KR20210025361A - An Intergrated Solution System of PV-ESS with Reinforced Safety - Google Patents

Abstract

The present invention relates to a PV-ESS integrated solution system and, more particularly, to a PV-ESS integrated solution system with a reinforced safety function which diagnoses safety in advance in accordance with the temperature, arc, and earthquake monitoring information of an ESS device and notifies a user, thereby quickly performing preparation for fire, earthquake, and the like. To this end, the PV-ESS integrated solution system comprises a solar power generation device, the ESS device, and a diagnostic server.

Description

An Intergrated Solution System of PV-ESS with Reinforced Safety}

The present invention relates to a PV-ESS integrated solution system, and more particularly, by pre-diagnosing the safety according to the temperature, arc, and earthquake monitoring information of the ESS device and notifying the user, preparation for fire and earthquake can be quickly made. It relates to a PV-ESS integrated solution system with enhanced safety functions that enable it.

ESS devices that store excess power produced in power plants and transmit power when there is a temporary lack of power are being used, and recently, large-scale energy storage devices have been constructed in small sizes to prepare for power outages or peak power in general customers such as buildings, factories, and homes. Increasingly, they are used for reduction purposes.

In recent years, as interest in new and renewable energy has rapidly increased due to unbalanced power supply and demand, the development of technology to store electricity generated by utilizing renewable energy through energy storage devices and to utilize it at the required time has been continuously developed. It is being done.

Among them, in recent years, the development of a system that combines a photovoltaic power generation device and an ESS device to store power generated by solar power and to use it for various loads has been actively made.

However, the conventional ESS device accommodates a battery that stores energy, a BMS that manages the battery, and a PCS that converts power in a battery rack as shown in the following patent documents, and accommodates and operates such a battery rack in a certain space. At this time, in the summer when the external temperature is high, the temperature of the ESS system is excessively increased due to a lot of heat generated from the battery of the ESS system, and accordingly, there is a problem that the risk of fire is high, and in fact, fire accidents occur frequently. I'm doing it.

However, there is no development of a technology to detect and prevent fire in advance in a battery environment where a lot of heat is generated, and damage from earthquakes is also a concern.

In addition, the photovoltaic power generation device connected to the ESS device does not produce efficient power due to frequent breakdowns, and various technologies for diagnosing the breakdown are being developed. It has not been properly diagnosed.

(Patent Literature)

Unexamined Patent Publication No. 10-2016-0094216 (published on Aug. 09, 2016) "ESS Battery RACK"

The present invention was devised to solve the above problems,

The present invention is a PV-ESS integrated solution system with reinforced safety functions that enable rapid preparation for fire, earthquake, etc. by pre-diagnosing the safety according to the temperature, arc, and earthquake monitoring information of the ESS device and notifying the user. There is a purpose to provide.

An object of the present invention is to provide a PV-ESS integrated solution system with enhanced safety functions to increase the accuracy of monitoring by accurately determining and reporting the degree of overheating of an ESS device according to temperature and the degree of fire risk due to arc occurrence. have.

In the present invention, when an earthquake is detected, the operation of the ESS device is stopped to minimize the damage caused by the earthquake, and the earthquake is monitored only when the ESS device is shaken over a certain degree, thereby power consumption due to earthquake monitoring. The purpose is to provide a PV-ESS integrated solution system with enhanced safety functions that can minimize

The present invention calculates the safety index according to the temperature of the ESS device, the difference between the temperature of the ESS device and the external temperature, and the number of arc occurrences, and generates a fire risk alarm accordingly, thereby enabling a more accurate alarm of the fire risk. The purpose is to provide a PV-ESS integrated solution system with enhanced functions.

The present invention is not a condition diagnosis through a comparison of the actual power generation amount compared to the calculated power generation amount predicted value of a specific solar power generation device, but a grouped photovoltaic power generation through a trend analysis of the generation amount in the same period in the past through machine learning using artificial intelligence. The purpose of this is to provide a PV-ESS integrated solution system with enhanced safety functions to increase the accuracy of the condition diagnosis by comparing the difference in power generation within the power generation devices and diagnosing the state of a specific photovoltaic power generation device.

The present invention processes, refines, and corrects power generation data in consideration of the failure/maintenance history, surrounding weather and environmental information, and facility characteristics of each photovoltaic device, thereby forming a group, thereby diagnosing accuracy through precise grouping. The purpose of this is to provide a PV-ESS integrated solution system with enhanced safety functions that enable the improvement of the system.

The present invention compares abnormality diagnosis with actual abnormality and changes the standard of the degree of processing, refinement, and correction to be applied to grouping, thereby enhancing the safety function that enables the establishment of a more accurate abnormality diagnosis system as time passes. -The purpose is to provide an ESS integrated solution system.

An object of the present invention is to provide a PV-ESS integrated solution system with enhanced safety functions that enable not only failure of a solar power generation device but also failure prediction and diagnosis of deterioration within a certain period of time.

In the present invention, power generation efficiency is increased by leveling the power output from each string, and this leveling process is performed through charging and discharging of the power storage unit connected to each string, so that a simple configuration of the device is possible, and an abnormality of each string is diagnosed. The purpose of this is to provide a PV-ESS integrated solution system with enhanced safety functions.

The present invention is implemented by an embodiment having the following configuration in order to achieve the above object.

According to an embodiment of the present invention, a PV-ESS integrated solution system according to the present invention includes a photovoltaic device for generating power using sunlight; ESS device for storing power produced by the solar power generation device; Includes a diagnostic server for diagnosing and managing the state of the photovoltaic power generation device and the ESS device, wherein the diagnostic server includes an ESS management unit that detects and notifies a danger according to temperature, arc, and earthquake monitoring information measured by the ESS device. Characterized in that.

According to another embodiment of the present invention, in the PV-ESS integrated solution system according to the present invention, the ESS management unit includes an overheat monitoring unit that generates an alarm by monitoring overheating according to the temperature of the ESS device, and the overheat detection unit The temperature information receiving module that receives the temperature information of the ESS device, the temperature rise time determination module that determines whether the temperature rise time of the received ESS device continues for a certain period of time, and the temperature rise does not continue for a certain period of time. A temperature rise rate determination module that determines whether the temperature rise rate exceeds a set value, and a temperature rise maintenance time determination module that determines whether the time for which the temperature rise rate exceeds the set value is maintained exceeds the set time. And, an overheating alarm module for generating an alarm for overheating when the temperature increase continues for a predetermined time or longer by the temperature rise time determination module or when an exceeding of the set time is detected by the temperature rise maintenance time determination module. It is characterized by that.

According to another embodiment of the present invention, in the PV-ESS integrated solution system according to the present invention, the ESS management unit is an arc monitoring that generates an alarm about the risk of fire according to information about the arc generated in the ESS device. A unit, wherein the arc monitoring unit includes an arc information receiving module that receives information about an arc generated from an ESS device, an arc occurrence count determination module that determines whether the number of arc occurrences exceeds a set number of times for a certain period of time; Arc occurrence time determination module that determines whether the duration of the arc exceeds a set time, and arc occurrence when it is determined that the arc generation exceeds the set number or time by the arc generation frequency determination module or the arc generation time determination module. It characterized in that it comprises an arc alarm module for generating an alarm.

According to another embodiment of the present invention, in the PV-ESS integrated solution system according to the present invention, the ESS management unit recognizes and alerts the earthquake risk according to the shaking information detected by the ESS device, and controls the operation of the ESS device. The earthquake monitoring unit receives a signal about the degree of shaking measured by the ESS device and detects the shaking of the ESS device, and the shaking detection module detects the shaking of the ESS device. An earthquake monitoring module that starts monitoring for earthquakes, an operation stop module that stops the operation of the ESS device when it is judged as an earthquake by detecting the intensity and duration of shaking by the earthquake monitoring module, and stops the operation of the ESS device. An earthquake alarm generation module that generates an earthquake-related alarm together, an automatic restart module that automatically resumes the operation of the ESS device when an earthquake stop is detected by the earthquake monitoring module, and an earthquake monitoring when an earthquake stop is detected. It characterized in that it comprises a standby conversion module for stopping.

According to another embodiment of the present invention, in the PV-ESS integrated solution system according to the present invention, the ESS management unit calculates a safety index for a fire risk according to the temperature and arc occurrence of the ESS device, and thus a fire risk alarm. It includes a safety index calculation unit that outputs, and the safety index calculation unit calculates a temperature index calculation module that calculates a temperature index according to the temperature range of the ESS device, and a temperature difference index according to the difference between the ESS device and the external temperature. A temperature difference index calculation module, an arc index calculation module that calculates the arc index according to the number of arc occurrences, and a safety index calculation module that calculates a safety index for fire risk by summing the temperature index, temperature difference index, and arc index. , And a fire risk alarm generating module that generates a fire risk alarm when the safety index exceeds a set value.

