BIPV module imbalance monitoring system
The BIPV module imbalance monitoring system addresses inefficiencies in diagnosing voltage imbalances by calculating an imbalance index and using IV coordinate plane analysis, ensuring rapid and accurate fault detection in BIPV systems, thereby preventing damage and fire risks.
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- E2Z CO LTD
- Filing Date
- 2024-11-29
- Publication Date
- 2026-04-23
AI Technical Summary
Conventional methods for diagnosing imbalances in Building Integrated Photovoltaic (BIPV) systems are inefficient, placing a heavy burden on data processing and analysis, and fail to provide rapid diagnosis of voltage imbalances between modules, leading to potential damage and fire risks due to uneven power generation and aging.
A BIPV module imbalance monitoring system that calculates an imbalance index using voltage and current fluctuations, allowing for rapid and accurate diagnosis of imbalances by comparing the voltage of a specific module with the entire string, and identifying fault types on an IV coordinate plane.
Enables efficient data processing and rapid, accurate diagnosis of imbalances, allowing for quick identification and response to faults, reducing maintenance costs and preventing damage by detecting voltage and insulation resistance issues.
Smart Images

Figure KR2024019345_23042026_PF_FP_ABST
Abstract
Description
BIPV Module Imbalance Monitoring System
[0001] The present invention relates to a BIPV module imbalance monitoring system, and more specifically, to a BIPV module imbalance monitoring system that enables efficient data processing and diagnosis of imbalance by diagnosing imbalance between modules where an abnormality occurs in the power generation amount of a BIPV string, and enables accurate diagnosis of the imbalance state of the module output within the string by diagnosing the imbalance state according to the degree of voltage imbalance and voltage fluctuation between modules within the string.
[0002] Solar power generation, a sector of renewable energy, has recently seen a surge in demand due to its many advantages, and technologies to improve power generation efficiency have also advanced significantly. Recently, solar power generation devices are being installed in various forms and locations, including on building rooftops and on water, and in particular, the installation of Building Integrated Photovoltaics (BIPV), which are formed integrally with the building as exterior materials, is on the rise.
[0003] Building-integrated photovoltaic (BIPV) systems are recognized for their high utility as they do not require separate installation space and can operate with high efficiency since they are formed integrally with the exterior walls of buildings, but there is a problem that maintenance and management are difficult once installed.
[0004] Therefore, it is important to accurately assess the condition and take necessary measures before a failure occurs, as the structure installed on the building's exterior walls means that a problem in one part will affect the entire BIPV system.
[0005] In addition, since a fire in a BIPV can have a direct impact not only on the entire BIPV but also on the entire building, it is of utmost importance to accurately and quickly recognize abnormal or dangerous conditions of the BIPV and take appropriate action.
[0006] Meanwhile, in the case of BIPV, solar modules are connected in series to form strings, just like in general photovoltaic power generation devices, and multiple strings are connected in parallel to form a single BIPV device, and these BIPV devices are installed along the exterior walls of a building.
[0007] Even in such BIPV devices, if an imbalance occurs between modules forming a string, the power generation decreases, reducing power generation efficiency. Furthermore, uneven usage between modules accelerates aging and causes failures, and it also affects other connected BIPV devices, leading to damage, fire, etc.
[0008] However, conventional methods diagnose imbalances by measuring voltage for each module as described in the patent document below place a heavy burden on data processing and analysis. Furthermore, rapid diagnosis of imbalances is difficult, leading to a situation where imbalances are diagnosed only after damage or failure has occurred in the entire BIPV system.
[0009] (Patent Document) Registered Patent Publication No. 10-0930132 (Registered Nov. 27, 2009) "Photovoltaic junction box equipped with monitoring function"
[0010] The present invention has been devised to solve the above-mentioned problems,
[0011] The present invention aims to provide a BIPV module imbalance monitoring system that enables efficient data processing and diagnosis of imbalance by diagnosing imbalance between modules where an abnormality occurs when an abnormality in power generation occurs in a string of BIPV.
[0012] The present invention aims to provide a BIPV module imbalance monitoring system that enables accurate diagnosis of an imbalance state by diagnosing the imbalance state of the module output within the string according to the degree of voltage imbalance and voltage fluctuation between modules within the string.
