Method for monitoring running state of solar street lamp

Abstract

The invention discloses a method for monitoring the running state of a solar street lamp, which relates to the technical field of intelligent monitoring and comprises the following steps of: S1, establishing a characteristic monitoring reference of an electric energy transmission link of the solar street lamp; s2, performing photovoltaic output stability analysis by using the electric energy characteristic reference; s3, performing energy storage unit energy conversion consistency analysis by using the photovoltaic output state set; s4, performing load power supply link health assessment by using the energy storage operation feature set; s5, performing system comprehensive operation state identification by using the energy storage operation feature set and the load power supply state set; and S6, determining a street lamp operation state result according to the system operation state identification set. According to the method, abnormal disturbance identification is carried out based on a multi-source operation data reference, dynamic analysis can be carried out on operation characteristics of the solar street lamp on a system-level data level, accurate judgment of disturbance consistency among multi-dimensional operation parameters is realized, and a data basis with higher robustness is provided for subsequent state identification.

Description

Technical Field

[0001] This invention relates to the field of intelligent monitoring technology, specifically a method for monitoring the operating status of solar streetlights. Background Technology

[0002] Solar streetlights, as an important component of distributed renewable energy utilization systems, have been widely used in urban roads, rural roads, and park lighting. These streetlights convert solar energy into electrical energy through photovoltaic modules and store this energy through energy storage devices for nighttime lighting. Due to the complexity of their system composition, including photovoltaic power generation modules, energy storage modules, load modules, and control modules, real-time monitoring of their operating status is crucial for stable system operation and energy efficiency management. Existing solar streetlight monitoring methods largely rely on the direct acquisition and comparison of static parameters such as power, voltage, and current, which fails to comprehensively reflect the system's collaborative operating characteristics under dynamic environments.

[0003] In existing technologies, there is a lack of consistency analysis mechanisms based on the correlation characteristics between multi-source operating data, which makes it impossible to comprehensively identify the dynamic operating differences between photovoltaic, energy storage and load modules, resulting in insufficient accuracy of system status monitoring results. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method for monitoring the operational status of solar streetlights, thereby resolving the problems mentioned in the background section.

[0005] To achieve the above objectives, the present invention provides the following technical solution: In a first aspect, embodiments of the present invention provide a method for monitoring the operating status of a solar street light, comprising the following steps: S1. Establish a characteristic monitoring benchmark for the power transmission link of solar street lights; S2. Perform photovoltaic output stability analysis using electrical energy characteristic benchmarks to obtain the photovoltaic output state set; S3. Use the photovoltaic output state set to perform energy conversion consistency analysis of the energy storage unit and obtain the energy storage operation characteristic set; S4. Use the energy storage operation feature set to perform a load power supply link health assessment to obtain a load power supply status set; S5. Use the energy storage operation feature set and the load power supply status set to identify the overall system operation status and obtain the system operation status identifier set; S6. Determine the street light operating status result based on the system operating status identifier set.

[0006] To further optimize this technical solution, step S1 monitors the basic characteristics of the solar street light during its operation, and the monitoring process includes the following steps: Monitoring node identification and sampling channel establishment; Data synchronization and time base establishment; Signal filtering and timing alignment; Feature data extraction and structured processing.

[0007] To further optimize this technical solution, the electrical energy characteristic benchmark dataset obtained in step S1... Its expression is: ; In the formula, : No. There are 10 monitoring nodes, of which: For the output end of photovoltaic modules, For energy storage input, For energy storage output, For load driving end; : No. Each sampling time point; :node In time The voltage value; :node In time The current value; :node In time The instantaneous power characteristics; :node In time The cumulative energy characteristics; :node The power and energy normalization results; : Time synchronization identifier, used to ensure time consistency of data across multiple nodes.

[0008] To further optimize this technical solution, step S2 is based on the electrical energy characteristic benchmark dataset output in step S1. The analysis focuses on the stability of the voltage, current, and power characteristics at the output of photovoltaic modules as a function of sunlight. Step S2 in the photovoltaic output stability analysis process includes the following steps: Photovoltaic output feature extraction; Stability index calculation; Determining the photovoltaic output state set.

