System and method for predicting remaining capacity of energy storage system (ESS)

Abstract

The present invention discloses a system and method for predicting remaining capacity of an ESS. The system according to the present invention includes an ESS controller operably coupled to an energy storage system (ESS) having a plurality of battery racks and a rack controller. The ESS controller may be configured to obtain a state of charge of the battery rack from the rack controller, determine an actual usage pattern of the ESS indicating a change in the state of charge of the ESS for each reference time period, apply an average of the actual usage pattern to an entire period of an end-of-life (EOL) life to determine a remaining capacity of a first ESS at the time of elapse of the EOL life, and record a first deviation between the remaining capacity of the first ESS and a reference remaining capacity.

Description

[Technical field]

[0001] The present invention relates to a system and method for predicting the remaining capacity of an energy storage system (ESS), and more particularly to a system and method for predicting the remaining capacity of an ESS at the end of life (EOL) by analyzing an actual usage pattern of the ESS.

[0002] This application claims priority to Korean Patent Application No. 10-2021-0131983, filed on October 5, 2021, and the contents of the invention described in the priority application are incorporated herein as part of this specification. [Background technology]

[0003] In recent years, the use of renewable energy sources such as solar, wind, and geothermal energy has been gradually increasing due to the environmental pollution problem caused by fossil fuels. Renewable energy is stored in an energy storage system called an ESS. An ESS converts renewable energy into electrical energy, stores it in a battery, and transmits the electrical energy stored in the battery to the power grid. Provided to the public.

[0004] In addition to storing renewable energy, ESSs are also used in homes and factories to store electrical energy from the power grid in batteries during times when electricity rates are low, and then supply the electrical energy stored in the batteries to various electrical devices during daytime hours.

[0005] ESS manufacturers obtain the usage pattern (charge / discharge pattern), daily usage capacity, and usage period of the ESS in advance to design the EOL life. The remaining capacity of the ESS decreases as the usage time increases. decrease The remaining capacity of an ESS refers to the capacity that can be charged or discharged into the ESS. Therefore, when designing the EOL life, the EOL life is designed to be 10, 15, 20 years, etc. so that the remaining capacity of the ESS at the end of EOL is equal to or greater than the usage capacity desired by the customer.

[0006] After installing the ESS at the site of use, ESS manufacturers periodically perform remaining capacity tests on the ESS. The remaining capacity test cycle for ESS is usually one year. The purpose of the remaining capacity test is to check whether the EOL life can be guaranteed based on the time of the test.

[0007] For example, if the EOL life is 20 years and the remaining capacity test time is 10 years after the ESS installation, it is checked whether the remaining capacity of the ESS after 10 years can guarantee the usage capacity desired by the customer.

[0008] If the inspection determines that the EOL life is not guaranteed, the ESS usage log will be obtained and an investigation will be conducted to determine whether the ESS is being operated appropriately in accordance with the usage pattern previously discussed.

[0009] If it is determined that the customer has used the ESS in a manner that exceeds the usage pattern that was considered when the ESS was designed, the ESS manufacturer will either work with the customer to increase the ESS to meet the EOL life or propose to reduce the EOL life guaranteed to the customer.

[0010] The above-mentioned ESS remaining capacity test work requires a huge amount of data analysis, because it is necessary to analyze all past daily usage patterns of the ESS. Therefore, from the perspective of the ESS manufacturer, it is a burden to invest a large amount of human and material costs, from obtaining the data to analyzing it.

[0011] Therefore, in the technical field to which the present invention pertains, there is an urgent need for a technique that can facilitate and simplify the remaining capacity test operation of an ESS. Summary of the Invention [Problem to be solved by the invention]

[0012] The present invention has been devised against the background of the conventional technology as described above, and aims to provide a system and method for predicting the remaining capacity of an ESS, which analyzes the usage pattern of the ESS, predicts the remaining capacity of the ESS when the EOL life has elapsed, records a log of the prediction results, and provides the result to the customer in real time, thereby eliminating the need to perform a remaining capacity test on the ESS. [Means for solving the problem]

[0013] In order to achieve the above technical objective, an ESS remaining capacity prediction system according to one aspect of the present invention includes an ESS controller operably coupled to an energy storage system (ESS) having a plurality of battery racks and a rack controller.

[0014] Preferably, the ESS controller may be configured to obtain a state of charge of the battery rack from the rack controller, determine an actual usage pattern of the ESS indicating a change in the state of charge of the ESS for each reference time interval, apply an average of the actual usage pattern to an entire period of an end-of-life (EOL) life to determine a remaining capacity of a first ESS at the time of an EOL life, and record a first deviation between the remaining capacity of the first ESS and a reference remaining capacity.

[0015] In one aspect, the reference time period may be one day.

[0016] In another aspect, the ESS controller may be configured to determine a remaining capacity of the second ESS at the EOL time by applying an average of the actual usage pattern determined by the reference time up to the current time and applying a usage pattern of the ESS design for a period from the current time to the remaining EOL life, and to record a second deviation between the remaining capacity of the second ESS and the reference remaining capacity.

