Fire diagnosis system using insulation resistance

Abstract

The present invention relates to a fire diagnosis system and, more specifically, to a fire diagnosis system using insulation resistance, which while measuring insulation resistance by applying a voltage to a string for a predetermined time, calculates a kick index indicating a degree of change for each unit time, so as to enable accurate diagnosis of abnormality in the insulation resistance, and causes a fire risk alert to be generated according to an abnormal state of the insulation resistance so as to enable a prompt response to a fire risk.

Description

Fire diagnosis system using insulation resistance

[0001] The present invention relates to a fire diagnosis system, and more specifically, to a fire diagnosis system using insulation resistance that enables accurate diagnosis of insulation resistance abnormalities by applying voltage to a string for a certain period of time to measure insulation resistance and calculating a kick index indicating the degree of change per unit time, and enables rapid response to fire hazards by generating a fire hazard warning according to the insulation resistance abnormality state.

[0002] Solar power generation, a sector of renewable energy, has recently seen a surge in demand due to its numerous advantages, and technologies aimed at increasing generation efficiency have also advanced significantly. In particular, solar power generation devices are currently being installed in various forms, including on building rooftops and on water, as well as in Building Integrated Photovoltaics (BIPV) systems that are integrated with the building itself.

[0003] Solar power generation devices must be constantly exposed to the sun for high efficiency and pose a high fire risk due to the heat generated by power generation; in particular, the decrease in insulation resistance is identified as a major cause of fire.

[0004] Therefore, it is necessary to frequently measure and check the insulation resistance of a photovoltaic power generation device. To this end, as shown in the patent document below, a technician is required to periodically visit the site to measure the insulation resistance and check whether it exceeds a standard value.

[0005] However, in such cases, not only is there the inconvenience of requiring periodic visits by technicians, but since insulation resistance is affected by environmental factors such as humidity, an accurate diagnosis of the insulation resistance status cannot be achieved by simply comparing it to a standard value.

[0006] Furthermore, if the insulation resistance drops below the standard value, it is considered to be already exposed to a fire risk; there is a problem in that the gradual deterioration of insulation resistance makes it impossible to prevent a fire from occurring.

[0007] (Patent Document) Registered Patent Publication No. 10-1529476 (Registered June 11, 2015) "Insulation Resistance Monitoring System for Solar Module Strings"

[0008] The present invention has been devised to solve the above-mentioned problems,

[0009] The present invention aims to provide a fire diagnosis system that enables accurate diagnosis of insulation resistance abnormalities by applying voltage to a string for a certain period of time to measure insulation resistance and calculating a kick index indicating the degree of change per unit time, and enables rapid response to fire hazards by generating a fire hazard warning according to the insulation resistance abnormality state.

[0010] The present invention aims to provide a fire diagnosis system that enables more accurate identification of the insulation resistance degradation state by calculating the kick index while gradually changing the voltage applied over a certain period of time.

[0011] The present invention aims to provide a fire diagnosis system that enables efficient diagnosis work by diagnosing the imbalance between photovoltaic modules in a string and the cause of the imbalance, and by diagnosing the insulation resistance condition when an imbalance caused by a decrease in insulation resistance is suspected.

[0012] The present invention aims to provide a fire diagnosis system that enables accurate diagnosis of an unbalanced state by diagnosing the unbalanced state of the solar module output according to the degree of voltage imbalance and voltage fluctuation between modules in a string.

[0013] The present invention aims to provide a fire diagnosis system that can detect a voltage imbalance in a simple way without measuring the voltage of all solar modules by diagnosing a voltage imbalance by comparing the voltage of a specific module multiplied by the number of modules with the voltage of the entire string.

[0014] The present invention aims to provide a fire diagnosis system that calculates an imbalance index indicating the degree of output imbalance between modules using the degree of voltage imbalance and voltage fluctuation within the string, and detects the cause of the imbalance state according to the imbalance index, thereby enabling a rapid and accurate response to the imbalance state.

[0015] The present invention is implemented by an embodiment having the following configuration to achieve the aforementioned objective.

[0016] According to one embodiment of the present invention, a fire diagnosis system using insulation resistance according to the present invention includes a fire risk diagnosis unit that precisely diagnoses whether the insulation resistance of a string has decreased and notifies of a fire risk, wherein the fire risk diagnosis unit includes a voltage application module that applies voltage to the string for a certain period of time, an insulation resistance measurement module that measures the insulation resistance at unit time intervals according to the voltage application, a kick index calculation module that calculates a kick index indicating the degree of change of insulation resistance per unit time for a certain period of time, an abnormality detection module that determines an abnormality in insulation resistance when the calculated kick index exceeds a set reference value, a fire risk judgment module that determines a fire risk when the abnormal state of insulation resistance persists for a set period of time or when the degree of increase of the kick index exceeds a set value, and a fire warning module that generates a warning signal when a fire risk is determined.

[0017] According to another embodiment of the present invention, in a fire diagnosis system using insulation resistance according to the present invention, the fire risk diagnosis unit is characterized by including a diagnosis timing setting module for setting the diagnosis timing of the insulation resistance state.