According to another embodiment of the present invention, in the PV-ESS integrated solution system according to the present invention, the diagnosis server includes a photovoltaic management unit for diagnosing the state of the photovoltaic device based on the power generation amount data of the photovoltaic device. The photovoltaic management unit comprises a grouping unit for grouping photovoltaic devices with similar power generation trends in the past, and a specific photovoltaic device representing the amount of power generated outside the error range within the grouped photovoltaic photovoltaic devices. A power generation data collection module for collecting power generation amount information of the photovoltaic device; A power generation data processing module for processing power generation information through information such as failure history and maintenance history of each photovoltaic device; A power generation data purification module for refining power generation information processed according to weather information and environmental information of a region where each photovoltaic power generation device is located; A power generation data correction module for correcting the refined power generation data according to the facility characteristics of each photovoltaic device; And a grouping module for grouping photovoltaic devices by applying a clustering algorithm to the corrected power generation data.

According to another embodiment of the present invention, in the PV-ESS integrated solution system according to the present invention, the grouping unit includes a group optimization module for optimizing a group by feeding back a diagnosis result of the abnormality diagnosis unit, and the group optimization module A diagnostic verification module for verifying accuracy of the abnormality diagnosis by comparing information of the solar power generation device diagnosed as an abnormality by the abnormality diagnosis unit and the solar power generation device in which the actual abnormality has occurred; An index control module that adjusts the degree of modification of the power generation data by the power generation data processing module, power generation data purification module, and power generation data correction module so that the abnormality diagnosis and the actual abnormality are matched for the photovoltaic power generation device in which the abnormality diagnosis does not match. and; And a group automatic change module for changing a group according to the degree adjusted by the index control module.

According to another embodiment of the present invention, in the PV-ESS integrated solution system according to the present invention, the group optimization module processes the power generation data for a photovoltaic device in which the abnormality diagnosis by the abnormality diagnosis unit does not match. A module, a power generation data refining module, and an index comparison module for comparing the degree of modification of the power generation data by the power generation data correction module, and the index control module is the power generation data processing module according to the result compared by the index comparison module. , A power generation data refining module, and a power generation data correction module, a module having a large degree of revised power generation data is adjusted as a priority.

According to another embodiment of the present invention, in the PV-ESS integrated solution system according to the present invention, the abnormality diagnosis unit diagnoses a specific photovoltaic device as a failure, which indicates the amount of power generated outside a certain error range within the same group. A diagnostic unit; If the error range diagnosed as a failure is not out of the range, but the generation amount of the error in a specific range continues for a certain period of time, the risk index is calculated using the error degree and duration, and the time predicted to occur according to the risk index is calculated and notified. A failure risk prediction unit; Including a deterioration detection unit that detects deterioration of a specific photovoltaic device by analyzing the rate of change of the generation amount error, although a signal regarding a failure has not been output, the failure risk prediction unit is a photovoltaic power generation device having an error range of a certain degree or more. An error monitoring module that monitors errors in power generation, a duration measurement module that measures the duration of the error, a risk index calculation module that calculates a risk index according to the degree and duration of the error, and a failure prediction time point according to the risk index. And a failure prediction information notification module that calculates and informs, and the deterioration detection unit includes a slope calculation module that calculates a slope according to a degree of change of an error for a certain period, and a threshold check module that measures a degree of whether the slope deviates from a set threshold. , A time information measurement module that measures a time out of the threshold value, and a deterioration alarm module that notifies when the degree of deterioration is out of a certain range by calculating the degree of deterioration according to the degree and duration of the slope deviating from the threshold value. .

According to another embodiment of the present invention, in the PV-ESS integrated solution system according to the present invention, the photovoltaic device is connected to each of the photovoltaic devices and a plurality of strings in the array of each photovoltaic device. A string leveling unit that minimizes power deviation between strings due to shade or failure in a specific module when an abnormality occurs in the power generation device, wherein the string leveling unit measures a power measurement unit that measures output currents or voltages for each of a plurality of strings, and a plurality of strings. A power storage unit for compensating or absorbing power for each power unit, and a control unit for controlling an operation of the power storage unit based on data of the power measurement unit, wherein the control unit includes a storage state determination module for determining a state of a charge amount of the power storage unit and , A storage control module that controls charging and discharging of the power storage unit according to the state of the charge amount of the power storage unit, and a connection control module that adjusts the connection between the power storage unit and the string according to whether each string is charged or discharged, and the storage control module Is a discharge control module that supplies power to a string whose output is degraded when the charging amount of the power storage unit is sufficient, and a charging control module that minimizes power deviation between strings by absorbing the power of a string having a high output when the charging amount of the power storage unit is insufficient. Including, the connection control module is a compensation connection module that connects the power storage unit and the string to be supplied with power when the power storage unit is discharged by the discharge control module, and the power storage unit is charged by the charging control module. In this case, it is characterized in that it comprises an absorption connection module that connects the string to be supplied with power and the power storage unit.

According to another embodiment of the present invention, in the PV-ESS integrated solution system according to the present invention, the string leveling unit includes a string diagnosis unit for detecting an abnormal string, and the string diagnosis unit is performed by the connection control module. A connection string detection module that senses a connected string, a charge/discharge recognition module that recognizes the charge/discharge of the string sensed by the connection string detection module, and a charge that measures the degree of charge/discharge perceived by the charge/discharge recognition module. A discharge measurement module, an abnormality index calculation module that calculates the abnormality index of each string according to the charge/discharge degree measured by the charge/discharge measurement module, and the abnormality index of each string calculated by the abnormality index calculation module for a certain period of time. An abnormality index accumulation module to accumulate, and an abnormality string diagnosis module for diagnosing a corresponding string as a string in which an abnormality has occurred when the accumulated abnormality index exceeds a predetermined value.

The present invention can obtain the following effects by the configuration, combination, and use relationship to be described below with the present embodiment.

According to the present invention, safety is diagnosed in advance according to the temperature, arc, and earthquake monitoring information of the ESS device and notified to the user, thereby enabling rapid preparation for fire, earthquake, and the like.

The present invention has the effect of increasing the accuracy of monitoring by accurately determining and reporting the degree of overheating of the ESS device according to the temperature and the degree of fire risk due to the occurrence of an arc.

In the present invention, when an earthquake is detected, the operation of the ESS device is stopped to minimize the damage caused by the earthquake, and the earthquake is monitored only when the ESS device is shaken over a certain degree, thereby power consumption due to earthquake monitoring. It has the effect of minimizing.

The present invention calculates the safety index according to the temperature of the ESS device, the difference between the temperature of the ESS device and the external temperature, and the number of arc occurrences, and generates a fire risk alarm accordingly, thereby enabling a more accurate alarm of the fire risk. There is.

The present invention is not a condition diagnosis through a comparison of the actual power generation amount compared to the calculated power generation amount predicted value of a specific solar power generation device, but a grouped photovoltaic power generation through a trend analysis of the generation amount in the same period in the past through machine learning using artificial intelligence. There is an effect of increasing the accuracy of the condition diagnosis by diagnosing the state of a specific photovoltaic device by comparing the difference in the amount of power generated within the power generation devices.

The present invention processes, refines, and corrects power generation data in consideration of the failure/maintenance history, surrounding weather and environmental information, and facility characteristics of each photovoltaic device, thereby forming a group, thereby diagnosing accuracy through precise grouping. There is an effect that enables the improvement of.

The present invention has the effect of making it possible to construct a more accurate abnormality diagnosis system as time passes by changing the criteria of the degree to be processed, refined, and corrected by comparing the abnormality diagnosis with the actual abnormality and applying it to the grouping.

The present invention has the effect of enabling not only a failure of a photovoltaic device, but also prediction of a failure within a certain period and diagnosis of deterioration.

In the present invention, power generation efficiency is increased by leveling the power output from each string, and this leveling process is performed through charging and discharging of the power storage unit connected to each string, so that a simple configuration of the device is possible, and an abnormality of each string is diagnosed. There is an effect that allows you to do it.

1 is a configuration diagram of a PV-ESS integrated solution system with enhanced safety functions according to an embodiment of the present invention
2 is a block diagram showing the configuration of the ESS device of FIG. 1
3 is a block diagram showing the configuration of the diagnostic server of FIG. 1
Figure 4 is a block diagram showing the configuration of the ESS management unit of Figure 3
5 is a reference diagram showing a state in which photovoltaic devices are grouped to perform diagnosis in the present invention
6 is a block diagram showing a configuration of a grouping unit of FIG. 3
7 is a block diagram showing the configuration of the abnormality diagnosis unit of FIG. 3
8 is a conceptual diagram including a string leveling unit in the photovoltaic device of FIG. 1
9 is a detailed configuration diagram of the string leveling unit of FIG. 8
10 is a block diagram showing the configuration of the control unit of FIG. 9
11 is a block diagram showing the configuration of the string diagnosis unit of FIG. 9

Hereinafter, preferred embodiments of the PV-ESS integrated solution system with enhanced safety functions according to the present invention will be described in detail with reference to the accompanying drawings. In the following description of the present invention, when it is determined that a detailed description of a known function or configuration may unnecessarily obscure the subject matter of the present invention, a detailed description thereof will be omitted. Throughout the specification, when a part "includes" a certain component, it means that other components may be further included, and other components are not excluded unless specifically stated to the contrary, and also described in the specification. Terms such as "... unit" and "... module" mean a unit that processes at least one function or operation, which may be implemented by hardware or software, or a combination of hardware and software.

