Heat pump operation monitoring system based on digital twinborn cultivation

Abstract

The invention discloses a heat pump operation monitoring system based on digital twin cultivation. The system comprises a data acquisition module used for acquiring weather data of a preset monitoring scene, heat pump operation power, power supply power of solar power supply equipment, and operation characteristic data of each solar cell panel in the solar power supply equipment; the data processing module is used for acquiring a preset monitoring condition according to weather data of a preset monitoring scene, and acquiring twin feature vectors corresponding to the solar cell panels according to the operation feature data of the solar cell panels when the operation power of the heat pump and the power supply power of the solar power supply equipment meet the preset monitoring condition; and the twinborn iteration module is used for carrying out iteration on the twinborn body of each solar cell panel in the preset monitoring scene according to the twinborn feature vector corresponding to each solar cell panel for monitoring. The technical problem that the monitoring efficiency of the solar cell panel is low in the heat pump operation monitoring process in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment operation monitoring, and specifically to a digital twin-based operation monitoring system for aquaculture heat pumps. Background Art

[0002] Heat pump systems play an important role in the process of modern agricultural cultivation, especially having significant advantages in greenhouse cultivation, precise temperature control, energy conservation and environmental protection, and efficient utilization of resources. They can increase crop yields, help crops survive the winter, and improve crop quality, etc. In order to further save energy and improve resource utilization efficiency, solar energy can be used as the power supply for heat pump systems. However, the power generation power and power generation of solar power supply systems are greatly affected by the environment, and the solar panels need to be cleaned and maintained regularly to ensure stable power generation power.

[0003] In the prior art, through a combination of remote parameter monitoring and regular manual inspections, the solar panels are maintained in a timely manner to ensure the stable operation of the solar power supply system. However, this method has a large workload and relies on personal maintenance experience, which easily leads to the failure of some solar panels not being checked and detected in a timely manner.

[0004] It can be seen from this that the low monitoring efficiency of solar panels during the operation monitoring of heat pumps in the prior art is a technical problem that urgently needs to be solved at present. Summary of the Invention

[0005] The purpose of the present invention is to provide a digital twin-based operation monitoring system for aquaculture heat pumps, which solves the technical problem of low monitoring efficiency of solar panels during the operation monitoring of heat pumps in the prior art.

[0006] The present invention provides a digital twin-based operation monitoring system for aquaculture heat pumps, and the system includes:

[0007] A data acquisition module, which is used to acquire weather data, heat pump operation power, power supply power of solar power supply equipment, and operation characteristic data of each solar panel in the solar power supply equipment in a preset monitoring scenario;

[0008] A data processing module, which is used to obtain preset monitoring conditions according to the weather data in the preset monitoring scenario, and when the heat pump operation power and the power supply power of the solar power supply equipment meet the preset monitoring conditions, obtain the twin feature vectors corresponding to each solar panel according to the operation characteristic data of each solar panel;

[0009] A twin iteration module, which is used to iterate the twins of each solar panel in the preset monitoring scenario according to the twin feature vectors corresponding to each solar panel for monitoring.

[0010] Furthermore, the operation characteristic data includes environmental characteristic data and electrical characteristic data; the environmental characteristic data includes temperature data and irradiance data; the electrical characteristic data includes operating current data and operating voltage data; the data processing module obtains the twin feature vectors corresponding to each solar panel according to the operation characteristic data of each solar panel, including:

[0011] Based on the irradiance data in the environmental characteristic data of the solar panel, confirm the light intensity feature vector;

[0012] Based on the temperature data, irradiance data, operating current data and operating voltage data of the solar panel, confirm a number of operation feature vectors, and the number of operation feature vectors includes an efficiency feature vector, a temperature loss feature vector and a power loss feature vector;

[0013] Based on the light intensity feature vector, efficiency feature vector, temperature loss feature vector and power loss feature vector, obtain the twin feature vector of the solar panel.