[0018] According to another embodiment of the present invention, in a fire diagnosis system using insulation resistance according to the present invention, the kick index calculation module is characterized by calculating the time kick index by the following mathematical formula 1.

[0019] (Mathematical Formula 1)

[0020]

[0021] According to another embodiment of the present invention, a fire diagnosis system using insulation resistance according to the present invention is characterized by including a voltage adjustment module that enables the measurement of insulation resistance while varying the voltage in steps.

[0022] According to another embodiment of the present invention, in a fire diagnosis system using insulation resistance according to the present invention, the kick index calculation module is characterized by calculating the voltage kick index by the following mathematical formula 2.

[0023] (Mathematical Formula 2)

[0024]

[0025] According to another embodiment of the present invention, a fire diagnosis system using insulation resistance according to the present invention includes a module imbalance diagnosis unit that diagnoses imbalance between photovoltaic modules in a string, and the fire risk diagnosis unit is characterized by performing an insulation resistance diagnosis when the imbalance is diagnosed as a decrease in insulation resistance by the module imbalance diagnosis unit.

[0026] According to another embodiment of the present invention, in a fire diagnosis system using insulation resistance according to the present invention, the module imbalance diagnosis unit comprises a voltage imbalance calculation unit that calculates the degree of imbalance regarding voltage between modules constituting a string, a fluctuation abnormality calculation unit that calculates the degree of abnormality according to voltage and current fluctuations of the string, and an imbalance detection unit that detects imbalance between modules of the string according to the degree of voltage imbalance and the degree of fluctuation abnormality.

[0027] According to another embodiment of the present invention, in a fire diagnosis system using insulation resistance according to the present invention, the voltage imbalance calculation unit comprises a string voltage measurement module that measures the voltage of power output from a string, a module voltage measurement module that measures the voltage at one specific module within the string, and a voltage imbalance coefficient calculation module that calculates a voltage imbalance coefficient indicating the degree of voltage imbalance between modules by subtracting the value obtained by multiplying the number of solar modules included in the string by the voltage of the specific module from the string voltage.

[0028] According to another embodiment of the present invention, in a fire diagnosis system using insulation resistance according to the present invention, the voltage imbalance calculation unit comprises a voltage imbalance diagnosis module that compares a voltage imbalance coefficient calculated by the imbalance coefficient calculation module with a reference value, diagnoses a voltage imbalance between modules when the value exceeds the reference value, and executes a fluctuation abnormality calculation unit.

[0029] According to another embodiment of the present invention, in a fire diagnosis system using insulation resistance according to the present invention, the fluctuation abnormality calculation unit comprises a voltage measurement module that measures a voltage output from a string for a certain period of time, a current measurement module that measures a current output from a string for a certain period of time, and a power fluctuation coefficient calculation module that calculates a power fluctuation coefficient indicating the degree of fluctuation of voltage and current by calculating the value of the ratio of voltage change amount to current change amount for the ratio of voltage to current per unit time for a certain period of time and the average value.

[0030] According to another embodiment of the present invention, in a fire diagnosis system using insulation resistance according to the present invention, the fluctuation abnormality calculation unit is characterized by including a coefficient adjustment module that increases the scale while changing the standard for the normal state of the power fluctuation coefficient to 0.

[0031] According to another embodiment of the present invention, in a fire diagnosis system using insulation resistance according to the present invention, the coefficient adjustment module is characterized by adjusting the power fluctuation coefficient according to Equation 3 to calculate the final power fluctuation coefficient.

[0032] (Mathematical Formula 3)

[0033] Pf = (1-Pd)*10

[0034] (Here, Pf is the adjusted power variation coefficient, and Pd is the initial power variation coefficient)

[0035] According to another embodiment of the present invention, in a fire diagnosis system using insulation resistance according to the present invention, the imbalance detection unit comprises a voltage imbalance coefficient loading module that retrieves a voltage imbalance coefficient, a power fluctuation coefficient loading module that retrieves a power fluctuation coefficient, an imbalance index calculation module that calculates an imbalance index representing the degree of imbalance in output between modules by multiplying the voltage imbalance coefficient and the power fluctuation coefficient, and an abnormal information diagnosis module that diagnoses an abnormal state due to output imbalance between modules of a string according to the calculated imbalance index.

[0036] According to another embodiment of the present invention, in a fire diagnosis system using insulation resistance according to the present invention, the abnormal information diagnosis module is characterized by diagnosing module damage, shading, or contamination when the imbalance index is positive, and diagnosing PID, cell cracking, or insulation resistance degradation when the imbalance index is negative.

[0037] The present invention can achieve the following effects through the combination and usage relationship of the embodiments described above and the configuration described below.

[0038] The present invention has the effect of enabling accurate diagnosis of insulation resistance abnormalities by applying voltage to a string for a certain period of time to measure insulation resistance and calculating a kick index that indicates the degree of change per unit time, and enabling rapid response to fire hazards by generating a fire hazard warning according to the insulation resistance abnormality state.