[0017] In one embodiment, the ESS controller receives a temperature T of the battery rack from the rack controller in a k-th reference time interval (k is an index).k and charge / discharge C rate c k Obtain the temperature T and temperature Attenuation Rate A T Using a predefined correlation between the temperature T k Temperature corresponding to Attenuation Rate A T , k Determine the charge / discharge C rate c and C rate Attenuation Rate A c Using a predefined correlation between the charge and discharge rate C and k C rate corresponding to Attenuation Rate A c,k Determine the discharge depth (Depth of Discharge: DoD) from the actual usage pattern. k ) and determine the depth of discharge DoD and Attenuation Rate A DoD Depth of discharge DoD using a predefined correlation between k The corresponding discharge depth Attenuation Rate A DoD,k and determining a remaining capacity (Capacity1) of the first ESS using the following formula:

[0018]

number

[0019] In another embodiment, the ESS controller receives a temperature T k and charge / discharge C rate ck Obtain the temperature T and temperature Attenuation Rate A T Using a predefined correlation between the temperature T k Temperature corresponding to Attenuation Rate A T,k Determine the charge / discharge C rate c and C rate Attenuation Rate A c Using a predefined correlation between the charge and discharge rate C and k C rate corresponding to Attenuation Rate A c,k Determine the discharge depth (Depth of Discharge: DoD) from the actual usage pattern. k ) and determine the depth of discharge DoD and Attenuation Rate A DoD Depth of discharge DoD using a predefined correlation between k The corresponding discharge depth Attenuation Rate A DoD,k and determining a remaining capacity (Capacity2) of the second ESS using the following formula:

[0020]

number

[0021] In yet another aspect, the ESS controller may be configured to record an event log including a time point when an event occurs in which the first deviation is equal to or greater than a first threshold.

[0022] Furthermore, the ESS controller may be configured to record an event log including a time point when an event occurs in which the second deviation is equal to or greater than a second threshold value.

[0023] In yet another aspect, the system according to the present invention may further include an ESS integrated management device operatively coupled to the ESS controller, the ESS controller being configured to provide the event log to the ESS integrated management device.

[0024] To achieve the above technical objective, a method for predicting remaining capacity of an ESS according to one aspect of the present invention is a method in which an ESS controller operably coupled to an ESS (Energy Storage System) having a plurality of battery racks and a rack controller predicts remaining capacity of the ESS, and may include the steps of: (a) acquiring a state of charge of the battery rack from the rack controller; (b) determining an actual usage pattern of the ESS indicating changes in the state of charge of the ESS for each reference time interval; (c) applying an average of the actual usage pattern to the entire period of the EOL life to determine a remaining capacity of a first ESS at the time of the EOL life elapse; and (d) recording a first deviation between the remaining capacity of the first ESS and a reference remaining capacity.

[0025] Preferably, the reference time period may be one day.

[0026] In another aspect, the method of the present invention may further include determining a remaining capacity of the second ESS at the end of its EOL life by applying an average of the actual usage pattern up to a current time and applying a usage pattern of the ESS design from the current time for the remainder of the EOL life, and recording a second deviation between the remaining capacity of the second ESS and a reference remaining capacity.

[0027] According to one embodiment, the method of the present invention comprises: receiving a temperature T k and charge / discharge C rate c k and the step of acquiring temperature T and temperature Attenuation Rate A T Using a predefined correlation between the temperature T k Temperature corresponding to Attenuation Rate A T , k Steps for determining the charge / discharge C rate c and C rate Attenuation Rate A c Using a predefined correlation between the charge and discharge rate C and k C rate corresponding to Attenuation Rate A c,k The step of determining the discharge depth (Depth of Discharge: DoD) from the actual usage pattern. k ) and the steps to determine the depth of discharge (DoD) and the depth of discharge (DOD) Attenuation Rate A DoD Depth of discharge DoD using a predefined correlation between k The corresponding discharge depth Attenuation Rate A DoD,k and determining a remaining capacity (Capacity1) of the first ESS using the following formula:

[0028]

number

[0029] According to another embodiment, the method of the present invention comprises: receiving a temperature T k and charge / discharge C rate c k and the step of acquiring temperature T and temperature Attenuation Rate A T Using a predefined correlation between the temperature T k Temperature corresponding to Attenuation Rate A T,k Steps for determining the charge / discharge C rate c and C rate Attenuation Rate A c Using a predefined correlation between the charge and discharge rate C and k C rate corresponding to Attenuation Rate A c,k The step of determining the discharge depth (Depth of Discharge: DoD) from the actual usage pattern. k ) and the steps to determine the depth of discharge (DoD) and the depth of discharge (DOD) Attenuation Rate A DoD Depth of discharge DoD using a predefined correlation between k The corresponding discharge depth Attenuation Rate A DoD,k and determining a remaining capacity (Capacity2) of the second ESS using the following formula:

[0030]

number

[0031] In another aspect, the method according to the present invention may further include the step of recording an event log including a time point when an event occurs in which the first deviation is equal to or greater than a first threshold.

[0032] Furthermore, the method according to the present invention may further include a step of recording an event log including a time point of the event occurrence when an event occurs in which the second deviation is equal to or greater than a second threshold value.

[0033] In still another aspect, the method according to the present invention may further include providing the event log to an ESS integrated management device. Effect of the Invention

[0034] According to the present invention, the remaining capacity when the EOL life has elapsed is calculated by considering the actual usage pattern of the ESS and the usage pattern of the design of the ESS, and is stored and managed as log information, thereby making it possible to omit a time-consuming and expensive test of the remaining capacity of the ESS. In addition, by providing the remaining capacity of the ESS when the EOL life has elapsed to a customer, it is possible to help manage the ESS usage pattern and the expansion of the ESS. As an example, if the remaining capacity of the ESS when the EOL life has elapsed is smaller than the remaining capacity of the design, the customer can reduce the daily usage capacity of the ESS or expand the ESS in advance at an appropriate time. As another example, if the remaining capacity of the ESS when the EOL life has elapsed is larger than the remaining capacity of the design, the daily usage capacity can be increased to improve the usage efficiency of the ESS.

