Maintenance method and system of solar power generation street lamp

Abstract

The invention discloses a maintenance method and system of a solar power generation street lamp, and relates to the maintenance method and system of the solar power generation street lamp. The method comprises the following steps: acquiring detection data of each solar power generation street lamp in a target area within a preset duration and environmental data of the target area; judging whether the solar power generation street lamps in the target area are in a shielding state or not based on the detection data and the environmental data, wherein the shielding state is used for representing the shielding degree of the solar power generation street lamps by trees in the target area; and if it is determined that the solar power generation street lamp in the target area is in the shielding state, generating a maintenance suggestion corresponding to the shielding state. By implementing the technical scheme provided by the invention, the maintenance suggestion corresponding to the shielding state can be automatically generated, so that the maintenance personnel can reasonably plan the maintenance work, the maintenance efficiency is improved, and the waste of maintenance resources is avoided.

Description

Technical Field

[0001] The present application relates to a maintenance method and system for solar-powered street lights, and in particular to a maintenance method and system for solar-powered street lights. Background Art

[0002] As a clean and environmentally friendly lighting device, solar-powered street lights are widely used in scenes such as highways and municipal roads. This type of street light converts solar energy into electricity through photovoltaic panels and stores it in batteries for nighttime lighting. However, in actual applications, since there are often green belts or shelterbelts on both sides of the road, the growth of trees may block the photovoltaic panels, resulting in a decrease in power generation efficiency and affecting the normal operation of street lights.

[0003] At present, the maintenance of solar-powered street lights mainly relies on manual inspections. Maintenance personnel regularly inspect street lights and determine whether there is a problem of tree shading by observing the environment around the photovoltaic panels or measuring the power generation. After discovering the problem, relevant personnel are arranged to carry out maintenance work such as tree pruning.

[0004] However, this manual inspection method has great limitations. Since solar-powered street lights are usually widely distributed and numerous, it is difficult to detect shading problems in time by relying solely on manual inspections. At the same time, relying solely on manual observation or simple power measurement cannot accurately determine the degree of shading, which can easily lead to problems such as untimely maintenance or waste of maintenance resources. Summary of the invention

[0005] The present application provides a maintenance method and system for solar-powered street lights, which can automatically generate maintenance suggestions corresponding to the shading status, help maintenance personnel to rationally plan maintenance work, improve maintenance efficiency, and avoid waste of maintenance resources.

[0006] In a first aspect of the present application, the present application provides a maintenance method for a solar-powered street lamp, comprising: Acquire detection data of each solar-powered street lamp in a target area within a preset time period, as well as environmental data of the target area; Based on the detection data and the environmental data, determining whether the solar-powered street lamps in the target area are in a shielding state, wherein the shielding state is used to characterize the degree to which the solar-powered street lamps in the target area are shielded by trees; If it is determined that the solar-powered street lamps in the target area are in a shielded state, a maintenance suggestion corresponding to the shielded state is generated.

[0007] Optionally, the detection data includes actual power generation of the photovoltaic panels in each of the solar-powered street lamps and the geographical location of each of the solar-powered street lamps; the environmental data includes light intensity; and judging whether the solar-powered street lamps in the target area are in a shielded state based on the detection data and the environmental data includes: Calculating the expected power generation of each solar-powered street lamp based on the geographical location and light intensity of each solar-powered street lamp; Based on the difference between the expected power generation and the actual power generation of each of the solar-powered street lamps, determining whether the solar-powered street lamps in the target area are in a shielded state; If the difference between the expected power generation and the actual power generation of each of the solar-powered street lamps is greater than a preset threshold, it is determined that the solar-powered street lamps in the target area are in a shielded state; If the difference between the expected power generation and the actual power generation of each of the solar power generation street lamps is less than or equal to a preset threshold, it is determined that the solar power generation street lamps in the target area are in a non-shielded state.

[0008] Optionally, the environmental data further includes wind speed, and after determining that the solar-powered street lamps in the target area are in a shielded state, the method further includes: Calculating the power fluctuation of the solar-powered street lamps in the target area within the preset time period based on the expected power generation and the actual power generation of each of the solar-powered street lamps; Based on the wind speed, calculating the wind speed fluctuation of the target area within the preset time period; calculating a correlation coefficient between the power fluctuation and the wind speed fluctuation; The occlusion state is determined to be a dynamic occlusion state or a fixed occlusion state according to the correlation coefficient.

[0009] Optionally, the generating a maintenance suggestion corresponding to the obstruction state includes: generating a heat map based on the geographic locations of the solar-powered street lamps in the blocked state; Maintenance recommendations are generated based on the heat map.

[0010] Optionally, generating a heat map based on the geographical location of the solar-powered street lamp in the shielded state includes: Obtaining the degree of shading of the solar-powered street lamp in the shading state; Based on the shading degree and geographical location of each of the solar-powered street lamps in the shading state, the target area is divided into a plurality of cluster areas with different shading degrees; A heat map is generated based on each of the clustered regions.

[0011] Optionally, generating a maintenance suggestion based on the thermal map includes: If the occlusion state is a fixed occlusion state, generating a tree pruning suggestion based on the heat map; If the shading state is a non-fixed shading state, a power scheduling suggestion is generated based on the thermal map.

[0012] In a second aspect of the present application, a maintenance system for a solar-powered street lamp is provided, comprising: A data acquisition module, used to acquire detection data of each solar-powered street lamp in a target area within a preset time period, as well as environmental data of the target area; an occlusion judgment module, used to judge whether the solar-powered street lamps in the target area are in an occlusion state based on the detection data and the environmental data, wherein the occlusion state is used to characterize the degree to which the solar-powered street lamps in the target area are occluded by trees; The suggestion generating module is used for generating a maintenance suggestion corresponding to the blocking state if it is determined that the solar-powered street lamps in the target area are in the blocking state.

[0013] In a third aspect of the present application, a computer storage medium is provided, wherein the computer storage medium stores a plurality of instructions, wherein the instructions are suitable for being loaded by a processor and executing the above method steps.

[0014] In a fourth aspect of the present application, an electronic device is provided, comprising: a processor and a memory; wherein the memory stores a computer program, and the computer program is suitable for being loaded by the processor and executing the above-mentioned method steps.

[0015] In a fifth aspect of the present application, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the method steps described above are implemented.