A PV-ESS integrated solution system with enhanced safety functions according to an embodiment of the present invention will be described with reference to FIGS. 1 to 11, wherein the PV-ESS integrated solution system is a photovoltaic device that generates power using sunlight. (3); ESS device 1 for storing power produced by the photovoltaic device 3; And a diagnosis server 5 for diagnosing and managing the state of the photovoltaic device 3 and the ESS device 1.

The PV-ESS integrated solution system according to the present invention monitors the temperature of the ESS device 1 and the occurrence of arcs in real time in order to prepare for frequent fire accidents of the ESS device 1 so that the risk of fire can be recognized in advance, Earthquakes can be monitored so that rapid preparation can be made. In addition, the present invention diagnoses failures and abnormalities of the solar power generation device 3 so that a quick response can be made. In particular, the photovoltaic power generation devices 3 are grouped to diagnose failures and abnormalities. To be able to diagnose.

The ESS device 1 stores power produced by the photovoltaic device 3 and supplies power to each load as needed, and includes a plurality of battery modules to perform repetitive charging and discharging. In addition, the ESS device 1 includes a configuration such as a connection board and a distribution board for charging and discharging power, and a plurality of battery modules are accommodated in facilities such as a battery rack and installed in a sealed space together with a connection board and a distribution board. . Accordingly, the ESS device 1 generates a lot of heat and has a very high fire risk as it is formed in an enclosed space, and when a fire occurs, not only power is cut off, but also enormous damage is caused to the surroundings. Accordingly, the ESS device 1 detects temperature, arc occurrence, and shake in real time and transmits it to the diagnosis server 5. To this end, the ESS device 1 may include a temperature sensing unit 11, an arc sensing unit 13, and an earthquake sensing unit 15.

The temperature sensing unit 11 is configured to measure the temperature of the ESS device 1, and may preferably measure the temperature of a battery rack in which batteries are accommodated, but is not limited thereto. In addition, the temperature sensing unit 11 may additionally measure the temperature around the ESS device 1 and transmit it to the diagnosis server 5, through which the safety index of the ESS device 1 can be calculated. . A detailed description of this will be described later. Accordingly, the temperature sensing unit 11 may include a first temperature sensor 111 that measures the temperature of the ESS device 1 and a second temperature sensor 113 that measures the temperature around the ESS device 1. have. At this time, the temperature measured by the first temperature sensor 111 is monitored by the overheating monitoring unit 511 of the ESS management unit 51 to be described later, and the safety index calculation unit 517. It is used to calculate the safety index, and the temperature measured by the second temperature sensor 113 may be used to calculate the safety index by the safety index calculation unit 517.

The arc sensing unit 13 is configured to detect an arc generated in the ESS device 1 and transmit it to the diagnosis server 5, so that a UV sensor may be applied. Accordingly, the arc sensing unit 13 generates a discharge pulse according to the occurrence of an arc, and analyzes the pulse signal to detect the number, time, and intensity of the arc.

The earthquake sensing unit 15 is configured to detect an earthquake by sensing shaking of the ESS device 1, and an acceleration sensor may be applied. The earthquake sensing unit 15 detects the shaking of the ESS device 1 and transmits information about the shaking to the diagnosis server 5 when the shaking exceeds a certain value, and starts monitoring the earthquake.

The photovoltaic device 3 is a device that generates electrical energy using sunlight (light energy), and the solar modules 31 of the minimum unit are gathered to form a string 32 and an array 33, Arrays 33, which are generally referred to as solar panels, are clustered to form the solar power generation device 3. The photovoltaic power generation device 3 in the present invention does not mean only a photovoltaic power plant installed on the ground, but various forms including a building-integrated photovoltaic device (BIPV) installed on the roof of a building, on the water surface, or on the exterior wall of a building, etc. Including the solar power generation device (3). In addition, power produced by the photovoltaic device 3 is stored in the ESS device 1. The photovoltaic device (3) includes a string (32) in which a photovoltaic module (31) is connected in series to form a series circuit, an array (33) formed by connecting a plurality of strings (32) in parallel, and solar light. An inverter 34 that converts the DC power generated by using the DC power to AC power and supplies it to the customer, and a connection board 35 that facilitates connection between the array 33 and the inverter 34 and performs various protection functions, etc. It includes the configuration of, which is a common configuration constituting the photovoltaic device 3, and a separate description will be omitted.

The diagnosis server 5 diagnoses and manages the state of the photovoltaic device 3 and the ESS device 1, and the ESS management unit 51 and the photovoltaic device ( It may include a photovoltaic management unit 53 to manage 3).

The ESS management unit 51 receives signals related to the temperature, arc generation, and shake of the ESS device 1 to detect the dangers. In particular, the safety index is calculated according to the temperature and arc generation to reduce the risk of fire. To be able to generate an alarm. To this end, the ESS management unit 51 may include an overheating monitoring unit 511, an arc monitoring unit 513, an earthquake monitoring unit 515, and a safety index calculation unit 517.

The overheat monitoring unit 511 is configured to monitor overheating of the ESS device 1 according to the temperature measured by the temperature sensing unit 11, in particular, the first temperature sensor 111, and the time when the temperature rises, Depending on the degree of rise, an alarm for overheating should be generated. To this end, the overheating monitoring unit 511 includes a temperature information receiving module 511a, a temperature rise time determination module 511b, a temperature rise rate determination module 511c, a temperature rise maintenance time determination module 511d, and an overheating alarm module. (511e) may be included.

The temperature information receiving module 511a is configured to receive temperature information from the temperature sensing unit 11, in particular, the first temperature sensor 111, and receives temperature information in real time.

The temperature rise time determination module 511b is configured to determine whether or not the rise time exceeds a predetermined value by calculating a time when the temperature of the ESS device 1 rises. For example, the temperature rise time exceeds 2 seconds. If it exceeds 2 seconds, the overheating alarm can be generated.

The temperature rise rate determination module 511c determines the degree to which the temperature rises when the temperature rise time does not exceed a predetermined value by the temperature rise time determination module 511b. Even if the temperature increase rate determination module 511c does not continuously increase for a certain period of time, when the rate of increase exceeds a set degree, an alarm can be generated according to the time that the excess degree is maintained. For example, the temperature increase rate determination module 511c compares the average temperature for a certain time immediately before and the current temperature, and when the degree exceeds two times, the duration of the temperature increase maintenance time determination module 511d is determined. It can be calculated to determine whether or not an alarm is generated.

When the temperature rise maintenance time determination module 511d determines that the temperature rise rate exceeds a set value in the temperature rise ratio determination module 511c, whether the maintenance time in the exceeded state exceeds a set time. As an example, if the exceeded condition continues for more than 4 seconds, an alarm is generated.

The overheating alarm module 511e is configured to generate an alarm according to overheating of the ESS device 1, and the temperature rise time determination module 511b determines whether the temperature rise time exceeds a certain value or the temperature rise maintenance time By the module 511d, an alarm can be generated when the degree of temperature rise exceeds a certain ratio continues for a set time or longer.

The arc monitoring unit 513 is configured to monitor the danger of arc occurrence in the ESS device 1, and generates an alarm according to the number of arc occurrences and time. To this end, the arc monitoring unit 513 may include an arc information receiving module 513a, an arc generation frequency determination module 513b, an arc generation time determination module 513c, and an arc alarm module 513d.

The arc information receiving module 513a is configured to receive information on arc generation measured by the arc sensing unit 13, and generates an alarm according to the number of arc occurrences and arc duration.

The arc occurrence frequency determination module 513b is a configuration that determines whether or not an arc occurs exceeding a set value by calculating the number of arc occurrences for a predetermined unit time, for example, determining whether an arc occurs more than 5 times for 2 seconds. You can do it.

The arc generation time determination module 513c is configured to determine whether the duration of the arc exceeds a set time by calculating the duration of the arc. For example, the arc generation time determination module 513c may determine whether or not it continues for more than 4 seconds.

The arc alarm module 513d is configured to generate an alarm of a fire hazard due to arc occurrence, and the arc occurrence frequency exceeds a set value by the arc occurrence frequency determination module 513b or the arc generation time determination module 513c As a result, an alarm can be generated when the arc duration exceeds the set time.

The earthquake monitoring unit 515 is configured to monitor the occurrence of an earthquake in the ESS device 1, and a shake detection module 515a, an earthquake monitoring module 515b, an operation stop module 515c, an earthquake alarm generation module ( 515d), an operation resume module 515e, and a standby conversion module 515f.

The shaking detection module 515a is configured to receive shaking information transmitted from the earthquake sensing unit 15, and the earthquake sensing unit 15 transmits shaking information when the shaking exceeds a certain value. The detection module 515a receives shaking information and starts monitoring the earthquake by the earthquake monitoring module 515b.

The earthquake monitoring module 515b is configured to monitor earthquakes for the ESS device 1 when shaking information of the ESS device 1 is received by the shaking detection module 515a. It receives information about the shaking in real time and calculates the intensity, frequency, and time of shaking.

The operation stop module 515c is configured to stop the operation of the ESS device 1 when the intensity, number, and time of shaking exceeds a set value during monitoring by the earthquake monitoring module 515b. Can be minimized. For example, the operation stop module 515c may stop the operation of the ESS device 1 when the shaking continues for a predetermined time or longer with a predetermined intensity or more or exceeds a predetermined number of times within a predetermined time.