[0009] To further optimize this technical solution, in step S2, when extracting photovoltaic output features, the dataset is... Extracting photovoltaic nodes voltage Current and power ; Power and light intensity Establish mapping relationships; Time series data according to time synchronization identifier Alignment.

[0010] To further optimize this technical solution, step S2, when calculating stability indicators, includes the following three categories of indicators: Output fluctuation amplitude ; Output lag time ; Output continuity index .

[0011] To further optimize this technical solution, in step S2, when calculating the output fluctuation amplitude, the calculation formula is as follows: ; For length is The average power within the time window; pass Measure the magnitude of short-term power fluctuations.

[0012] To further optimize this technical solution, in step S2, when calculating the output lag time, the calculation formula is as follows: ; The peak time of light intensity within the current window, that is, the time node when the light intensity value identified in the light intensity measurement sequence within this window reaches the highest point; pass This indicates a delay in the photovoltaic output response.

[0013] To further optimize this technical solution, in step S2, when calculating the output continuity index, the calculation formula is as follows: ; For indicator functions; The minimum effective output power threshold; pass Characterizes the continuity of power output.

[0014] To further optimize this technical solution, in step S2, when determining the photovoltaic output state set, the index obtained during the stability index calculation is combined with a preset threshold to determine the output state. The preset threshold includes a power fluctuation amplitude limit. Output response hysteresis limit and output continuity index limit ; by , , There are three judgment conditions; When all three conditions are met, the system is considered highly stable, and the output is... ; The system is considered moderately stable and the output is determined only if one or two of the three conditions are met. ; If none of the three conditions are met, the system is classified as low stability, and the output is... ; Obtain the photovoltaic output state set corresponding to the time series. .

[0015] In a second aspect, embodiments of the present invention provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the computer program instructions, when executed by the processor, implement the steps of a solar street light operation status monitoring method as described in the first aspect of the present invention.

[0016] Thirdly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, they implement the steps of a solar street light operation status monitoring method as described in the first aspect of the present invention.

[0017] Compared with existing technologies, this invention provides a method for monitoring the operating status of solar streetlights, involving machine learning and deep learning technologies, which has the following beneficial effects: This solar street light operation status monitoring method, by setting up anomaly identification based on multi-source operation data benchmarks, can dynamically analyze the operation characteristics of solar street lights at the system-level data level, and accurately determine the consistency of disturbances among multi-dimensional operation parameters. This mechanism can effectively identify abnormal disturbance signals caused by environmental changes or module failures, and output a set of suspicious signals in an aggregated form, providing a more robust data foundation for subsequent status identification, thereby significantly improving the accuracy and reliability of solar street light system operation status monitoring. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating a method for monitoring the operating status of solar streetlights proposed in this invention. Figure 2 This is a schematic diagram of the photovoltaic output stability analysis process of a solar street light operation status monitoring method proposed in this invention; Figure 3 This is a schematic diagram of the energy conversion consistency analysis process of the energy storage unit in the solar street light operation status monitoring method proposed in this invention. Figure 4 This is a schematic diagram of the system-wide operation status identification process of a solar street light operation status monitoring method proposed in this invention. Detailed Implementation

[0020] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0021] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0022] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single embodiment or an embodiment selectively excluded from other embodiments.

[0023] Example 1: Reference Figures 1-4 This is the first embodiment of the present invention, which provides a method for monitoring the operating status of a solar street light, including the following steps: S1. Establish a characteristic monitoring benchmark for the power transmission link of solar street lights; Step S1 monitors the basic characteristics of the solar streetlights during operation, and the monitoring process includes the following steps: Monitoring node identification and sampling channel establishment: Based on the power transmission path of solar streetlights, four core monitoring nodes are identified from photovoltaic power generation to load driving, including: : Output end of photovoltaic module; Energy storage unit input terminal; : Output terminal of energy storage unit; : Load driver end; At each node, voltage sampling channels and current sampling channels are deployed, wherein: The voltage signal is stepped down and electrically isolated using a resistor divider sampling technique. The current signal is acquired in real time using a Hall sensor or shunt sampling technology; The sampled signal is converted into a digital signal by an analog-to-digital converter (ADC) and then input to the monitoring and control unit.