[0016] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: By acquiring the detection data and environmental data of each solar-powered street light in the target area, and judging the shading status of the solar-powered street lights based on these data, the automatic identification of shading problems can be realized without relying on manual inspections, thus overcoming the defect that it is difficult to detect shading problems in a timely manner under traditional manual inspection methods. At the same time, because the judgment process comprehensively considers the detection data and environmental data, it can accurately assess the degree of shading and avoid the judgment bias caused by relying solely on manual observation or simple power measurement. In addition, the system can automatically generate maintenance suggestions corresponding to the shading status, which helps maintenance personnel to rationally plan maintenance work, improve maintenance efficiency, and avoid waste of maintenance resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flow chart of a maintenance method of a solar-powered street light provided in an embodiment of the present application; Figure 2 It is a structural schematic diagram of a maintenance system for solar-powered street lights provided in an embodiment of the present application; Figure 3 It is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present application. DETAILED DESCRIPTION

[0018] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0019] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0020] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0021] Please refer to Figure 1 , Figure 1 This is a flow chart of a maintenance method for solar-powered street lights provided in an embodiment of the present application. The method can be implemented by a computer program, can be implemented by a single-chip microcomputer, or can be run on a maintenance system for solar-powered street lights based on the von Neumann system. The computer program can be integrated into an application or run as an independent tool application. Specifically, the maintenance method for solar-powered street lights can also include the following steps: Step 101: Acquire detection data of each solar-powered street lamp in a target area within a preset time period, as well as environmental data of the target area.

[0022] The target area refers to a specific geographical area where the shading status of solar-powered street lamps needs to be monitored and maintained. In the embodiment of the present application, it can be understood as a continuous area along the highway where multiple solar-powered street lamps are installed, and the area has clear geographical boundaries and unified management requirements. For example, the target area can be a section of a highway with a length of 10 kilometers, or an area around a transportation hub, where several solar-powered street lamps are installed as road lighting facilities.

[0023] By dividing the target area, it is easy to determine the number and distribution range of solar-powered street lights that need to be monitored, and achieve accurate coverage of data collection; secondly, it helps to reasonably arrange the locations of environmental monitoring stations to ensure the representativeness of environmental data; finally, the operating status of adjacent solar-powered street lights can be correlated and analyzed to identify regional shading problems.

[0024] The preset duration refers to the continuous time interval for data collection and shading status analysis of solar-powered street lights. In the embodiment of the present application, it can be understood as 24 hours, that is, a complete sunshine cycle. The power generation of solar-powered street lights shows obvious periodic characteristics as the solar altitude angle changes. By collecting data from a complete sunshine cycle, the power generation status of photovoltaic panels at different time periods can be fully reflected, and the influence of shading on power generation efficiency can be accurately identified.

[0025] Two types of data need to be collected within a preset time period: detection data and environmental data. Detection data refers to the operating parameters obtained directly from the solar power generation street light equipment body, which can be understood as the actual power generation data and geographic location data of each solar power generation street light in the embodiment of the present application. Among them, the actual power generation data is collected in real time by the current sensor and voltage sensor installed at the output end of the photovoltaic panel, and is calculated based on the product of the current value and the voltage value; the geographic location data is obtained through the built-in GPS positioning module, including longitude, latitude and altitude information. These detection data are used to reflect the real-time working status of the solar power generation street light.

[0026] Environmental data refers to external environmental parameters that affect the power generation efficiency of solar-powered street lights. In the embodiment of the present application, it can be understood as light intensity data and wind speed data in the target area. Among them, the light intensity data is collected by the light sensor arranged in the environmental monitoring station and is used to calculate the theoretical power generation power of the solar-powered street lights; the wind speed data is collected by the wind speed sensor and is used to analyze whether the power fluctuation is caused by dynamic shading caused by the swinging of tree branches.

[0027] Specifically, within each preset time period, the system continuously collects the above detection data and environmental data according to a sampling period of 1 minute, thereby forming time series data of 1440 sampling points. This sampling strategy can not only ensure the continuity of the data, but also capture power fluctuations in a short period of time. For example, in the early morning and evening when the solar altitude angle is small, the impact of tree shading on power generation efficiency is most significant; at noon, due to the large solar altitude angle, the shading effect is relatively small. This time-varying characteristic can be identified by analyzing the data of the complete sunshine cycle.

[0028] Through the above data collection, we can ensure the accuracy of the shading status judgment, and timely discover and deal with the shading problem, thereby improving the overall operating efficiency of the solar power generation street light system. At the same time, this analysis method based on the complete sunshine cycle also provides reliable data support for the formulation of long-term maintenance strategies.

[0029] Step 102: Determine whether the solar-powered street lamps in the target area are in a shielded state based on the detection data and the environmental data. The shielded state is used to characterize the degree to which the solar-powered street lamps in the target area are shielded by trees.

[0030] The blocking state refers to the working state of the photovoltaic panel of the solar power street light being blocked by external objects such as trees at a specific moment, which directly affects the power generation efficiency of the photovoltaic panel. In the embodiment of the present application, it can be understood as two types: fixed blocking state and dynamic blocking state. The fixed blocking state refers to the photovoltaic panel being continuously blocked by stationary objects such as leaves, which is manifested as the power generation being lower than the expected value for a long time; the dynamic blocking state refers to the photovoltaic panel being periodically blocked by objects such as branches swaying in the wind, which is manifested as the power generation fluctuating with the wind speed.

[0031] In actual applications, the power generation efficiency of solar-powered street lights will be affected by a variety of environmental factors, among which tree shading is one of the most important influencing factors. Specifically, the system determines whether the solar-powered street lights are in a shading state by analyzing the collected detection data such as the actual power generation power of the photovoltaic panels, the geographical location, and the environmental data such as the light intensity. The shading state is a quantitative indicator that can accurately characterize the severity of the solar-powered street lights being shaded by trees.

[0032] Through the above judgment method, not only can the abnormal operation of solar power generation street lights be identified in time and the urgency of maintenance be determined, but also a reliable basis can be provided for formulating targeted maintenance plans, thereby improving maintenance efficiency and ensuring the normal operation of the solar power generation street light system.

[0033] Based on the above embodiment, as an optional embodiment, the detection data includes the actual power generation of the photovoltaic panels in each solar-powered street lamp, and the geographical location of each solar-powered street lamp; the environmental data includes the light intensity; step 102 may further include the following steps: Step 201: Calculate the expected power generation of each solar-powered street lamp based on its geographical location and light intensity.

