A cold roof photovoltaic in-situ diagnosis early warning method based on a thermal-electric trade-off index

Abstract

The present application relates to a kind of cold roof photovoltaic in-situ diagnosis early warning method based on thermal-electric trade-off index, the method refers to the synchronous acquisition of the photovoltaic module backsheet temperature and direct current input power of the cold roof photovoltaic system to be monitored and the control roof photovoltaic system, calculate relative power gain, module temperature difference and thermal-electric trade-off index TETI, calibrate reference interval in the initial stage of system operation;Current TETI is calculated in real time with sliding window in running stage and compared with reference interval, combine the change amount of module backsheet temperature difference relative to reference working condition to carry out root cause discrimination, output hierarchical maintenance instruction.The present application realizes the in-situ quantitative diagnosis of thermal-electric coupling state, significantly reduces the false alarm rate and the risk of missed detection, and is suitable for the operation state monitoring and accurate operation and maintenance of distributed roof photovoltaic project.

Description

Technical Field

[0001] This invention relates to the field of operation and maintenance technology of distributed photovoltaic systems, and in particular to an in-situ diagnostic and early warning method for cold roof photovoltaic systems based on the heat-electricity trade-off index. Background Technology

[0002] Current rooftop photovoltaic (PV) system operation monitoring primarily relies on two single dimensions: module temperature alarms or power generation monitoring. Overheating alarms are triggered when module temperature exceeds a threshold, and power anomaly alarms are triggered when power generation is lower than expected. However, for cold roof PV systems, the technology lies in using high-reflectivity roof coatings to enhance the back-side irradiance gain of bifacial modules. This gain and module temperature rise have an inherent thermo-electrical trade-off: higher coating reflectivity results in greater back-side gain, but also increases the amount of ambient heat radiation absorbed by the module, leading to higher operating temperatures. Existing technologies cannot assess the overall health of cold roof PV systems from the perspective of "how much power gain is gained per unit of temperature cost," resulting in the following engineering challenges: 1. High false alarm rate: During the high-temperature period in summer, the temperature rise of components may be due to the ambient temperature itself rather than a system failure. A single temperature alarm will cause a large number of invalid maintenance operations to be dispatched. 2. Risk of missed detection: When dust accumulation on the coating causes a decrease in reflectivity, the power gain shrinks, but the temperature change of the module backsheet is masked by the fluctuation of the ambient temperature, and performance degradation cannot be detected by single temperature monitoring. 3. Unknown root cause: Power loss may be due to inverter failure, hot spots on components, or coating aging, which cannot be distinguished in situ by existing technology. Summary of the Invention

[0003] The technical problem to be solved by this invention is to provide an in-situ diagnostic and early warning method for cold roof photovoltaic systems based on the heat-electricity trade-off index to reduce the false alarm rate and the risk of missed detection in operation and maintenance.

[0004] To address the aforementioned issues, this invention provides an in-situ diagnostic and early warning method for cold roof photovoltaic systems based on the heat-electricity trade-off index (TETI). The method involves simultaneously collecting the backsheet temperature of the photovoltaic modules and the DC input power of the monitored cold roof photovoltaic system and a control roof photovoltaic system. It calculates the relative power gain, module temperature difference, and TETI, and calibrates a baseline range during the initial system commissioning phase. During operation, a sliding window is used to calculate the current TETI in real time and compare it with the baseline range. Root cause analysis is performed based on the change in module backsheet temperature difference relative to the baseline operating conditions, and graded maintenance instructions are output.