[0024] Data synchronization and time base establishment: To ensure time consistency of data across multiple nodes, a unified time base is established through a GPS timing module or a local NTP clock synchronization mechanism. In multi-light cluster scenarios, node clock synchronization is achieved by broadcasting synchronization signals via the CAN bus; The time drift error of all sampling channels is controlled within ±10 ms, and the sampling frequency is set to no less than 1 kHz to ensure the time resolution of energy transfer analysis.

[0025] Signal filtering and timing alignment: The monitoring and control unit performs the following two preprocessing steps on the acquired signals: Filtering: Kalman filtering or third-order low-pass filtering is used to suppress transient noise and spike interference, ensuring signal smoothness; Time alignment: To address the offset of sampling times in different channels, linear interpolation resampling technology is used to achieve signal time synchronization, ensuring that all node signals are aligned on the same time axis.

[0026] Feature data extraction and structured processing: After filtering and alignment, the monitoring and control unit extracts characteristic parameters such as voltage, current, power and energy of each node according to the time series and establishes a node-level data structure. This structure uses timestamp as the main index and is used for subsequent status determination and link stability analysis.

[0027] After the above process, step S1 finally yields the electrical energy characteristic benchmark dataset. Its expression is: ; In the formula, : No. monitoring nodes ( For the output end of photovoltaic modules, For energy storage input, For energy storage output, (For load-driven end). : No. Each sampling time point; :node In time The voltage value; :node In time The current value; :node In time The instantaneous power characteristics; :node In time The cumulative energy characteristics; :node The power and energy normalization results; : Time synchronization identifier, used to ensure time consistency of data across multiple nodes.

[0028] The dataset It represents the characteristic changes of each node in the power transmission link of solar street lights in the time domain, forming a power monitoring benchmark with time synchronization, characteristic consistency and traceability.

[0029] S2. Perform photovoltaic output stability analysis using electrical energy characteristic benchmarks to obtain the photovoltaic output state set; Step S2 is based on the electrical energy characteristic benchmark dataset output in step S1. The focus is on analyzing the output end (node) of photovoltaic modules. The stability of the voltage, current, and power characteristics of a light source as they change with illumination.

[0030] Step S2 in the photovoltaic output stability analysis process includes the following steps: Photovoltaic output feature extraction: From the dataset Extracting photovoltaic nodes voltage Current and power ; Power and light intensity A mapping relationship is established, and the light intensity is obtained through real-time data collection by sensors or historical data. Time series data according to time synchronization identifier Alignment ensures the analysis is reproducible.

[0031] Stability index calculation: Stability calculations include the following three categories of metrics: Output fluctuation range: ; For length is The average power within the time window; pass Measure the magnitude of short-term power fluctuations.

[0032] Output lag time: ; The peak time of light intensity within the current window, that is, the time node when the light intensity value identified in the light intensity measurement sequence within this window reaches the highest point; pass This indicates a delay in the photovoltaic output response.

[0033] Output continuity index: ; For indicator functions; The minimum effective output power threshold; pass Characterizes the continuity of power output.