[0035] The following drawings attached to this specification are intended to illustrate one embodiment of the present invention and, together with the detailed description of the invention described below, serve to further understand the technical concept of the present invention. Therefore, the present invention should not be interpreted as being limited to only the matters depicted in such drawings. [Brief description of the drawings]

[0036] [Figure 1] 1 is a diagram illustrating a configuration of an ESS remaining capacity prediction system according to an embodiment of the present invention. [Diagram 2] 4 is a graph illustrating an example of an actual usage pattern of an ESS according to an embodiment of the present invention. [Diagram 3] 1 is a graph illustrating an example of a usage pattern of an ESS design according to an embodiment of the present invention. [Figure 4a] 4 is a flowchart showing the flow of a method for predicting remaining capacity of an ESS according to an embodiment of the present invention. [Figure 4b] 4 is a flowchart showing the flow of a method for predicting remaining capacity of an ESS according to an embodiment of the present invention. [Diagram 5] 10 is a flowchart showing the flow of a method for predicting remaining capacity of an ESS according to another embodiment of the present invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0037] Hereinafter, a preferred embodiment of the present invention will be described in detail with reference to the accompanying drawings. Prior to this, the terms and words used in this specification and claims should not be interpreted as being limited to their ordinary or dictionary meanings, but should be interpreted as being in accordance with the meaning and concept of the technical idea of ​​the present invention, in accordance with the principle that the inventor himself can appropriately define the concept of the term in order to best describe the invention. Therefore, it should be understood that the embodiment described in this specification and the configuration shown in the drawings are merely the most preferred embodiment of the present invention, and do not represent the entire technical idea of ​​the present invention, and therefore there may be various equivalents and modifications that can be substituted for them at the time of this application.

[0038] FIG. 1 is a block diagram showing a schematic configuration of an ESS remaining life prediction system 10 according to an embodiment of the present invention.

[0039] With reference to FIG. 1, a system 10 according to an embodiment of the present invention is coupled to an ESS 11 having a plurality of battery racks 12 and a rack controller 13 operably coupled to each battery rack 12 .

[0040] The battery rack 12 includes a plurality of battery cells 12a. The plurality of battery cells 12a may be connected in series and / or parallel. The battery cells 12a may be lithium ion batteries, but the present invention is not limited by the type of cells.

[0041] The battery rack 12 has a structure well known in the ESS technical field. The battery rack 12 includes a shelf on which a plurality of battery cells 12a are mounted, and an air conditioning device such as a cooling fan for adjusting the temperature.

[0042] The multiple battery racks 12 included in the ESS 11 are charged or discharged by a power conversion system (PCS) 20. The PCS 20 is a system that receives power from a renewable energy generator using solar, geothermal, wind, etc. and / or a power grid, stores the power in the ESS 11, and changes electrical characteristics (frequency, voltage, etc.) and performs AC-DC conversion in order to release the energy stored in the ESS 11 to the power grid and / or a power system 23.

[0043] Preferably, the battery rack 12 includes a voltage measuring unit 14, a current measuring unit 15 and a temperature measuring unit 16.

[0044] The voltage measurement unit 14 measures the cell voltages at regular time intervals while the multiple battery cells 12a are being charged or discharged, and outputs the cell voltage measurement values ​​to the rack controller 13. The rack controller 13 receives the cell voltage measurement values ​​and records them in the memory device 13a. The voltage measurement unit 14 may include a voltage measurement circuit known in the art.

[0045] The current measuring unit 15 measures the magnitude of the charge / discharge current at regular time intervals while the multiple battery cells 12a are being charged or discharged, and outputs the current measurement value to the rack controller 13. The rack controller 13 receives the measured charge / discharge current value and records it in the memory device 13a. The rack controller 13 also determines a C-rate of the charge / discharge current and stores it in the memory device 13a. The C-rate of the charge / discharge current can be determined using the magnitude of the charge / discharge current and the capacity of the battery cells 12a. The current measuring unit 15 may be a Hall sensor or a sense resistor that outputs a voltage value corresponding to the magnitude of the current. The voltage value can be converted into a current value according to Ohm's law.

[0046] The temperature measurement unit 16 measures the temperature of the battery rack 12 at regular time intervals while the battery rack 12 is being charged or discharged, and outputs the temperature measurement value to the rack controller 13. The rack controller 13 can receive the rack temperature measurement value and store it in the memory device 13a. Since the temperature of the battery rack 12 is uniformly controlled by an air conditioning device, the rack temperature measurement value can be regarded as the temperature measurement value of the battery cells 12a. Needless to say, it is also possible for the temperature measurement unit 16 to directly measure the temperature of the battery cells 12a.

[0047] The temperature measurement unit 16 may be a thermocouple or a temperature measurement element that outputs a voltage value corresponding to the temperature. The voltage value can be converted to a temperature value using a voltage-temperature conversion lookup table (function).

[0048] The rack controller 13 can determine and store in the memory device 13a the state of charge of the battery rack 12 while the battery rack 12 is being charged or discharged. The state of charge of the battery rack 12 is a sum of the states of charge of the battery cells 12a. Therefore, after the rack controller 13 determines the states of charge for the multiple battery cells 12a, the rack controller 13 can determine the sum of the states of charge as the state of charge of the battery rack 12.