[0014] Furthermore, the twin iteration module iterates the twins of each solar panel in the preset monitoring scenario according to the twin feature vectors corresponding to each solar panel, including:

[0015] Based on the twin feature vectors of each solar panel, confirm the twin iteration order of each solar panel;

[0016] According to the twin iteration order of each solar panel, iterate the twins of each solar panel in the preset monitoring scenario.

[0017] Furthermore, based on the twin feature vectors of each solar panel, confirm the twin iteration order of each solar panel, including:

[0018] Obtain the standard feature vector of the solar panel;

[0019] Based on the standard feature vector and the current twin feature vector of the solar panel, obtain the twin priority of the solar panel;

[0020] Based on the twin priorities of each solar panel, confirm the twin iteration order of each solar panel.

[0021] Furthermore, based on the standard feature vector and the current twin feature vector of the solar panel, obtain the twin priority of the solar panel, including:

[0022] Based on the standard feature vector and the current twin feature vector, obtain the feature vector difference; the feature vector difference includes a number of vector element differences;

[0023] Based on the vector element differences and the element weight parameters corresponding to each vector element, obtain the twin priority.

[0024] Furthermore, the operation characteristic data further includes the surface image of the solar panel; the data processing module obtains the corresponding twin feature vectors of each solar panel according to the operation characteristic data of each solar panel, and further includes:

[0025] Based on the surface image of the solar panel, obtain the attachment feature vector and perform normalization processing on the attachment feature vector.

[0026] Furthermore, based on the surface image of the solar panel, obtaining the attachment feature vector includes:

[0027] Perform image preprocessing on the surface image of the solar panel to obtain the preprocessed image;

[0028] Divide the preprocessed image into several sub-region images according to the preset division rule;

[0029] Compare the grayscale of each sub-region image with the standard panel image to obtain the grayscale difference value;

[0030] Based on the grayscale difference value, confirm the dust thickness corresponding to each sub-region;

[0031] Based on the dust thickness corresponding to each sub-region, obtain the attachment feature vector.

[0032] Furthermore, the environmental characteristic data further includes illuminance data and illumination angle data; based on the surface image of the solar panel, obtaining the attachment feature vector further includes: based on the illuminance data and illumination angle data in the environmental characteristic data of the solar panel, obtain the standard panel image corresponding to the solar panel.

[0033] Furthermore, the weather data of the preset monitoring scenario includes the scenario temperature, scenario irradiance, and geographical location; the data processing module obtains the preset monitoring conditions according to the weather data of the preset monitoring scenario, including:

[0034] According to the set period, based on the scenario temperature and scenario irradiance of the preset monitoring scenario within the power supply time sliding window, obtain the monitoring condition parameters; the monitoring condition parameters include the preset insufficient duration, preset insufficient times, and preset power supply ratio;

[0035] When the insufficient power supply duration within the power supply time sliding window is greater than the preset insufficient duration, and / or the insufficient power supply times is greater than the preset insufficient times, and / or the power supply ratio is lower than the preset power supply ratio, it is determined that the operation power of the heat pump and the power supply power of the solar power supply device meet the preset monitoring conditions.

[0036] Furthermore, the weather data of the preset monitoring scenario further includes geographical location data; the data processing module obtains the preset monitoring conditions according to the weather data of the preset monitoring scenario, and further includes:

[0037] Obtain the start time and end time of the current power supply cycle according to the geographical location data of the preset monitoring scenario;

[0038] Respectively use the start time and end time of the current power supply cycle as the start window point and end window point of the power supply time sliding window;

[0039] The data processing module starts to obtain the preset monitoring conditions at the first power supply time sliding window after the start time of the current power supply cycle until the end time of the current power supply cycle.