[0005] The above-described in-situ diagnostic and early warning method for cold roof photovoltaic systems based on the heat-electricity trade-off index includes the following steps: (1) Temperature sensors were installed on the backsheet surfaces of the photovoltaic modules of the cold roof photovoltaic system to be monitored and the control roof photovoltaic system, respectively. Power acquisition devices were installed at the DC input terminals of the two systems to synchronously acquire the temperature of the backsheet of the modules of the cold roof photovoltaic system. T Cool-PV Compare the backsheet temperature of the rooftop photovoltaic system components. T PV Real-time input power of cold roof photovoltaic systems P Cool-PV and the real-time input power of the rooftop photovoltaic system. P PV ; (2) Connect the temperature sensor and the power acquisition device to the data processing terminal, perform quality control on the synchronously acquired data, and calculate the relative power gain Δ of the cold roof photovoltaic system relative to the control roof photovoltaic system. P / P PV Component temperature difference Δ T and the heat-electricity tradeoff index TETI: Δ P / P PV =( P Cool-PV - P PV ) / P PV ;Δ T = T Cool-PV - T PV ;TETI=(Δ P / P PV ) / Δ T ; In the formula: TETI is in units of % / ℃, and its physical meaning is the relative power gain of the cold roof photovoltaic system relative to the control roof photovoltaic system per unit temperature difference; (3) Under baseline operating conditions during the initial stage of system commissioning or after maintenance, collect effective samples from multiple sunny days during high-irradiance periods, statistically analyze the mean μ and standard deviation σ of the heat-electricity tradeoff index, and determine the baseline interval [TETI] based on the mean μ and standard deviation σ. min ,TETI max ]; among which TETI min =μ–k·σ,TETI max =μ+ k·σ, where k is a preset multiple; calculate and store the reference interval; (4) During system operation, the current TETI value is calculated in real time within a preset time window and compared with the benchmark interval. If the current TETI value is within the benchmark interval, the system's thermal-electric coupling state is determined to be normal. If the current TETI value is continuously lower than the benchmark lower limit and the duration exceeds the preset threshold, the system's thermal-electric coupling operation performance is determined to be abnormal. (5) When the thermal-electric coupling performance of the system is determined to be abnormal, the root cause is determined by combining the change in the component temperature difference between the cold roof photovoltaic system and the control roof photovoltaic system relative to the baseline operating condition: if the component temperature difference increases by more than the preset temperature difference threshold relative to the baseline operating condition, the abnormality is determined to be mainly due to thermal management factors; if the component temperature difference does not increase by more than the preset temperature difference threshold relative to the baseline operating condition, the abnormality is determined to be mainly due to electrical performance factors. ⑹ Output graded maintenance instructions based on the TETI attenuation magnitude and root cause determination results.

[0006] In step (1), the temperature sensor is a patch thermocouple temperature sensor or a platinum resistance temperature sensor, which is placed in the center area of ​​the photovoltaic module backsheet and at a distance of not less than 5 cm from the module frame.

[0007] In step (1), the power acquisition device is a DC power acquisition module with a communication protocol and a sampling frequency of not less than 1 Hz.

[0008] In step (2), before calculating the Thermal-Electric Tradeoff Index (TETI), the temperature and power data are first subjected to quality control and screening: samples with solar irradiance below the preset irradiance threshold are removed, samples with component backplane temperature below the preset temperature threshold are removed, and missing measurement records caused by communication abnormalities of the power acquisition unit are removed. Only valid samples from the midday period on sunny days are retained for TETI calculation.

[0009] The criteria for determining the baseline operating conditions in step (3) are: solar irradiance G ≥ preset irradiance threshold, ambient wind speed u ≤ 3 m / s, and cloud cover not exceeding 20%; the baseline interval [TETI] min ,TETI max Take the TETI mean plus or minus 1.5 times the standard deviation from at least 5 sunny days.

[0010] Step 4 also includes an extreme weather determination step during the system operation phase: when the environmental meteorological parameters are determined to be sandstorm weather or rainy weather and exceed the preset meteorological threshold, the TETI diagnostic algorithm is automatically paused and switched to extreme weather standby mode.

[0011] In step (5), the preset temperature difference threshold refers to the range determined by adding or subtracting 1.5 to 2.0 times the standard deviation of the statistical mean of the temperature difference ΔT of the module backsheet under the reference operating conditions; thermal management factors include the degradation of the reflective performance of the cold roof coating, the deterioration of the module heat dissipation conditions, or the hot spot failure of the module; electrical performance factors include the degradation of the inverter's maximum power point tracking efficiency, the degradation of the module's electrical performance, or the increase in the contact resistance of the DC cable.

[0012] In step (6), the hierarchical maintenance instructions are remotely pushed to the operation and maintenance terminal via the Internet of Things communication module.

[0013] In step (6), when the root cause determination result is a thermal management factor, a Level 1 warning is output. The Level 1 warning includes text information suggesting cleaning the roof coating, checking the ventilation gaps of the module backsheet, and troubleshooting hot spot faults in the module. When the root cause determination result is an electrical performance factor, a Level 2 warning is output. The Level 2 warning includes text information suggesting testing the inverter's maximum power point tracking efficiency and troubleshooting the degradation of the module's electrical performance. The urgency of the Level 1 and Level 2 warnings also refers to the TETI degradation range. When the degradation range is 20%~40%, a regular warning is output, and when the degradation range exceeds 40%, an emergency warning is output.