[0034] Photovoltaic output state set determination: The output state is determined by combining the three types of indicators calculated in the previous process with a preset threshold. The preset threshold is: threshold The power fluctuation limit represents the maximum permissible fluctuation range of photovoltaic output power, used to determine the instantaneous stability of power output. It is obtained by recording the power output curve of the photovoltaic module under stable illumination using historical operating data under typical sunny conditions, and statistically analyzing the normal fluctuation range of power changes over multiple consecutive sampling periods. Through statistical analysis of this data (such as standard deviation or percentile statistics), the fluctuation range that will not be exceeded under most normal operating conditions is taken as the limit. ; threshold The output response hysteresis limit is used to define the maximum permissible response delay of photovoltaic modules to changes in light intensity. It is obtained by monitoring the response time difference of photovoltaic output power to changes in light intensity in a controlled experimental environment with varying light conditions (e.g., using an artificial light source to simulate sudden changes in light). The upper limit is then taken from the majority of the response time difference results obtained from multiple sets of samples. ; threshold To output the continuity index limit, which represents the minimum proportion of photovoltaic output power that can be continuously and effectively output within a specific time window; the method of obtaining it is to monitor the proportion of continuous effective output of photovoltaic module power under multiple different weather conditions (sunny, cloudy, overcast), and combine it with the energy acceptance characteristics of energy storage units in the power transmission link to determine the minimum continuous output ratio required to ensure the stable operation of the system. by , , There are three judgment conditions; When all three conditions are met, the system is considered highly stable, and the output is... ; The system is considered moderately stable and the output is determined only if one or two of the three conditions are met. ; If none of the three conditions are met, the system is classified as low stability, and the output is... ; Obtain the photovoltaic output state set corresponding to the time series. .

[0035] Traditional photovoltaic monitoring methods typically focus only on instantaneous power thresholds or single anomaly detection; Step S2 uses multi-index coupled analysis logic (fluctuation amplitude, response lag, output continuity) to form a time series state set, providing a systematic, dynamic, and reusable photovoltaic output state determination framework; The output is a structured state set, which can be directly used for energy storage analysis or subsequent state assessment, rather than a single-point anomaly alarm.

[0036] S3. Use the photovoltaic output state set to perform energy conversion consistency analysis of the energy storage unit and obtain the energy storage operation characteristic set; Step S3: Based on the photovoltaic output state set obtained in Step S2, establish a dynamic correlation model between the output characteristics of the photovoltaic end and the input energy of the energy storage end. Using the photovoltaic output state as the trigger condition, perform partitioned calculations on the energy input, power change and conversion efficiency of the energy storage unit to form an energy storage operation characteristic set, which is used to reflect the response law of the energy storage unit under different photovoltaic states.

[0037] Step S3, during the consistency analysis, includes the following process: Data correspondence: Based on the photovoltaic output state range obtained in step S2, extract the operating parameters of the energy storage unit for the same time period, including: energy storage unit voltage. Current and state of charge ; By employing time synchronization and sampling alignment techniques (using a mature timestamp synchronization mechanism and mean filtering interpolation technology), the photovoltaic output power is... With energy storage input power Establish a one-to-one correspondence.

[0038] Energy conversion analysis: Within each photovoltaic output state range, the ratio of photovoltaic input energy to energy storage absorption energy is calculated to analyze the consistency of energy transfer. The calculation method is as follows: Photovoltaic energy input: ; Energy storage and absorption: ; Therefore, the energy conversion consistency coefficient can be obtained: ; This coefficient reflects the proportion of photovoltaic energy absorbed and converted by the energy storage unit. A value close to 1 indicates high consistency in energy transfer. A significant deviation from 1 indicates low consistency.

[0039] Consistency determination: Within each photovoltaic output state range, the corresponding Values ​​and Consistency Threshold Set Comparison: when At that time, it was determined to be highly consistent; when When the time is right, it is determined to be consistent with the middle. when When the time is right, it is judged as low consistency; when When this occurs, it is determined to be an abnormal or inconsistent state of energy conversion.

[0040] Based on the determination results for each time interval, an energy storage operation feature set is generated: ; in: Time sampling point; : The energy conversion consistency coefficient at this point in time; : The consistency level at any given time (high consistency, medium consistency, low consistency).

[0041] The result is a structured dataset that can be directly used for trend extraction or operational status analysis in subsequent steps.

[0042] Existing energy storage operation analysis is usually based on static evaluation of the energy storage unit's own charge and discharge efficiency or energy loss curve, which fails to synchronously couple the dynamic output characteristics of the photovoltaic side with the energy conversion characteristics of the energy storage side. Step S3 introduces photovoltaic output state partitioning and establishes a time-synchronized energy conversion consistency analysis mechanism, which enables the assessment of the energy storage unit's operating status to have time-varying correlation and energy link consistency correlation, and realizes the identification of the whole process correlation of system energy flow.

