transmission mechanism and superposition mechanism, to construct a current wave parameter change prediction model with high prediction accuracy and good effect for a short period of time in the future from the current time point.

[0102] In some embodiments, the above-mentioned use of the current wave parameter change prediction model to determine the target wave parameters of the photovoltaic components at the target time point may include: substituting the target time point into the current wave parameter change prediction model, and combining the wave parameters of the reference position at the current time point to determine the wave parameters at the photovoltaic component position in the area where the floating photovoltaic array is located at the target time point, that is, the target wave parameters.

[0103] In some embodiments, see Figure 6 As shown, the above prediction of the inclination angle change data of the photovoltaic assembly at the target time point based on the target wave parameters of the photovoltaic assembly at the target time point and the motion parameters of the photovoltaic assembly at the current time point may include the following contents during specific implementation:

[0104] S1: using a preset photovoltaic module motion prediction model 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 a corresponding target prediction result;

[0105] S2: Determine the motion state data of the photovoltaic module at the target time point based on the target prediction result;

[0106] S3: Determine the tilt angle change data of the photovoltaic assembly at the target time point according to the motion state data of the photovoltaic assembly at the target time point and the motion parameters of the photovoltaic assembly at the current time point.

[0107] Among them, the preset motion prediction model of photovoltaic components can be specifically understood as an algorithm model that is obtained by pre-using a large amount of sample data through deep learning training, and can predict the corresponding motion parameters of photovoltaic components based on the wave parameters in the environment.

[0108] Before specific implementation, an experimental area can be set up at sea, and sample photovoltaic modules can be arranged in the experimental area; wherein, the sample photovoltaic modules are set on a supporting float, and a motion sensor is set at the bottom of the supporting float; and a wave sensor is set in the vicinity of the sample photovoltaic modules; during the implementation process, wave parameters and motion parameters corresponding to the same time point are synchronously collected and combined to obtain multiple data groups; wherein, one data group corresponds to one time point and contains the wave parameters and motion parameters corresponding to the time point; from the above multiple data groups, two data groups with time intervals within a valid time range are extracted and combined to obtain multiple sample groups; motion parameters corresponding to the previous time point are extracted from the multiple sample groups, and combined with the motion parameters and wave parameters corresponding to the subsequent time point to obtain a sample data; according to the above method, multiple sample data can be constructed; data cleaning is performed on the multiple sample data to obtain cleaned sample data; an initial model based on FCOS (Fully Convolutional One-Stage) is constructed; and by using the cleaned sample data, deep learning is performed on the initial model to obtain a preset photovoltaic module motion prediction model that meets the requirements.

[0109] Based on the above embodiment, the preset photovoltaic assembly motion prediction model can be used to accurately and efficiently predict the inclination angle change data of the photovoltaic assembly at a target time point after the current time point.

[0110] In some embodiments, after obtaining the corresponding target prediction result, the method may further include the following steps when implemented:

[0111] S1: determining the motion response type of the photovoltaic assembly at the target time point according to the motion state data of the photovoltaic assembly at the target time point;

[0112] S2: Determine the matching target response type label based on the motion response type;

[0113] S3: combining the target wave parameters of the photovoltaic assembly at the target time point, the motion parameters of the photovoltaic assembly at the current time point, and the target response type label to obtain target combination data;

[0114] S4: using a preset photovoltaic assembly motion prediction model to process the target combination data to determine the motion state data of the photovoltaic assembly at the target time point.

[0115] Specifically, during the training of a pre-defined PV module motion prediction model, it was discovered that for different motion response types, the patterns in how the PV module's motion parameters change with wave parameters vary locally. Given a known motion response type, the pre-defined PV module motion prediction model can more accurately predict the corresponding PV module motion state based on the previously learned patterns for that motion response type.

[0116] Based on the above considerations, the preset motion prediction model of the photovoltaic component can be used to directly process the target wave parameters of the photovoltaic component at the target time point and the motion parameters of the photovoltaic component at the current time point to perform a first prediction and obtain a first prediction result; based on the first prediction result, the motion state data of the photovoltaic component at the target time point with relatively low accuracy can be determined; and then the motion state data can be used to match the preset motion response template to determine the motion response type of the photovoltaic component at the target time point.

[0117] The preset motion response template is established by clustering motion state data of a large number of sample photovoltaic modules corresponding to different motion response types.

[0118] Furthermore, a matching target response type label can be determined based on the motion response type. The target response type label is then 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 target combination data containing motion response type information that can be recognized by the model.

[0119] The preset motion prediction model of photovoltaic components is then used to process the above target combination data. When the motion response type is known, a second prediction is made using the changing rules of the motion parameters of the matching and targeted photovoltaic components with the wave parameters, so that the motion status data of the photovoltaic components at the target time point can be determined more accurately.