The earthquake alarm generating module 515d is configured to notify the user when the operation of the ESS device 1 is stopped by the operation stop module 515c, and a quick response to an earthquake can be made.

The operation resumption module 515e is configured to automatically start the operation of the ESS device 1 when the intensity and number of shakings fall below a set value after the operation of the ESS device 1 is stopped. It should be able to automatically and quickly recover from the interruption of the system.

The standby conversion module 515f determines that the earthquake has ended when information about the shaking is not received from the ESS device 1 by the shaking detection module 515a for a certain period of time, and the ESS device 1 senses the earthquake. With the configuration of returning the unit 15 to the standby mode, transmission of the shaking information is stopped until shaking of a predetermined value or more occurs again, thereby minimizing power consumption.

The safety index calculation unit 517 is configured to generate a fire risk alarm by calculating a comprehensive safety index for the risk of fire according to the temperature and arc occurrence of the ESS device 1, and the first temperature sensor 111 Safety according to the temperature of the ESS device 1 measured by ), the temperature around the ESS device 1 measured by the second temperature sensor 113, and the number of arc occurrences measured by the arc monitoring unit 513 Calculate the index. To this end, the safety index calculation unit 517 includes a temperature index calculation module 517a, a temperature difference index calculation module 517b, an arc index calculation module 517c, a safety index calculation module 517d, and a fire risk alarm generation module. (517e) may be included.

The temperature index calculation module 517a is configured to calculate a temperature index according to the temperature of the ESS device 1 measured by the first temperature sensor 111, and may calculate a temperature index according to a temperature range. Accordingly, the temperature index calculation module 517a sets a certain temperature range, and linearly calculates the temperature index within the temperature range, and if it is above the upper limit of the certain temperature range, the lowest temperature index is obtained, and the lower limit of the certain temperature range. If it is below, the highest temperature index can be calculated. For example, the temperature index calculation module 517a sets a temperature range of 50°C to 80°C, and the temperature index is 100 points if it is 50°C or less, 5 points if it is 80°C or more, and linearly between 50°C and 80°C. It can be set to lower the score.

The temperature difference index calculation module 517b is configured to calculate a temperature difference index according to the difference between the temperature measured by the first temperature sensor 111 and the ambient temperature measured by the second temperature sensor 113. The temperature difference index may be calculated according to the range of the temperature difference, such as the index calculation module 517a. Accordingly, the temperature difference index calculation module 517b also linearly changes the temperature difference index in a certain temperature difference range, and if it is more than the upper limit of the certain temperature difference range, the lowest temperature difference index is obtained, and if it is less than the lower limit, the highest temperature difference index is calculated. Can be given. For example, the temperature difference index calculation module 517b sets a temperature difference range of 5°C to 30°C, and if the temperature difference is 5°C or less, 100 points, 30°C or more, 5 points, and between 5°C and 30°C The temperature index can be changed linearly.

The arc index calculation module 517c is configured to calculate an arc index according to the number of arc occurrences, and calculates the arc index according to the number of arc occurrences for a predetermined unit time. The arc index calculation module 517c sets a range of the number of arc occurrences, and within that range, the arc index linearly changes according to the number of arc occurrences, and if it is less than the lower limit of the range, the highest arc index is set, and if it is more than the upper limit, The lowest arc index can be output. For example, the arc index calculation module 517c sets a range of 0 to 50 times, and the highest 100 points if the number of arc occurrences is 0, 5 points if it is 50 times or more, and the number of times between 0 and 50 times. Depending on the arc index can be set to decrease linearly.

The safety index calculation module 517d is configured to calculate the overall safety index for fire risk by summing the temperature index, the temperature difference index, and the arc index.In particular, when the temperature index and the temperature difference index are summed, the temperature index is higher. You can give it a weight. Therefore, the safety index calculation module 517d can calculate the safety index according to temperature by multiplying the temperature index by 0.7 and the temperature difference index by 0.3, and by summing the arc index to this value, the overall safety index can be calculated. To be there.

The fire risk alarm generation module 517e is configured to generate an alarm about the risk of fire when the safety index calculated by the safety index calculation module 517d is less than a set value, and thus, a quick response can be made. .

The photovoltaic management unit 53 diagnoses and manages the state of the photovoltaic device 3, and diagnoses the state based on the power generation data of the photovoltaic device 3. In order to increase the accuracy of diagnosis, the photovoltaic management unit 53 groups the photovoltaic devices 3 having a strong power generation amount for a certain period of time into the same group and diagnoses abnormality when an error in the amount of power generation occurs within the same group. . In the conventional system for diagnosing an abnormality in a solar power generation device, the expected power generation amount that can be generated in the photovoltaic power generation facility is calculated using various prediction techniques, and then, when the actual power generation amount is out of a certain range compared to the expected power generation amount, this Judging from the above, it is approaching with a concept that allows precise diagnosis or maintenance to be performed.This predicted amount of power generation is a problem that the accuracy of the power generation amount forecast is already low because it cannot accurately reflect all of the various factors affecting solar power generation. Therefore, the fault diagnosis technology based on the expected power generation with such a large error range also has a limitation in that the false diagnosis rate of judgment is increased. Accordingly, in the present invention, in the present invention, a grouping unit 531 for grouping the photovoltaic devices 3 having a strong power generation trend in the past same period through the diagnosis server 5, and the photovoltaic power generation device of the same group ( 3) It includes an abnormality diagnosis unit 533 for selecting a specific solar power generation device 3 representing the amount of power generation out of the error range.

The grouping unit 531 is a configuration for grouping (refer to FIG. 5) photovoltaic devices 3 of which the power generation trend of the same period in the past is similar among photovoltaic devices 3, and preferably, artificial intelligence is software-based. Based on the power generation data of the same period in the past, clustering is performed for each of the solar power generation devices 3 with similar trends through machine learning implemented as a method. The grouping unit 531 collects power generation information from each photovoltaic device 3 to analyze the power generation trend, and the failure history or maintenance history of each photovoltaic device 3, surrounding weather information or environment information, and facilities In consideration of characteristics, etc., the power generation data of each photovoltaic device 3 is processed, refined, and corrected, and the modified power generation data is used to more accurately classify the group. In addition, the grouping unit 531 compares the result of the abnormality diagnosed by the abnormality diagnosis unit 533 for each set group and the information on the actual abnormality to verify the accuracy, and determines the group according to the verified result. By automatically updating and optimizing, the accuracy of abnormality diagnosis can be further improved over time. To this end, the grouping unit 531 is a power generation data collection module 531a, a power generation data processing module 531b, a power generation data purification module 531c, a power generation data correction module 531d, as shown in FIG. A module 531e and a group optimization module 531f may be included.

The power generation data collection module 531a is a component that collects information such as daily generation amount and daily generation amount deviation from each photovoltaic device 3, and can be collected using an internet network such as an IoT network. Basic information is collected for grouping of the power generation devices 3.

The power generation data processing module 531b is configured to process the information collected by the power generation data collection module 531a through information such as failure history and maintenance history of each photovoltaic device 3. That is, even when information on which the amount of power generated by a specific photovoltaic device 3 is rapidly decreased during a specific period is collected, some or most of the photovoltaic device 3 is maintained for reasons such as periodic inspection or failure during that period. If the maintenance is in progress, the power generation data processing module 531b reflects this and corrects and processes the power generation amount information of the corresponding photovoltaic power generation device 3 to obtain accurate power generation amount trend information for the photovoltaic power generation device 3. You will be able to. To this end, the power generation data processing module 531b includes a fault maintenance degree receiving module 531b-1, a fault maintenance time information receiving module 531b-2, a fault maintenance index calculation module 531b-3, and a processing calculation module 531b. -4) may be included.

The failure maintenance degree receiving module 531b-1 is a configuration for receiving information on the degree of failure or maintenance for each solar power generation device 3, and all of each photovoltaic power generation device 3 has a failure. Or, receive information about whether maintenance has been performed, and at what rate the failure or maintenance has been interrupted. For example, the photovoltaic device 3 may include a plurality of arrays 33 and the like as a unit, and when a failure or maintenance work is performed on only some of them, the photovoltaic device 3 may receive information on the ratio. can do. The failure maintenance degree receiving module 531b-1 may receive information according to a separate input from an operator when a failure or maintenance is performed.

The failure maintenance time information receiving module 531b-2 is configured to receive information on a failure or maintenance time, and may also receive information by a separate input from an operator.

The failure repair index calculation module (531b-3) uses the degree and time information on the failure or maintenance received by the failure repair degree receiving module (531b-1) and the failure repair time information receiving module (531b-2). This is a configuration that calculates an index for fault repair (hereinafter referred to as a'fault repair index'), where the fault repair index refers to the degree to which each photovoltaic device (3) is inoperable due to failure or maintenance. Means.

The processing calculation module (531b-4) is a configuration for processing the power generation data using the fault repair index calculated by the fault repair index calculation module (531b-3). Increase the so that it can be modified. For example, in the case where power production is stopped due to a failure or maintenance for 24 hours for 1/3 of the entire array of a specific photovoltaic device 3, the failure repair index can be calculated as 1/3, and the collected The processed power generation data can be calculated by multiplying the daily power generation data of the solar power generation device 3 by 3/2 (1.5 times).