[0043] S4. Use the energy storage operation feature set to perform a load power supply link health assessment to obtain a load power supply status set; Step S4 uses the energy storage operation feature set obtained in step S3. As input, a health status assessment of the load power supply link is performed, including the following process: Time series matching: For each time sampling point in the energy storage operation feature set Extract the consistency coefficient Consistency level and energy storage output power ; By using timestamp synchronization and linear interpolation techniques, the energy storage output power is aligned with the actual voltage and current at the load end. and This ensures that the energy storage output and load input at each sampling point are matched.

[0044] Energy transfer and matching analysis: Calculate the load power demand at each time point .

[0045] Calculate the load power matching rate based on the energy storage output power and the consistency coefficient: Energy storage consistency coefficient With energy storage output power Multiply to obtain the load power matching rate. ; Matching rate and load power The deviations are analyzed, and mature power quality indicators (such as voltage deviation percentage or power deviation ratio) are used to evaluate link stability.

[0046] Power supply health level assessment: Mapping match rate to health level Thresholds are set based on historical experience data or industry standards: High health: Match rate close to or higher than 95% Zhongjiankang: Matching rate between 80% and 95% Low health: Match rate below 80%.

[0047] Step S4 finally organizes the health assessment results for each time sampling point to obtain a structured set of load power supply states: ; in: Time sampling point; : Load terminal voltage; Load current; Load power matching rate; Power supply health level (high health, medium health, low health).

[0048] Dataset It is directly used as input to step S5 for further analysis of the impact of photovoltaic energy storage synergy on the load power supply link and identification of operational anomalies.

[0049] S5. Use the energy storage operation feature set and the load power supply status set to identify the overall system operation status and obtain the system operation status identifier set; Step S5, based on the energy storage operation feature set output in step S3 and the load power supply status set output in step S4, comprehensively identifies the overall operating status of the system. Through joint analysis of the two feature sets, a comprehensive judgment on the continuity of system-level energy transfer and the consistency of response is achieved.

[0050] Step S5 in the state recognition process includes the following steps: Time synchronization and feature matching: right and Time Index Perform synchronization; If the sampling intervals are inconsistent, they can be aligned using a moving average or time interpolation method.

[0051] Energy storage continuity assessment: in accordance with Sequence continuity index calculation: ; in The length of the sliding window; The smaller the value, the more stable and continuous the energy storage output.

[0052] Load response consistency analysis: Based on energy storage consistency level As a parameter of the health status of the energy storage side, combined with the load power matching rate Calculate the response consistency coefficient: ; in A linear piecewise model can be used to map the expected power based on the energy storage level.

[0053] System status level determination: Set system health threshold set ; according to and Overall assessment: High health status: and ; Medium health status: or ; Low health status: and .

[0054] Step S5 ultimately yields the system operating status identifier set: ; in, Energy storage continuity indicators; Response consistency metrics; System operating status level (high, medium, low health); This set provides the basic input for subsequent prediction of system health trends or intelligent regulation.

[0055] Existing system monitoring typically analyzes only the energy storage end or the load end independently, ignoring the dynamic characteristics of the coupling between the two.

[0056] Step S5 achieves dynamic health identification at the system level through bidirectional constraint analysis based on energy storage consistency level and load response characteristics. Unlike traditional static or single-domain assessment methods, it can more accurately reflect the overall operating status of the energy storage link.

[0057] S6. Determine the street light operating status result based on the system operating status identifier set; Step S6, in determining the street light's operating status, includes: Input data acquisition and preprocessing: The steps are based on the system operating status identifier set output in step S5. For input data, conventional processing methods such as data integrity checks, outlier removal, and time series smoothing are used to ensure the accuracy and stability of subsequent analyses.

[0058] State classification mapping: By assessing the system's operational status level The judgment results are categorized, and the street light operating status type is determined based on their corresponding relationships, including: when When the condition is in a high health state, the corresponding street light operation status is normal. when When the street light is in a medium-health state, the corresponding operating status is abnormal output. when When the condition is in a low health state, the corresponding street light operation status is abnormal energy storage or power supply.