[0039] The present invention has the effect of enabling a more accurate determination of the insulation resistance degradation state by allowing the calculation of the kick index to be performed while gradually changing the voltage applied for a certain period of time.

[0040] The present invention has the effect of enabling efficient diagnostic work by diagnosing the unbalanced state between photovoltaic modules in a string and the cause of the unbalanced state, and by diagnosing the insulation resistance state when an unbalanced state caused by a decrease in insulation resistance is suspected.

[0041] The present invention has the effect of enabling accurate diagnosis of the unbalanced state by diagnosing the unbalanced state of the solar module output according to the degree of voltage imbalance and voltage fluctuation between modules in the string.

[0042] The present invention has the effect of enabling the detection of a voltage imbalance state in a simple way without measuring the voltage of all solar modules by diagnosing the voltage imbalance state by comparing the value obtained by multiplying the voltage of a specific module by the number of modules with the voltage of the entire string.

[0043] The present invention has the effect of enabling a rapid and accurate response to an unbalanced state by calculating an unbalance index that indicates the degree of output unbalance between modules using the degree of voltage unbalance and voltage fluctuation within the string, and by detecting the cause of the unbalanced state according to the unbalance index.

[0044] FIG. 1 is a block diagram showing the configuration of a fire diagnosis system using insulation resistance according to an embodiment of the present invention.

[0045] Figure 2 is a block diagram showing the configuration of the fire risk diagnosis unit.

[0046] Figure 3 is a graph showing an example of insulation resistance measurement.

[0047] Figure 4 is a block diagram showing the configuration of the module imbalance diagnosis unit.

[0048] Figure 5 is a reference diagram showing an example of voltage measurement by the voltage imbalance calculation unit.

[0049] Figure 6 is a graph showing an example of voltage change according to string condition.

[0050] Figure 7 is a reference diagram showing the operating point on the IV curve according to the unbalance index.

[0051] FIG. 8 is a block diagram showing the configuration of the power generation prediction unit.

[0052] FIG. 9 is a block diagram showing the configuration of the fault diagnosis unit

[0053] FIG. 10 is a reference diagram showing an IV graph used by the fault diagnosis unit.

[0054] Explanation of symbols used in drawings

[0055] 1: Fire Hazard Diagnosis Unit 2: Module Imbalance Diagnosis Unit

[0056] 21: Voltage Imbalance Calculation Unit 22: Fluctuation Anomaly Calculation Unit

[0057] 23: Imbalance detection unit 3: Power generation prediction unit

[0058] 4: Power generation measurement unit 5: Fault diagnosis unit

[0059] Preferred embodiments of a fire diagnosis system using insulation resistance according to the present invention will be described in detail below with reference to the attached drawings. In describing the present invention below, if it is determined that a detailed description of known functions or configurations may unnecessarily obscure the essence of the present invention, such detailed description will be omitted. Throughout the specification, when a part is described as "including" a certain component, this means that, unless specifically stated otherwise, it does not exclude other components but may include additional components. Furthermore, terms such as "...part," "...module," etc., described in the specification refer to a unit that processes at least one function or operation, and this may be implemented in hardware, software, or a combination of hardware and software.

[0060] A fire diagnosis system using insulation resistance according to one embodiment of the present invention is described with reference to FIGS. 1 to 10. The fire diagnosis system using insulation resistance includes a fire risk diagnosis unit (1) that precisely diagnoses whether the insulation resistance of a string has decreased and notifies of a fire risk, a module imbalance diagnosis unit (2) that diagnoses imbalance between modules within the string, a power generation prediction unit (3) that predicts the power generation amount for each string of a photovoltaic power generation device, a power generation measurement unit (4) that measures the power generation amount of the current string in real time, and a fault diagnosis unit (5) that diagnoses the type of fault of the string using the area on the IV coordinate plane according to the predicted power generation amount and the measured power generation amount.

[0061] Conventional insulation resistance diagnosis was limited to verifying the measured insulation resistance value by comparing it with a reference value, which resulted in a problem in that it could not diagnose localized degradation of insulation resistance or deterioration conditions in various environments. Therefore, the fire diagnosis system monitors the change in insulation resistance while applying voltage for a certain period of time and diagnoses the degradation of insulation resistance according to the change, thereby enabling accurate diagnosis of insulation resistance degradation even in various environments and localized defects. Furthermore, when insulation resistance degradation is diagnosed, it monitors the system to determine the fire risk condition and issues a warning, thereby enabling a rapid response to fire risks.

[0062] In addition, the fire diagnosis system can diagnose an unbalanced state between solar modules within the string, and if a decrease in insulation resistance is suspected while an unbalanced state is diagnosed, it can diagnose the insulation resistance to enable efficient operation of the system.

[0063] In addition, the fire diagnosis system can diagnose a decrease in power generation for the string, and by using the area on the IV coordinate plane to identify the type of fault in addition to comparing the existing predicted power generation with the current power generation, a more rapid response to the decrease in power generation can be made, and if the cause of the decrease in power generation is suspected to be insulation resistance, a precise diagnosis of insulation resistance can be made by the fire risk diagnosis unit (1).