The power generation data purification module 531c is a configuration for minimizing error information on the power generation trend through information such as regional weather information and environment information where each photovoltaic power generation device 3 is located. That is, even if the amount of power generation is similar among the photovoltaic devices 3 in a specific period, the environment in which each photovoltaic device 3 is located, that is, in the case of a situation in which the amount of insolation information, temperature, humidity, etc. differ When grouped into groups showing the same amount of power generation, the reliability of the grouping result is degraded. Therefore, in the power generation data purification module 531c, in addition to the information provided by the power generation data collection module 531a to the power generation data processing module 531b, local weather information, environment information, and By reflecting the same information, error information on the power generation trend of each photovoltaic device 3 is minimized, and through this, reliable grouping can be performed in the grouping module 531e, which will be described later. To this end, the power generation data purification module 531c may include an environment information receiving module 531c-1, an environment index calculation module 531c-2, and a refinement calculation module 531c-3.

The environmental information receiving module 531c-1 is configured to collect weather and environmental information of a region where each photovoltaic device 3 is located, and allows information such as solar radiation, temperature, and humidity to be received.

The environmental index calculation module 531c-2 is a configuration for calculating an environmental index according to the environmental information received by the environmental information receiving module 531c-1. The environmental index can be calculated according to the following. As an example, the environmental index calculation module 531c-2 may be set to have a higher environmental index as the amount of insolation or temperature is higher, and the environmental index by analyzing the correlation between each environmental information and the amount of power generation based on past power generation data. Can be determined. In addition, in the present invention, since the environmental index and the like are continuously updated by verification of the abnormality diagnosis result, the value of the environmental index and the like is continuously updated according to the use of the system, thereby increasing the accuracy thereof.

The refinement calculation module 531c-3 is configured to refine the processed power generation data by applying the environment index calculated by the environment index calculation module 531c-2. For example, the refined power generation data is the same environmental condition. Refined power generation data can be calculated by multiplying the processed power generation data by the reciprocal of each environmental index so that they can be compared under assumptions.

The power generation data correction module 531d is a configuration for correcting the refined power generation data according to the facility characteristics of each photovoltaic device, and reflects the facility characteristics according to the number of photovoltaic modules 31, the installation angle, and the type of module. To correct it. To this end, the power generation data correction module 531d may include a facility information receiving module 531d-1, a characteristic index calculation module 531d-2, and a correction calculation module 531d-3.

The facility information receiving module 531d-1 is configured to collect facility information for each photovoltaic device 3, and collects information such as the number of photovoltaic modules 31, installation angle or direction, and the type of module. In addition, information registered in the diagnosis server 5 can be loaded. Specifically, each photovoltaic device 3 cannot be said to have the same installation direction, and since the type or number of modules may be different, the amount of power generation is different even if other conditions are the same. Therefore, it is possible to correct the power generation data by using the facility information of each photovoltaic device 3.

The characteristic index calculation module 531d-2 is a configuration that calculates an index according to the facility characteristics of the photovoltaic device 3 that affects the amount of power generation. For example, the number of modules, the ratio of the amount of power generation according to the installation direction, etc. Let's set it. For example, if the number of modules is set to 100, the solar power generation device 3 with 400 solar modules 31 is to be multiplied by 0.25 by the amount of power generation data. Compared to that, when the amount of power generation is only 50%, the power generation data can be doubled for the north-facing photovoltaic device (3), and the photovoltaic module (31) is 400 and the photovoltaic device (3) facing north. For each, a characteristic index of 0.25 X 2 = 0.5 can be calculated.

The correction calculation module 531d-3 is configured to correct the power generation data according to the characteristic index calculated by the characteristic index calculation module 531d-2, and the characteristic index calculated in consideration of the number of modules and the installation direction, etc. Apply it to the power generation data. Accordingly, when the characteristic index is calculated as 0.5 as described above, the correction data can be calculated by multiplying the power generation data by 0.5, and the power generation data can be corrected according to various formulas and criteria.

The grouping module 531e applies a clustering algorithm (a program that clusters based on a clustering criterion) to the data calculated by the power generation data correction module 531d to group the photovoltaic devices 3 into groups showing similar power generation trends. It is a configuration.

As an example, the grouping module 531e may perform grouping of power plants for each of the solar power generation devices 3 with the most similar daily deviation based on the daily cumulative power generation data for a certain period of time for each photovoltaic power generation device 3. I can. This is achieved by grouping by photovoltaic power generation devices (3) showing the most similar daily power generation pattern by reflecting the corresponding environmental information, maintenance history information, and facility characteristics of each photovoltaic power generation device (3). If any one of the power generation devices 3 shows a daily power generation pattern that is out of the error range differently from the other photovoltaic devices 3, the abnormality diagnosis unit 533 will diagnose the abnormality.

As another example, the grouping module 531e is for each photovoltaic device 3 having the most similar average power generation rate based on the average power generation rate trend (data) for a certain period of time for each photovoltaic device 3 Grouping of power plants can be carried out. This is by grouping by photovoltaic devices (3) showing the most similar power generation pattern over a certain period, so that one of the grouped photovoltaic devices (3) is averaged differently from other photovoltaic devices (3). If the previous day's power generation is out of the error range compared to the power generation rate, the abnormality diagnosis unit 533 will diagnose the abnormality.

As another example, the grouping module 531e groups power plants by photovoltaic devices 3 having the most similar deviation in the maximum daily generation amount considering the installed capacity based on the trend (data) of the maximum daily power generation compared to the installed capacity for a certain period of time. You can proceed. This is grouped based on the data of the shortest period of time compared to the accumulated data or average data, and based on this, the abnormality diagnosis unit 533 detects that the deviation of the maximum amount of power generation per day is out of the error range compared to other solar power generation devices 3 in the group By diagnosing whether or not, it has characteristics that can be diagnosed relatively quickly.

The group optimization module 531f is a configuration that updates and optimizes the group set by the grouping module 531e according to use, and the abnormality information of the photovoltaic power generation device 3 diagnosed by the abnormality diagnosis unit 533 and The accuracy is verified by comparing the actual abnormality information, and each index is corrected accordingly so that regrouping can be performed. The group optimization module 531f modifies the fault repair index, environment index, and characteristic index if the diagnosis result does not coincide with the actual result so that the diagnosis result coincides with the reality, and the correction of each index is the degree of reflection of the power generation data. Adjustment can be made from the largest index of. To this end, the group optimization module 531f includes a diagnostic verification module 531f-1, an index comparison module 531f-2, an index control module 531f-3, and an automatic group change module 531f-4. I can.

The diagnostic verification module 531f-1 is configured to verify the accuracy of the abnormality diagnosis, and the abnormality diagnosis of the photovoltaic power generation device 3 by the abnormality diagnosis unit 533, more precisely, a failure diagnosis unit 533a to be described later. ) To verify the failure of the photovoltaic device (3) and the actual photovoltaic device (3). Accordingly, the diagnostic verification module 531f-1 adjusts each index and performs regrouping so that the results are matched when the diagnosed failure status and the actual failure occurrence do not coincide.

The index comparison module 531f-2 is configured to compare each index when the diagnosis result does not coincide with the actual index. The index for changing the power generation data to the largest ratio by comparing the failure repair index, environment index, and characteristic index From this, the index can be adjusted by the index control module 531f-3.

The index control module (531f-3) is configured to match the diagnosis result of the failure by the abnormality diagnosis unit 533 and the actual failure result by adjusting each index, and compared by the index comparison module (531f-2). According to the result, the adjustment is made from the index that has the greatest influence on the generation data. However, the index control module 531f-3 allows the range that can be adjusted for each index to be determined in advance, and if the failure result does not coincide with the adjustment up to the corresponding range, the index that has the next greatest influence is determined in advance. Adjust so that you can match the results. Accordingly, the index control module 531f-3 may be adjusted sequentially for each index, and may be adjusted by changing a set range until the results match.

The automatic group change module 531f-4 automatically changes and regroups the group according to the index adjusted by the index control module 531f-3. Accordingly, the group automatic change module 531f-4 automatically improves the accuracy of grouping as time passes, thereby increasing the accuracy of abnormality diagnosis.

The abnormality diagnosis unit 533 is a configuration for selecting a specific photovoltaic device 3 representing the amount of power generation out of the error range within the grouped photovoltaic devices 3, in addition to simply diagnosing the occurrence of a failure. Although a failure has not occurred, a risk of a failure occurring within a certain period can be diagnosed and predicted, and even if it is not a failure risk, it can be detected and notified that the output of the photovoltaic device 3 is deteriorating. To this end, the abnormality diagnosis unit 533 may include a failure diagnosis unit 533a, a failure risk prediction unit 533b, and a deterioration detection unit 533c, as shown in FIG. 7.

The failure diagnosis unit 533a is a configuration for diagnosing a failure of the photovoltaic device 3, and the generation amount deviation within the photovoltaic devices 3 designated as the same group by the grouping unit 531 is a certain error. The photovoltaic device 3 that is out of range is diagnosed as a failure. Accordingly, the fault diagnosis unit 533a compares the generation amount of the previous day and the generation amount of the present day according to the grouping criteria, and when any one of the cumulative daily generation amount, the average generation rate, and the maximum generation amount is out of the error range, the solar power generation device 3 Diagnose as a malfunction.