[0034] The expected power generation refers to the theoretical power value that the photovoltaic panel of the solar power street light should output under specific lighting conditions under ideal working conditions. In the embodiments of the present application, it can be understood as the power generation value calculated based on parameters such as ambient light intensity, photoelectric conversion efficiency, photovoltaic panel area and solar incident angle.

[0035] Specifically, before calculating the expected power generation, the collected raw data must be preprocessed. Data may be missing during data collection due to equipment failure, communication interruption, etc. The system uses cubic spline interpolation to complete the missing data. For data missing of a short duration, interpolation calculations are performed using data from adjacent time points; for data missing of a longer duration, the mean of historical data in the same period is used to fill the gap. This hierarchical filling strategy ensures the continuity of the data while maintaining the authenticity of the data to the greatest extent possible.

[0036] On the basis of data completion, due to the differences in measurement accuracy and range of different types of sensors, directly using the original data may introduce systematic errors. Therefore, the system normalizes data such as light intensity and power generation, and maps all data to the [0,1] interval.

[0037] In order to eliminate the influence of sensor measurement noise on the calculation results, the system uses sliding average filtering to reduce the noise of the normalized data. For example, for a data sequence with a sampling period of 1 minute, a 5-minute time window is selected for sliding average, that is, the value of each data point is replaced by the arithmetic mean of the 5 sampling points before and after it for 2 minutes. This processing method can effectively suppress the interference caused by short-term fluctuations without over-smoothing the real power changes.

[0038] After completing the data preprocessing, the system calculates the expected power generation based on the cleaned data. The expected power generation is obtained through a preset calculation formula, where the ambient light intensity is collected by the light sensor, the photoelectric conversion efficiency is the nominal efficiency value of the photovoltaic panel, the photovoltaic panel area is the actual installation area, and the sunlight incident angle is calculated in real time by an astronomical algorithm based on the geographical location of the solar power street lamp and the current time. Exemplarily, the preset formula can be expressed as: ; In the formula, Indicates the expected power generation; is the light intensity; is the photoelectric conversion efficiency of the photovoltaic panel, is the area of ​​the photovoltaic panel, is the solar incidence angle, which can be calculated from the geographical location and time.

[0039] The above data preprocessing and expected power generation calculation method can not only effectively eliminate the influence of noise and outliers in the original data and ensure the accuracy of the calculation results, but also provide a reliable reference for subsequent shading status judgment. At the same time, this standardized data processing process is also convenient for system expansion and maintenance, and can flexibly adapt to solar power generation street lighting systems of different sizes.

[0040] Step 202: Based on the difference between the expected power generation and the actual power generation of each solar power generation street lamp, determine whether the solar power generation street lamp in the target area is in a shielded state.

[0041] In practical applications, the shading status of solar street lights can be judged by the difference between the expected power generation and the actual power generation. The expected power generation reflects the power generation capacity of the photovoltaic panel under ideal working conditions, while the actual power generation reflects the actual output under the current working conditions. The difference between the two can directly reflect whether the photovoltaic panel is blocked and the severity of the shading.

[0042] Specifically, the system first calculates the difference between the expected power generation and the actual power generation. The power difference is obtained through a preset calculation formula, which is expressed as: ; In the formula, is the difference between the expected power generation and the actual power generation. is the actual power generated.

[0043] Step 203: If the difference between the expected power generation and the actual power generation of each solar-powered street lamp is greater than a preset threshold, it is determined that the solar-powered street lamps in the target area are in a shielded state.

[0044] Step 204: If the difference between the expected power generation and the actual power generation of each solar-powered street lamp is less than or equal to a preset threshold, it is determined that the solar-powered street lamps in the target area are in a non-shielded state.

[0045] Specifically, after obtaining the power difference, the system compares it with a preset threshold to determine whether the solar-powered street light is in a blocked state. Exemplarily, the judgment rule can be expressed as: ; In the formula, is the preset threshold.

[0046] The selection of the preset threshold value needs to comprehensively consider the performance parameters, environmental factors and historical operation data of the photovoltaic panels. Preferably, the preset threshold value can be set to 20% of the expected power generation, that is, when the actual power generation is lower than 80% of the expected power generation, it is determined that shading occurs.

[0047] In order to improve the accuracy of judgment, the system can also analyze the power difference in the time dimension. Since instantaneous power fluctuations may be caused by short-term factors such as cloud cover, the system uses the average power difference within a 5-minute time window for judgment. This processing method can effectively filter out the influence of environmental noise and improve the reliability of occlusion status judgment. At the same time, the system will also record the duration of the power difference exceeding the preset threshold, which will be used to distinguish between dynamic occlusion and fixed occlusion status later.

[0048] In practical applications, the system's judgment of the shading state also needs to consider the influence of weather factors. For example, on cloudy or rainy days, due to the generally low ambient light intensity, the power of solar-powered street lights in the entire target area may be generally low. In response to this situation, the system will dynamically adjust the preset threshold based on the light intensity data. For example, when the ambient light intensity is lower than 50% of the nominal value, the system will increase the preset threshold accordingly to avoid misjudging the power drop caused by weather factors as a shading state.

[0049] Through the above judgment method, not only can the shading status of solar power generation street lights be accurately identified, but the shading status can also be quantified, providing a reliable basis for subsequent maintenance decisions. At the same time, this judgment method based on power difference has the characteristics of simple calculation and easy implementation, and is suitable for promotion and application in large-scale solar power generation street light systems. In addition, by adjusting the preset threshold and time window size, this method can also flexibly adapt to the needs of different application scenarios and has good scalability.

[0050] Based on the above embodiment, as an optional embodiment, the environmental data also includes wind speed. After step 203: determining that the solar-powered street lamps in the target area are in a shielded state, the following steps may also be included: Step 301: Based on the expected power generation and actual power generation of each solar-powered street lamp, calculate the power fluctuation of the solar-powered street lamps in the target area within a preset time period.

[0051] Among them, power fluctuation refers to the degree to which the actual power generation of solar street lights deviates from its time series mean within a preset time period. Specifically, power fluctuation is quantified and calculated using the standard deviation method, reflecting the severity and fluctuation characteristics of power generation over time.