[0013] The present invention aims to provide a BIPV module imbalance monitoring system that can detect a voltage imbalance in a simple way without measuring the voltage of all solar modules by diagnosing the voltage imbalance 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.
[0014] The present invention aims to provide a BIPV module imbalance monitoring 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 aims to provide a BIPV module imbalance monitoring system that enables rapid response to failures by diagnosing the type of failure using the area on the IV coordinate plane, thereby allowing the location and type of failure to be identified quickly even remotely, and enabling visual confirmation of the failure status and type.
[0016] The present invention is implemented by an embodiment having the following configuration to achieve the aforementioned objective.
[0017] According to one embodiment of the present invention, the BIPV module imbalance monitoring system according to the present invention is characterized by comprising a power generation prediction unit that predicts the power generation amount for each string of BIPV, a power generation measurement unit that measures the power generation amount of the string in real time, a fault diagnosis unit that diagnoses a fault based on the predicted power generation amount and the measured power generation amount, and a module imbalance diagnosis unit that diagnoses the imbalance between modules within the string when a fault in the string is diagnosed by the fault diagnosis unit.
[0018] According to another embodiment of the present invention, in a BIPV module imbalance monitoring system according to the present invention, the module imbalance diagnosis unit comprises a voltage imbalance calculation unit that calculates the degree of imbalance regarding the 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.
[0019] According to another embodiment of the present invention, in a BIPV module imbalance monitoring system 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 photovoltaic modules included in the string by the voltage of the specific module from the string voltage.
[0020] According to another embodiment of the present invention, in a BIPV module imbalance monitoring system 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 coefficient exceeds the reference value, and executes a fluctuation abnormality calculation unit.
[0021] According to another embodiment of the present invention, in a BIPV module imbalance monitoring system 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.
[0022] According to another embodiment of the present invention, in a BIPV module imbalance monitoring system 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 steady state of the power fluctuation coefficient to 0.
[0023] According to another embodiment of the present invention, in a BIPV module imbalance monitoring system according to the present invention, the coefficient adjustment module is characterized by adjusting the power fluctuation coefficient according to Equation 2 to calculate the adjusted power fluctuation coefficient.
[0024] (Mathematical Formula 2)
[0025] Pf = (1-Pd)*10
[0026] (Here, Pf is the adjusted power variation coefficient, and Pd is the initial power variation coefficient)
[0027] According to another embodiment of the present invention, in a BIPV module imbalance monitoring system 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.
[0028] According to another embodiment of the present invention, in a BIPV module imbalance monitoring system 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.
[0029] According to another embodiment of the present invention, in a BIPV module imbalance monitoring system according to the present invention, the fault diagnosis unit comprises: a power generation degradation diagnosis module that diagnoses a decrease in power generation when the degree to which the measured power generation falls short of the predicted power generation is greater than a certain level; an Isc area calculation module that calculates the area of the Isc area formed by a line connecting points on the IV coordinate plane according to the voltage and current values of the predicted power generation and the measured power generation, and a line connecting points indicating short-circuit current; a Voc area calculation module that calculates the area of the Voc area formed by a line connecting points on the IV coordinate plane according to the voltage and current values of the predicted power generation and the measured power generation, and a line connecting points indicating open-circuit voltage; an area comparison module that compares the areas of the Isc area and the Voc area; and a fault cause detection module that detects the type of fault according to the difference in the compared areas.
[0030] According to another embodiment of the present invention, in a BIPV module imbalance monitoring system according to the present invention, the fault cause detection module is characterized by determining that a fault is caused by an increase in series resistance when the area of the Isc region is larger than the area of the Voc region.
[0031] According to another embodiment of the present invention, in a BIPV module imbalance monitoring system according to the present invention, the fault cause detection module is characterized by determining that a fault is caused by a decrease in module parallel resistance when the area of the Voc region is larger than the area of the Isc region.
[0032] The present invention can achieve the following effects through the combination and usage relationship of the embodiments described above and the configuration described below.
[0033] The present invention has the effect of enabling efficient data processing and diagnosis of imbalance by diagnosing the imbalance between modules where an abnormality occurs when an abnormality in power generation occurs in the string of BIPV.