[0040] Compared with the prior art, the beneficial effects of the present invention are:

[0041] In the present invention, a data acquisition module is set to collect the weather data of the preset monitoring scenario, the operating power of the heat pump, the power supply power of the solar power supply device, and the operating characteristic data of each solar panel in the solar power supply device. It is convenient for the data processing module to obtain the corresponding preset monitoring conditions according to the weather data in a timely manner to judge whether the power supply power of the solar power supply device is coordinated with the current operating power of the heat pump. When the operating power of the heat pump and the power supply power of the solar power supply device meet the preset monitoring conditions, the data module obtains the twin feature vectors according to the operating characteristic data of the solar panels, so as to facilitate the twin iteration module to iterate the twins of each solar panel in the preset monitoring scenario. It can intuitively display the status of each current solar panel. It is convenient for maintenance and management personnel to carry out operation monitoring work according to the twins of the solar panels, improving the monitoring efficiency. It solves the technical problem of low monitoring efficiency of solar panels in the prior art during the operation monitoring of heat pumps. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic block diagram of a digital twin-based heat pump operation monitoring system for aquaculture according to the present invention.

[0043] Figure 2 It is a solar-heat pump temperature control system. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Apparently, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0045] As shown Figure 1 in the figure, a digital twin-based operation monitoring system for a heat pump for cultivation includes:

[0046] A data acquisition module, which is used to acquire weather data, heat pump operation power, power supply power of a solar power supply device, and operation characteristic data of each solar panel in the solar power supply device in a preset monitoring scenario;

[0047] A data processing module, which is used to obtain preset monitoring conditions according to the weather data in the preset monitoring scenario, and when the heat pump operation power and the power supply power of the solar power supply device meet the preset monitoring conditions, obtain the twin feature vectors corresponding to each solar panel according to the operation characteristic data of each solar panel;

[0048] A twin iteration module, which is used to iterate the twins of each solar panel in the preset monitoring scenario according to the twin feature vectors corresponding to each solar panel for monitoring.

[0049] The specific implementation process of this embodiment includes:

[0050] In this embodiment, a data acquisition module is set to acquire weather data, heat pump operation power, power supply power of a solar power supply device, and operation characteristic data of each solar panel in the solar power supply device in a preset monitoring scenario. It is convenient for the data processing module to obtain the corresponding preset monitoring conditions according to the weather data in time to judge whether the power supply power of the solar power supply device is coordinated with the current heat pump operation power. When the heat pump operation power and the power supply power of the solar power supply device meet the preset monitoring conditions, the data module obtains the twin feature vectors according to the operation characteristic data of the solar panel, so that the twin iteration module can iterate the twins of each solar panel in the preset monitoring scenario. It can intuitively display the current state of each solar panel. It is convenient for maintenance and management personnel to carry out operation monitoring work according to the twins of the solar panel, improving the monitoring efficiency. It solves the technical problem of low monitoring efficiency of solar panels in the process of heat pump operation monitoring in the prior art.

[0051] It should be noted that in this embodiment, the preset monitoring scenario includes the installation environment scenario of the solar panel constructed by digital twin technology.

[0052] As Figure 2As shown, it is a solar - heat pump temperature control system involved in this embodiment; a power supply device composed of multiple solar panels supplies power to an air - energy unit, so that a heat pump device composed of multiple air - energy units generates hot water, and then transfers the heat to a heat dissipation terminal at various planting greenhouses to adjust the temperature of the planting greenhouses. In this embodiment, the power supply device and the heat pump device are connected through a direct - drive frequency - conversion controller; the solar power supply device directly supplies power to the heat pump device through the direct - drive frequency - conversion controller. In this embodiment, when the solar power supply device generates insufficient electricity, the heat pump device needs to be connected to the power grid to ensure the normal and stable operation of the heat pump device. If the solar power supply device causes insufficient power supply due to abnormal events (such as failure not detected in time, surface dust not cleaned in time) and is frequently connected to the power grid, it will lead to an increase in the overall cost of plant cultivation. Therefore, the power supply stability of the solar power supply device is very important for the solar - heat pump temperature control system.