[0014] Compared with the prior art, the present invention has the following advantages: 1. Achieve in-situ quantitative diagnosis of thermo-electric coupling state.

[0015] Existing technologies only monitor a single dimension, such as component temperature or power generation, which cannot reflect the unique "backside gain-temperature loss" coupling relationship of cold roof photovoltaic systems. This invention constructs a thermal-electrical tradeoff index (TETI), which couples temperature costs and power gains into an efficiency indicator, enabling in-situ assessment of system-level health status.

[0016] 2. Significantly reduces the false alarm rate and missed detection risk in operation and maintenance.

[0017] Traditional temperature alarms generate numerous invalid warnings during the high-temperature period in summer (the ambient temperature itself causes the module to heat up). This invention, through the relativistic design of TETI (Thermal-Electrical Efficiency Trade-off), uses ambient temperature changes as a common background factor to offset them, only alarming for abnormal deviations in the "thermal-electrical efficiency trade-off," thus reducing the false alarm rate. For example, when dust accumulation on the coating causes a decrease in reflectivity, the power gain shrinks, but the change in the module's backsheet temperature is masked by ambient temperature fluctuations, making it undetectable by traditional temperature monitoring. However, TETI will decrease due to the shrinking power gain, effectively avoiding missed detections.

[0018] 3. Possesses the ability to determine the root cause of a fault in situ.

[0019] Existing technologies still require manual on-site troubleshooting after an alarm is triggered. This invention, through a joint judgment logic based on the temperature difference between the backsheets of the TETI-based cold roof photovoltaic system and the control roof photovoltaic system, can automatically distinguish between "thermal management deterioration" (coating / heat dissipation issues) and "electrical performance degradation" (inverter / module issues) at the data processing terminal, providing direct basis for operation and maintenance decisions.

[0020] 4. Low deployment cost and wide applicability.

[0021] This invention only requires the addition of one temperature sensor and one power acquisition device to each of the existing cold roof photovoltaic system and the control roof photovoltaic system. Without modifying the photovoltaic array structure, it can be connected to the existing data logger or power station data acquisition and monitoring control system, making it particularly suitable for the retrofitting of already operational distributed roof photovoltaic projects. Attached Figure Description

[0022] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0023] Figure 1 This is a schematic diagram of the hardware deployment and sensor arrangement of the cold roof photovoltaic system and the control roof photovoltaic system in this embodiment of the invention.

[0024] Figure 2 This is a flowchart of the calculation and benchmark calibration of the heat-electricity trade-off index (TETI) in this invention.

[0025] Figure 3 This is a schematic diagram of the TETI real-time diagnostic logic and hierarchical early warning decision tree in this invention.

[0026] Figure 4 A schematic diagram of the daily distribution and benchmark interval of TETI for the benchmark calibration period (March-April 2026) of the Lanzhou observation platform provided in this embodiment of the invention.

[0027] Figure 5 This is a schematic diagram illustrating the characteristic simulation of TETI response (a) and Cool-PV backsheet temperature response (b) under two typical failure modes provided by the present invention.

[0028] Figure 6 The images show the on-site verification of the operation and maintenance response and effect of the dust accumulation fault in the cold roof coating provided in the embodiments of the present invention. Among them: (a) shows the dust accumulation condition of the coating before cleaning on June 3, 2026 (temperature difference approaching the warning threshold); (b) shows the high-pressure water gun cleaning process on June 4; and (c) shows the recovery effect after cleaning. Detailed Implementation

[0029] A method for in-situ diagnosis and early warning of cold roof photovoltaic systems based on the heat-electricity trade-off index is proposed. This method involves simultaneously collecting the backsheet temperature of photovoltaic modules and DC input power of the monitored cold roof photovoltaic system and a control roof photovoltaic system, calculating the relative power gain, module temperature difference, and heat-electricity trade-off index (TETI), and calibrating a benchmark range during the initial stage of system commissioning. During the operation phase, the current TETI is calculated in real time using a sliding window and compared with the benchmark range. The root cause is determined by combining the change in module backsheet temperature difference relative to the benchmark operating condition, and graded maintenance instructions are output.