[0120] The motion state data of the photovoltaic module at the target time point obtained by the second prediction can be combined 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.

[0121] In some embodiments, the motion response type may specifically include at least one of the following: surge, sway, heave, roll, pitch, bow pitch, etc.

[0122] During the deep learning process, the preset PV module motion prediction model not only learns the basic law of change of PV module motion parameters with wave parameters, but also automatically identifies and distinguishes different motion response types, and learns and masters relatively more detailed and targeted change laws for different motion response types.

[0123] In some embodiments, the method may further include the following when implemented:

[0124] S1: Get the temperature data at the current time point;

[0125] S2: Based on the temperature data at the current time point, predict the temperature change data at the target time point;

[0126] S3: Adjust the floating photovoltaic array according to the tilt angle change data of the photovoltaic module and the temperature change data at the target time point.

[0127] During specific implementation, in addition to obtaining the temperature data at the current time point, it is also necessary to obtain the temperature records of the current time period and the condition information at the current time point; wherein the above-mentioned condition information may include at least one of the following: weather information, seasonal information, wind direction information, etc.; then, according to the preset splicing rules, the temperature data at the current time point, the temperature records of the current time period, the target time point, and the condition information at the current time point are spliced ​​to obtain the combined temperature data; then, the preset temperature prediction model is used to process the combined temperature data to predict the temperature data at the target time point; wherein, the preset temperature prediction model is a neural network model obtained by deep learning training using sample combined temperature data in advance; then, based on the temperature data at the target time point and the temperature data at the current time point, the temperature change data at the target time point is determined.

[0128] Based on the above embodiment, by introducing temperature change data, the temperature change data and the tilt change data can be combined to more comprehensively predict and analyze the situation characteristics of the floating photovoltaic array at the target time point, thereby achieving more effective and accurate adjustment of the floating photovoltaic array, so that the floating photovoltaic array can obtain relatively optimal power generation at the target time point.

[0129] During specific implementation, a corresponding target prompt word can be determined based on preset prompt word rules, in combination with temperature change data at a target time point and tilt angle change data of photovoltaic modules at a target time point; a preset large language model is then used to determine a matching target adjustment strategy based on the target prompt word; wherein the preset large language model is connected to a preset adjustment strategy library, which can store a plurality of preset adjustment strategies for different situations that are pre-organized by combining expert experience and a large number of historical adjustment records; and then, based on the target adjustment strategy, the photovoltaic inverters of the photovoltaic modules in the floating photovoltaic array can be controlled in a targeted manner to make corresponding adjustments, so that the power generation power of the photovoltaic modules at the target time point is relatively optimal, thereby ensuring that the power generation power of the floating photovoltaic array as a whole at the target time point is relatively optimal.

[0130] When making specific adjustments, the current, voltage and other electrical parameters of the corresponding photovoltaic modules can be specifically adjusted using the photovoltaic inverter through small perturbation methods and other methods according to the target adjustment strategy.

[0131] In some embodiments, a plurality of wave sensors may be provided outside the floating photovoltaic array at reference positions at specified distances from the floating photovoltaic array in multiple directions;

[0132] Accordingly, when the method is implemented, it may further include the following contents:

[0133] S1: Acquire wave parameters of multiple reference positions at current time points collected by multiple wave sensors;

[0134] S2: determining the main wave direction at the current time point based on the wave parameters of multiple reference positions at the current time point;

[0135] S3: According to the main wave direction at the current time point, determine the effective wave parameters at the current time point from the wave parameters of multiple reference positions 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.

[0136] Specifically, for example, the historical wave monitoring records of the area where the floating photovoltaic array is located can be obtained and, through big data processing, four relatively common wave directions can be determined; and four different wave sensors can be set at four reference positions at specified distances from the floating photovoltaic array along the four wave directions, see Figure 7 Shown, for example, are wave sensor 1 , wave sensor 2 , wave sensor 3 , and wave sensor 4 .

[0137] In specific implementation, multiple wave sensors can be used to collect wave parameters of multiple reference positions at the same time point corresponding to multiple reference positions at the current time point. The wave parameters of the multiple reference positions at the current time point can then be used together for cross-validation to determine the main wave direction at the current time point. A reference position at a specified distance from the floating photovoltaic array along the main wave direction, or the reference position closest to the position, can then be selected from the multiple reference positions as a valid reference position. The wave parameters of the reference position at the current time point collected based on the valid reference position can then be used as the valid wave parameters at the current time point. Subsequently, the valid wave parameters at the current time point can be used as the wave parameters of the reference position at the current time point used this time to determine the wave transmission delay of the reference position relative to the photovoltaic module. A matching current wave parameter change prediction model can then be constructed to determine the target wave parameters of the photovoltaic module at the target time point. This can further reduce errors and improve data processing accuracy.