[0064] The above fire diagnosis system can enable remote monitoring of multiple solar power generation facilities, and allows monitoring to be performed by receiving voltage, current, insulation resistance, etc., measured through junction boxes, remotely without the need for a worker to go to the site.

[0065] The above fire risk diagnosis unit (1) is configured to precisely diagnose whether the insulation resistance of the string has decreased and to notify of a fire risk, and preferably, it can be executed at night when the solar power generation facility is not operating. In addition, as described above, it can be executed when an imbalance between modules is diagnosed by the module imbalance diagnosis unit (2) or when a decrease in power generation is diagnosed by the fault diagnosis unit (5) and an insulation resistance is suspected. The above fire risk diagnosis unit (1) can monitor the change in insulation resistance by applying voltage for a certain period of time to accurately determine the state of insulation resistance decrease due to various environments, the state of deterioration due to local defects, etc., and can determine an abnormal state of insulation resistance if the range of change in insulation resistance is large or a rapid change occurs. In addition, the above fire risk judgment unit (1) can determine that there is a high risk of fire if such an abnormal state of insulation resistance persists, and can generate a warning to enable a quick response to the fire risk. To this end, the fire risk diagnosis unit (1) may include a diagnosis timing setting module (11), a voltage application module (12), a voltage adjustment module (13), an insulation resistance measurement module (14), a kick index calculation module (15), an abnormality detection module (16), a fire risk judgment module (17), and a fire warning module (18).

[0066] The above diagnostic timing setting module (11) is configured to set the time for measuring insulation resistance, and the measurement can be performed at night when no power generation is taking place. For example, the above diagnostic timing setting module (11) can set a specific time, or the measurement can be initiated automatically by monitoring the amount of power generated. In addition, the above diagnostic timing setting module (11) can be configured to operate at the set time only when a decrease in insulation resistance is suspected by the fault diagnosis unit (5) or the module imbalance diagnosis unit (2), thereby enabling efficient measurement and diagnosis.

[0067] The above voltage application module (12) is configured to apply voltage to a string for measuring insulation resistance, and can apply voltage for a certain period of time, for example, 10 minutes.

[0068] The above voltage adjustment module (13) is configured to adjust the voltage applied by the voltage application module (12), and can measure changes in insulation resistance under various voltage conditions by increasing the voltage in steps. For example, the above voltage adjustment module (13) can increase the voltage in steps from 100V to 500V.

[0069] The insulation resistance measuring module (14) is configured to measure insulation resistance during a certain period of time when voltage is applied. For example, when voltage is applied for 10 minutes, insulation resistance can be measured at 1-second intervals. Additionally, when insulation resistance is measured while increasing the voltage stepwise by the voltage adjustment module (13), insulation resistance can be measured each time the voltage is increased.

[0070] The above kick index calculation module (15) is configured to calculate a kick index indicating the degree of change in insulation resistance. If the insulation resistance measured in units of time or voltage by the insulation resistance measurement module (14) does not change linearly, and the range of change is large or rapid as shown in FIG. 3, it can be determined that the insulation resistance has decreased. Accordingly, the above kick index calculation module (15) can calculate the degree of change in insulation resistance on average as a kick index. When a constant voltage is applied for a certain period of time, it can calculate a time kick index regarding the degree of change per unit time, and when the voltage is applied while adjusting it step by step for a certain period of time, it can calculate a voltage kick index regarding the degree of change each time the voltage is changed. At this time, the time kick index can be calculated by the following (Equation 1), and the voltage kick index can be calculated by the following (Equation 2).

[0071] (Mathematical Formula 1)

[0072]

[0073] (Mathematical Formula 2)

[0074]

[0075] The above abnormality detection module (16) is configured to detect an abnormal state due to a decrease in insulation resistance, and can determine an abnormal state due to a decrease in insulation resistance when the time kick index or voltage kick index calculated by the above kick index calculation module (15) exceeds a set reference value.

[0076] The above fire risk judgment module (17) is configured to determine a fire risk due to a decrease in insulation resistance, and can determine the fire risk based on the kick index calculated by the above kick index calculation module (15). The above fire risk judgment module (17) can determine a fire risk state if an abnormal state in which the time kick index or voltage kick index exceeds a reference value persists for a set time or longer, or if the degree of change increases beyond a set degree.

[0077] The above fire warning module (18) is configured to warn of a fire risk, and when a fire risk judgment module (17) determines a fire risk state, it transmits a warning to the solar power generation device itself or to an administrator, etc., so that a quick response to the fire risk can be made.