[0030] The specific process includes the following steps: (1) Temperature sensors were installed on the backsheet surfaces of the photovoltaic modules in both the Cool-PV system to be monitored and the control PV system, and power acquisition units were installed at the DC input terminals of both systems. The temperature sensors and power acquisition units were synchronously connected to a Campbell CR1000X data logger or a data acquisition terminal of equivalent performance, with a synchronous acquisition interval of 5 minutes. The backsheet temperature of the Cool-PV system modules was acquired synchronously. T Cool-PV Compare the backsheet temperature of the rooftop photovoltaic system components. T PV Real-time input power of cold roof photovoltaic systems P Cool-PV and the real-time input power of the rooftop photovoltaic system. P PV Record the corresponding environmental meteorological parameters (solar irradiance, wind speed, and wind direction) at the corresponding time.

[0031] The temperature sensor is either a surface-mount thermocouple or a PT100 platinum resistance temperature sensor, with a range of -40℃ to +120℃ and an accuracy of ±0.2℃. It is positioned in the center of the photovoltaic module backsheet, at least 5 cm from the module frame to avoid edge thermal bridging. The sensor probe is tightly attached to the backsheet using thermally conductive silicone grease. The power acquisition unit is a DC power acquisition module with a communication protocol and a sampling frequency of at least 1 Hz. Preferably, it is a DC power acquisition module with Modbus-RTU communication protocol, a range of 0~5 kW, and an accuracy of ±0.5%, connected to the data logger via an RS485 bus.

[0032] (2) Connect the temperature sensor and power acquisition unit to the data processing terminal and execute the following calculation process: ① Perform quality control on the synchronously collected data: First, quality control and screening are performed on temperature and power data: samples with solar irradiance below the preset irradiance threshold are removed (the temperature-power relationship is unstable under low irradiance conditions), samples with module backsheet temperature below the preset temperature threshold are removed (the linearity assumption of the temperature coefficient fails), and missing records due to communication anomalies of the power acquisition unit (communication timeout or numerical jumps) are removed. Only valid samples from the midday period on sunny days are retained for TETI calculation, as this period has a high solar altitude angle, is dominated by direct radiation, and has a stable spectral distribution, which can minimize weather fluctuation interference. The preset irradiance threshold and preset temperature threshold can be dynamically adjusted according to the local climate season and module operating characteristics. For example, in the spring / summer benchmark calibration in Lanzhou, the irradiance threshold is set to 600 W / m. 2 Temperature threshold: 25℃; in winter, it can be reduced to 400 W / m. 2 Temperatures of 10°C are maintained to ensure that valid samples are still available for TETI calculations during periods of low radiation.

[0033] ②Indicator Calculation: For samples that passed quality control, calculate the relative power gain Δ of the cold roof photovoltaic system relative to the control roof photovoltaic system. P / P PV Component temperature difference Δ T and the heat-electricity tradeoff index TETI: Δ P / P PV =( P Cool-PV - P PV ) / P PV ;Δ T = T Cool-PV - T PV ;TETI=(Δ P / P PV ) / Δ T ; In the formula: TETI is in units of % / ℃, and its physical meaning is the relative power gain of the cold roof photovoltaic system relative to the control roof photovoltaic system per unit temperature difference.

[0034] (3) Under the baseline operating conditions during the initial stage of system commissioning or after maintenance, collect valid samples from multiple sunny days during high-irradiance periods. The criteria for determining the baseline operating conditions are: solar irradiance G ≥ preset irradiance threshold, ambient wind speed u ≤ 3 m / s, and cloud cover not exceeding 20%. Calculate the TETI for samples that meet the baseline conditions, statistically analyze the mean μ and standard deviation σ of the heat-electricity tradeoff index TETI, and determine the baseline interval [TETI] based on the mean μ and standard deviation σ.min ,TETI max ]; among which TETI min =μ–k·σ,TETI max =μ + k·σ, where k is a preset multiple, which can take values ​​from 1.0 to 2.0, preferably 1.5; calculate and store the benchmark interval in the data processing terminal as a comparison benchmark for real-time diagnosis during the operation phase, such as Figure 2 As shown.

[0035] Wherein: the benchmark interval [TETI] min ,TETI max The mean of TETI data from at least 5 sunny days is taken plus or minus 1.5 times the standard deviation. This interval covers approximately 87% of the normal operating condition samples, taking into account both sensitivity and stability.