[0052] Power fluctuation can be understood as an indicator of the instability of the output power of solar-powered street lights. When the power generation remains relatively stable, the power fluctuation value is small; when the power generation changes frequently and significantly, the power fluctuation value is large. For example, in clear and unobstructed weather conditions, the power fluctuation of solar-powered street lights is usually small; when there are dynamic obstructions such as tree branches, the power generation power will show greater fluctuations due to the periodic movement of the obstruction causing changes in light intensity.

[0053] Power fluctuations are mainly used to identify and evaluate the dynamic shading status of solar-powered street lights. By calculating and monitoring the power fluctuation value, the system can distinguish between static shading and dynamic shading, especially when combined with wind speed fluctuations, it can effectively determine whether there is dynamic shading such as wind-induced tree branch swaying.

[0054] For example, the following formula can be used to calculate the power fluctuation of solar-powered street lights in the target area within a preset time period: ; In the formula, For power fluctuation, is the total length of the time series, that is, the number of time points recorded within the preset time length, is the actual power of the solar-powered street light at time t, is the time series mean of solar-powered street lights.

[0055] Specifically, the system first calculates the time series mean of the actual power within the preset time length. This mean reflects the basic level of power and can be used as a benchmark for evaluating the degree of power deviation. In the embodiment of the present application, the time series mean is obtained by calculating the arithmetic average of all power sampling points within the preset time length.

[0056] After obtaining the mean of the time series, the system calculates the square of the deviation between the actual power and the mean at each moment. This square of deviation reflects the degree to which the power at that moment deviates from the average level. The larger the deviation, the more significant the power fluctuation. By calculating the square of the deviation instead of the simple deviation, the problem of positive and negative deviations canceling each other out can be avoided, while the impact of large deviations is amplified, making violent fluctuations easier to detect.

[0057] Then, the system accumulates and sums the squares of the deviations at all times within the preset time. This cumulative sum comprehensively reflects the power fluctuations during the entire time period. In order to eliminate the influence of the time length on the calculation result, the system divides the cumulative sum by the number of samples to obtain the average square deviation. Finally, in order to make the calculation result have the same dimension as the original power, the system performs square root processing on the average square deviation to obtain the final standard deviation value.

[0058] In practical applications, a larger standard deviation indicates that there are dramatic power fluctuations, which are usually related to dynamic shading caused by tree branches swaying in the wind; a smaller standard deviation indicates that the power is relatively stable, which may be in an unobstructed or fixed shading state.

[0059] Step 302: Based on the wind speed, calculate the wind speed fluctuation in the target area within a preset time period.

[0060] The wind speed fluctuation refers to the degree to which the wind speed in the target area deviates from its time series mean within a preset time period. Specifically, the wind speed fluctuation is quantified by the standard deviation method, reflecting the severity and fluctuation characteristics of the wind force changes in the target area.

[0061] Wind speed fluctuation can be understood as an indicator of the instability of wind strength in the target area. When the wind remains relatively stable, the wind speed fluctuation value is small; when the wind changes frequently and significantly, the wind speed fluctuation value is large. For example, in calm or uniform wind conditions, wind speed fluctuations are usually small; when there are gusts or unstable wind conditions, the wind speed will show greater fluctuations. This fluctuation may cause surrounding obstructions such as tree branches to swing, thereby affecting the power generation efficiency of solar power street lights.

[0062] Wind speed fluctuations are mainly used to predict and evaluate the impact of wind changes on the dynamic shading of solar-powered street lights. By calculating and monitoring wind speed fluctuation values, the system can determine whether the wind changes are sufficient to cause significant swaying of obstructions such as tree branches. Especially when combined with power fluctuations, wind speed fluctuation data can help the system more accurately identify wind-induced shading phenomena, providing key reference information for intelligent operation and maintenance and fault diagnosis of solar-powered street lights.

[0063] For example, the following formula may be used to calculate the wind speed fluctuation in the target area within a preset time period: ; In the formula, is the wind speed fluctuation, is the wind speed of the solar-powered street light at time t, is the time series mean of wind speed.

[0064] The system uses a standard deviation method similar to the power fluctuation calculation to quantify wind speed fluctuations. Through a preset calculation formula, the system first obtains the mean of the wind speed time series within a preset time period. This mean reflects the average wind level during the observation period and can be used as a benchmark for evaluating wind speed changes. In actual applications, the system collects wind speed data at fixed time intervals through meteorological sensors installed in the target area.

[0065] After obtaining the wind speed data, the system calculates the square of the deviation between the actual wind speed at each moment and the mean of the time series. This square deviation reflects the degree to which the wind speed at that moment deviates from the average level. The larger the deviation, the more significant the wind speed fluctuation. The wind speed fluctuation value is finally obtained by accumulating and averaging the square of the deviations at all moments and taking the square root. A larger wind speed fluctuation value indicates that the wind force changes violently, which is more likely to cause obstructions such as tree branches to swing.

[0066] Step 303: Calculate the correlation coefficient between power fluctuation and wind speed fluctuation.

[0067] The correlation coefficient is a quantitative indicator of the degree of linear correlation between power fluctuations and wind speed fluctuations. Specifically, the correlation coefficient is calculated through standardized covariance, and its value range is between -1 and 1, reflecting the strength of the association and the direction of change between the two fluctuations.

[0068] The correlation coefficient can be understood as a statistic that measures the degree of synchronous change of power fluctuations and wind speed fluctuations. When the correlation coefficient is close to 1, it means that the two fluctuations show a strong positive correlation, that is, when the wind speed increases, the power fluctuation also increases; when the correlation coefficient is close to -1, it means that the two fluctuations show a strong negative correlation; when the correlation coefficient is close to 0, it means that there is basically no linear correlation between the two fluctuations. For example, when power fluctuations are caused by tree branches, since the swing of tree branches is mainly affected by wind force, the power fluctuations and wind speed fluctuations usually show a high positive correlation.

[0069] The correlation coefficient is mainly used to determine whether the power fluctuation of solar-powered street lights is caused by wind-induced shading. By analyzing the size of the correlation coefficient, the system can effectively distinguish between dynamic shading caused by wind-induced tree branch swinging and power fluctuations caused by other reasons. This correlation analysis provides reliable data support for the system to accurately identify the type of shading, evaluate the degree of shading impact, and formulate corresponding maintenance strategies.