[0138] In some embodiments, when the method is specifically implemented, the following may further be included: determining other wave parameters of the wave parameters of the reference positions at the current time point, excluding the valid wave parameters at the current time point, as reference wave parameters at the current time point;

[0139] Accordingly, after determining the target wave parameters of the photovoltaic module at the target time point using the current wave parameter change prediction model, the method may further include the following when implemented:

[0140] S1: Using the reference wave parameters at the current time point as auxiliary verification, detect whether there is an error in the target wave parameters of the PV modules at the target time point;

[0141] S2: When it is determined that there is an error, the target wave parameters of the photovoltaic module at the target time point are corrected using the reference wave parameters at the current time point.

[0142] In addition, the effective wave parameters at the current time point can 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.

[0143] In some embodiments, the method may further include the following when implemented:

[0144] S1: every preset time period, obtain the wave parameters of the reference position of the current time period;

[0145] S2: Determine whether the wave fluctuation amplitude of the current time period is greater than a preset amplitude threshold based on the wave parameters of the reference position of the current time period;

[0146] S3: When it is determined that the wave fluctuation amplitude in the current time period is greater than a preset amplitude threshold, triggering the use of a motion sensor to collect motion parameters of the photovoltaic component at the current time point; and using the wave sensor to collect wave parameters of a reference position at the current time point.

[0147] Based on the above embodiment, at predetermined time intervals, the wave fluctuation amplitude of the current time interval can be evaluated based on the wave parameters at the reference location during the current time interval to determine whether the wave fluctuations in the current time interval will have a significant impact on the floating photovoltaic array. If a significant impact is determined, the floating photovoltaic array data processing method provided in this specification can be triggered in a timely and automatic manner. Conversely, if a significant impact is not determined, the floating photovoltaic array data processing method provided in this specification is not triggered, and monitoring continues for the next time interval.

[0148] In some embodiments, after the wave parameters of the reference position in the current time period, the method may further include the following when implemented:

[0149] S1: Determine the wave transmission delay of the current time period based on the wave parameters of the reference position of the current time period;

[0150] S2: Determine whether the specified distance is currently valid based on the wave transmission delay in the current time period and the preset reference adjustment time;

[0151] S3: When it is determined that the designated distance is currently invalid, an adjustment instruction regarding the reference position is generated.

[0152] The preset reference adjustment time can be determined based on the overall data processing time and the overall adjustment effective time.

[0153] During specific implementation, the speed of the waves will continue to change. When the wave speed is faster, 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 time. 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. At this time, it can be considered that the currently used specified distance is invalid. In this case, it is necessary to extend the specified distance to have enough time to complete the relevant data processing and adjustment in advance. Conversely, if the specified distance is too long, or 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 factors that cannot be predicted in advance, thereby resulting in a relatively large error and low credibility of the wave parameters of the photovoltaic components at the target time point. At this time, it can also be considered that the currently used specified distance is invalid.

[0154] Therefore, in accordance with the above method, real-time or periodic monitoring can be performed to determine whether the specified distance used is valid based on the actual situation; and when it is found that the specified distance is invalid, an adjustment instruction for the reference position is generated in time; and in response to the adjustment instruction, a corresponding reference position is re-determined based on the actual situation, and then a wave sensor can be deployed at the new reference position to collect the corresponding wave parameters.

[0155] Specifically, an underwater mobile module can be installed at the bottom of the wave sensor. This module can receive and respond to adjustment commands, perform a planning solution based on the current wave speed and dominant wave direction, and determine an updated reference position. The underwater mobile module can then be controlled to drive the wave sensor to and remain at this updated reference position. This allows for intelligent and efficient redetermination of the reference position and automated deployment of the wave sensor.

[0156] As can be seen from the above, the data processing method for the floating photovoltaic array provided in the embodiments of this specification can be pre-installed with corresponding motion sensors on the supporting floats of the photovoltaic modules of the floating photovoltaic array before implementation. At the same time, a wave sensor can be installed outside the floating photovoltaic array at least at a reference position at a specified distance from the floating photovoltaic array along the opposite direction of the main wave. During implementation, the motion sensor can be used to collect the motion parameters of the photovoltaic module at the current time point, and the wave sensor can be used to collect the wave parameters of the reference position at the current time point. Based on the wave parameters of the reference position at the current time point, the wave transmission delay of the reference position relative to the photovoltaic module is determined, and a matching current wave parameter change prediction model is constructed. Then, based on the current time point and the wave transmission delay, a target time point is determined. The current wave parameter change prediction model is used to determine the target wave parameters 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, the inclination change data of the photovoltaic module at the target time point is predicted. Based on the inclination change data of the photovoltaic module at the target time point, the floating photovoltaic array is adjusted. This allows for accurate and efficient prediction of the inclination change data of photovoltaic modules in advance, and timely and targeted adjustments to the photovoltaic modules based on the inclination change data, thereby effectively increasing the overall power generation of the floating photovoltaic array.