[0049] In one example, the rack controller 13 may determine the state of charge of the battery cell 12a using an ampere counting method. The initial value of the state of charge may be determined using open circuit voltage-state of charge lookup information. That is, when a state in which charging / discharging of the battery rack 12 is stopped is maintained for a certain period of time, the rack controller 13 may set the cell voltage measured at that time as the open circuit voltage and determine the initial value of the state of charge using the open circuit voltage-state of charge lookup information. The state of charge of the battery cell 12a may be determined by integrating the charging / discharging current based on the initial value of the state of charge.

[0050] In another example, the rack controller 13 can input information about the voltage, charge / discharge current, and temperature of the battery cells 12a into an extended Kalman filter to determine the state of charge of each battery cell. The extended Kalman filter, which can determine the state of charge from the voltage, charge / discharge current, and temperature of the battery cells, is known in the art.

[0051] For an example of estimation of the state of charge using an extended Kalman filter, see Gregory L. Plett's paper, "Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs Parts 1, 2 and 3" (Journal of Power Source 134, 2004, pp. 252-261), and the above paper may be incorporated as part of this specification.

[0052] The system 10 according to an embodiment of the present invention may include an ESS controller 17 operably coupled to the ESS 11 .

[0053] The ESS controller 17 may be connected to the rack controller 13 via a communication line. Preferably, the communication line may be a line that supports at least one of various communication protocols (communication rules) well known in the ESS technical field, such as a CAN protocol, TCP / IP, Modbus TCP, Modbus RTU, and RS-485.

[0054] Optionally, the ESS controller 17 may be configured to support Bluetooth, Zigbee (Registered Trademark) , may be connected so as to be able to communicate with the rack controller 13 via short-range wireless communication such as Wi-Fi.

[0055] The ESS controller 17 may also be connected to an ESS integrated management device 18 via a communication line. The ESS integrated management device 18 is a device known as an energy management system (EMS) in the ESS technology field. The ESS integrated management device 18 optimally adjusts the charge / discharge amount and charge / discharge time of the ESS 11 by integrally controlling the PCS 20 and the ESS 11. The ESS integrated management device 18 works in conjunction with sensors and measuring instruments to analyze charge / discharge data of the ESS 11 and control the ESS 11 so as to operate with optimal efficiency.

[0056] The ESS controller 17 can periodically obtain the state of charge of the battery rack 12 from the rack controller. For this purpose, the ESS controller 17 may transmit a state of charge request message to the rack controller at regular time intervals. The rack controller 13 may then read the state of charge of the battery rack 12 from the memory device 13a and transmit it to the ESS controller via a communication line. The ESS controller 17 can store the received state of charge of the battery rack 12 in the memory device 17a together with a time stamp. As a result, time-series data regarding the state of charge of the battery rack 12 is stored in the memory device 17a.

[0057] When the ESS 11 includes a plurality of battery racks 12, the ESS controller 17 calculates the average value of the states of charge of the battery racks 12 acquired at the same time as the state of charge SOC of the ESS 11 by using the following Equation 1: ESS The memory device 17a may store the state of charge SOC of the ESS 11 acquired in the reference time interval as: ESS The time series data is stored.

[0058]

number

[0059] The ESS controller 17 calculates the state of charge SOC stored in the memory device 17a every time a reference time period elapses. ESS The information may be referenced to determine an actual usage pattern of the ESS 11 indicative of changes in the state of charge of the ESS during a reference time interval, and the actual usage pattern may be stored in the memory device 17a.

[0060] Preferably, the reference time interval may be one day. In this case, the ESS controller 17 periodically reads the state of charge SOC stored in the memory device 17a during the most recent 24 hours every time one day passes. ESS The time series data may be used to determine an actual usage pattern of the ESS 11, which indicates a change in the state of charge of the ESS. In some cases, the reference time interval may be set to be longer or shorter than one day.

[0061] FIG. 2 is a graph showing an example of an actual usage pattern A of the ESS 11 according to an embodiment of the present invention.

[0062] Referring to FIG. 2, the actual usage pattern A is determined based on one day. The actual usage pattern A has two charging periods, two discharging periods, and four rest periods. The state of charge (SOC) of the ESS 11 in the reference time period is ESS The change in the above is shown.

[0063] The charging section is a section in which charging power is supplied to the ESS side from the renewable energy generator and / or the power grid. The time section corresponding to the charging section is when the power generation efficiency of the renewable energy is high or the power price of the power grid is low (nighttime). The discharging section is a section in which discharge power is released from the ESS to the power grid and / or the power system 23. The time section corresponding to the discharging section is a peak time of the power grid 22 or when the power system 23 requires power (e.g., weekly). The time section corresponding to the idle section is a section in which the ESS 11 stabilizes after charging or discharging the ESS 11. That is, in the idle section, the battery cells 12a of the battery rack 12 have a stabilized state in which the polarization state is eliminated. The voltage of the battery cells 12a measured at the end of the idle section may be used as an open-circuit voltage when determining the initial value of the state of charge.

[0064] The actual usage pattern A may vary depending on how the operator of the ESS 11 operates the usage policy of the ESS 11. When a policy for active use of the ESS 11 is applied, the discharge section may increase. On the other hand, when a policy for passive use of the ESS 11 is applied, the discharge section may decrease and the idle section may increase.

[0065] The actual usage pattern A is different from the design usage pattern that was considered when determining the EOL life of ESS11.