[0059] Timing state smoothing: To avoid instability in state determination caused by short-term fluctuations, the mature time window moving average method is used to smooth the state results over several consecutive time points: When the proportion of high health status exceeds the threshold for consecutive occurrences within a set time window (e.g., 5 minutes), the period is considered to be in a stable operating state. If the percentage of systems in a low-healthy state exceeds a set threshold, the system is determined to have a persistent tendency to fail. This method belongs to the standard time series analysis technique in power system condition assessment, which can ensure the consistency of condition output results and engineering usability.

[0060] Overall status assessment: By using a mature state mapping algorithm, the comprehensive state results of each time period are converted into corresponding running labels, providing standardized output data for subsequent system interface display or remote monitoring platform calls.

[0061] The final result of the street light operation status is expressed as follows: ; in: Time sampling point; The street light operation status result at the corresponding time point, and its values ​​include: "Normal Operation" - The system power supply link is stable, and both photovoltaic and energy storage outputs meet the benchmark requirements; “Output Anomaly” – There are slight fluctuations in the consistency of the system’s photovoltaic output or energy storage, but the power supply is not interrupted; “Energy storage / power supply anomaly” – Energy storage consistency or load power supply health has significantly declined, and the system is unstable.

[0062] The results are directly used for monitoring system interface display, remote maintenance alarms, and operation and maintenance data recording, realizing a closed loop from data collection and analysis to status output.

[0063] Example 2: This embodiment provides an application scenario of a solar street light operation status monitoring method in a practical application: In a smart city lighting management system, several sets of solar streetlights are deployed. Each set of streetlights includes a photovoltaic power generation unit, an energy storage battery unit, a lighting load unit, and a monitoring terminal. The monitoring terminal has a built-in microprocessor and communication module, which is used to collect the operating data of each unit in real time, including the output voltage, current, and power of the photovoltaic panel, the charge and discharge capacity and SOC (state of charge) of the energy storage battery, and the supply voltage and power consumption of the lighting load.

[0064] During system operation, the monitoring terminal first establishes an operational characteristic benchmark based on a preset photovoltaic power transmission link model, which describes the energy transfer relationship between photovoltaic, energy storage, and load under normal operating conditions. Subsequently, the monitoring terminal uses real-time multi-source operational data as input to compare and analyze the continuity and stability of photovoltaic output, identify potential power fluctuations or energy loss anomalies in different time periods, and thus form a photovoltaic output state set.

[0065] During the period when abnormal photovoltaic output is detected, the system further analyzes the charging and discharging response of the energy storage unit within the corresponding period to determine the consistency of its energy conversion. If a mismatch is found between the energy storage response and the photovoltaic output, the system records the operating characteristics of the corresponding period and marks it as a potential abnormal state. Next, the system combines the power supply status on the load side to analyze the overall health of the power supply link, identifying whether there are any lighting instabilities or power supply fluctuations caused by abnormal energy transfer.

[0066] By comprehensively analyzing the photovoltaic output status set, energy storage operation characteristic set, and load power supply status set, the system generates a system operation status identifier set and determines the operation status of each solar street light, such as "normal operation," "minor abnormality," or "power supply abnormality." The monitoring terminal sends this result to the cloud management platform via a wireless communication module for centralized display and remote early warning.

[0067] When the cloud platform detects multiple minor abnormalities in a street light cluster in a certain area, it automatically issues a maintenance prompt, allowing maintenance personnel to specifically check the cleanliness of the photovoltaic panels, the health of the energy storage batteries, or the wiring connections, thereby achieving proactive preventative maintenance and efficient operation and maintenance management of the solar street light system.

[0068] Example 3: This embodiment also provides a computer device applicable to a solar street light operation status monitoring method, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the solar street light operation status monitoring method proposed in the above embodiment.

[0069] This embodiment also provides a storage medium storing a computer program, which, when executed by a processor, implements a solar street light operation status monitoring method as proposed in the above embodiments.