[0036] When k = 1.5, [TETI min TETI max ] = [μ - 1.5σ, μ + 1.5σ] (4) During system operation, the data processing terminal calculates the current TETI value in real time within a preset time window and compares it with the baseline interval, such as... Figure 3 As shown: If the current TETI value is within the baseline range, the system's thermal-electric coupling is considered normal, and no intervention is required. If the current TETI value is continuously below the baseline lower limit and the duration exceeds the preset threshold, the system's thermal-electric coupling performance is considered abnormal.

[0037] The preferred preset time window is a sliding window of 5 to 15 minutes.

[0038] The system operation phase also includes an extreme weather detection step: when environmental meteorological parameters indicate dusty or rainy weather and exceed preset meteorological thresholds, the TETI diagnostic algorithm is automatically paused and switched to extreme weather standby mode to avoid misjudgments caused by drastic changes in the weather background. For example, in Lanzhou, the dusty weather threshold is set as visibility <1 km and PM10 concentration >500 μg / m³. 3 The threshold for rainfall is precipitation >0.1 mm / h.

[0039] (5) When the system's thermo-electric coupling performance is determined to be abnormal, the root cause should be determined by combining the change in the component temperature difference between the cold roof photovoltaic system and the control roof photovoltaic system relative to the baseline operating conditions. Figure 3 As shown: If the temperature difference of the components increases beyond the preset temperature difference threshold relative to the baseline operating condition, the anomaly is determined to be mainly due to thermal management factors; if the temperature difference of the components does not increase beyond the preset temperature difference threshold relative to the baseline operating condition, the anomaly is determined to be mainly due to electrical performance factors.

[0040] Among them, the preset temperature difference threshold refers to the range determined by adding or subtracting 1.5 to 2.0 times the standard deviation of the statistical mean of the temperature difference ΔT on the back panel of the component under the reference operating conditions.

[0041] Thermal management factors include deterioration of the reflectivity of the cold roof coating, deterioration of module heat dissipation conditions, or hot spot failure of the module; electrical performance factors include degradation of the inverter's maximum power point tracking efficiency, deterioration of module electrical performance, or increased contact resistance of DC cables.

[0042] To further illustrate the technical principles of the root cause identification mechanism, conceptual simulations are conducted based on the physical characteristics of two typical fault modes: coating dust accumulation degradation (thermal management type) and inverter efficiency degradation (electrical performance type). Figure 5 As shown. This deduction is based on the following physical assumptions: coating dust accumulation and degradation lead to increased module backsheet temperature and decreased power gain; inverter efficiency degradation leads to decreased power gain while the backsheet temperature remains normal. Figure 5 It can be observed that: under normal operating conditions, TETI remains stable within the baseline range; as the coating degrades due to dust accumulation, TETI gradually decreases to below the lower limit; and as the inverter efficiency degrades, TETI drops sharply (see [reference]). Figure 5 (a)). Coating dust accumulation degradation is accompanied by a significant increase in peak module backsheet temperature compared to the same period in previous years; inverter efficiency degradation is accompanied by normal backsheet temperature (see [reference]). Figure 5 (b)).

[0043] (6) Output graded maintenance instructions based on the TETI attenuation magnitude and root cause determination results, such as... Figure 3 As shown, tiered maintenance instructions are remotely pushed to the maintenance terminal (PC workstation or mobile terminal APP) via the IoT communication module.

[0044] When the root cause is identified as a thermal management factor, a Level 1 warning is issued. The Level 1 warning includes text messages suggesting cleaning the roof coating, checking the ventilation gaps of the component back panel, and troubleshooting hot spot faults in the component.

[0045] When the root cause is determined to be an electrical performance factor, a level 2 warning is output. The level 2 warning includes text information suggesting that the inverter's maximum power point tracking efficiency be checked and that the electrical performance of the components be investigated.

[0046] Specifically, the urgency levels of Level 1 and Level 2 warnings are also determined by the TETI attenuation rate. When the attenuation rate is between 20% and 40%, a regular warning is issued, prompting maintenance personnel to handle the situation according to the planned schedule. When the attenuation rate exceeds 40%, an emergency warning is issued, prompting maintenance personnel to take immediate on-site action.