[0078] The above module imbalance diagnosis unit (2) is configured to diagnose imbalance between solar modules within a string, and diagnoses performance imbalances caused by failure, damage, aging, etc. The above module imbalance diagnosis unit (2) may be configured to perform diagnosis in real time at regular intervals, or it may be executed when a decrease in power generation is diagnosed by the above failure diagnosis unit (5). In particular, the above module imbalance diagnosis unit (2) can improve the accuracy of the diagnosis by diagnosing the imbalance state by comprehensively considering the degree of voltage imbalance between solar modules and the degree of voltage fluctuation. In other words, the module imbalance diagnosis unit (2) detects the degree of voltage mismatch between solar modules and, in addition, considers the degree of voltage fluctuation in the diagnosis of the imbalance state. The inverter of the string performs maximum power point tracking (MPPT) to find the maximum output point and fluctuate the voltage and current. In a normal state, the voltage and current fluctuate within a certain range, but when an imbalance occurs between solar modules, the fluctuation range of the voltage and current exceeds a certain range and becomes larger or smaller. By reflecting this to diagnose the imbalance state, the accuracy of the diagnosis can be further improved. To this end, the module imbalance diagnosis unit (2) may include a voltage imbalance calculation unit (21), a fluctuation abnormality calculation unit (22), and an imbalance detection unit (23).

[0079] The above voltage imbalance calculation unit (21) is configured to calculate the degree of voltage imbalance between solar modules within a string, and specifically utilizes the voltage output from the string and the voltage measured from a specific module within the string. Conventionally, in order to detect voltage imbalance between modules within a string, it was necessary to measure and compare the voltages of each module, but this resulted in increased installation and maintenance costs. Therefore, the above voltage imbalance calculation unit (21) calculates the degree of voltage imbalance by comparing the voltage of the string with the value obtained by multiplying the voltage of a specific module by the number of modules, thereby simplifying installation and maintenance and reducing costs and time. In other words, if there is no imbalance between solar modules, the voltage of the string will be equal to the value obtained by multiplying the voltage of a specific module by the number of modules, so the degree of voltage imbalance can be calculated based on that difference. To this end, the voltage imbalance calculation unit (21) may include a string voltage measurement module (211), a module voltage measurement module (212), a voltage imbalance coefficient calculation module (213), and a voltage imbalance diagnosis module (214).

[0080] The string voltage measurement module (211) is configured to measure the voltage output from the string, and as shown in FIG. 5, the voltage can be measured at the output terminal of the string.

[0081] The above module voltage measurement module (212) is configured to measure the voltage of a specific module within a string, and measures the voltage of only one of the multiple solar modules included in the string, and, for example, can measure the voltage of the module at the final stage.

[0082] The above voltage imbalance coefficient calculation module (213) is configured to calculate a voltage imbalance coefficient indicating the degree of voltage imbalance of modules within a string, and can calculate the voltage imbalance coefficient by subtracting the value obtained by multiplying the voltage of a specific module by the number of modules from the string voltage. Therefore, the greater the degree of voltage imbalance between modules within a string, the larger the voltage imbalance coefficient.

[0083] The above voltage imbalance diagnosis module (214) is configured to diagnose the voltage imbalance state of the string when the voltage imbalance coefficient exceeds a set reference value, and can execute the fluctuation abnormality calculation unit (22) when the voltage imbalance state is diagnosed.

[0084] The above-mentioned fluctuation abnormality calculation unit (22) is configured to calculate the degree of abnormality regarding voltage fluctuation of the string, and represents the degree of voltage fluctuation as a numerical value to be reflected in the calculation of the degree of imbalance. As described above, in the case of a normal state as shown in FIG. 6, the string continues to track the maximum power point while maintaining voltage fluctuations within a certain range as shown in ①, but if it deviates from the voltage fluctuation range as shown in ② and ③ and shows fluctuations that are too large or too small, it is determined to be an abnormal state of fluctuation, and the degree thereof is calculated. In addition, the above-mentioned fluctuation abnormality calculation unit (22) adjusts the scale and reference value to calculate the degree of imbalance by linking the degree of abnormality of voltage fluctuation with the voltage imbalance coefficient. To this end, the above-mentioned fluctuation abnormality calculation unit (22) may include a voltage measurement module (221), a current measurement module (222), a power fluctuation coefficient calculation module (223), and a coefficient adjustment module (224).

[0085] The above voltage measurement module (221) is configured to measure the voltage output from the string, and measures it for a certain period of time to calculate the degree of change per unit time.

[0086] The above current measurement module (222) is configured to measure the current output from the string, and measures it for a certain period of time like voltage to calculate the degree of change with respect to voltage.

[0087] The power fluctuation coefficient calculation module (223) is configured to calculate a power fluctuation coefficient that indicates the degree of fluctuation in voltage and current, and calculates the degree of change in voltage and current per unit time. For example, the power fluctuation coefficient calculation module (223) can calculate the power fluctuation coefficient by dividing the ratio of the voltage and current change range by the ratio of the voltage and current magnitudes as shown in (Equation 3) below. If there is no imbalance between modules, the power fluctuation coefficient will have a value close to 1, if the voltage change range is large, it will have a value less than 1, and if the voltage change range is small, it will have a value greater than 1.