[0157] This specification provides a computer device, referring to Figure 8 The computer device includes a network communication port 801, a processor 802, and a memory 803, and the above structures are connected through internal cables so that each structure can perform specific data interaction.

[0158] The network communication port 801 can be used to receive trigger instructions.

[0159] The processor 802 can be specifically used to respond to a trigger instruction, use a motion sensor to collect motion parameters of the photovoltaic component at the current time point; use a wave sensor to collect wave parameters of a reference position at the current time point; determine the wave transmission delay of the reference position relative to the photovoltaic component based on the wave parameters of the reference position at the current time point; and construct a matching current wave parameter change prediction model; determine a target time point based on the current time point and the wave transmission delay; and use the current wave parameter change prediction model to determine the target wave parameters of the photovoltaic component at the target time point; predict the inclination change data of the photovoltaic component at the target time point based on the target wave parameters of the photovoltaic component at the target time point and the motion parameters of the photovoltaic component at the current time point; and adjust the floating photovoltaic array based on the inclination change data of the photovoltaic component at the target time point.

[0160] The memory 803 may be specifically used to store corresponding instruction programs, as well as relevant data such as motion parameters of the photovoltaic components at the current time point, wave parameters of the reference position at the current time point, etc.

[0161] Based on the above method, the relevant structural performance of computer equipment can be effectively utilized, the data processing speed of electronic equipment can be improved, and data processing of floating photovoltaic arrays can be efficiently realized.

[0162] In this embodiment, the network communication port 801 can be a virtual port that is bound to different communication protocols, thereby being capable of sending or receiving different data. For example, the network communication port can be a port responsible for web data communication, a port responsible for FTP data communication, or a port responsible for email data communication. Furthermore, the network communication port can also be a physical communication interface or communication chip. For example, it can be a wireless mobile network communication chip, such as GSM or CDMA; it can also be a Wi-Fi chip; or it can be a Bluetooth chip.

[0163] In this embodiment, the processor 802 can be implemented in any appropriate manner. For example, the processor can take the form of 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, an application-specific integrated circuit (ASIC), a programmable logic controller, an embedded microcontroller, etc. This specification is not intended to limit this.

[0164] In this embodiment, the memory 803 may 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 that has no 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 stick, TF card, etc.

[0165] The embodiments of this specification also provide a computer-readable storage medium based on the data processing method of the above-mentioned floating photovoltaic array, wherein the computer-readable storage medium stores computer program instructions, which, when executed, implement the following: using a motion sensor to collect motion parameters of the photovoltaic component at the current time point; using a wave sensor to collect wave parameters of a reference position at the current time point; determining the wave transmission delay of the reference position relative to the photovoltaic component based on the wave parameters of the reference position at the current time point; and constructing a matching current wave parameter change prediction model; determining a target time point based on the current time point and the wave transmission delay; and determining the target wave parameters of the photovoltaic component at the target time point using the current wave parameter change prediction model; predicting the inclination change data of the photovoltaic component at the target time point based on the target wave parameters of the photovoltaic component at the target time point and the motion parameters of the photovoltaic component at the current time point; and adjusting the floating photovoltaic array based on the inclination change data of the photovoltaic component at the target time point.

[0166] In this embodiment, the 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 an interface configured in accordance with a standard specified by a communication protocol and used for network connection and communication.

[0167] 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 implementations and will not be repeated here.

[0168] An embodiment of the present specification also provides a computer program product, which at least includes a computer program, and when the computer program is executed by a processor, implements the following method steps: using a motion sensor to collect motion parameters of a photovoltaic component at a current time point; using a wave sensor to collect wave parameters of a reference position at the current time point; determining the wave transmission delay of the reference position relative to the photovoltaic component based on the wave parameters of the reference position at the current time point; and constructing a matching current wave parameter change prediction model; determining a target time point based on the current time point and the wave transmission delay; and using the current wave parameter change prediction model to determine the target wave parameters of the photovoltaic component at the target time point; predicting the inclination change data of the photovoltaic component at the target time point based on the target wave parameters of the photovoltaic component at the target time point and the motion parameters of the photovoltaic component at the current time point; and adjusting the floating photovoltaic array based on the inclination change data of the photovoltaic component at the target time point.