[0047] Level 1 Warning (Deteriorating Thermal Management): Current TETI is continuously lower than TETI minThe duration exceeds 30 minutes, accompanied by a significant increase in the temperature difference ΔT between the Cool-PV module backsheet and the average temperature of PV modules operating at the same time, exceeding the preset temperature difference threshold. This indicates that the Cool-PV system experiences an increased temperature cost without a corresponding increase in power gain. The cause of this deterioration is attributed to factors such as decreased reflectivity of the cool roof coating (dust accumulation / aging), blocked ventilation gaps in the module backsheet (dust / bird droppings obstructing heat dissipation channels), or hot spot malfunctions in the module leading to localized heat dissipation deterioration. Level 1 Warning Push Notification (Regular / Emergency): [Level 1 Warning] TETI decreases by XX%, Cool-PV module temperature rises abnormally. Recommendations: ① Check the dust accumulation on the roof coating; clean with a high-pressure water gun if necessary; ② Check for blocked ventilation gaps in the module backsheet; ③ Use an infrared thermal imager to inspect for hot spots on the module.

[0048] Level 2 Warning (Electrical Performance Degradation): The current TETI is continuously lower than the TETI. min The duration exceeded 30 minutes, but the temperature difference between the Cool-PV and PV modules did not increase beyond the preset temperature difference threshold compared to the baseline operating condition. This mode indicates that the temperature environment has not deteriorated, but power gain has decreased. The deterioration is caused by degradation of the inverter's maximum power point tracking efficiency, degradation of module electrical performance (such as potential-induced degradation), or increased DC cable contact resistance. Level 2 warning push notification (regular / emergency): [Level 2 Warning] TETI degradation XX%, module temperature normal. Recommendations: ① Check the inverter's maximum power point tracking efficiency and DC input voltage-current matching; ② Investigate module electrical performance degradation.

[0049] Maintenance personnel, based on the warning level, root cause analysis results, and urgency, carry the appropriate tools to the site to achieve precise maintenance and avoid ineffective inspections.

[0050] Example An 18-meter-high rooftop of a building in the central urban area of ​​Lanzhou (35.87°N, 103.80°E) was selected as the experimental site. One Cool-PV system (roof coated with a white acrylic high-reflectivity cold roof coating, measured albedo 0.57) and one control rooftop photovoltaic (PV) system (bare roof, measured albedo 0.13) were deployed. Figure 1 As shown. Both systems use CH-450WP bifacial monocrystalline silicon modules, with 6 modules connected in series in each system, for a total installed capacity of 2.7 kW, a fixed tilt angle of 18°, and an azimuth angle of 180° (due south).

[0051] One PT100 temperature sensor is installed at the center of the backplane of each component group, and one DC power acquisition module is installed at the DC input terminal of each component group. The module is connected to a Campbell CR1000X data logger with a sampling interval of 5 minutes.

[0052] like Figure 4As shown, the benchmark periodically selects six sunny days: March 10, 11, 24, April 2, 3, and 4, 2026. The solar irradiance (G) is extracted based on local time from 12:30 to 15:00 and ≥600 W / m². 2 For samples with wind speed u ≤ 3 m / s, after quality control (backsheet temperature ≥ 25℃, ΔT > 0) and removal of outliers from the box plot, 58 valid samples were obtained. The calculated results are: 6-day average backsheet temperature difference between Cool-PV and PV modules ΔT = 2.83℃; 6-day average power gain of Cool-PV relative to PV ΔP / P PV =2.71%; TETI mean μ = 1.09% / ℃; TETI standard deviation σ = 1.72% / ℃; the baseline interval [TETI] is determined by adding or subtracting k times the standard deviation (k = 1.5) from the mean μ. min TETI max = [-1.49, 3.67]% / ℃.

[0053] This baseline range serves as the basis for subsequent operational diagnostics and is stored in the non-volatile memory of the data processing terminal.

[0054] In mid-April 2026, a severe sandstorm occurred in the area. Meteorological station monitoring showed that the peak PM10 concentration reached 1800 μg / m³. 3 Visibility <500 m, solar irradiance from 800 W / m 2 The temperature dropped sharply to 200 W / m 2 the following.

[0055] After receiving data from the weather station, the data processing terminal automatically determines that it is experiencing extreme sandstorm weather, suspends the TETI diagnostic algorithm, and enters standby mode. No warnings are issued during the sandstorm to avoid misjudgments under drastic weather conditions. On the second sunny day after the sandstorm ends, the system automatically resumes diagnostics, with a TETI value of 1.91% / ℃, within the baseline range, confirming that the system was not affected by the sandstorm.