[0088] (Mathematical Formula 3)

[0089]

[0090] (I, V = Current, Voltage / dI, dV = Fluctuation range of current, voltage)

[0091] In this case, a large voltage fluctuation range indicates that a specific module has deteriorated or that the power generation has decreased due to odors, pollution, etc., and means a state in which the voltage is changed significantly as shown in ② of FIG. 6 to find the maximum power point by the MPPT algorithm of the inverter. In addition, a small voltage fluctuation range and a power fluctuation coefficient greater than 1 means a case in which the voltage change amount is almost non-existent compared to the current change amount as shown in ③ of FIG. 6, which means a state in which the power generation performance of the module is significantly reduced. The power fluctuation coefficient calculation module (223) can calculate the power fluctuation coefficient for unit time periods of, for example, 5 seconds or 10 seconds, and can determine the final power fluctuation coefficient using the average value of the power fluctuation coefficients for unit time periods over a certain period.

[0092] The coefficient adjustment module (224) is configured to adjust the final power fluctuation coefficient calculated by the power fluctuation coefficient calculation module (223) to be linked with the voltage imbalance coefficient, converting the standard of the normal state from 1 to 0 and increasing the scale, and can calculate the adjusted power fluctuation coefficient according to the following (Equation 4).

[0093] (Mathematical Formula 4)

[0094] Pf = (3-Pd)*10

[0095] (Here, Pf is the adjusted power change coefficient, and Pd is the final power change coefficient)

[0096] Therefore, in a steady state where there is no imbalance between modules, the adjusted power fluctuation coefficient becomes 0, and power fluctuation coefficients less than 1 are converted into positive numbers, and power fluctuation coefficients greater than 1 are converted into negative numbers.

[0097] The above imbalance detection unit (23) is configured to detect the imbalance state of the modules within the string, and calculates the degree of imbalance between modules by reflecting the degree of voltage imbalance calculated by the above voltage imbalance calculation unit (21) and the degree of voltage fluctuation abnormality calculated by the above fluctuation abnormality calculation unit (22), and in particular, the cause of the module imbalance can be diagnosed according to the calculated degree of imbalance. To this end, the above imbalance detection unit (23) may include a voltage imbalance coefficient loading module (231), a power fluctuation coefficient loading module (232), an imbalance index calculation module (233), and an abnormal information diagnosis module (234).

[0098] The above voltage imbalance coefficient loading module (231) is configured to load the voltage imbalance coefficient calculated by the above voltage imbalance calculation unit (21), and loads the voltage imbalance coefficient calculated by the above voltage imbalance coefficient calculation module (213).

[0099] The power fluctuation coefficient loading module (232) is configured to load the power fluctuation coefficient calculated by the fluctuation abnormality calculation unit (22), and loads the power fluctuation coefficient adjusted by the coefficient adjustment module (224).

[0100] The above-mentioned imbalance index calculation module (233) is configured to calculate an imbalance index indicating the degree of imbalance between modules, and can calculate the imbalance index by multiplying the voltage imbalance coefficient and the power fluctuation coefficient.

[0101] The above-mentioned abnormal information diagnosis module (234) is configured to diagnose the imbalance state between modules according to the imbalance index, and can diagnose the imbalance state when the imbalance index exceeds a set value. Since the imbalance index is the product of the degree of voltage imbalance and the degree of abnormal fluctuation, a larger absolute value indicates a more severe degree of imbalance. Since the power fluctuation coefficient is calculated as positive or negative depending on the power fluctuation state, a positive imbalance index indicates a state where the voltage change is large, and a negative imbalance index indicates a state where the voltage change is small and the current change is large. Therefore, as shown in FIG. 7, if the imbalance index is positive, it means that it is operating to the left (ⓐ) of the normal maximum power point, which means that the series resistance has increased, and damage, shading, or contamination of the module may be suspected. Also, if the imbalance index is negative, it means that it is operating to the right (ⓑ) of the normal maximum power point, which means that the parallel resistance has decreased, which means that leakage current, cell cracking, or insulation resistance degradation may be suspected. Accordingly, it is possible to accurately diagnose the imbalance between modules, simultaneously identify the cause, and enable a rapid response. At this time, if the imbalance index is negative and a decrease in insulation resistance is suspected, the fire risk diagnosis unit (1) can be configured to operate automatically at a set time.

[0102] The above power generation prediction unit (3) is configured to predict the power generation of a solar power generation facility, and can predict the power generation for each string. In particular, the above power generation prediction unit (3) can increase the accuracy by predicting the power generation by reflecting the specifications and characteristics of each solar module, IV curve data, environmental information, and degradation rate. To this end, the above power generation prediction unit (3) may include a specification information collection module (31), a number information collection module (32), a power generation information collection module (33), an environmental information collection module (34), a solar radiation information collection module (35), a temperature information collection module (36), a degradation rate calculation module (37), and a predicted power generation amount generation module (38).

[0103] The above specification information collection module (31) is configured to collect specification information of a solar module included in a string, and can collect and store manufacturer and item information in advance.