[0070] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0071] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0072] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0073] More specific examples (a non-exhaustive list) of computer-readable media include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0074] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0075] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for monitoring the operating status of solar streetlights, characterized in that, Includes the following steps: S1. Establish a characteristic monitoring benchmark for the power transmission link of solar street lights; S2. Perform photovoltaic output stability analysis using electrical energy characteristic benchmarks to obtain the photovoltaic output state set; S3. Use the photovoltaic output state set to perform energy conversion consistency analysis of the energy storage unit and obtain the energy storage operation characteristic set; S4. Use the energy storage operation feature set to perform a load power supply link health assessment to obtain a load power supply status set; S5. Use the energy storage operation feature set and the load power supply status set to identify the overall system operation status and obtain the system operation status identifier set; S6. Determine the street light operating status result based on the system operating status identifier set.

2. The method for monitoring the operating status of a solar street light according to claim 1, characterized in that, Step S1 monitors the basic characteristics of the solar street light under its operating status, and the monitoring process includes the following steps: Monitoring node identification and sampling channel establishment; Data synchronization and time base establishment; Signal filtering and timing alignment; Feature data extraction and structured processing.

3. The method for monitoring the operating status of a solar street light according to claim 2, characterized in that, The electrical energy characteristic benchmark dataset obtained in step S1 Its expression is: ； In the formula, : No. There are 10 monitoring nodes, of which: For the output end of photovoltaic modules, For energy storage input, For energy storage output, For load driving end; : No. Each sampling time point; :node In time The voltage value; :node In time The current value; :node In time The instantaneous power characteristics; :node In time The cumulative energy characteristics; :node The power and energy normalization results; : Time synchronization identifier, used to ensure time consistency of data across multiple nodes.

4. The method for monitoring the operating status of a solar street light according to claim 1, characterized in that, Step S2 is based on the electrical energy characteristic benchmark dataset output in step S1. The analysis focuses on the stability of the voltage, current, and power characteristics at the output of photovoltaic modules as a function of sunlight. Step S2 in the photovoltaic output stability analysis process includes the following steps: Photovoltaic output feature extraction; Stability index calculation; Determining the photovoltaic output state set.

5. The method for monitoring the operating status of a solar street light according to claim 4, characterized in that, In step S2, when extracting photovoltaic output features, the dataset is... Extracting photovoltaic nodes voltage Current and power ; Power and light intensity Establish mapping relationships; Time series data according to time synchronization identifier Alignment.

6. The method for monitoring the operating status of a solar street light according to claim 4, characterized in that, In step S2, when calculating the stability index, the calculation includes the following three categories of indexes: Output fluctuation amplitude ; Output lag time ; Output continuity index .

7. The method for monitoring the operating status of a solar street light according to claim 6, characterized in that, In step S2, when calculating the output fluctuation amplitude, the calculation formula is as follows: ； For length is The average power within the time window; pass Measure the magnitude of short-term power fluctuations.

8. The method for monitoring the operating status of a solar street light according to claim 6, characterized in that, In step S2, when calculating the output lag time, the calculation formula is as follows: ； The peak time of light intensity within the current window, that is, the time node when the light intensity value identified in the light intensity measurement sequence within this window reaches the highest point; pass This indicates a delay in the photovoltaic output response.

9. A method for monitoring the operating status of a solar street light according to claim 6, characterized in that, In step S2, when calculating the output continuity index, the calculation formula is as follows: ； For indicator functions; The minimum effective output power threshold; pass Characterizes the continuity of power output.

10. A method for monitoring the operating status of a solar street light according to claim 4, characterized in that, In step S2, when determining the photovoltaic output state set, the indicators obtained during the stability index calculation are combined with preset thresholds to determine the output state. The preset thresholds include power fluctuation amplitude limits. Output response hysteresis limit and output continuity index limit ; by , , There are three judgment conditions; When all three conditions are met, the system is considered highly stable, and the output is... ; The system is considered moderately stable and the output is determined only if one or two of the three conditions are met. ; If none of the three conditions are met, the system is classified as low stability, and the output is... ; Obtain the photovoltaic output state set corresponding to the time series. .

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