The failure risk prediction unit 533b predicts that there is a risk of failure within a certain period of time when the error range is not diagnosed as a failure, but if a certain range of errors persists for a certain period of time or more, it can be notified. To this end, the failure risk prediction unit 533b calculates a risk index according to an error range and time, and may set and notify a period of high risk of failure according to the risk index. The failure risk prediction unit 533b includes an error monitoring module 533b-1, a duration time measurement module 533b-2, a risk index calculation module 533b-3, and a failure prediction information notification module 533b-4. do.

The error monitoring module 533b-1 is a configuration that continuously monitors the deviation of the generation amount of a specific photovoltaic device 3 within the same group, and monitors the risk index according to the error degree and time. Make it possible to calculate. Here, the deviation of the generation amount may be any one of the cumulative daily generation amount, the average generation rate, and the maximum generation amount, as in the case of fault diagnosis, and the set range is a lower value than the error range diagnosed as a malfunction, This means a high range.

The duration measurement module 533b-2 is configured to measure the duration when an error corresponding to the range set by the error monitoring module 533b-1 is detected, and a risk index is calculated according to the duration. To be able to.

The risk index calculation module 533b-3 is configured to calculate a risk index according to an error degree and duration, and the risk index may have a higher value as the error increases and the duration increases. Therefore, the higher the risk index calculated by the risk index calculation module 533b-3, the higher the risk of a failure occurring in a short time.

The failure prediction information notification module 533b-4 is a configuration that provides information on a time point at which a failure is likely to occur according to a risk index calculated by the risk index calculation module 533b-3, and failure according to the risk index A time point at which this is likely to occur is set in advance, and information can be provided accordingly. The time point information according to the risk index can be set based on experimental or historical data.For example, the risk index is divided into 10 sections and within 10 days for the highest section, within 10 days for the second section, etc. According to each section of the risk index, it is possible to predict and provide the time point at which the risk of failure is high.

The deterioration detection unit 533c does not correspond to failure diagnosis or failure risk prediction, but when the rate of change of the generation amount error exceeds a predetermined value and continues for a predetermined time or longer, it detects that the output of the photovoltaic device 3 is deteriorating. Make it possible to alert you. To this end, the deterioration detection unit 533c includes a slope calculation module 533c-1, a threshold check module 533c-2, a time information measurement module 533c-3, and a deterioration alarm module 533c-4. I can.

The slope calculation module 533c-1 is configured to calculate the slope according to the change rate of the generation amount error of the photovoltaic device 3, and within the same group as the failure diagnosis unit 533a and the failure risk prediction unit 533b. To calculate the rate of change of the specific solar power generation device (3) generation error. Also, the slope calculation module 533c-1 also calculates the rate of change of the generation amount error according to the grouping criterion, and when the slope exceeds a threshold value, the duration is measured so that an alarm for deterioration can be made.

The threshold check module 533c-2 is a configuration that checks whether the slope calculated by the slope calculation module 533c-1 exceeds a set threshold value, and when the threshold value is exceeded, the duration can be measured. To be there.

The time information measurement module 533c-3 enables the threshold confirmation module 533c-2 to measure the duration of the excess slope when it is determined that the rate of change of the error exceeds the threshold value.

The deterioration alarm module 533c-4 determines that the deterioration of the photovoltaic device 3 is in progress when the slope exceeding the threshold value continues for a predetermined time or longer, so that it can be notified to an operator, etc. So that management can be carried out. Accordingly, the present invention makes it possible to predict a failure or detect deterioration in advance even before a failure occurs, thereby making the operation and maintenance of the photovoltaic device 3 easier and cost saving.

According to another embodiment of the present invention, the photovoltaic device 3 can perform optimal photovoltaic power generation even before maintenance such as cleaning or replacement is performed on the photovoltaic device 3 diagnosed as having an abnormality. It may further include a string leveling unit 36 to enable. In this case, the string leveling unit 36 to be provided in the present invention is not limited to a method of compensating for low power for the difference in power generation generated between the series circuits (strings) constituting the solar power generation panel (array) as in the past. , It is characterized in that the solar power generation efficiency is increased by leveling the generated power between the strings in a manner that minimizes or eliminates the power deviation between the strings. Therefore, the present invention allows the abnormality diagnosis of the photovoltaic power generation device 3 to be made by the abnormality diagnosis unit 533, and is efficient by leveling the power between each string 32 until a measure for the abnormality diagnosis is made. By allowing the generation and supply of power to occur, it is possible to minimize damage caused by abnormalities in the photovoltaic device 3.

The string leveling unit 36 is each connected to the plurality of strings 32 to minimize power deviation between the strings 32 due to shade or failure in a specific module 31, and efficient power output is possible. Do it. In particular, the string leveling unit 36 provides a power storage unit 363 connected to each string 32 to minimize power deviation through charging and discharging with each string 32. Equalization of power can be made easily. In addition, the string leveling unit 36 accumulates and stores information on the charging/discharging operation for each string 32 to detect the string 32 in which frequent output deterioration occurs. To this end, the string leveling unit 36 compensates for the power measurement unit 361 for measuring output currents or voltages for each of the plurality of strings 32 and the power for each of the plurality of strings 32 as shown in FIG. 9. A power storage unit 363 that absorbs power, a control unit 365 that controls the power storage unit 363 based on data from the power measurement unit 361, and a string diagnosis that detects the string 32 in which an abnormality has occurred. It may include a part 367.

The power measurement unit 361 is configured to measure output currents or voltages for each of a plurality of strings 32, and for this purpose, each string 32 is configured through sensors 361a separately installed in each of the plurality of strings 32. By measuring the output current and/or voltage, information on the output power for each string 32 is transmitted to the controller 365. 9, the sensors 361a are installed at the end of each string 32 to measure the current and/or voltage output from each string 32 for each of the plurality of strings 32 The power measurement unit 361 may be formed of a current and/or voltage sensor, and the power measurement unit 361 provides information on the output power of each string 32 based on the information transmitted from the sensors 361a. Will be sent to. Through the information measured and transmitted by the power measurement unit 361, whether power in a normal state is produced and output from each string 32, or a failure or shadow of a specific solar module 31 in a specific string 32 As a result, it is possible to check the amount of power output for each string 32, such as whether the amount of power generated is reduced and the reduced power is output.

The power storage unit 363 is configured to compensate for or absorb power for each of the plurality of strings 32, and for this purpose, an energy storage device (ESS) capable of charging and discharging power is connected to each of the plurality of strings 32. The power difference between the parallel connected strings 32 forming the array 33 can be minimized or eliminated by compensating for or absorbing power for each specific string 32.

The control unit 365 is configured to control the power storage unit 363 based on the data of the power measurement unit 361, and targets only the string whose generation amount has decreased due to a shading or failure of a specific module. In the case of the conventional technology that supplies compensation power through a power compensation device, the amount of solar power generation is large because power must be previously stored in a separate power storage device (ESS) in order to compensate for the power in the string with reduced power generation. In the facility, the power storage device (ESS) for power compensation devices is also equipped with a large capacity (for example, in the case of 1 hour compensation with 10 kW generation, the 10 kWh battery capacity must be charged. In order to be prepared for the case, a power storage device with a large battery capacity compared to the photovoltaic power generation capacity must be provided for power compensation, so cost and economic efficiency are greatly reduced, as well as a system connection or configuration for charging a separate power storage device ( There was a problem in that a compensation solar panel, etc.) should be provided. In the present invention, the problem is not solved by simply compensating for the string 32 with reduced output power, but when viewed as a whole, each string ( 32) It is to propose a solution in a way that minimizes or eliminates the power deviation. To this end, the control unit 365 corresponds to the state of the charging amount of the power storage unit 363 determined by the storage state determination module 365a, which determines the state of the charging amount of the power storage unit 363, and the storage state determination module 365a. Accordingly, a storage control module 365b that determines whether to discharge or charge the power storage unit, and a string 32 to compensate for power or absorb power according to whether or not to discharge or charge determined by the storage control module 365b are determined. A connection control module 365c connected to the power storage unit 363 may be included. That is, according to the state of the charge amount of the power storage unit 363 connected to the end of each string 32 in order to minimize the power deviation between the strings 32, when the charge amount is sufficient, the output power is reduced to the string 32 Compensating power is supplied from the storage unit 363 (i.e., discharge of the power storage unit 363) to increase the power of the string 32 to eliminate the overall power deviation between the strings 32. Conversely, when the amount of charge is insufficient, output The power of the string 32 is reduced by absorbing power from the strings 32 having high power to the power storage unit 363 (that is, charging the power storage unit 363) to reduce the overall power deviation between the strings 32. By applying the method of eliminating, the power storage unit 363 does not have a structure in which the power storage unit 363 has to continuously supply the compensation power, so there is no need for the power storage unit 363 to be provided in a large capacity, and the charging of the power storage unit 363 Since discharging is performed within the array 33, there is no need to provide a separate system or configuration for charging the power storage unit 363.

The storage state determination module 365a is configured to determine the state of the charge amount of the power storage unit 363, and the amount of charge of the power storage unit 363 is sufficient to supply compensation power through the storage state determination module 365a. If information on whether the state is in a state is provided, the storage control module 365b to be described later determines whether to discharge or charge the power storage unit 363.