[0053] According to an embodiment of the present invention, the operation characteristic data includes environmental characteristic data and electrical characteristic data; the environmental characteristic data includes temperature data and irradiance data; the electrical characteristic data includes operating current data and operating voltage data; the data processing module obtains the corresponding twin feature vectors of each solar panel according to the operation characteristic data of each solar panel, including:

[0054] Based on the irradiance data in the environmental characteristic data of the solar panel, confirm the light - intensity feature vector;

[0055] Based on the temperature data, irradiance data, operating current data and operating voltage data of the solar panel, confirm several operation feature vectors, and the several operation feature vectors include an efficiency feature vector, a temperature - loss feature vector and a power - loss feature vector;

[0056] Based on the light - intensity feature vector, efficiency feature vector, temperature - loss feature vector and power - loss feature vector, obtain the twin feature vector of the solar panel.

[0057] The specific implementation process of this embodiment includes:

[0058] Based on the irradiance data, after normalization processing, obtain the light - intensity feature vector;

[0059] According to the operating current data and operating voltage data, obtain the operating power data.

[0060] The calculation formula of the efficiency feature vector in this embodiment includes:

[0061]

[0062] Among them, η is the power generation efficiency; P maxP is the peak power; E is the irradiance at the peak power, with the unit of watt per square meter; S is the area of the solar panel.

[0063] After normalizing the power generation efficiency, the efficiency feature vector is obtained.

[0064] In this embodiment, the calculation formula of the temperature loss feature vector includes:

[0065]

[0066] Among them, WS is the temperature loss; T max is the temperature peak; E is the irradiance at the temperature peak; P(T max , E) is the actual power generation at the temperature peak under the corresponding irradiance; T 标 is the standard temperature; P(T 标 , E) is the power generation at the standard temperature under the same irradiance.

[0067] After normalizing the temperature loss, the temperature loss feature vector is obtained.

[0068] In this embodiment, the calculation formula of the power loss feature vector includes:

[0069]

[0070] Among them, GS is the power loss; P min (Ti, Ei) is the minimum power generation at the temperature of Ti and the irradiance of Ei; P max (Ti, Ei) is the maximum power generation at the temperature of Ti and the irradiance of Ei.

[0071] After normalizing the power loss, the power loss feature vector is obtained.

[0072] Taking the light intensity feature vector, the efficiency feature vector, the temperature loss feature vector, and the power loss feature vector as vector elements, the twin feature vector is obtained.

[0073] According to another embodiment of the present invention, the twin iteration module iterates the twins of each solar panel in the preset monitoring scenario according to the twin feature vector corresponding to each solar panel, including:

[0074] Based on the twin feature vectors of each solar panel, confirm the twin iteration order of each solar panel;

[0075] According to the twin iteration order of each solar panel, iterate the twins of each solar panel in the preset monitoring scenario.

[0076] The specific implementation process of this embodiment includes:

[0077] In this embodiment, there are multiple solar panels. When the twin iteration module in the preset monitoring scenario is limited by the iteration ability and cannot perform simultaneous iteration on the twins of multiple solar panels, the twin iteration order of each solar panel is confirmed based on the twin feature vectors of each solar panel. Iterate on the twins of each solar panel according to the twin iteration order, reasonably utilize the iteration ability of the twin iteration module, and at the same time, maintenance personnel can also view the twins of the solar panels preferentially iterated by the twin iteration module, improving the fault troubleshooting efficiency of the panels.

[0078] In this embodiment, confirming the twin iteration order of each solar panel based on the twin feature vectors of each solar panel includes:

[0079] S11: Obtain the standard feature vector of the solar panel;

[0080] In this embodiment, each type of solar panel is provided with a corresponding standard feature vector, and the twin corresponding to the standard feature vector in the preset monitoring scenario is the standard twin.

[0081] S12: Based on the standard feature vector and the current twin feature vector of the solar panel, obtain the twin priority of the solar panel, including:

[0082] Based on the standard feature vector and the current twin feature vector, obtain the feature vector difference; the feature vector difference includes several vector element differences; based on the vector element differences and the element weight parameters corresponding to each vector element, obtain the twin priority, and the calculation formula is as follows:

[0083] YX = ∑α j *(x j - xb j ) 2 ;

[0084] Where YX is the twin priority, (x j - xb j ) is the j-th element vector difference in the feature vector difference; α j is the weight parameter of the j-th feature vector element difference.