[0034] The present invention has the effect of enabling accurate diagnosis of an unbalanced state by diagnosing the unbalanced state of the module output within the string according to the degree of voltage imbalance and voltage fluctuation between modules within the string.
[0035] 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.
[0036] 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.
[0037] The present invention has the effect of enabling rapid response to a fault by diagnosing the type of fault using the area on the IV coordinate plane, thereby allowing the location and type of the fault to be quickly identified even remotely, and enabling visual confirmation of whether a fault exists and the type of fault.
[0038] FIG. 1 is a block diagram showing the configuration of an IPV module imbalance monitoring system according to an embodiment of the present invention.
[0039] Figure 2 is a block diagram showing the configuration of the power generation prediction unit.
[0040] Figure 3 is a block diagram showing the configuration of the fault diagnosis unit.
[0041] Figure 4 is a reference diagram showing an IV graph used by the fault diagnosis unit.
[0042] FIG. 5 is a block diagram showing the configuration of the module imbalance diagnosis unit
[0043] Figure 6 is a reference diagram showing an example of voltage measurement by the voltage imbalance calculation unit.
[0044] Figure 7 is a graph showing an example of voltage change according to string condition.
[0045] Figure 8 is a reference diagram showing the operating point on the IV curve according to the unbalance index.
[0046] FIG. 9 is a block diagram showing the configuration of the insulation resistance diagnostic unit.
[0047] Figure 10 is a graph showing an example of insulation resistance measurement.
[0048] Explanation of symbols used in drawings
[0049] 1: Power generation prediction unit 2: Power generation measurement unit
[0050] 3: Fault Diagnosis Unit 4: Module Imbalance Diagnosis Unit
[0051] 41: Voltage Imbalance Calculation Unit 42: Fluctuation Anomaly Calculation Unit
[0052] 43: Imbalance detection unit 5: Insulation resistance diagnosis unit
[0053] Preferred embodiments of a BIPV module imbalance monitoring system according to the present invention will be described in detail below with reference to the accompanying 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 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., as 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.
[0054]
[0055] A BIPV module imbalance monitoring system according to one embodiment of the present invention is described with reference to FIGS. 1 to 10. The BIPV module imbalance monitoring system includes a power generation prediction unit (1) that predicts the power generation amount for each string of BIPV, a power generation measurement unit (2) that measures the power generation amount of a string in real time, a fault diagnosis unit (3) that diagnoses a fault in a string according to the predicted power generation amount and the measured power generation amount, a module imbalance diagnosis unit (4) that diagnoses the imbalance between modules within a string when a fault in a string is diagnosed by the fault diagnosis unit (3), and an insulation resistance diagnosis unit (5) that precisely diagnoses whether the insulation resistance has decreased.
[0056] In the present invention, the term "BIPV module" refers to an individual photovoltaic module that constitutes a BIPV (Building Integrated Photovoltaic) device formed integrally with the exterior wall of a building and producing electricity through sunlight. These modules are connected in series to form a string, multiple strings are connected in parallel to form a single BIPV device, and multiple BIPV devices are connected and installed on the exterior wall of a building.
[0057] As described above in the background technology, when an imbalance occurs between photovoltaic modules within a string, it lowers the overall power generated by the string and accelerates aging due to uneven use of the photovoltaic modules. In particular, in the case of BIPV devices, the entire BIPV is affected by damage to local strings, and there is a problem that recovery and repair are very difficult.
[0058] Furthermore, in the case of BIPV devices, since multiple units are installed across the entire exterior wall of a building, the conventional method of diagnosing imbalances by measuring the voltage of each module places a heavy burden on data processing and analysis, and also suffers from reduced accuracy.
[0059] Accordingly, the present invention enables precise diagnosis of inter-module imbalance only when the power generation of the string decreases, and improves efficiency by using the voltage of a specific module to diagnose the imbalance even during precise diagnosis of inter-module imbalance. In addition, the present invention enables more precise diagnosis of faults by additionally allowing the type of fault to be identified by utilizing the difference in area according to the amount of power generated on the IV coordinate plane.