[0169] See Figure 9 As shown, an embodiment of this specification further provides a data processing device for a floating photovoltaic array, which is applied to a floating photovoltaic array, wherein the floating photovoltaic array includes a plurality of photovoltaic modules, the photovoltaic modules are arranged on a supporting float, and the supporting float is provided with a motion sensor; a wave sensor is provided outside the floating photovoltaic array at least at a reference position at a specified distance from the floating photovoltaic array along the opposite direction of the main wave. The device may specifically include the following structural modules:

[0170] The acquisition module 901 may be specifically configured to acquire motion parameters of the photovoltaic module at the current time point using a motion sensor; and to acquire wave parameters of a reference position at the current time point using a wave sensor;

[0171] Processing module 902 may be specifically configured to determine the wave transmission delay between the reference location and the photovoltaic module based on the wave parameters at the reference location at the current time point, and to construct a matching current wave parameter change prediction model;

[0172] The determination module 903 may be specifically configured to determine a target time point based on the current time point and the wave transmission delay; and determine target wave parameters for the photovoltaic module at the target time point using the current wave parameter change prediction model;

[0173] The prediction module 904 may be specifically configured to 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;

[0174] The adjustment module 905 may be specifically configured to adjust the floating photovoltaic array according to the tilt angle change data of the photovoltaic module at the target time point.

[0175] In some embodiments, when the above-mentioned processing module 902 is specifically implemented, the wave transmission delay of the reference position relative to the photovoltaic component can be determined according to the wave parameters of the reference position at the current time point in the following manner: the wave speed of the wave at the current time point is determined according to the wave parameters of the reference position at the current time point; the layout parameters of the photovoltaic component with respect to the floating photovoltaic array are obtained; and the wave transmission delay of the reference position relative to the photovoltaic component is calculated according to the specified distance, the wave speed of the wave at the current time point, and the layout parameters of the photovoltaic component with respect to the floating photovoltaic array.

[0176] In some embodiments, when the above-mentioned processing module 902 is specifically implemented, a matching current wave parameter change prediction model can be constructed in the following manner: obtaining environmental parameters of the floating photovoltaic array; wherein the environmental parameters include at least 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 based on 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 based on 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.

[0177] In some embodiments, when the above-mentioned prediction module 904 is implemented, the inclination change data of the photovoltaic component at the target time point can be predicted according to the target wave parameters of the photovoltaic component at the target time point and the motion parameters of the photovoltaic component at the current time point in the following manner: the target wave parameters of the photovoltaic component at the target time point and the motion parameters of the photovoltaic component at the current time point are processed using a preset motion prediction model of the photovoltaic component to obtain a corresponding target prediction result; based on the target prediction result, the motion state data of the photovoltaic component at the target time point is determined; based on the motion state data of the photovoltaic component at the target time point and the motion parameters of the photovoltaic component at the current time point, the inclination change data of the photovoltaic component at the target time point is determined.

[0178] In some embodiments, after obtaining the corresponding target prediction result, the device can also be used, when implemented, to: determine the motion response type of the photovoltaic component at the target time point based on the motion state data of the photovoltaic component at the target time point; determine a matching target response type label based on the motion response type; combine the target wave parameters of the photovoltaic component at the target time point, the motion parameters of the photovoltaic component at the current time point, and the target response type label to obtain target combination data; and determine the motion state data of the photovoltaic component at the target time point by processing the target combination data using a preset photovoltaic component motion prediction model.

[0179] In some embodiments, the motion response type may specifically include at least one of the following: surge, sway, heave, roll, pitch, bow pitch, etc.

[0180] In some embodiments, when the device is implemented, it can also be used to: obtain temperature data at the current time point; predict temperature change data at the target time point based on the temperature data at the current time point; adjust the floating photovoltaic array based on the inclination change data of the photovoltaic component at the target time point and the temperature change data at the target time point.

[0181] In some embodiments, a plurality of wave sensors are provided outside the floating photovoltaic array at reference positions at specified distances from the floating photovoltaic array in multiple directions;

[0182] Accordingly, when the device is implemented, it can also be used to: obtain wave parameters of multiple reference positions at the current time points collected by multiple wave sensors; determine the main wave direction at the current time point based on the wave parameters at the reference positions at the multiple current time points; determine the effective wave parameters at the current time point from the wave parameters at the reference positions at the multiple current time points based on 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 components at the target time point.