[0085] In this embodiment, the greater the twin priority, the more forward the twin iteration order.

[0086] S13: Based on the twin priorities of each solar panel, confirm the twin iteration order of each solar panel.

[0087] In this embodiment, the solar panels are sorted in descending order of twin priority to obtain a sorting result; the sorting result is divided according to a preset ratio to obtain the twin iteration order of each solar panel. The preset ratio includes: 1:2:3:4.

[0088] It should be noted that in this embodiment, when the twin iteration module iterates the twins according to the twin feature vector, the update is performed according to the preset expression mode of each element in the twin feature vector in the preset monitoring scenario. For example, the preset expression mode of light intensity includes the high or low brightness on the surface of the twin; the expression modes of efficiency, temperature loss, and power loss include different colors at the edges of the twin.

[0089] According to another embodiment of the present invention, the operating characteristic data further includes the surface image of the solar panel; the data processing module obtains the twin feature vector corresponding to each solar panel according to the operating characteristic data of each solar panel, and further includes:

[0090] Based on the surface image of the solar panel, an attachment feature vector is obtained, and the attachment feature vector is normalized.

[0091] The specific implementation process of this embodiment includes:

[0092] Among them, obtaining the attachment feature vector based on the surface image of the solar panel includes:

[0093] S21: Perform image preprocessing on the surface image of the solar panel to obtain a preprocessed image;

[0094] In this embodiment, the image preprocessing includes Gaussian filtering and illumination correction. Gaussian filtering is used for denoising, and illumination correction is used to eliminate shadow and reflection interference. In this embodiment, the surface image of the solar panel is obtained by a camera distributed on site or collected by a drone.

[0095] S22: Divide the preprocessed image into several sub-region images according to a preset division rule;

[0096] In this embodiment, the preset division rule includes dividing according to the distribution of photovoltaic units on the solar panel. Each sub-region image includes at least one photovoltaic unit.

[0097] S23: Compare the gray levels of each sub-region image with the standard panel image to obtain a gray level difference value;

[0098] In this embodiment, the environmental characteristic data further includes illuminance data and illumination angle data; obtaining the standard panel image includes: obtaining the standard panel image corresponding to the solar panel based on the illuminance data and illumination angle data in the environmental characteristic data of the solar panel.

[0099] In this embodiment, the standard solar panel image is obtained from laboratory data.

[0100] S24: Based on the gray - scale difference value, confirm the dust thickness corresponding to each sub - region;

[0101] In this embodiment, the mapping relationship between the gray - scale difference value and the dust thickness is obtained in advance according to laboratory data;

[0102] Then, according to the gray - scale difference value of each sub - region image, obtain the dust thickness of each sub - region on the solar panel.

[0103] S25: Based on the dust thickness corresponding to each sub - region, obtain the attachment feature vector.

[0104] In this embodiment, the representation method of the attachment feature vector includes: [D1, D2,..., D k ; where D k is the dust thickness of the k - th sub - region after normalization processing.

[0105] In this embodiment, when the twin iterative module iterates the twins, according to the attachment feature vector, adjust the gray - scale of the corresponding sub - regions on the twins of the solar panel. In this embodiment, when the twin iterative module adjusts the gray - scale of each sub - region on the twins of the solar panel, it also marks the dust thickness of each sub - region.

[0106] According to another embodiment of the present invention, the preset weather data of the monitoring scenario includes the scenario temperature, the scenario irradiance, and the geographical location; the data processing module obtains the preset monitoring conditions according to the preset weather data of the monitoring scenario, including:

[0107] S31: According to the set period, slide the window of the power supply time based on the scenario temperature and the scenario irradiance of the preset monitoring scenario, and obtain the monitoring condition parameters; the monitoring condition parameters include the preset insufficient duration, the preset insufficient times, and the preset power supply ratio;

[0108] In this embodiment, the data acquisition module collects the weather data of the preset monitoring scenario, the heat pump operating power, the power supply power of the solar power supply device, and the operating characteristic data of each solar panel in the solar power supply device every set period; the power supply time sliding window includes multiple set periods. The data processing module obtains the monitoring condition parameters for the scenario temperature and the scenario irradiance of the preset monitoring scenario collected in multiple set periods within the power supply time sliding window every set period.