[0060] The above power generation prediction unit (1) is configured to predict the power generation amount for each string of BIPV, and can predict the power generation amount for each string. In particular, the above power generation prediction unit (1) can increase the accuracy by predicting the power generation amount by reflecting the specifications and characteristics of each photovoltaic module, IV curve data, environmental information, and degradation rate. To this end, the above power generation prediction unit (1) may include a specification information collection module (11), a number information collection module (12), a power generation information collection module (13), an environmental information collection module (14), a solar radiation information collection module (15), a temperature information collection module (16), a degradation rate calculation module (17), and a predicted power generation amount generation module (18).
[0061] The above specification information collection module (11) 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.
[0062] The above count information collection module (12) 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.
[0063] The above-mentioned power generation information collection module (13) 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.
[0064] The above environmental information collection module (14) is configured to collect environmental information around the solar module, and can collect information regarding temperature, humidity, etc.
[0065] The above-mentioned solar radiation information collection module (15) 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.
[0066] The above temperature information collection module (16) 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.
[0067] The above degradation rate calculation module (17) 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 (13) by reflecting the degree of degradation per day determined by the characteristics of the specifications of the solar module.
[0068] The above-mentioned predicted power generation module (18) 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 BIPV device. 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.
[0069] The above power generation measurement unit (2) 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.
[0070] The fault diagnosis unit (3) is configured to diagnose faults resulting from 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. Accordingly, if the measured power generation is lower than the predicted power generation by a certain amount or more, it is diagnosed as a fault, and the module imbalance diagnosis unit (4) can diagnose the imbalance between modules. In addition, the fault diagnosis unit (3) can generate an IV coordinate plane and detect the type of fault based on its area, and in particular, 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 (3) may include a power generation decrease diagnosis module (31), an Isc area calculation module (32), a Voc area calculation module (33), an area comparison module (34), and a fault cause detection module (35).
[0071] The above power generation degradation diagnosis module (31) 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.
[0072] The above Isc area calculation module (32) 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. 4. 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.
[0073] The above Voc area calculation module (33) 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 to calculate the area of ∆b in the graph shown in FIG. 4. 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.
[0074] The above area comparison module (34) 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.
[0075] The fault cause detection module (35) is configured to detect the cause of power generation reduction based on the comparison result by the area comparison module (34). If the area of the Isc region (∆a) is larger than the area of the Voc region (∆b), it is due to an increase in series resistance, and the power generation reduction can be seen as caused by 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 is due to a decrease in parallel resistance, and the power generation reduction can be seen as caused by leakage current, cell cracking, or a decrease in insulation resistance. Accordingly, rapid inspection and response to the power generation reduction can be carried out based on the result detected by the fault cause detection module (35).
[0076] The above module imbalance diagnosis unit (4) is configured to diagnose imbalance between solar modules within a string, and can be executed when a fault in the string is diagnosed by the above fault diagnosis unit (3), and diagnoses imbalance in performance caused by fault, damage, aging, etc. In particular, the above module imbalance diagnosis unit (4) 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 (4) 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 (4) may include a voltage imbalance calculation unit (41), a fluctuation abnormality calculation unit (42), and an imbalance detection unit (43).
[0077] The above voltage imbalance calculation unit (41) is configured to calculate the degree of voltage imbalance between solar modules within a string, specifically using the voltage output from the string and the voltage measured from a specific module within the string. Conventionally, 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 (41) 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 (41) may include a string voltage measurement module (411), a module voltage measurement module (412), a voltage imbalance coefficient calculation module (413), and a voltage imbalance diagnosis module (414).
[0078] The string voltage measurement module (411) is configured to measure the voltage output from the string, and as shown in FIG. 6, the voltage can be measured at the output terminal of the string.
[0079] The above module voltage measuring module (412) 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 final module.
[0080] The above voltage imbalance coefficient calculation module (413) 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.
[0081] The above voltage imbalance diagnosis module (414) 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 (42) when the voltage imbalance state is diagnosed.
[0082] The above-mentioned fluctuation abnormality calculation unit (42) 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. 7, 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 (42) 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 (42) may include a voltage measurement module (421), a current measurement module (422), a power fluctuation coefficient calculation module (423), and a coefficient adjustment module (424).
[0083] The above voltage measurement module (421) 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.
[0084] The above current measurement module (422) 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.