[0066] FIG. 3 is a graph showing an example of a usage pattern B of the design of the ESS 11 according to an embodiment of the present invention.

[0067] 3, the design usage pattern B of the embodiment is determined based on one day. The design usage pattern B has a charging section, a discharging section, and a resting section, and the state of charge (SOC) of the ESS 11 in the reference time section. ESS The EOL life of the ESS11 was determined on the assumption that the ESS11 would be repeatedly charged and discharged according to the usage pattern for which it was designed.

[0068] If the actual usage pattern in the reference time period differs from the design usage pattern, the difference in the usage pattern is accumulated, and as a result, the EOL life is also changed. The actual usage pattern shown in FIG. 2 has two discharge periods. Therefore, when the ESS 11 is repeatedly charged and discharged in the pattern shown in FIG. 2, the ESS 11 is used more actively than in the design usage pattern. Therefore, when the ESS 11 is repeatedly charged and discharged in the usage pattern shown in FIG. 2, the remaining capacity of the ESS at the time when the EOL life has elapsed is reduced more than when the ESS 11 is repeatedly charged and discharged in the design usage pattern of FIG. 3.

[0069] Preferably, the ESS controller 17 may determine the remaining capacity of the first ESS at the time of the EOL life expiration by applying the average of the actual usage pattern determined for each reference time period over the entire period of the EOL life. The remaining capacity of the first ESS corresponds to the remaining capacity predicted when the EOL life expires if charging and discharging are repeated according to the actual usage pattern.

[0070] Specifically, the ESS controller 17 receives the state of charge (SOC) of the battery rack 12 from the rack controller in the kth reference time interval (one day), where k is an order index and is a natural number equal to or greater than 1. Rack,k , the temperature of the battery rack T k and charge / discharge C rate c k is periodically acquired and stored in memory device 17a.

[0071] In addition, the ESS controller 17 calculates the state of charge (SOC) of the battery rack 12 acquired at the same time by using Equation 1. Rack,k The average value of the above is calculated to determine the state of charge (SOC) of the ESS11. ESS is determined and stored in memory device 17a.

[0072] Through the above process, the memory device 17a stores the state of charge (SOC) of the ESS 11. ESS , the temperature T of the multiple battery racks 12 k , and charge / discharge C rate c kTime series data relating to is stored.

[0073] The ESS controller 17 calculates the state of charge SOC of the ESS 11 in the kth reference time interval. ESS The actual usage pattern of the ESS 11 (see FIG. 2) is determined using time series data on the power consumption and the power consumption and is stored in the memory device 17a.

[0074] The ESS controller 17 also calculates the depth of discharge (DoD) from the actual usage pattern determined in the kth reference time interval. k Determine the depth of discharge (DoD) k The DoD corresponds to the total change in the state of charge in each discharge section in the actual usage pattern. The more actively the ESS11 is used, the greater the DoD k In contrast, the more the ESS11 is used passively, the lower the discharge depth DoD k decreases.

[0075] In addition, the ESS controller 17 detects the temperature T and the temperature Attenuation Rate A T Using a predefined correlation between the temperature of the battery rack T k Temperature corresponding to Attenuation Rate A T,k It is possible to determine the temperature T and the temperature Attenuation Rate A T The correlation between the charge / discharge temperature T and temperature can be determined by an experiment. That is, by performing a charge / discharge cycle experiment on the battery cell 12a under different temperature conditions, Attenuation Rate A T The correlation with may be defined as a lookup table or a lookup function.

[0076] temperature Attenuation Rate A T,k The temperature T used to determine k is the temperature T of the plurality of battery racks 12 stored in the memory device 17a. k Alternatively, the temperature T may be set as an average value of time series data on the temperature Tk is the temperature T of all the battery racks 12 stored in the memory device 17a. k It may be set as the maximum, median or mode of the time series data for

[0077] In addition, the ESS controller 17 controls the charge / discharge C rate and C rate Attenuation Rate A c Using the predefined correlation between the charge and discharge C rate c k C rate corresponding to Attenuation Rate A c,k The charge / discharge C rate c and C rate Attenuation Rate A c The correlation between the charge / discharge C rate c and the C rate β can be determined by an experiment. That is, a charge / discharge cycle experiment is performed on the battery cell 12a under different charge / discharge C rate conditions to determine the charge / discharge C rate c and the C rate β. Attenuation Rate A c The correlation with may be defined as a lookup table or a lookup function.

[0078] C-rate Attenuation Rate A c,k The charge / discharge rate c used in determining k is the charge / discharge rate C of the plurality of battery racks 12 stored in the memory device 17a. k However, the present invention is not limited to this. k is the charge / discharge rate C of the plurality of battery racks 12 stored in the memory device 17a. k It may be set as the maximum, median or mode of the time series data for

[0079] In addition, the ESS controller 17 controls the depth of discharge (DoD) and Attenuation Rate A DoD Depth of discharge (DoD) determined from actual usage patterns using a predefined correlation between k The corresponding discharge depth Attenuation Rate A DoD,k It is also possible to determine the depth of discharge (DoD) and the depth of discharge (Depth of Discharge). Attenuation Rate A DoD The correlation between the depth of discharge DoD and the depth of discharge ΔT can be determined by an experiment. That is, a charge / discharge cycle experiment is performed on the battery cell 12a under different discharge depth conditions to determine the correlation between the depth of discharge DoD and the depth of discharge ΔT. Attenuation Rate A DoD The correlation with may be defined as a lookup table or a lookup function.