[0109] In this embodiment, the mapping relationship between the scenario temperature, the scenario irradiance and the monitoring condition parameters is set in advance; according to the mapping relationship between the scenario temperature, the scenario irradiance and the monitoring condition parameters, obtain the monitoring condition parameters of the current preset monitoring scenario.

[0110] S32: When the insufficient power supply duration within the power supply time sliding window is greater than the preset insufficient duration, and / or the number of insufficient power supply times is greater than the preset number of times, and / or the power supply ratio is lower than the preset power supply ratio, it is determined that the operating power of the heat pump and the power supply power of the solar power supply device meet the preset monitoring conditions.

[0111] In this embodiment, the insufficient power supply duration includes the duration when the power of the solar power supply device is less than the operating power of the heat pump within the power supply time sliding window; the number of insufficient power supply times includes the number of times when the power supply power drops from not less than the operating power of the heat pump to less than the operating power of the heat pump within the power supply time sliding window; the power supply ratio includes the ratio of the power supply amount of the solar power supply device to the power consumption of the heat pump operation within the power supply time sliding window.

[0112] The specific implementation process of this embodiment includes:

[0113] The weather data of the preset monitoring scenario further includes geographical location data; the data processing module obtaining the preset monitoring conditions according to the weather data of the preset monitoring scenario further includes:

[0114] Obtaining the start time and end time of the current power supply cycle according to the geographical location data of the preset monitoring scenario;

[0115] In this embodiment, the power supply cycle includes: days. According to the geographical location data, the sunrise time of the current day is obtained as the start time of the power supply cycle by connecting to the meteorological platform, and the sunset time of the current day is obtained as the end time of the power supply cycle.

[0116] Taking the start time and end time of the current power supply cycle as the sliding window start point and sliding window end point of the power supply time sliding window respectively;

[0117] The data processing module starts to obtain the preset monitoring conditions at the start of the first power supply time sliding window after the start time of the current power supply cycle until the end time of the current power supply cycle.

[0118] It should be noted that in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the said element.

[0119] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A digital twin-based operation monitoring system for aquaculture heat pumps, characterized in that: The system includes: A data acquisition module, which is used to acquire weather data of a preset monitoring scenario, the operating power of a heat pump, the power supply of a solar power supply device, and the operating characteristic data of each solar panel in the solar power supply device; A data processing module, which is used to obtain preset monitoring conditions according to the weather data of the preset monitoring scenario, and when the operating power of the heat pump and the power supply of the solar power supply device meet the preset monitoring conditions, obtain the twin feature vectors corresponding to each solar panel according to the operating characteristic data of each solar panel; A twin iteration module, which is used to iterate the twins of each solar panel in the preset monitoring scenario according to the twin feature vectors corresponding to each solar panel for monitoring.

2. The operation monitoring system of a digital twin-based aquaculture heat pump according to claim 1, characterized in that: The operating characteristic data includes environmental characteristic data and electrical characteristic data; the environmental characteristic data includes temperature data and irradiance data; the electrical characteristic data includes operating current data and operating voltage data; the data processing module obtains the twin feature vectors corresponding to each solar panel according to the operating characteristic data of each solar panel, including: Based on the irradiance data in the environmental characteristic data of the solar panel, confirm the light intensity feature vector; Based on the temperature data, irradiance data, operating current data and operating voltage data of the solar panel, confirm a number of operating feature vectors, and the number of operating feature vectors includes an efficiency feature vector, a temperature loss feature vector and a power loss feature vector; Based on the light intensity feature vector, efficiency feature vector, temperature loss feature vector and power loss feature vector, obtain the twin feature vector of the solar panel.