[0085] The power fluctuation coefficient calculation module (423) 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 (423) 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 1) 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.
[0086] (Mathematical Formula 1)
[0087]
[0088] (I, V = Current, Voltage / dI, dV = Fluctuation range of current, voltage)
[0089] 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. 7 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. 7, which means a state in which the power generation performance of the module is significantly reduced. The power fluctuation coefficient calculation module (423) 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.
[0090] The coefficient adjustment module (424) is configured to adjust the final power fluctuation coefficient calculated by the power fluctuation coefficient calculation module (423) 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 2).
[0091] (Mathematical Formula 2)
[0092] Pf = (1-Pd)*10
[0093] (Here, Pf is the adjusted power change coefficient, and Pd is the final power change coefficient)
[0094] 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.
[0095] The above imbalance detection unit (43) 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 voltage imbalance calculation unit (41) and the degree of voltage fluctuation abnormality calculated by the fluctuation abnormality calculation unit (42), 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 (43) may include a voltage imbalance coefficient loading module (431), a power fluctuation coefficient loading module (432), an imbalance index calculation module (433), and an abnormal information diagnosis module (434).
[0096] The above voltage imbalance coefficient loading module (431) is configured to load the voltage imbalance coefficient calculated by the above voltage imbalance calculation unit (41), and loads the voltage imbalance coefficient calculated by the above voltage imbalance coefficient calculation module (413).
[0097] The power fluctuation coefficient loading module (432) is configured to load the power fluctuation coefficient calculated by the fluctuation abnormality calculation unit (42), and loads the power fluctuation coefficient adjusted by the coefficient adjustment module (424).
[0098] The above-mentioned imbalance index calculation module (433) 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.
[0099] The above-mentioned abnormal information diagnosis module (434) is configured to diagnose an unbalanced state between modules according to an unbalance index, and can diagnose an unbalanced state when the unbalance index exceeds a set value. Since the unbalance index is the product of the degree of voltage unbalance and the degree of abnormal fluctuation, a larger absolute value indicates a more severe degree of unbalance. Since the power fluctuation coefficient is calculated as positive or negative depending on the power fluctuation state, a positive unbalance index indicates a state where voltage fluctuation is large, and a negative unbalance index indicates a state where voltage fluctuation is small and current fluctuation is large. Therefore, as shown in FIG. 8, if the unbalance index is positive, it means that the module is operating to the left (ⓐ) of the normal maximum power point, indicating a state where the series resistance has increased, and damage, shading, or contamination of the module may be suspected. In addition, if the unbalance index is negative, it means that the module is operating to the right (ⓑ) of the normal maximum power point, indicating a state where the parallel resistance has decreased, and 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.
[0100] The insulation resistance diagnosis unit (5) is configured to diagnose a decrease in the insulation resistance of the string, and preferably, it can be executed at night when the BIPV device is not operating. A decrease in insulation resistance in a photovoltaic power generation device is a major cause of fire, and conventionally, the condition of the insulation resistance has been measured periodically. However, conventionally, it was limited to checking whether the insulation resistance, which varies depending on the environment such as humidity, exceeded a reference value, so there was a problem in that it could not diagnose localized decreases in insulation resistance or deterioration conditions in various environments. In addition, in the case of a BIPV device, there is a problem that if a fire occurs due to a decrease in insulation resistance, it directly affects the entire building and leads to a large fire. Therefore, the insulation resistance diagnosis unit (5) monitors the change in the insulation resistance while applying voltage for a certain period of time, and diagnoses the decrease in insulation resistance according to the change state, thereby enabling accurate diagnosis of the decrease in insulation resistance even in various environments and local defects. To this end, the insulation resistance diagnosis unit (5) may include a diagnosis timing setting module (51), a voltage application module (52), a voltage adjustment module (53), an insulation resistance measurement module (54), a kick index calculation module (55), and an abnormality detection module (56).
[0101] The above diagnostic timing setting module (51) 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 (51) 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 (51) can be configured to operate at the set time only when a decrease in insulation resistance is suspected by the fault diagnosis unit (3) or the module imbalance diagnosis unit (4), thereby enabling efficient measurement and diagnosis. In other words, the above diagnostic timing setting module (51) can initiate the diagnosis of insulation resistance when the area of the Voc region (∆b) is larger than the area of the Isc region (∆a) in the fault diagnosis unit (3), or when the imbalance index calculated by the imbalance index calculation module (433) is negative.