[0070] Exemplarily, the correlation coefficient between power fluctuation and wind speed fluctuation may be calculated using the following formula: ; In the formula, is the correlation coefficient. The denominator represents the product of the standard deviations of power fluctuations and wind speed fluctuations, reflecting the magnitude of the fluctuation intensities of the two. The numerator represents the covariance of power fluctuations and wind speed fluctuations, reflecting the synchronization and directionality of the fluctuations of the two.

[0071] Specifically, the system uses a standardized correlation coefficient calculation method that takes into account the two key characteristics of fluctuation intensity and synchronization. In the calculation formula, the denominator uses the product of the standard deviation of power fluctuation and the standard deviation of wind speed fluctuation. This standardization eliminates the dimensional differences between different physical quantities, making the correlation coefficient have a unified measurement standard. The numerator reflects the synchronous change characteristics of the two fluctuation sequences by calculating their covariance. The positive or negative value of the covariance indicates the directional relationship of the fluctuation change.

[0072] Step 304: Determine whether the occlusion state is a dynamic occlusion state or a fixed occlusion state according to the correlation coefficient.

[0073] After obtaining the correlation coefficient between power fluctuation and wind speed fluctuation, the system needs to further determine the specific type of shading state. Since different types of shading will cause power fluctuation to present different characteristic patterns, by analyzing the correlation coefficient and other key parameters, dynamic shading and fixed shading states can be accurately distinguished, thus providing a more targeted basis for subsequent maintenance decisions.

[0074] Specifically, the system first analyzes the size of the correlation coefficient r. When the correlation coefficient is greater than the preset correlation threshold (such as r>0.7), it indicates that the power fluctuation has a significant positive correlation with the wind speed fluctuation, that is, the change trend of the power is basically consistent with the change trend of the wind speed. This situation usually occurs in dynamic shading caused by obstructions such as tree branches swinging with the wind, because the increase in wind speed will aggravate the swing of tree branches, resulting in periodic changes in the shading state of the photovoltaic panel, which ultimately manifests as periodic fluctuations in power. At this time, the system determines the shading state as dynamic shading.

[0075] The judgment of fixed occlusion requires comprehensive consideration of multiple conditions. First, the system checks whether the duration of the power anomaly exceeds the preset fixed occlusion time threshold. This time threshold is usually set to a longer period of time to distinguish between continuous occlusion and short-term power fluctuations. Secondly, the system calculates the rate of change of ambient light intensity. When this rate of change is close to zero, it indicates that the ambient light conditions are basically stable and the power anomaly is not caused by weather changes. Finally, the system also checks whether the correlation coefficient r is less than the preset correlation threshold to rule out the possibility of dynamic occlusion. When these three conditions are met at the same time, the system determines the occlusion state as fixed occlusion.

[0076] For example, the judgment conditions are: (1) ; (2) Duration of power abnormality Exceeding the fixed occlusion time threshold : ; (3) The rate of change of ambient light intensity is close to zero: ; Dynamic occlusion only needs to meet the following requirements: .

[0077] By introducing correlation coefficient analysis, the system can accurately identify dynamic shading caused by wind-induced tree branch swinging, which often requires different treatment measures than fixed shading. Secondly, by setting a reasonable time threshold and introducing the light intensity change rate judgment, the system can effectively distinguish fixed shading from other factors that cause power anomalies to avoid misjudgment. Finally, this judgment method has a small amount of calculation and is suitable for application in real-time monitoring systems. It can quickly respond to changes in shading status and adjust maintenance strategies in a timely manner.

[0078] Step 103: If it is determined that the solar-powered street lamps in the target area are in a shielded state, a maintenance suggestion corresponding to the shielded state is generated.

[0079] Specifically, based on the shading status information obtained in the above steps, the system needs to generate corresponding maintenance suggestions to guide maintenance personnel to take appropriate treatment measures to ensure the normal operation of the solar power generation street light system. The generation process of maintenance suggestions needs to comprehensively consider multiple factors such as shading type, shading status, geographical location, etc., and form an operational maintenance plan through a systematic analysis method.

[0080] Based on the above embodiment, as an optional embodiment, step 103 may further include the following steps: Step 401: Generate a heat map based on the geographic locations of solar-powered street lights that are in a blocked state.

[0081] In the actual operation and maintenance of solar-powered street lighting systems, shading problems often show obvious spatial clustering characteristics. In order to help maintenance personnel quickly identify and locate shading problems, the system needs to use an intuitive visualization method to display the spatial distribution of shading status. Heatmaps, as a visualization tool that maps data values ​​to color depth, can effectively express the spatial distribution density and severity of shading problems.

[0082] Among them, heat map refers to a data representation form that maps data values ​​to color depth and visualizes them in a spatial coordinate system. In the embodiment of the present application, it can be understood as a two-dimensional visualization map generated based on the geographical location and shading status of solar-powered street lights, which is used to intuitively display the distribution density, severity and spatial aggregation characteristics of shading problems in the target area.

[0083] Based on the above embodiment, as an optional embodiment, step 401 may further include the following steps: Step 501: Obtain the shading degree of the solar-powered street light in a shading state.

[0084] Before generating the heat map, the system needs to first clarify the shading severity of each solar power street lamp, which is the basic data for subsequent spatial distribution analysis and visualization. The shading degree Di is a standardized quantitative indicator that can accurately reflect the severity of the solar power street lamp affected by shading by calculating the relative deviation between the actual power generation and the expected power generation.

[0085] The degree of shading refers to the degree of deviation of the actual power generation of the photovoltaic panel of the solar power street lamp relative to the expected power generation. In the embodiment of the present application, it can be understood as a standardized parameter calculated based on the ratio of the expected power generation to the actual power generation, which is used to quantitatively characterize the severity of the impact of shading on the solar power street lamp.

[0086] Exemplarily, the calculation formula of the occlusion degree can be expressed as: ; In the formula, For the The occlusion degree of a street lamp ranges from ,The larger the value, the more serious the occlusion; For the The expected power generation of a street lamp is For the The actual power generation of a street lamp, is the total number of street lights in the target area.

[0087] The above is normalized by dividing the power difference by the expected power to obtain the degree of occlusion is limited to the interval [0,1], eliminating the dimensional differences between street lamps of different power levels; secondly, The value of is positively correlated with the severity of the occlusion. When it is close to 0, it indicates that the actual power generation is close to the expected value and there is basically no shading effect. When it is close to 1, it indicates that there is a serious occlusion problem and it needs to be dealt with in time.