[0183] It should be noted that the units, devices or modules described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. For the convenience of description, the above devices are described in terms of functions and are divided into various modules 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 module that implements the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, such as 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 mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0184] As can be seen from the above, the data processing device for the floating photovoltaic array provided in the embodiments of this specification can accurately and efficiently predict the inclination change data of the photovoltaic modules in advance, and make targeted adjustments to the photovoltaic modules in a timely manner according to the above inclination change data, thereby effectively improving the overall power generation of the floating photovoltaic array.

[0185] In a specific scenario example, the data processing method for a floating photovoltaic array provided in this specification can be applied to realize the prediction and adjustment of the optimal power of a floating photovoltaic array based on incident waves.

[0186] In this scenario, for fixed photovoltaic systems, the factors affecting maximum power are solar irradiance, temperature, and resistance. Solar irradiance is primarily affected by various external environmental factors, such as the angle of sunlight, cloud cover, and shadows. For floating offshore photovoltaic systems, in addition to the factors affecting fixed photovoltaic systems, the floating base supporting the photovoltaic modules will reciprocate under the action of waves, causing the inclination angle of the floating photovoltaic modules to change at any time. Currently, the photovoltaic industry has not yet clearly formulated a corresponding maximum power point tracking strategy for floating offshore photovoltaic systems, resulting in reduced output power of photovoltaic modules and affected power generation.

[0187] To address the above issues, this scenario example further considers a floating photovoltaic float motion prediction method based on incident wave data, which predicts the motion response law of the photovoltaic module base float through the parameters of the incident wave; and a floating photovoltaic maximum power prediction method, which obtains the motion response law of the floating photovoltaic base float through the incident wave and predicts the maximum power according to the predicted inclination angle. For specific implementation, please refer to Figure 10 As shown, the following contents may be included.

[0188] See Figure 2 and Figure 3 The floating photovoltaic array (also known as a floating photovoltaic array) consists of 20 photovoltaic modules arranged in a 5*4 pattern. The main wave direction is from north to south. The 1-5 module support float is located on the far left, and the floating wave sensor is located in the main wave direction.

[0189] Among them, the photovoltaic modules are placed on supporting floats, the floats are connected by connecting structures, and the array photovoltaics are connected to the seabed through four mooring chains.

[0190] The floating wave sensor is used to obtain wave parameters (eg, wave parameters of a reference position at the current time point) at the periphery of the array floating photovoltaic system at the time t0 (eg, the current time point).

[0191] According to the distance L1 from the floating wave sensor to the 1# photovoltaic support float and the wave speed c, the time it takes for the wave to pass from the floating wave sensor to the 1# photovoltaic support float is calculated. (e.g., wave propagation delay).

[0192] The wave parameters of the photovoltaic array field wave passing through the transmission distance L1 at the time t0+△t1 (for example, the target time point) to the 1# photovoltaic support float (for example, the target wave parameters of the photovoltaic module at the target time point) are calculated and predicted.

[0193] When making specific calculations and predictions, we can first calculate the attenuation coefficient of the wave in the array photovoltaic field area after it has passed through the periphery of the array photovoltaic field area for a period of time of △t1; then, considering the above attenuation coefficient, according to the principle of wave transmission and superposition, we can obtain the wave parameters at the target support float position of the array photovoltaic field area at the time t0+△t1.

[0194] Among them, the above-mentioned wave transmission and superposition principle can specifically include the following contents.

[0195] For N waves superimposed at the same point, the displacement of each wave can be expressed as:

[0196]

[0197] Among them, 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.

[0198] The total displacement y after the superposition of N waves is the sum of the displacements of all single waves:

[0199] .

[0200] If the frequency of each wave is the same, that is, ω1=ω2=...=ω N , we use trigonometric identities to convert the above sum into a single sine function, namely:

[0201] (1) Expand the sine function of each term into a complex exponential form: .

[0202] (2) Add up all the terms: .

[0203] (3) Convert the sum into complex form: .

[0204] , .

[0205] (4) Convert the complex form back to real form: . Where |Y| is the amplitude of the final wave, is the phase of the final wave.

[0206] By using the parameters of the supporting float and mooring system of the 5*4 array floating photovoltaic system, the motion response of each float in all directions under the full working conditions is obtained in advance through numerical calculation, such as Figure 11As shown in the figure, the partial images indicated by 1#, 2#, 3#, 4#, and 5# represent the motion responses of photovoltaic modules 1#, 2#, 3#, 4#, and 5#, respectively. The vertical axis (T) represents the wave period in seconds; the grayscale value represents the tilt angle in the motion response in rad.

[0207] Will The wave conditions at the target wind turbine position in the array photovoltaic field at the moment are compared in the information processing center with the pre-obtained wave conditions required for the array floating photovoltaic response data under all working conditions, and the motion state of the 1-5# component supporting float in the array photovoltaic field under the current working conditions is obtained.