[0080] In addition, the ESS controller 17 can determine the remaining capacity (Capacity1) of the first ESS at the time when the EOL life has elapsed, using the following Equation 2, and store it in the memory device 17a.

[0081]

number

[0082] In Equation 2, power conversion efficiency A is the power conversion efficiency of the PCS 20, and is a value that is predetermined according to the performance specifications of the PCS 20. The capacity loss compensation rate is a factor that takes into consideration the power consumption of the rack controller 13, power cable loss, capacity deviation between racks, capacity deviation between cells, etc., when the rack controller 13 is supplied with power from a battery rack, and is a predefined value. When the reference time unit is one day, n is the total number of days of use of the ESS 11, and W is the total number of days corresponding to the EOL life. When the usage time of the ESS 11 is 10 years and the EOL life is 20 years, n is 365×10, and W is 365×20.

[0083] The ESS controller 17 also calculates the remaining capacity Capacity1 of the first ESS and the reference remaining capacity Capacity refer A first deviation between the first and second deviations can be recorded in the memory device 17a.

[0084] Standard remaining capacity refer means the remaining capacity of the ESS at the end of its EOL life when the ESS is used for the entire EOL life according to the design usage pattern (Figure 3).

[0085] Standard remaining capacity (Capacity refer ) may be calculated in advance based on the following Equation 3, and may be recorded in the memory device 17a for reference.

[0086]

number

[0087] In formula 3, temperature Attenuation Rate A T is the temperature T of the battery rack 12 and the temperature Attenuation Rate A T The C rate may be determined using a predefined correlation between Attenuation Rate A c is the charge and discharge C rate of the battery rack 12 and C rate Attenuation Rate A c The depth of discharge may be determined using a predefined correlation between the Attenuation Rate A DoD Depth of discharge DoD and depth of discharge AttenuationRate A DoD It may be determined using a predefined correlation between

[0088] The ESS controller 17 also calculates the remaining capacity Capacity1 of the first ESS and the reference remaining capacity Capacity refer When an event occurs in which a first deviation between the reference remaining capacity Capacity and the reference remaining capacity Capacity is equal to or greater than a first threshold, an event log including the time point of the event can be recorded in the memory device 17a. refer The range may be about 1% to about 10% of the above, but the present invention is not limited to this range.

[0089] The ESS controller 17 may be configured to provide the event log to the ESS integrated management device. refer and information regarding a first deviation therebetween may be provided to the ESS integrated management device 18.

[0090] The ESS integrated management device 18 calculates the remaining capacity Capacity1 of the first ESS, the reference remaining capacity Capacity refer and information regarding the first deviation therebetween may be output to the graphic user interface via the display.

[0091] Furthermore, the ESS integrated management device 18 can output the time series data regarding the remaining capacity Capacity1 of the first ESS and the time series data regarding the first deviation in the form of graphs via a display.

[0092] According to another aspect, the ESS controller 17 can determine the remaining capacity Capacity2 of the second ESS at the end of the EOL life by applying an average of the actual usage patterns determined at each reference time interval up to the current time, and applying the designed usage pattern of the ESS from the current time to the remaining period of the EOL life.

[0093] Specifically, the ESS controller 17 periodically receives the state of charge (SOC) of the battery rack 12 from the rack controller 13 during the kth (k is an order index, a natural number equal to or greater than 1) reference time period (one day). Rack,k , the temperature of the battery rack T k and charge / discharge C rate c k is acquired and stored in the memory device 17a.

[0094] In addition, the ESS controller 17 calculates the state of charge (SOC) of the battery rack 12 acquired at the same time by using Equation 1. Rack,k The average value of the above is calculated to determine the state of charge (SOC) of the ESS11. ESS is determined and stored in memory device 17a.

[0095] Through the above process, the memory device 17a stores the state of charge (SOC) of the ESS 11. ESS , the temperature T of the multiple battery racks 12 k and charge / discharge C rate c k Time series data relating to is stored.

[0096] The ESS controller 17 calculates the state of charge SOC of the ESS 11 in the k-th reference time interval. ESS Using the time series data on the actual usage pattern of the ESS 11 (see FIG. 2), it is determined and stored in the memory device 17a.

[0097] The ESS controller 17 also calculates the depth of discharge (DoD) from the actual usage pattern determined in the kth reference time interval. k Determine the depth of discharge (DoD) k The DoD corresponds to the total change in the state of charge in each discharge section in the actual usage pattern. The more actively the ESS11 is used, the greater the DoD k In contrast, the more the ESS11 is used passively, the lower the discharge depth DoD k decreases.

[0098] In addition, the ESS controller 17 detects the temperature Tk Temperature corresponding to Attenuation Rate A T,k , charge / discharge rate c k C rate corresponding to Attenuation Rate A c,k , and the depth of discharge (DoD) determined from actual usage patterns k The corresponding discharge depth Attenuation Rate A DoD,k can be determined.

[0099] In addition, the ESS controller 17 can determine the remaining capacity Capacity2 of the second ESS at the time when the EOL life has elapsed by using the following Equation 4, and store it in the memory device 17a.

[0100]

number

[0101] In Equation 4, power conversion efficiency A is the power conversion efficiency of the PCS 20, and is a value that is predetermined according to the performance specifications of the PCS 20. The capacity loss compensation rate is a factor that takes into consideration the power consumption of the rack controller 13, power cable loss, deviation in capacity between racks, deviation in capacity between cells, etc., when the rack controller 13 receives power from the battery rack, and is a predefined value. When the reference time unit is one day, n is the total number of days of use of the ESS 11, and W is the total number of days corresponding to the EOL life. If the usage time of the ESS 11 is 10 years and the EOL life is 20 years, n is 365×10, and W is 365×20.