[0088] Through the above-mentioned method of calculating the degree of shading, the system can quantify the shading status of solar power generation street lights, providing reliable data support for subsequent spatial distribution analysis and maintenance decisions. At the same time, since the calculation results have been standardized, it is also convenient to perform color mapping and level division of the heat map, which improves the intuitiveness of the visualization effect. In addition, the versatility of this calculation method makes it suitable for solar power generation street light systems of different types and sizes, and has strong practical value.

[0089] Step 502: Based on the shading degree and geographical location of each solar-powered street lamp in a shading state, the target area is divided into a plurality of cluster areas with different shading degrees.

[0090] In the actual maintenance process, the shading problem of solar-powered street lights often shows obvious spatial clustering characteristics, which may be caused by common environmental factors. In order to improve maintenance efficiency, the system needs to identify and locate the concentrated areas of these shading problems. Through spatial clustering analysis, street lights with similar geographical locations and similar shading levels can be grouped together to discover the spatial distribution pattern of shading problems.

[0091] In a feasible implementation, the system uses the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm for cluster analysis. Since the occlusion problem of solar-powered street lights usually presents regional characteristics, for example, the same forest may affect multiple adjacent street lights at the same time, or the undulating terrain may cause street lights in a specific area to be generally blocked. This spatial distribution feature is highly consistent with the density clustering principle of the DBSCAN algorithm. The DBSCAN algorithm can not only detect clusters of irregular shapes, but also automatically identify and remove abnormal points, which makes it particularly suitable for processing the analysis of occlusion problems of solar-powered street lights.

[0092] In the specific implementation process, the system first needs to determine two key parameters: the cluster radius ε and the minimum number of neighbor points minPts. Among them, ε is defined as the maximum distance threshold for judging whether two street lights form a neighbor relationship. This parameter is usually set according to the actual installation spacing of the street lights. For example, it can be 1.5 times the standard spacing of the street lights; minPts specifies the minimum number of street lights required to form an effective cluster. The setting of this parameter needs to balance the effectiveness of the clustering and the maintenance efficiency. It can usually be set to 3-5. Based on these two parameters, the system first calculates the geographical distance between any two street lights. When the distance is less than ε, the two street lights are marked as neighbors. Then, the system checks the number of neighbors of each street light. If the number of neighbors of a street light is not less than minPts, it is marked as a core point. For each core point, the system classifies it and all reachable neighbor street lights into the same clustering area.

[0093] Through the above clustering method, the system can effectively identify the spatial distribution characteristics of the occlusion problem. For example, when multiple street lamps in a certain area have occlusion problems at the same time, these street lamps will be divided into the same cluster, indicating that there may be a common occlusion source in the area; and those street lamps marked as noise points may be occluded due to local reasons. This analysis result not only helps maintenance personnel to quickly locate the problem area, but also helps to formulate more targeted maintenance strategies. For example, for occlusion problems in the cluster area, regional tree pruning or street lamp position adjustment measures may be required; while for noise points, only local processing may be required. At the same time, by appropriately adjusting the ε and minPts parameters, the system can flexibly control the granularity of clustering and achieve a good balance between the accuracy of problem location and maintenance efficiency.

[0094] After obtaining the preliminary clustering results, the system Perform feature calculation and analysis, where , where K represents the number of clusters.

[0095] First, calculate the number of street lights in the area ,The number of street lights directly reflects the scale of the ,obstruction problem, which helps maintenance personnel to assess the required ,maintenance resources and workload, which is of great significance for formulating ,reasonable maintenance plans.

[0096] Specifically, the system traverses the DBSCAN clustering results, counts the number of street lights corresponding to each cluster label, and accumulates the street light counts belonging to the same cluster to obtain the total number of street lights in the cluster area. This counting statistic not only reflects the spatial scale of the occlusion problem, but also helps maintenance personnel evaluate the required operation time and equipment quantity.

[0097] Secondly, since the maintenance resources of solar-powered street lighting systems are usually limited and areas with more severe shading need to be treated first, it is of great significance to calculate and evaluate the overall shading severity of the area.

[0098] Exemplarily, the calculation of the average occlusion degree can be expressed as: ,in, It represents the average occlusion degree corresponding to the jth cluster area. The average occlusion degree index can reflect the overall occlusion severity of the area and help determine the maintenance priority.

[0099] Then, record the occlusion severity range: ,in, Represents the minimum and maximum values ​​of the occlusion degree in the jth cluster area, which is used to characterize the degree of change of the occlusion problem in the area.

[0100] The occlusion severity range can reflect the discrete degree of occlusion problems in the area, helping maintenance personnel to determine the nature and distribution characteristics of occlusion sources. For example, if the occlusion severity range in a certain area is narrow, that is, the maximum and minimum values ​​are close, it may indicate that the street lights in the area are affected by similar degrees of occlusion, suggesting the existence of a single major occlusion source, such as a relatively uniform forest; while areas with a wider occlusion severity range may have multiple occlusion factors or uneven occlusion sources, such as scattered trees or buildings. Through this range analysis, maintenance personnel can better understand the spatial characteristics of occlusion problems and thus develop more targeted maintenance strategies. Finally, calculate the cluster area coverage radius ;in, Represents the maximum distance between two points in the jth cluster area, which is used to describe the geographical coverage of the area.

[0101] The cluster area coverage radius can characterize the geographical coverage of the problem area, which helps to plan maintenance routes and evaluate the geographical span of maintenance work.

[0102] After obtaining the preliminary clustering results, the system Perform feature calculation and analysis, where , where K represents the number of clusters.

[0103] Step 503: Generate a heat map based on each cluster area.

[0104] After obtaining the basic characteristics of the clustered areas, the system needs to further evaluate the severity of the occlusion problem in each area and display the evaluation results in an intuitive and visual way. To this end, the system introduces a maintenance priority scoring mechanism to quantify multiple key characteristics of the occlusion problem into a single indicator, and generates a heat map based on this indicator to help maintenance personnel quickly identify key areas.

[0105] Specifically, the system first calculates the maintenance priority score of each cluster area. As a comprehensive indicator, the priority score needs to consider the scale, severity and spatial distribution characteristics of the occlusion problem at the same time.