[0056] In early June 2026, the system monitored an increasing temperature difference between the Cool-PV and PV modules for several consecutive days. On the afternoon of June 3rd (12:30-15:00), the average temperature difference reached 3.44℃, with a maximum difference of 5.29℃. This approached but did not reach the Level 1 warning threshold (1.5-2 times the standard deviation of the baseline temperature difference of 1.72℃, i.e., 2.6-3.4℃, corresponding to an absolute temperature difference of approximately 5.8℃), and the power gain decreased compared to the baseline operating condition. The data processing terminal recorded this trend and alerted maintenance personnel, but no tiered warning was triggered.

[0057] On June 5, maintenance personnel conducted an on-site inspection and found that the surface of the cold roof coating beneath the components was covered with a crust of sand and dust (see [link]). Figure 6 (a) was then used to clean the roof coating with a high-pressure water gun (see [reference]). Figure 6 (b)). The coating surface was restored after cleaning (see...). Figure 6 (c)).

[0058] On June 6, the system resumed stable operation. The average temperature difference dropped to 1.22℃ in the afternoon, with the maximum temperature difference being only 2.31℃. The TETI was within the baseline range, confirming that the system's thermo-electric coupling state had returned to normal.

[0059] The technical solution provided by this invention has been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this invention. It should be noted that those skilled in the art can make several improvements and modifications to this invention without departing from its principles. For example, combining the TETI index with machine learning algorithms to achieve adaptive threshold adjustment, or extending this method to the performance diagnosis of photovoltaic-green roof coupling systems, these improvements and modifications also fall within the protection scope of the claims of this invention.

Claims

1. A method for in-situ diagnosis and early warning of cold roof photovoltaic systems based on the heat-electricity trade-off index, characterized in that: This method involves simultaneously collecting the backsheet temperature of photovoltaic modules and DC input power of the monitored cold roof photovoltaic system and the control roof photovoltaic system, calculating the relative power gain, module temperature difference, and thermal-electric tradeoff index TETI, calibrating the baseline range at the initial stage of system commissioning, and calculating the current TETI in real time using a sliding window during the operation phase and comparing it with the baseline range. The root cause is determined by combining the change in module backsheet temperature difference relative to the baseline operating condition, and the graded maintenance instructions are output.

2. The in-situ diagnostic and early warning method for cold roof photovoltaic systems based on the heat-electricity trade-off index as described in claim 1, comprising the following steps: (1) Temperature sensors were installed on the backsheet surfaces of the photovoltaic modules of the cold roof photovoltaic system to be monitored and the control roof photovoltaic system, respectively. Power acquisition devices were installed at the DC input terminals of the two systems to synchronously acquire the temperature of the backsheet of the modules of the cold roof photovoltaic system. T Cool-PV Compare the backsheet temperature of the rooftop photovoltaic system components. T PV Real-time input power of cold roof photovoltaic systems P Cool-PV and the real-time input power of the rooftop photovoltaic system. P PV ; (2) Connect the temperature sensor and the power acquisition device to the data processing terminal, perform quality control on the synchronously acquired data, and calculate the relative power gain Δ of the cold roof photovoltaic system relative to the control roof photovoltaic system. P / P PV Component temperature difference Δ T and the heat-electricity tradeoff index TETI: D P / P PV =( P Cool-PV - P PV ) / P PV ;D T = T Cool-PV - T PV ;TETI=(D P / P PV ) / D T ; In the formula: TETI is in units of % / ℃, and its physical meaning is the relative power gain of the cold roof photovoltaic system relative to the control roof photovoltaic system per unit temperature difference; (3) Under baseline operating conditions during the initial stage of system commissioning or after maintenance, collect effective samples from multiple sunny days during high-irradiance periods, statistically analyze the mean μ and standard deviation σ of the heat-electricity tradeoff index, and determine the baseline interval [TETI] based on the mean μ and standard deviation σ. min ,TETI max ]; among which TETI min =μ–k·σ,TETI max =μ+ k·σ, where k is a preset multiple; calculate and store the reference interval; (4) During system operation, the current TETI value is calculated in real time within a preset time window and compared with the benchmark interval; If the current TETI value is within the reference range, the system's thermo-electric coupling state is considered normal. If the current TETI value is continuously lower than the baseline lower limit and the duration exceeds the preset threshold, the system's thermal-electric coupling performance is determined to be abnormal. (5) When the thermal-electric coupling performance of the system is determined to be abnormal, the root cause is determined by combining the change in the component temperature difference between the cold roof photovoltaic system and the control roof photovoltaic system relative to the baseline operating condition: if the component temperature difference increases by more than the preset temperature difference threshold relative to the baseline operating condition, the abnormality is determined to be mainly due to thermal management factors; if the component temperature difference does not increase by more than the preset temperature difference threshold relative to the baseline operating condition, the abnormality is determined to be mainly due to electrical performance factors. ⑹ Output graded maintenance instructions based on the TETI attenuation magnitude and root cause determination results.