The storage control module 365b is configured to determine whether to discharge or charge the power storage unit 363 according to the state of the charge amount of the power storage unit 363 determined by the storage state determination module 365a. The control module 365b includes a discharge control module 365b-1 that compensates for power to the string 32 whose output power is reduced through the discharge of the power storage unit when the charge amount of the power storage unit 363 is sufficient, and When the amount of charge in the power storage unit 363 is insufficient, a charging control module 365b-2 capable of minimizing power deviation between the strings 32 by absorbing the power of the string 32 having high output power through charging of the power storage unit 363 ) Can be included.

When the amount of charge of the power storage unit 363 determined by the storage state determination module 365a is sufficient, the discharge control module 365b-1 is applied to the string 32 whose output power is reduced through the discharge of the power storage unit based on this. This is a configuration for controlling to compensate for power. The discharge control module 365b-1 compensates for power to the string 32 whose output power is reduced through the discharge of the power storage unit, thereby reducing the overall power deviation between the strings 32. When the control is determined to be minimized, the connection control module 365c, which will be described later, determines the string 32 to compensate for power and connects it to the power storage unit 363, thereby controlling by the discharge control module 365b-1. So that it can be done smoothly.

When the charging amount of the power storage unit 363 determined by the storage state determination module 365a is insufficient, the charging control module 365b-2 charges the power of the string 32 having high output power by charging the power storage unit based on this. The charging control module 365b-2 absorbs power from the string 32 having high output power through charging of the power storage unit, thereby minimizing the power deviation between the strings 32 as a whole. When the control is determined to be controlled, the connection control module 365c, which will be described later, determines the string 32 to absorb power and connects it to the power storage unit 363, thereby facilitating control by the charging control module 365b-2. So that it can be done.

The connection control module 365c is configured to connect with the power storage unit 363 by determining a string 32 to compensate for power or absorb power according to whether or not to discharge or charge determined by the storage control module 365b. , The amount of discharge or charge for each string 32 is determined so that the power output from each string 32 is the same so that the connection can be made. To this end, the connection control module 365c is the output power of the plurality of strings 32 when the discharge control module 365b-1 discharges the power storage unit 363. A compensation connection module 365c-1 for specifying the lowered string 32 and connecting it to the power storage unit 363, and a plurality of compensation connection modules 365c-1 and the charging control module 365b-2 charging the power storage unit 363 An absorption connection module 365c-2 for connecting the string 32 having high output power among the strings 32 of FIG. 2 to the power storage unit 363 may be included.

When the discharge control module 365b-1 discharges the power storage unit 363, the compensation connection module 365c-1 specifies the string 32 whose output power is lowered among the plurality of strings 32 This configuration is connected to the power storage unit 363. For example, referring to FIG. 9, output power is lowered due to shade or failure in a specific solar module 31 in the string 32 1, and the remaining string 32 ) In 2 to 4, when normal output power comes out, when the amount of charge of the power storage unit 363 determined by the storage state determination module 365a is sufficient, power is stored in the discharge control module 365b-1 based on this. When the control is determined to compensate for power to the string 32 1 whose output power is reduced through negative discharge, the compensation connection module 365c-1 specifies the string 32 1 whose output power is reduced to generate power. Compensating power is provided from the power storage unit 363 to the strings 32 and 1 by connecting to the storage unit 363 to minimize the overall power deviation between the strings 32.

When the charging control module 365b-2 charges the power storage unit 363, the absorption connection module 365c-2 stores the string 32 having high output power among the plurality of strings 32 as a power storage unit. As an example, referring to FIG. 9, output power is lowered due to shade or failure in a specific photovoltaic module 31 in the string 32 1, and the remaining string 32 2- In 4, when the amount of charge of the power storage unit 363 determined by the storage state determination module 365a is insufficient in a situation where normal output power is generated, the charging control module 365b-2 performs charging of the power storage unit based on this. When control is determined to absorb power from the strings 32 2 to 4 having high output power, the absorption connection module 365c-2 specifies the strings 32 2 to 4 with high output power to store power. The power storage unit 363 is connected to the unit 363 to absorb electric power from the strings 32 to 4 to be charged, thereby minimizing the overall power deviation between the strings 32.

As described above, the string leveling unit 36 according to the present invention, unlike the prior art, according to the state of the charging amount of the power storage unit 363 connected to each end of the string 32 in order to minimize the power deviation between the respective strings 32, If the amount of charge is sufficient, the power of the string 32 is increased by supplying compensation power from the power storage unit 363 to the string 32 whose output power is degraded, thereby eliminating the overall power deviation between the strings 32, and conversely, the amount of charge. If insufficient, the power is absorbed from the strings 32 having high output power to the power storage unit 363 to lower the power of the string 32 to eliminate the power deviation between the strings 32 as a whole. Since the storage unit 363 does not have a structure in which the compensation power must be continuously supplied, the power storage unit 363 does not need to be provided with a large capacity, and the charging/discharging of the power storage unit 363 can be performed by the corresponding array 33 Since it is performed within the power storage unit 363, there is no need to provide a separate system or configuration only for charging, and charging and discharging are performed without power conversion, thereby increasing efficiency.

The string diagnosis unit 367 accumulates and stores information on the charge/discharge operation for each string 32 through the string leveling unit 36 so that an abnormality of the string 32 that causes frequent output deterioration can be diagnosed. 11, a connection string detection module 367a, a charge/discharge recognition module 367b, a charge/discharge measurement module 367c, an abnormality index calculation module 367d, and an abnormality index accumulation module 367e, as shown in FIG. , It may include an abnormal string diagnosis module (367f).

The connection string detection module 367a is configured to detect the string 32 connected to the power storage unit 363 by the connection control module 365c. Make it measurable.

The charge/discharge recognition module 367b is configured to detect whether the string sensed by the connection string detection module 367a is charged or discharged, and receives information about the operation of the storage control module 365b.

The charge/discharge measurement module 367c measures the amount of power charged and discharged for the sensed string, and is supplied from the power storage unit 363 to each string 32 or the power storage unit 363 from each string 32. Measure the amount of power supplied to ).

The abnormality index calculation module 367d is configured to calculate the abnormality index of each string 32 by measuring the amount of power charged and discharged from each string 32 to the power storage unit 363. This indicates the degree to which the output of each string 32 is degraded. Therefore, the abnormality index calculation module 367d supplies power to the specific string 32 from the power storage unit 363, that is, when discharge occurs, it means that an abnormality has occurred in the corresponding string 32. The abnormality index for a specific string 32 may be calculated according to the amount of power. On the other hand, if the power storage unit 363 is charged from a specific string 32, it means that an abnormality has occurred in the remaining strings 32, not the corresponding string 32. Therefore, the amount of charge through the specific string 32 Accordingly, the abnormality index of the remaining strings 32 can be calculated.

The abnormality index accumulation module 367e accumulates and stores the abnormality index calculated by the abnormality index calculation module 367d. do.

The abnormal string diagnosis module 367f is configured to diagnose an abnormality with respect to the corresponding string 32 when the accumulated abnormality index for each string 32 exceeds a set value. Action can be taken.

In the above, the applicant has described various embodiments of the present invention, but such embodiments are only one embodiment embodying the technical idea of the present invention, and any changes or modifications may be made as long as the technical idea of the present invention is implemented. It should be construed as falling within the scope of.

1: ESS device
11: temperature sensing unit 111: first temperature sensor 113: second temperature sensor
13: Arc sensing unit 15: Earthquake sensing unit
3: solar power generation device
31: solar module 32: string 33: array
34: inverter 35: connection panel 36: string leveling unit
361: power measurement unit 361a: sensor
363: power storage unit 365: control unit 365a: storage state determination module
365b: storage control module 365b-1: discharge control module 365b-2: charge control module
365c: connection control module 365c-1: compensation connection module 365c-2: absorption connection module
367: string diagnosis unit 367a: connection string detection module 367b: charge/discharge recognition module
367c: charge/discharge measurement module 367d: abnormality index calculation module
367e: Fault index accumulation module 367f: Fault string diagnosis module
5: diagnostic server
51: ESS management department
511: overheating monitoring unit 511a: temperature information receiving module
511b: temperature rise time determination module 511c: temperature rise rate determination module
511d: temperature rise maintenance time determination module 511e: overheating alarm module
513: arc monitoring unit 513a: arc information receiving module 513b: arc occurrence frequency determination module
513c: arc generation time determination module 513d: arc alarm module
515: earthquake monitoring unit 515a: shaking detection module 515b: earthquake monitoring module
515c: operation stop module 515d: earthquake alarm generation module
515e: operation resume module 515f: standby switching module
517: safety index calculation unit 517a: temperature index calculation module
517b: temperature difference index calculation module 517c: arc index calculation module
517d: safety index calculation module 517e: fire risk alarm generation module
53: Solar management department
531: grouping unit 531a: power generation data collection module
531b: power generation data processing module 531c: power generation data purification module
531d: power generation data correction module 531e: grouping module 531f: group optimization module
533: abnormality diagnosis unit
533a: failure diagnosis unit 533b: failure risk prediction unit 533c: deterioration detection unit