[0106] Exemplarily, the priority score of the j-th cluster region may be calculated using the following formula: ; In the formula, Represents the priority score of the jth clustering area. The larger the value, the more serious the occlusion problem in the area is, and it needs to be handled with priority. represents the number of street lights in the jth cluster area, represents the average occlusion degree of the jth cluster area, represents the area of ​​the jth cluster region, ∝ .

[0107] in, and The larger it is, the more concentrated the occlusion problem is in the hotspot area and the higher the severity of the problem. The larger the value, the more dispersed the problem is and the lower the priority is. The above scoring formula takes into account the scale, severity and distribution density of the occlusion problem, which is convenient for the reasonable allocation of maintenance resources.

[0108] After obtaining the priority scores, the system maps these score values ​​to the color depth of the heat map. In the specific implementation process, the system first normalizes the priority scores of all clustered areas and maps the score values ​​to the [0,1] interval. Then, the system uses a preset color mapping scheme, such as a gradient color spectrum from green to red, where green represents lower priority areas and red represents higher priority areas. For each clustered area, the system selects the corresponding color value in the color spectrum based on its normalized priority score.

[0109] In order to generate a continuous and smooth heat map, the system needs to process the transition area between cluster areas. The kernel density estimation method is used here to convert the discrete score value into a continuous density distribution. Specifically, the system takes the position of each street lamp as the center and generates a two-dimensional Gaussian kernel function according to the priority score of the cluster area to which it belongs. By superimposing the kernel functions of all street lamp positions, a continuous density distribution of the entire target area is formed. This processing method can not only smoothly display the spatial distribution of priority, but also reflect the impact range and intensity gradient of the occlusion problem.

[0110] During the generation of the heat map, the system will also add necessary legends and annotation information. For example, the corresponding relationship between color and priority score is indicated in the legend, and the key features of each cluster area are marked on the map. These auxiliary information can help maintenance personnel better understand and use the heat map.

[0111] Step 402: Generate maintenance suggestions based on the thermal map; Based on the above embodiment, as an optional embodiment, step 402 may specifically include the following steps: Step 601: if the occlusion state is a fixed occlusion state, generating tree pruning suggestions based on the heat map; Step 602: If the shading state is a non-fixed shading state, generating power scheduling suggestions based on the thermal map.

[0112] During the operation and maintenance of the solar street lighting system in the target area, different types of shading problems require different processing strategies. Fixed shading and dynamic shading correspond to different maintenance requirements. The system needs to generate targeted maintenance suggestions based on the results of the thermal map analysis to ensure the continuous and stable operation of the system.

[0113] When the system detects a fixed shading state, it indicates that the solar-powered street lights are mainly continuously blocked by stationary objects such as leaves. In response to this situation, the system needs to generate tree pruning recommendations. Specifically, the system first extracts the geographic range and shading characteristics of high-priority areas from the heat map. Then, based on the average shading degree and area coverage radius of these areas, the system calculates the recommended pruning range. At the same time, the system determines the urgency of pruning based on the average shading degree and makes corresponding grade divisions to guide the priority of maintenance work.

[0114] For each area that needs to be mowed, the system generates a mowing suggestion that includes the geographic coordinate range of the mowing area, the number of street lights affected in the area, the recommended mowing height, the recommended mowing time, and other elements. These suggestions are presented in a structured manner to facilitate maintenance personnel to understand and implement. The system determines the appropriate mowing height by analyzing parameters such as the installation height of the street lights and the sun's incidence angle, and selects the appropriate maintenance time window based on the power load characteristics.

[0115] When the system detects a dynamic shading state, direct tree pruning may not be economical because such shading is usually caused by temporary factors such as swaying branches. In response to this situation, the system instead generates power scheduling recommendations to reduce the impact of shading by optimizing energy allocation. Specifically, the system first analyzes the spatiotemporal distribution characteristics of the dynamic shading areas in the thermal map and evaluates the power fluctuation patterns of each area. Based on the average shading degree and power fluctuation characteristics of each cluster area, the system calculates the additional energy compensation requirements.

[0116] The power dispatching proposal mainly includes the calculation of the expected power gap in the dynamic shielding area at different time periods, and the prediction of the power fluctuation period based on historical data. The system identifies potential energy supply sources from adjacent non-shielded areas, giving priority to areas with closer distances and more power generation surplus. Finally, the system generates a specific dispatching plan containing information such as energy transmission path, dispatching time window, and expected compensation power.

[0117] Through the above-mentioned differentiated maintenance suggestion generation mechanism, the system realizes refined management of shading problem handling. For fixed shading, by accurately positioning and rationally planning the pruning range, maintenance costs can be minimized and work efficiency can be improved; for dynamic shading, through intelligent power scheduling strategies, the power supply stability of the affected area can be guaranteed, unnecessary tree pruning can be avoided, and optimal resource allocation can be achieved. At the same time, this suggestion generation method is highly practical and scalable, and can flexibly adjust parameters and strategies according to actual operation and maintenance needs.

[0118] Reference Figure 2 The present application also provides a maintenance system for solar-powered street lights, including: A data acquisition module, used to acquire detection data of each solar-powered street lamp in a target area within a preset time period, as well as environmental data of the target area; an occlusion judgment module, used to judge whether the solar-powered street lamps in the target area are in an occlusion state based on the detection data and the environmental data, wherein the occlusion state is used to characterize the degree to which the solar-powered street lamps in the target area are occluded by trees; The suggestion generating module is used for generating a maintenance suggestion corresponding to the blocking state if it is determined that the solar-powered street lamps in the target area are in the blocking state.

[0119] On the basis of the above embodiments, as an optional embodiment, the detection data includes the actual power generation of the photovoltaic panels in each of the solar power generation street lamps, and the geographical location of each of the solar power generation street lamps; the environmental data includes light intensity; the shielding judgment module is also used to calculate the expected power generation of each of the solar power generation street lamps based on the geographical location and light intensity of each of the solar power generation street lamps; based on the difference between the expected power generation and the actual power generation of each of the solar power generation street lamps, judge whether the solar power generation street lamps in the target area are in a shielded state; if the difference between the expected power generation and the actual power generation of each of the solar power generation street lamps is greater than a preset threshold, it is determined that the solar power generation street lamps in the target area are in a shielded state; if the difference between the expected power generation and the actual power generation of each of the solar power generation street lamps is less than or equal to the preset threshold, it is determined that the solar power generation street lamps in the target area are in a non-shielded state.