[0104] The above count information collection module (32) is configured to collect information on the number of solar modules included in the string, and can generate prediction information by summing the predicted power generation information for each solar module according to the number of solar modules.

[0105] The above-mentioned power generation information collection module (33) is configured to collect information regarding the number of days of power generation of a solar power module, and can calculate and collect information regarding the number of days of power generation by accumulating and storing information on power generation from the time of installation.

[0106] The above environmental information collection module (34) is configured to collect environmental information around the solar module, and can collect information regarding temperature, humidity, etc.

[0107] The above-mentioned solar radiation information collection module (35) is configured to collect solar radiation information reaching the solar module, and can predict the amount of power generated using IV curve data based on the collected solar radiation.

[0108] The above temperature information collection module (36) is configured to collect module temperature information of a solar module, and can collect temperature information measured by a sensor installed in each solar module.

[0109] The above degradation rate calculation module (37) is configured to calculate a degradation rate indicating the degree of degradation of a solar module, and calculates the degradation rate according to the power generation day information collected by the above power generation information collection module (33) by reflecting the degree of degradation per day determined by the characteristics of the solar module specifications.

[0110] The above-mentioned predicted power generation module (38) is configured to predict the power generation of a string, and the prediction of power generation is made by considering IV curve data, environmental information, and degradation rate according to solar irradiance and module temperature. The prediction of power generation based on IV curve data and environmental information can be done experimentally or by analyzing measurement information collected from a solar power generation facility. For example, a correlation can be derived by learning by reflecting environmental information and degradation rate to the power generation based on IV curve data provided by the manufacturer of each solar module, and the power generation can be predicted using the derived correlation.

[0111] The above power generation measurement unit (4) is configured to measure the power generation of each string, and can calculate the power generation by measuring the voltage and current output from each string.

[0112] The fault diagnosis unit (5) described above is configured to diagnose a fault caused by a decrease in power generation, and diagnoses the decrease in power generation based on the difference between the predicted power generation and the measured power generation. In particular, it is configured to detect the type of fault that causes the decrease in power generation based on the area of ​​the region connecting the location on the IV coordinate plane according to the power generation and the point representing the short-circuit current and open-circuit voltage. To this end, the fault diagnosis unit (5) may include a power generation decrease diagnosis module (51), an Isc area calculation module (52), a Voc area calculation module (53), an area comparison module (54), and a fault cause detection module (55).

[0113] The above power generation degradation diagnosis module (51) is configured to diagnose a decrease in power generation, and diagnoses a decrease in power generation when the measured power generation falls short of the predicted power generation to a certain degree or more, and enables the detection of the cause of the decrease in power generation by using the area of ​​the region on the IV coordinate plane.

[0114] The above Isc area calculation module (52) is configured to calculate the area of ​​the Isc region formed by a point on the IV coordinate plane representing the predicted power generation and the measured power generation and a point (Isc) representing the short-circuit current, and calculates the area of ​​∆a in the graph shown in FIG. 10. The area of ​​∆a is an area that occurs according to the difference between the predicted power generation and the measured power generation, and a large area of ​​∆a means a decrease in current, that is, an increase in the series resistance on the string.

[0115] The above Voc area calculation module (53) is configured to calculate the area of ​​the Voc region formed by a point on the IV coordinate plane representing the predicted power generation and the measured power generation and a point (Voc) representing the open-circuit voltage, and calculates the area of ​​∆b in the graph shown in FIG. 10. The area of ​​∆b is also an area that occurs according to the difference between the predicted power generation and the measured power generation, and a large area of ​​∆b means a decrease in voltage, that is, a decrease in parallel resistance in the string.

[0116] The above area comparison module (54) is configured to compare the areas of the Isc area (∆a) and the Voc area (∆b), and depending on which area is larger, it is possible to determine whether the cause of the decrease in power generation is due to an increase in series resistance or a decrease in parallel resistance.

[0117] The fault cause detection module (55) is configured to detect the cause of the decrease in power generation based on the comparison result by the area comparison module (54). If the area of ​​the Isc region (∆a) is larger than the area of ​​the Voc region (∆b), it can be seen that the decrease in power generation is caused by an increase in series resistance, such as the cable connection condition, line condition, or shading within the module. If the area of ​​the Isc region (∆a) is smaller than the area of ​​the Voc region (∆b), it can be seen that the decrease in power generation is caused by a decrease in parallel resistance, such as leakage current, cell cracking, or a decrease in insulation resistance. In this case, the fire risk diagnosis unit (1) can be activated. Therefore, rapid inspection and response to the decrease in power generation can be carried out based on the result detected by the fault cause detection module (55).

[0118] Although the applicant has described various embodiments of the present invention above, such embodiments are merely examples of implementing the technical concept of the present invention, and any modification or alteration that implements the technical concept of the present invention should be interpreted as falling within the scope of the present invention.