[0208] The motion responses of the component-supported floating body in various directions include: motion responses in one or more directions of surge, sway, heave, roll, pitch, and bow.

[0209] According to the six-degree-of-freedom motion sensor, the motion state of the 1# component supporting float at time t0 and the inclination angle α0 at time t0 are obtained. The movement of the supporting float at the moment is obtained The inclination angle at time is .

[0210] according to The inclination angle changes during time, which can be advanced time, predict and adjust the maximum power, adjust the IV curve to achieve the maximum power.

[0211] Through the above scenario examples, it is verified that the data processing method for the floating photovoltaic array provided in this manual can indeed accurately and efficiently predict the tilt change data of the photovoltaic modules in advance, and make targeted adjustments to the photovoltaic modules in a timely manner according to the above tilt change data, thereby effectively improving the overall power generation of the floating photovoltaic array.

[0212] 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 of executing the steps among many, and does not represent the only execution order. When the device or client product is actually executed, it can be executed in sequence or in parallel according to the method shown in the embodiments or the drawings (for example, in a parallel processor or multi-threaded processing environment, or even a distributed data processing environment). The terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, product or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, product or device. Without further restrictions, it is not excluded that there are other identical or equivalent elements in the process, method, product or device including the elements. Words such as first, second, etc. are used to indicate names and do not indicate any particular order.

[0213] Those skilled in the art will also appreciate that, in addition to implementing the controller in pure computer-readable program code, it is entirely possible to implement the same functionality by logically programming the method steps in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, embedded microcontrollers, and the like. Therefore, such a controller can be considered a hardware component, and the devices included therein for implementing various functions can also be considered structures within the hardware component. Alternatively, the devices for implementing various functions can be considered both software modules implementing the method and structures within the hardware component.

[0214] This specification may be described in the general context of computer-executable instructions, such as program modules, executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, classes, and the like that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communications network. In a distributed computing environment, program modules may be located in local and remote computer-readable storage media, including storage devices.

[0215] As can be seen from the above description of the embodiments, those skilled in the art will clearly understand that this specification can be implemented using software plus a necessary general-purpose hardware platform. Based on this understanding, the technical solution of this specification can essentially be embodied in the form of a software product. This computer software product can be stored in a storage medium such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for enabling a computer device (such as a personal computer, mobile terminal, server, or network device) to execute the methods described in various embodiments or portions of the embodiments of this specification.

[0216] The various embodiments in this specification are described in a progressive manner. References to the common or similar parts of the various embodiments are sufficient. Each embodiment focuses on the differences from the other embodiments. This specification can be used in a variety of general-purpose or specialized computer system environments or configurations. For example, personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable electronic devices, network PCs, minicomputers, mainframe computers, and distributed computing environments that include any of the above systems or devices.

[0217] Although the present specification has been described through embodiments, those skilled in the art will appreciate that there are many modifications and variations to the present specification without departing from the spirit of the present specification. It is intended that the appended claims include these modifications and variations without departing from the spirit of the present specification.

Claims

1. A data processing method for a floating photovoltaic array, characterized in that: The method is applied to a floating photovoltaic array, wherein the floating photovoltaic array includes a plurality of photovoltaic modules, the photovoltaic modules are arranged on a supporting float, and the supporting float is provided with a motion sensor; a wave sensor is provided outside the floating photovoltaic array at least at a reference position along the opposite direction of the main wave and at a specified distance from the floating photovoltaic array, and an underwater mobile module is further provided at the bottom of the wave sensor. The method comprises: The motion sensor is used to collect the motion parameters of the photovoltaic module at the current time point; the wave sensor is used to collect the wave parameters of the reference position at the current time point; Based on the wave parameters at the reference position at the current time point, the wave transmission delay of the reference position relative to the photovoltaic module is determined; and a matching current wave parameter change prediction model is constructed; Determine the target time point based on the current time point and the wave transmission 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; Predicting 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; Adjust the floating photovoltaic array according to the inclination change data of the photovoltaic modules at the target time point; The method further includes: obtaining wave parameters of a reference position in the current time period at intervals of a preset time period; determining a wave transmission delay in the current time period based on the wave parameters of the reference position in the current time period; judging whether a specified distance is currently valid based on the wave transmission delay in the current time period and a preset reference adjustment time; the preset reference adjustment time is determined based on the overall computational data processing time and the overall adjustment effectiveness time; and, if it is determined that the specified distance is currently invalid, generating an adjustment instruction for the reference position to control the underwater mobile module to drive the wave sensor to and remain at the updated reference position.