[0120] On the basis of the above embodiment, as an optional embodiment, the environmental data also includes wind speed. The shading judgment module is also used to calculate the power fluctuation of the solar power street lamps in the target area within the preset time period based on the expected power generation power and the actual power generation power of each solar power street lamp; calculate the wind speed fluctuation of the target area within the preset time period based on the wind speed; calculate the correlation coefficient between the power fluctuation and the wind speed fluctuation; and determine whether the shading state is dynamic shading or fixed shading state according to the correlation coefficient.

[0121] Based on the above embodiment, as an optional embodiment, the suggestion generation module is further used to generate a heat map based on the geographical location of the solar-powered street lamp in the blocked state; and generate maintenance suggestions based on the heat map.

[0122] On the basis of the above-mentioned embodiment, as an optional embodiment, it is suggested that the generation module is also used to obtain the shading degree of the solar-powered street lamps in the shading state; based on the shading degree and geographical location of each of the solar-powered street lamps in the shading state, the target area is divided into a plurality of cluster areas with different shading degrees; and a heat map is generated based on each of the cluster areas.

[0123] Based on the above embodiment, as an optional embodiment, the suggestion generation module is also used to generate tree pruning suggestions based on the thermal map if the occlusion state is a fixed occlusion state; if the occlusion state is a non-fixed occlusion state, generate power scheduling suggestions based on the thermal map.

[0124] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0125] The embodiment of the present application also provides a computer storage medium, which can store multiple instructions. The instructions are suitable for being loaded by a processor and executed as the maintenance method of the solar-powered street lamp in the above embodiment. The specific execution process can refer to the specific description of the embodiment shown, which will not be repeated here.

[0126] An embodiment of the present application also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the maintenance methods for solar-powered street lights provided by the above methods.

[0127] The present application also discloses an electronic device. Figure 3 , Figure 3 The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .

[0128] The communication bus 302 is used to realize the connection and communication between these components.

[0129] The user interface 303 may include a display interface and a camera interface. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0130] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0131] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface diagrams and applications, etc.; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.

[0132] Among them, the memory 305 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may optionally also be at least one storage device located away from the aforementioned processor 301. Refer to Figure 3 The memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program of a method for maintaining a solar-powered street lamp.

[0133] exist Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 301 can be used to call the application program stored in the memory 305 for a maintenance method of a solar-powered street light. When executed by one or more processors 301, the electronic device 300 executes one or more of the methods described in the above embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0134] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0135] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, 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 service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0136] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0137] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0138] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0139] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present disclosure.

[0140] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not described in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for maintaining a solar-powered street light, characterized in that: include: Acquire detection data of each solar-powered street lamp in a target area within a preset time period, as well as environmental data of the target area; Based on the detection data and the environmental data, determining whether the solar-powered street lamps in the target area are in a shielding state, wherein the shielding state is used to characterize the degree to which the solar-powered street lamps in the target area are shielded by trees; If it is determined that the solar-powered street lamps in the target area are in a shielded state, a maintenance suggestion corresponding to the shielded state is generated.

2. The maintenance method of solar-powered street lights according to claim 1, characterized in that: The detection data includes the actual power generation of the photovoltaic panels in each of the solar-powered street lamps, and the geographical location of each of the solar-powered street lamps; the environmental data includes light intensity; and judging whether the solar-powered street lamps in the target area are in a shielded state based on the detection data and the environmental data includes: Calculating the expected power generation of each solar-powered street lamp based on the geographical location and light intensity of each solar-powered street lamp; Based on the difference between the expected power generation and the actual power generation of each of the solar-powered street lamps, determining whether the solar-powered street lamps in the target area are in a shielded state; If the difference between the expected power generation and the actual power generation of each of the solar-powered street lamps is greater than a preset threshold, it is determined that the solar-powered street lamps in the target area are in a shielded state; If the difference between the expected power generation and the actual power generation of each of the solar power generation street lamps is less than or equal to a preset threshold, it is determined that the solar power generation street lamps in the target area are in a non-shielded state.

3. The maintenance method of solar-powered street lights according to claim 2, characterized in that: The environmental data also includes wind speed. After determining that the solar-powered street lamps in the target area are in a shielded state, the method further includes: Calculating the power fluctuation of the solar-powered street lamps in the target area within the preset time period based on the expected power generation and the actual power generation of each of the solar-powered street lamps; Based on the wind speed, calculating the wind speed fluctuation of the target area within the preset time period; calculating a correlation coefficient between the power fluctuation and the wind speed fluctuation; The occlusion state is determined to be a dynamic occlusion state or a fixed occlusion state according to the correlation coefficient.

4. The maintenance method of solar-powered street lights according to claim 1, characterized in that: The generating a maintenance suggestion corresponding to the occlusion state includes: generating a heat map based on the geographic locations of the solar-powered street lamps in the blocked state; Maintenance recommendations are generated based on the heat map.

5. The maintenance method of solar-powered street lights according to claim 4, characterized in that: The generating of a heat map based on the geographical location of the solar-powered street lamp in the shielded state comprises: Obtaining the degree of shading of the solar-powered street lamp in the shading state; Based on the shading degree and geographical location of each of the solar-powered street lamps in the shading state, the target area is divided into a plurality of cluster areas with different shading degrees; A heat map is generated based on each of the clustered regions.

6. The maintenance method of solar-powered street lights according to claim 4, characterized in that: Generating maintenance suggestions based on the thermal map includes: If the occlusion state is a fixed occlusion state, generating a tree pruning suggestion based on the heat map; If the shading state is a non-fixed shading state, a power scheduling suggestion is generated based on the thermal map.

7. A maintenance system for solar-powered street lights, characterized in that: include: A data acquisition module, used to acquire detection data of each solar-powered street lamp in a target area within a preset time period, as well as environmental data of the target area; an occlusion judgment module, used to judge whether the solar-powered street lamps in the target area are in an occlusion state based on the detection data and the environmental data, wherein the occlusion state is used to characterize the degree to which the solar-powered street lamps in the target area are occluded by trees; The suggestion generating module is used for generating a maintenance suggestion corresponding to the blocking state if it is determined that the solar-powered street lamps in the target area are in the blocking state.

8. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method as described in any one of claims 1-6.

9. A computer storage medium, characterized in that The computer storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 6 is performed.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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