3. The in-situ diagnostic and early warning method for cold roof photovoltaic systems based on the heat-electricity trade-off index as described in claim 2, characterized in that: In step (1), the temperature sensor is a patch thermocouple temperature sensor or a platinum resistance temperature sensor, which is placed in the center area of ​​the photovoltaic module backsheet and at a distance of not less than 5 cm from the module frame.

4. The in-situ diagnostic and early warning method for cold roof photovoltaic systems based on the heat-electricity trade-off index as described in claim 2, characterized in that: In step (1), the power acquisition device is a DC power acquisition module with a communication protocol and a sampling frequency of not less than 1Hz.

5. The in-situ diagnostic and early warning method for cold roof photovoltaic systems based on the heat-electricity trade-off index as described in claim 2, characterized in that: In step (2), before calculating the Thermal-Electric Tradeoff Index (TETI), the temperature and power data are first subjected to quality control and screening: samples with solar irradiance below the preset irradiance threshold are removed, samples with component backplane temperature below the preset temperature threshold are removed, and missing measurement records caused by communication abnormalities of the power acquisition unit are removed. Only valid samples from the midday period on sunny days are retained for TETI calculation.

6. The in-situ diagnostic and early warning method for cold roof photovoltaic systems based on the heat-electricity trade-off index as described in claim 2, characterized in that: The criteria for determining the baseline operating conditions in step (3) are: solar irradiance G ≥ preset irradiance threshold, ambient wind speed u ≤ 3 m / s, and cloud cover not exceeding 20%. Reference range [TETI] min ,TETI max Take the TETI mean plus or minus 1.5 times the standard deviation from at least 5 sunny days.

7. The in-situ diagnostic and early warning method for cold roof photovoltaic systems based on the heat-electricity trade-off index as described in claim 2, characterized in that: Step 4 also includes an extreme weather determination step during the system operation phase: when the environmental meteorological parameters are determined to be sandstorm weather or rainy weather and exceed the preset meteorological threshold, the TETI diagnostic algorithm is automatically paused and switched to extreme weather standby mode.

8. The in-situ diagnostic and early warning method for cold roof photovoltaic systems based on the heat-electricity trade-off index as described in claim 2, characterized in that: In step (5), the preset temperature difference threshold refers to the range determined by adding or subtracting 1.5 to 2.0 times the standard deviation from the statistical mean of the temperature difference ΔT on the back panel of the component under the reference operating conditions. Thermal management factors include deterioration of the reflectivity of the cold roof coating, deterioration of module heat dissipation conditions, or hot spot failure of the module; electrical performance factors include degradation of the inverter's maximum power point tracking efficiency, deterioration of module electrical performance, or increased contact resistance of DC cables.

9. The in-situ diagnostic and early warning method for cold roof photovoltaic systems based on the heat-electricity trade-off index as described in claim 2, characterized in that: In step (6), the hierarchical maintenance instructions are remotely pushed to the operation and maintenance terminal via the Internet of Things communication module.

10. The in-situ diagnostic and early warning method for cold roof photovoltaic systems based on the heat-electricity trade-off index as described in claim 2, characterized in that: In step (6), when the root cause determination result is a thermal management factor, a first-level warning is output; the first-level warning includes text information suggesting cleaning the roof coating, checking the ventilation gaps of the component back panel, and troubleshooting hot spot faults in the component; when the root cause determination result is an electrical performance factor, a second-level warning is output. The secondary warning includes text information suggesting the detection of the inverter's maximum power point tracking efficiency and the investigation of component electrical performance degradation; wherein: the urgency of the primary warning and the secondary warning also refers to the TETI degradation range; when the degradation range is 20%~40%, a regular warning is output, and when the degradation range exceeds 40%, an emergency warning is output.

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