3. The operation monitoring system of a digital twin-based aquaculture heat pump according to claim 2, wherein: The twin iteration module iterates the twins of each solar panel in the preset monitoring scenario according to the twin feature vectors corresponding to each solar panel, including: Based on the twin feature vectors of each solar panel, confirm the twin iteration order of each solar panel; According to the twin iteration order of each solar panel, iterate the twins of each solar panel in the preset monitoring scenario.

4. The operation monitoring system of a digital twin-based aquaculture heat pump according to claim 3, wherein: Based on the twin feature vectors of each solar panel, confirming the twin iteration order of each solar panel includes: Obtain the standard feature vector of the solar panel; Based on the standard feature vector and the current twin feature vector of the solar panel, obtain the twin priority of the solar panel; Based on the twin priorities of each solar panel, confirm the twin iteration order of each solar panel.

5. The operation monitoring system of a digital twin-based aquaculture heat pump according to claim 4, wherein: Based on the standard feature vector and the current twin feature vector of the solar panel, obtaining the twin priority of the solar panel includes: Based on the standard feature vector and the current twin feature vector, obtain the feature vector difference; the feature vector difference includes a number of vector element differences; Based on the vector element differences and the element weight parameters corresponding to each vector element, obtain the twin priority.

6. The operation monitoring system of a digital twin-based aquaculture heat pump according to claim 2, characterized in that: The operating characteristic data also includes the surface image of the solar panel; the data processing module obtains the twin feature vectors corresponding to each solar panel according to the operating characteristic data of each solar panel, and also includes: Based on the surface image of the solar panel, obtain the attachment feature vector and perform normalization processing on the attachment feature vector.

7. The operation monitoring system of a digital twin-based aquaculture heat pump according to claim 6, characterized in that: Based on the surface image of the solar panel, obtain the attachment feature vector, including: Perform image preprocessing on the surface image of the solar panel to obtain a preprocessed image; Divide the preprocessed image into several sub-region images according to a preset division rule; Compare the grayscale of each sub-region image with the standard solar panel image to obtain the grayscale difference value; Based on the grayscale difference value, confirm the dust thickness corresponding to each sub-region; Based on the dust thickness corresponding to each sub-region, obtain the attachment feature vector.

8. The operation monitoring system of a digital twin-based aquaculture heat pump according to claim 7, characterized in that: The environmental feature data also includes illuminance data and illumination angle data; based on the surface image of the solar panel, obtaining the attachment feature vector also includes: Based on the illuminance data and illumination angle data in the environmental feature data of the solar panel, obtain the standard solar panel image corresponding to the solar panel.

9. The operation monitoring system of a digital twin-based aquaculture heat pump according to claim 1, characterized in that: The weather data of the preset monitoring scenario includes the scenario temperature, scenario irradiance, and geographical location; The data processing module obtains the preset monitoring conditions according to the weather data of the preset monitoring scenario, including: According to the set period, based on the scenario temperature and scenario irradiance of the preset monitoring scenario within the power supply time sliding window, obtain the monitoring condition parameters; the monitoring condition parameters include the preset insufficient duration, preset insufficient times, and preset power supply ratio; When the insufficient power supply duration within the power supply time sliding window is greater than the preset insufficient duration, and / or the insufficient power supply times is greater than the preset insufficient times, and / or the power supply ratio is lower than the preset power supply ratio, it is determined that the operating power of the heat pump and the power supply power of the solar power supply device meet the preset monitoring conditions.

10. The operation monitoring system of a digital twin-based aquaculture heat pump according to claim 9, wherein: The weather data of the preset monitoring scenario also includes geographical location data; The data processing module obtaining the preset monitoring conditions according to the weather data of the preset monitoring scenario also includes: According to the geographical location data of the preset monitoring scenario, obtain the start time and end time of the current power supply cycle; Respectively use the start time and end time of the current power supply cycle as the sliding window start point and sliding window end point of the power supply time sliding window; The data processing module starts to obtain the preset monitoring conditions from the first power supply time sliding window after the start time of the current power supply cycle until the end time of the current power supply cycle.

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