[0102] In addition, the ESS controller 17 calculates the remaining capacity Capacity2 of the second ESS and the reference remaining capacity Capacity refer A second deviation between the first deviation and the second deviation can be recorded in memory device 17a.

[0103] In addition, the ESS controller 17 calculates the remaining capacity Capacity2 of the second ESS and the reference remaining capacity Capacity refer When an event occurs in which a second deviation between the reference remaining capacity Capacity and the reference remaining capacity Capacity is equal to or greater than a second threshold, an event log including the time point of the event can be recorded in the memory device 17a. refer The value can be set to about 1% to about 10% of the above, but the present invention is not limited to this.

[0104] The ESS controller 17 may also be configured to provide the event log to the ESS integrated management device. refer and information regarding a second deviation therebetween can be provided to the ESS integrated management device 18.

[0105] The ESS integrated management device 18 calculates the remaining capacity Capacity2 of the second ESS, the reference remaining capacity Capacity referand information regarding a second deviation therebetween may be output to the graphic user interface via a display.

[0106] Furthermore, the ESS integrated management device 18 can output the time series data regarding the remaining capacity Capacity2 of the second ESS and the time series data regarding the second deviation in the form of graphs via a display.

[0107] According to the embodiment of the present invention described above, the remaining capacity at the end of the EOL life is calculated by taking into consideration the actual usage pattern of the ESS and the usage pattern for which the ESS is designed, and then stored and managed as log information, thereby making it possible to eliminate the need for time-consuming and expensive remaining capacity testing of the ESS.

[0108] In addition, the remaining capacity of the ESS at the end of its EOL life span can be calculated based on two criteria and provided to customers, which can help them manage ESS usage patterns and ESS expansion.

[0109] As an example, if the remaining capacity of the ESS at the time of the EOL life is smaller than the reference remaining capacity by a threshold value or more, the customer can reduce the daily usage capacity of the ESS or add an additional ESS in advance.

[0110] As another example, if the remaining capacity of the ESS at the end of its life is greater than the reference remaining capacity, the daily depth of discharge (DoD) can be increased to improve the usage efficiency of the ESS.

[0111] In the present invention, the ESS controller 17 may optionally include a processor, application-specific integrated circuit (ASIC), other chipset, logic circuit, register, communication modem, data processing device, etc., as known in the art, for executing various control logic.

[0112] There is no particular limitation on the type of memory device 13a, 17a as long as it is a medium capable of recording and erasing information. For example, memory device 13a, 17a may be a hard disk, RAM, ROM, EEPROM, register, or flash memory.

[0113] The memory devices 13a, 17a can store and / or update and / or erase and / or transmit programs including control logic executed by the controller, and / or data generated when the control logic is executed, as well as predefined look-up tables, functions, parameters, chemical / physical / electrical constants, etc.

[0114] At least one of the control logics of the ESS controller 17 may be combined, and the combined control logic may be created in a computer-readable code system and stored in the memory device 17a. The code system may be distributed and stored in and executed by computers connected via a network. In addition, functional programs, codes, and code segments for realizing the combined control logic may be easily inferred by a programmer skilled in the art to which the present invention pertains.

[0115] Hereinafter, a method for predicting remaining capacity of an ESS according to an embodiment of the present invention will be described in detail with reference to FIGS. 4a and 4b.

[0116] 4a and 4b are flowcharts illustrating a method for predicting remaining capacity of an ESS according to an embodiment of the present invention.

[0117] The steps shown in Figures 4a and 4b are performed by the ESS controller 17. Also, the reference time interval is set to one day. In some cases, the reference time interval can be longer or shorter than one day.

[0118] 4a and 4b, first, the ESS controller 17 initializes an order index k of a reference time interval to 1 in step S10.

[0119] Next, in step S20, the ESS controller 17 receives the state of charge SOC of the battery rack 12 from the rack controller 13 in the kth reference time interval (the current value is 1). Rack,k , temperature T k and charge / discharge C rate c k is periodically acquired and stored in the memory device 17a.

[0120] Next, in step S30, the ESS controller 17 calculates the state of charge SOC of the battery rack 12 acquired at the same time. Rack,k The average value of the state of charge (SOC) of ESS11 ESS and stores the state of charge SOC of the ESS 11 determined in the reference time interval in the memory device 17a. ESS Time series data relating to is stored.

[0121] Next, in step S40, the ESS controller 17 reads the state of charge SOC stored in the memory device 17a. ESS An actual usage pattern of the ESS 11, which indicates a change in the state of charge of the ESS, is determined from the time series data, and the actual usage pattern is stored in the memory device 17a.

[0122] Next, in step S50, the ESS controller 17 calculates the depth of discharge (DoD) from the actual usage pattern determined in the kth reference time interval. k Determine.

[0123] Next, in step S60, the ESS controller 17 calculates the temperature T and the temperature Attenuation Rate A T Using a predefined correlation between k Temperature corresponding to Attenuation Rate A T,k Determine the temperature Attenuation Rate A T,k The temperature T referred to when determining kAs the temperature, the average value, median value, maximum value, mode value, etc. of the temperatures of the multiple battery racks 12 may be used.