Claims (11)

Solar power generation device that generates power using sunlight;
ESS device for storing power produced by the solar power generation device;
Includes; a diagnostic server for diagnosing and managing the state of the photovoltaic device and the ESS device,
The diagnostic server,
PV-ESS integrated solution system, characterized in that it comprises an ESS management unit to detect and notify the danger according to the temperature, arc, earthquake monitoring information measured by the ESS device. The method of claim 1, wherein the ESS management unit
It includes an overheating monitoring unit that monitors overheating according to the temperature of the ESS device and generates an alarm,
The overheat detection unit,
The temperature information receiving module that receives the temperature information of the ESS device, the temperature rise time determination module that determines whether the temperature rise time of the received ESS device continues for a certain period of time, and the temperature rise does not continue for a certain period of time. A temperature rise rate determination module that determines whether the temperature rise rate exceeds a set value, and a temperature rise maintenance time determination module that determines whether the time for which the temperature rise rate exceeds the set value is maintained exceeds the set time. And, an overheating alarm module for generating an alarm for overheating when the temperature increase continues for a predetermined time or longer by the temperature rise time determination module or when an exceeding of the set time is detected by the temperature rise maintenance time determination module. PV-ESS integrated solution system, characterized in that. The method of claim 1, wherein the ESS management unit
It includes an arc monitoring unit that generates an alarm about the risk of fire according to the information on the arc generated by the ESS device,
The arc monitoring unit,
The arc information receiving module that receives information about the arc generated from the ESS device, the arc occurrence frequency discrimination module that determines whether the number of arc occurrences exceeds the set number of times for a certain period of time, and the time for which the duration of the arc is set. An arc generation time determination module that determines whether it is exceeded, and an arc alarm module that generates an arc risk alarm when it is determined that the arc generation number or time exceeds the set number or time by the arc generation frequency determination module or the arc generation time determination module. PV-ESS integrated solution system, characterized in that it comprises. The method of claim 1, wherein the ESS management unit
It includes an earthquake monitoring unit that recognizes and alerts the earthquake risk according to the shaking information detected by the ESS device, and controls the operation of the ESS device.
The earthquake monitoring unit,
A shake detection module that detects shake of the ESS device by receiving a signal about the degree of shake measured by the ESS device, and an earthquake monitoring module that starts monitoring for earthquakes when the shake of the ESS device is detected by the shake detection module , An operation stop module that stops the operation of the ESS device when it is judged as an earthquake by detecting the intensity and duration of the shaking by the earthquake monitoring module, and an earthquake alarm that generates an earthquake-related alarm along with stopping the operation of the ESS device. A module and an automatic restart module that automatically resumes the operation of the ESS device when an earthquake stop is detected by the earthquake monitoring module, and a standby conversion module that stops the earthquake monitoring when the earthquake stop is detected. PV-ESS integrated solution system. The method of claim 1, wherein the ESS management unit
It includes a safety index calculation unit that calculates the safety index for fire risk according to the temperature and arc occurrence of the ESS device and outputs a fire risk alarm accordingly,
The safety index calculation unit,
A temperature index calculation module that calculates the temperature index according to the temperature range of the ESS device, the temperature difference index calculation module that calculates the temperature difference index according to the difference between the ESS device and the external temperature, and the arc index according to the number of arc occurrences. The calculated arc index calculation module, the safety index calculation module that calculates the safety index for fire risk by summing the temperature index, temperature difference index, and arc index, and a fire risk alarm when the safety index exceeds the set value. PV-ESS integrated solution system, characterized in that it comprises a fire risk alarm generating module. The method of claim 1, wherein the diagnosis server
It includes a photovoltaic management unit that diagnoses the state of the photovoltaic device based on the generation amount data of the photovoltaic device,
The solar management unit,
Including a grouping unit for grouping photovoltaic devices with similar power generation trends in the past, and an abnormality diagnosis unit for selecting a specific photovoltaic device representing the amount of power generated outside the error range within the grouped photovoltaic photovoltaic devices. ,
The grouping unit,
A power generation data collection module for collecting power generation information of the photovoltaic device; A power generation data processing module for processing power generation information through information such as failure history and maintenance history of each photovoltaic device; A power generation data purification module for refining power generation information processed according to weather information and environmental information of a region where each photovoltaic power generation device is located; A power generation data correction module for correcting the refined power generation data according to the facility characteristics of each photovoltaic device; PV-ESS integrated solution system comprising a grouping module for grouping photovoltaic devices by applying a clustering algorithm to the corrected generation amount data. The method of claim 6, wherein the grouping unit
A group optimization module for optimizing a group by feeding back a diagnosis result of the abnormality diagnosis unit,
The group optimization module,
A diagnostic verification module for verifying accuracy of the abnormality diagnosis by comparing information of the photovoltaic power generation device diagnosed as an abnormality by the abnormality diagnosis unit and the photovoltaic power generation device where an actual abnormality has occurred; An index control module that adjusts the degree of modification of the power generation data by the power generation data processing module, power generation data purification module, and power generation data correction module so that the abnormality diagnosis and the actual abnormality are matched for the photovoltaic power generation device in which the abnormality diagnosis does not match and; PV-ESS integrated solution system comprising a; group automatic change module for changing the group according to the degree adjusted by the index control module. The method of claim 7, wherein the group optimization module
An index comparison module for comparing the degree of modification of the power generation data by the power generation data processing module, the power generation data purification module, and the power generation data correction module with respect to the photovoltaic power generation device in which the abnormality diagnosis by the abnormality diagnosis unit does not match, and ,
The index control module prioritizes a module with a higher degree of modification of the power generation data among the power generation data processing module, power generation data purification module, and power generation data correction module according to the result of comparison by the index comparison module. PV-ESS integrated solution system, characterized in that to. The method of claim 6, wherein the abnormality diagnosis unit
A fault diagnosis unit for diagnosing a specific photovoltaic device indicating a power generation amount out of a certain error range within the same group as a failure; If the error range diagnosed as a failure is not out of the range, but the generation amount of the error in a specific range continues for a certain period of time, the risk index is calculated using the error degree and duration, and the time predicted to occur according to the risk index is calculated and notified. A failure risk prediction unit; Including; a deterioration detection unit for detecting the deterioration of a specific solar power generation device by analyzing the rate of change of the generation amount error although the signal regarding the failure was not output,
The failure risk prediction unit,
An error monitoring module that monitors an error in the amount of generation of solar power generation devices with an error range of a certain degree or more, a duration measurement module that measures the duration of the error, and a risk index that calculates a risk index according to the degree and duration of the error. It includes a calculation module and a failure prediction information notification module that calculates and informs the failure prediction time point according to the risk index,
The deterioration detection unit,
A slope calculation module that calculates the slope according to the degree of change of the error over a certain period of time, a threshold check module that measures the degree of whether the slope is out of a set threshold, a time information measurement module that measures the time out of the threshold, and the slope is a threshold. PV-ESS integrated solution system, characterized in that it comprises a deterioration alarm module that notifies when the degree of deterioration is out of a certain range by calculating the degree of deterioration according to the degree of deviation and duration time. The method of claim 6, wherein the photovoltaic device
Each of the photovoltaic devices includes a string leveling unit that is connected to a plurality of strings in the array of each photovoltaic device to minimize power deviation between strings due to shade or failure in a specific module when an abnormality occurs in the power generation device,
The string leveling unit,
A power measuring unit that measures output currents or voltages for each of a plurality of strings, a power storage unit that compensates or absorbs power for each of the plurality of strings, and a control unit that controls the operation of the power storage unit based on the data of the power measurement unit. And
The control unit,
A storage state determination module that determines the state of the charge amount of the power storage unit, a storage control module that controls charging and discharging of the power storage unit according to the state of the charge amount of the power storage unit, and the connection of the power storage unit and the string according to whether each string is charged or discharged. It includes a connection control module for adjusting the,
The storage control module,
A discharge control module that supplies power to a string with a low output when the charge amount of the power storage unit is sufficient, and a charging control module that minimizes power deviation between strings by absorbing the power of a string having a high output when the charging amount of the power storage unit is insufficient. Includes,
The connection control module,
When the power storage unit is discharged by the discharge control module, a compensation connection module that connects a string to be supplied with power and a power storage unit, and a string to supply power and a power storage unit when the power storage unit is charged by the charging control module PV-ESS integrated solution system, characterized in that it comprises an absorption connection module to connect. The method of claim 10, wherein the string leveling unit
Includes a string diagnosis unit for detecting a string in which an abnormality has occurred,
The string diagnostic unit,
A connection string detection module that senses a string connected by the connection control module, a charge/discharge recognition module that recognizes the charge/discharge of the string sensed by the connection string detection module, and the charge/discharge recognized by the charge/discharge recognition module. A charge/discharge measurement module that measures the degree of, an abnormality index calculation module that calculates an abnormality index of each string according to the charge/discharge degree measured by the charge/discharge measurement module, and the abnormality index calculation module for a certain period of time. PV-ESS integration, characterized in that it includes an abnormality index accumulation module that accumulates an abnormality index of each string, and an abnormality string diagnosis module that diagnoses the corresponding string as an abnormal string when the accumulated abnormality index exceeds a certain value. Solution system.

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