Claims

1. A fire diagnosis system that diagnoses a fire using the insulation resistance status of a string of a solar power generation facility, It includes a fire risk diagnosis unit that precisely diagnoses whether the insulation resistance of the string has decreased and alerts to the fire risk, and The above fire risk diagnosis unit is, A fire diagnosis system using insulation resistance, characterized by comprising: a voltage application module that applies voltage to a string for a set period of time; an insulation resistance measurement module that measures insulation resistance at unit time intervals according to the voltage application; a kick index calculation module that calculates a kick index indicating the degree of change in insulation resistance per unit time for a set period of time; an abnormality detection module that determines an abnormality in insulation resistance if the calculated kick index exceeds a set reference value; a fire risk judgment module that determines a fire risk if the abnormal state of insulation resistance persists for a set period of time or if the degree of increase in the kick index exceeds a set value; and a fire warning module that generates a warning signal when a fire risk is determined.

2. In claim 1, the fire risk diagnosis unit A fire diagnosis system using insulation resistance characterized by including a diagnosis timing setting module for setting the diagnosis timing of the insulation resistance status.

3. In claim 1, the kick index calculation module is A fire diagnosis system using insulation resistance characterized by calculating the time kick index according to the mathematical formula 1 below. (Mathematical Formula 1) 4. In claim 1, the fire diagnosis system is A fire diagnosis system using insulation resistance characterized by including a voltage adjustment module that enables the measurement of insulation resistance while varying the voltage in steps.

5. In Clause 4, the above kick index calculation module is A fire diagnosis system using insulation resistance characterized by calculating the voltage kick index according to the mathematical formula 2 below. (Mathematical Formula 2) 6. In claim 1, the fire diagnosis system is It includes a module imbalance diagnosis unit that diagnoses imbalance between photovoltaic modules within a string, and The above fire risk diagnosis unit is, A fire diagnosis system using insulation resistance characterized by performing an insulation resistance diagnosis when an imbalance caused by a decrease in insulation resistance is diagnosed by the above-mentioned module imbalance diagnosis unit.

7. In Clause 6, the module imbalance diagnosis unit is, A voltage imbalance calculation unit that calculates the degree of voltage imbalance between modules constituting a string, and A fluctuation abnormality calculation unit that calculates the degree of abnormality based on voltage and current fluctuations of the string, and A fire diagnosis system using insulation resistance characterized by including an imbalance detection unit that detects imbalance between modules of a string according to the degree of voltage imbalance and the degree of abnormal fluctuation.

8. In Clause 7, the voltage imbalance calculation unit is A fire diagnosis system using insulation resistance, characterized by including a string voltage measurement module for measuring the voltage of power output from a string, a module voltage measurement module for measuring the voltage at a specific module within the string, and a voltage imbalance coefficient calculation module for calculating a voltage imbalance coefficient indicating the degree of voltage imbalance between modules by subtracting the value obtained by multiplying the number of photovoltaic modules included in the string by the voltage of the specific module from the string voltage.

9. In Clause 8, the voltage imbalance calculation unit is A fire diagnosis system using insulation resistance, characterized by including a voltage imbalance diagnosis module that compares the voltage imbalance coefficient calculated by the above-mentioned imbalance coefficient calculation module with a reference value, diagnoses voltage imbalance between modules when the coefficient exceeds the reference value, and executes a fluctuation abnormality calculation unit.

10. In Clause 8, the above fluctuation abnormality calculation unit A fire diagnosis system using insulation resistance, characterized by including a voltage measurement module that measures a voltage output from a string for a certain period of time, a current measurement module that measures a current output from a string for a certain period of time, and a power fluctuation coefficient calculation module that calculates a power fluctuation coefficient indicating the degree of fluctuation of voltage and current by calculating the value of the ratio of voltage change amount to current change amount for the ratio of voltage to current per unit time for a certain period of time and the average value.

11. In Clause 10, the above fluctuation abnormality calculation unit A fire diagnosis system using insulation resistance characterized by including a coefficient adjustment module that increases the scale while changing the standard for the steady state of the power fluctuation coefficient to zero.

12. In claim 11, the coefficient adjustment module A fire diagnosis system using insulation resistance characterized by calculating the final power fluctuation coefficient by adjusting the power fluctuation coefficient according to mathematical formula 3. (Mathematical Formula 3) Pf = (1-Pd)*10 (Here, Pf is the adjusted power variation coefficient, and Pd is the initial power variation coefficient) 13. In claim 11, the imbalance detection unit A fire diagnosis system using insulation resistance, characterized by including a voltage imbalance coefficient loading module for retrieving a voltage imbalance coefficient, a power fluctuation coefficient loading module for retrieving a power fluctuation coefficient, an imbalance index calculation module for calculating an imbalance index representing the degree of output imbalance between modules by multiplying the voltage imbalance coefficient and the power fluctuation coefficient, and an abnormal information diagnosis module for diagnosing an abnormal state due to output imbalance between modules of a string according to the calculated imbalance index.

14. In claim 13, the above abnormal information diagnosis module is A fire diagnosis system using insulation resistance characterized by diagnosing module damage, shading, or contamination when the imbalance index is positive, and diagnosing PID, cell cracking, or insulation resistance degradation when the imbalance index is negative.

Images