[0102] The above voltage application module (52) 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.
[0103] The above voltage adjustment module (53) is configured to adjust the voltage applied by the voltage application module (52), and can measure changes in insulation resistance under various voltage conditions by increasing the voltage stepwise. For example, the above voltage adjustment module (53) can increase the voltage stepwise from 100V to 500V.
[0104] The insulation resistance measuring module (54) 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 (53), insulation resistance can be measured each time the voltage is increased.
[0105] The above kick index calculation module (55) 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 (54) does not change linearly, and the range of change is large or rapid changes occur as shown in FIG. 10, it can be determined that the insulation resistance has decreased. Accordingly, the above kick index calculation module (55) 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 3), and the voltage kick index can be calculated by the following (Equation 4).
[0106] (Mathematical Formula 3)
[0107]
[0108] (Mathematical Formula 4)
[0109]
[0110] The above abnormality detection module (56) is configured to detect an abnormal state due to a decrease in insulation resistance, and can determine that a dangerous state has occurred due to a decrease in insulation resistance when the time kick index or voltage kick index calculated by the above kick index calculation module (55) exceeds a set value.
[0111]
[0112] 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. An imbalance monitoring system for monitoring the imbalance between modules within a string of BIPV formed integrally on the exterior wall of a building, A power generation prediction unit that predicts the power generation amount for each string of BIPV, and A power generation measurement unit that measures the amount of power generated by the string in real time, and A fault diagnosis unit that diagnoses faults based on predicted power generation and measured power generation, and A BIPV module imbalance monitoring system characterized by including a module imbalance diagnosis unit that diagnoses imbalance between modules within a string when a string fault is diagnosed by the fault diagnosis unit above.
2. In claim 1, the module imbalance diagnosis unit 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 BIPV module imbalance monitoring system 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.
3. In Clause 2, the voltage imbalance calculation unit is A BIPV module imbalance monitoring system 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.
4. In Clause 3, the voltage imbalance calculation unit is A BIPV module imbalance monitoring system 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.
5. In Paragraph 3, the above fluctuation abnormality calculation unit A BIPV module imbalance monitoring system 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.
6. In Clause 5, the above fluctuation abnormality calculation unit A BIPV module imbalance monitoring system 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 0.
7. In claim 6, the coefficient adjustment module A BIPV module imbalance monitoring system characterized by calculating an adjusted power fluctuation coefficient by adjusting the power fluctuation coefficient according to mathematical formula 2. (Mathematical Formula 2) Pf = (1-Pd)*10 (Here, Pf is the adjusted power variation coefficient, and Pd is the initial power variation coefficient) 8. In claim 6, the imbalance detection unit A BIPV module imbalance monitoring system 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.
9. In claim 8, the above abnormal information diagnosis module is A BIPV module imbalance monitoring system 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.
10. In claim 1, the fault diagnosis unit A BIPV module imbalance monitoring system characterized by including: a power generation degradation diagnosis module that diagnoses a decrease in power generation when the measured power generation falls short of the predicted power generation by a certain amount or more; an Isc area calculation module that calculates the area of the Isc region formed by a line connecting points on an IV coordinate plane according to the voltage and current values of the predicted power generation and the measured power generation, and a line connecting points indicating short-circuit current; a Voc area calculation module that calculates the area of the Voc region formed by a line connecting points on an IV coordinate plane according to the voltage and current values of the predicted power generation and the measured power generation, and a line connecting points indicating open-circuit voltage; an area comparison module that compares the areas of the Isc region and the Voc region; and a fault cause detection module that detects the type of fault based on the difference in the compared areas.
11. In claim 10, the fault cause detection module is A BIPV module imbalance monitoring system characterized by determining that a fault is caused by an increase in series resistance when the area of the Isc region is larger than the area of the Voc region.
12. In claim 10, the fault cause detection module is A BIPV module imbalance monitoring system characterized by determining that a failure is caused by a decrease in module parallel resistance when the area of the Voc region is larger than the area of the Isc region.
Citation Information
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