2. The method according to claim 1, characterized in that Based on the wave parameters of the reference position at the current time point, the wave transmission delay of the reference position relative to the photovoltaic module is determined, including: Determine the wave speed of the wave at the current time point based on the wave parameters of the reference position at the current time point; Obtaining layout parameters of photovoltaic modules with respect to a floating photovoltaic array; The wave transmission delay of the reference position relative to the photovoltaic module is calculated based on the specified distance, the wave speed at the current time point, and the layout parameters of the photovoltaic module with respect to the floating photovoltaic array.

3. The method according to claim 1, characterized in that Construct a matching prediction model for current wave parameter changes, including: Acquiring 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 floating photovoltaic array relative to the reference position based on the wave parameters of the reference position at the current time point and the environmental parameters of the floating photovoltaic array; 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, a matching current wave parameter change prediction model is constructed.

4. The method according to claim 1, wherein 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, the tilt angle change data of the photovoltaic module at the target time point is predicted, including: Using a preset photovoltaic module motion prediction model 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, a corresponding target prediction result is obtained; According to the target prediction results, the motion state data of the photovoltaic components at the target time point is determined; According to the motion state data of the photovoltaic assembly at the target time point and the motion parameters of the photovoltaic assembly at the current time point, the tilt angle change data of the photovoltaic assembly at the target time point is determined.

5. The method according to claim 4, characterized in that After obtaining the corresponding target prediction result, the method further includes: determining a motion response type of the photovoltaic assembly at the target time point based on the motion state data of the photovoltaic assembly at the target time point; According to the motion response type, a matching target response type label is determined; combining the target wave parameters of the photovoltaic assembly at the target time point, the motion parameters of the photovoltaic assembly at the current time point, and the target response type label to obtain target combination data; The target combination data is processed using a preset photovoltaic assembly motion prediction model to determine motion state data of the photovoltaic assembly at a target time point.

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, and yaw.

7. The method according to claim 1, characterized in that The method further comprises: Get the temperature data at the current time point; Based on the temperature data at the current time point, predict the temperature change data at the target time point; The floating photovoltaic array is adjusted 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 A plurality of wave sensors are arranged outside the floating photovoltaic array at reference positions at specified distances from the floating photovoltaic array in multiple directions; Accordingly, the method further includes: Acquire wave parameters of multiple reference positions at current time points collected by multiple wave sensors; Determine the main wave direction at the current time point based on the wave parameters of multiple reference positions at the current time point; According to the main wave direction at the current time point, the effective wave parameters at the current time point are determined from the wave parameters of multiple reference positions 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 components at the target time point.

9. A data processing device for a floating photovoltaic array, characterized in that: The invention is applied to a floating photovoltaic array, wherein the floating photovoltaic array includes a plurality of photovoltaic modules, the photovoltaic modules are arranged on a supporting float, and the supporting float is provided with a motion sensor; a wave sensor is provided outside the floating photovoltaic array at least at a reference position along the opposite direction of the main wave and at a specified distance from the floating photovoltaic array, and an underwater mobile module is further provided at the bottom of the wave sensor. The device comprises: An acquisition module is used to acquire motion parameters of the photovoltaic module at the current time point using a motion sensor; and to acquire wave parameters of a reference position at the current time point using a wave sensor; A processing module is used to determine the wave transmission delay of the reference position relative to the photovoltaic module based on the wave parameters of the reference position at the current time point; and to construct a matching current wave parameter change prediction model; A determination module is used to determine a target time point based on the current time point and the wave transmission delay; and to determine the target wave parameters of the photovoltaic module at the target time point using the current wave parameter change prediction model; A prediction module is used to 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; An adjustment module, used to adjust the floating photovoltaic array according to the inclination change data of the photovoltaic components at the target time point; The device is also used to obtain wave parameters of a reference position in the current time period at intervals of a preset time period; determine the wave transmission delay of the current time period based on the wave parameters of the reference position in the current time period; determine whether the specified distance is currently valid based on the wave transmission delay in the current time period and a preset reference adjustment time; the preset reference adjustment time is determined based on the overall calculation data processing time and the overall adjustment effectiveness time; and when it is determined that the specified distance is currently invalid, generate an adjustment instruction for the reference position to control the underwater mobile module to drive the wave sensor to and stay at the updated reference position.

10. A computer device, characterized in that: The method comprises a processor and a memory for storing processor-executable instructions, wherein the processor implements the steps of the method according to any one of claims 1 to 8 when executing the instructions.

11. A computer program product, characterized in that The invention comprises a computer program, which implements the steps of the method according to any one of claims 1 to 8 when the computer program is executed by a processor.

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