[0124] Next, in step S70, the ESS controller 17 calculates the charge / discharge C rate c and the C rate Attenuation Rate A c Using a predefined correlation between the charge and discharge rate C of the battery rack 12, k C rate corresponding to Attenuation Rate A c,k Determine the C rate. Attenuation Rate A c,k The C rate c is used as a reference when determining k As the C rate, the average value, median value, maximum value, mode value, etc. of the C rates of the multiple battery racks 12 may be used.

[0125] Next, in step S80, the ESS controller 17 calculates the depth of discharge DoD and the depth of discharge Attenuation Rate A DoD Depth of discharge (DoD) determined from actual usage patterns using a predefined correlation between k The corresponding discharge depth Attenuation Rate A DoD,k Determine.

[0126] Next, in step S90, the ESS controller 17 uses the following Equation 2, applying the condition that the average of the actual usage patterns determined for each reference time interval up to the current time point is applied to the entire EOL life, to determine the remaining capacity Capacity1 of the first ESS at the time when the EOL life has elapsed, and stores it in the memory device 17a.

[0127]

number

[0128] Next, in step S100, the ESS controller 17 calculates the remaining capacity Capacity1 of the first ESS and the reference remaining capacity Capacity refer and stores in memory device 17a a first deviation between

[0129] Standard remaining capacity refer means the remaining capacity of the ESS at the time when the EOL life has elapsed when the ESS 11 is used for the entire EOL life period according to the usage pattern for which the ESS 11 is designed.

[0130] Next, in step S110, the ESS controller 17 calculates the remaining capacity Capacity1 of the first ESS and the reference remaining capacity Capacity refer When an event occurs in which a first deviation between the reference remaining capacity Capacity and the reference remaining capacity Capacity is equal to or greater than a first threshold, an event log including the time point of the event can be stored in the memory device 17a. refer The range may be about 1% to about 10% of the above, but the present invention is not limited to this range.

[0131] Next, in step S120, the ESS controller 17 provides the event log to the ESS integrated management device. The ESS controller 17 provides the event log and also provides the remaining capacity Capacity1 of the first ESS, the reference remaining capacity Capacity refer and information regarding a first deviation therebetween may be provided to the ESS integrated management device 18.

[0132] Then, the ESS integrated management device 18 calculates the remaining capacity Capacity1 of the first ESS, the reference remaining capacity Capacity referand information regarding the first deviation therebetween may be output to the graphic user interface via the display.

[0133] In addition, the ESS integrated management device 18 can output the time series data regarding the remaining capacity Capacity1 of the first ESS and the time series data regarding the first deviation in the form of a graph via a display.

[0134] After step S120, the process proceeds to step S130.

[0135] In step S130, the ESS controller 17 determines whether or not the reference time interval has elapsed. If the determination in step S130 is NO, the execution of the process is suspended. On the other hand, if the determination in step S130 is YES, the ESS controller 17 increments the order index k of the reference time interval by 1 in step S140, and then the process proceeds to step S20, where steps S20 to S120 are executed again in the next reference time interval.

[0136] Therefore, the remaining capacity Capacity1 of the first ESS is calculated every time one day, which is the reference time period, elapses, and the remaining capacity Capacity1 of the first ESS and the reference remaining capacity Capacity refer When a first deviation between is equal to or greater than a first threshold, an event log is stored in the memory device 17a, and the event log can be provided to the ESS integrated management device 18.

[0137] FIG. 5 is a flowchart showing a method for predicting remaining capacity of an ESS according to another embodiment of the present invention.

[0138] In another embodiment, the ESS controller 17 performs steps S10 to S80 of FIG. 4a in the same manner, and then optionally performs steps S150 to S230 of FIG.

[0139] In step S150, the ESS controller 17 calculates the temperature T and the temperature Attenuation Rate AT Using a predefined correlation between Attenuation Rate A T Determine.

[0140] Next, in step S160, the charge / discharge C rate c and the C rate Attenuation Rate A c Using the predefined correlation between Attenuation Rate A c Determine.

[0141] Next, in step S170, the depth of discharge DoD and the depth of discharge Attenuation Rate A DoD Using the predefined correlation between the depth of discharge of the ESS11 design depth of discharge DoD Attenuation Rate A DoD Determine.

[0142] Next, in step S180, the ESS controller 17 applies a condition that an average of the actual usage patterns determined for each reference time interval is applied up to the current time point, and a usage pattern of the ESS design is applied for the remaining period of the EOL life from the current time point, and can determine a remaining capacity Capacity2 of the second ESS at the time of the EOL life elapse according to the following Equation 4.

[0143]

number

[0144] Next, in step S190, the ESS controller 17 calculates the remaining capacity Capacity2 of the second ESS and the reference remaining capacity Capacity refer and stores in memory device 17a a second deviation between the first deviation and the second deviation.

[0145] Standard remaining capacity refer means the remaining capacity of the ESS at the time when the EOL life has elapsed when the ESS 11 is used for the entire EOL life period according to the usage pattern for which the ESS 11 is designed.

[0146] Next, in step S200, the ESS controller 17 calculates the remaining capacity Capacity2 of the second ESS and the reference remaining capacity Capacity refer When an event occurs in which a second deviation between the reference remaining capacity Capacity and the reference remaining capacity Capacity is equal to or greater than a second threshold, an event log including the time point of the event can be stored in the memory device 17a. refer The range may be about 1% to about 10% of the above, but the present invention is not limited to this range.

[0147] Next, in step S210, the ESS controller 17 provides the event log to the ESS integrated management device. In addition to providing the event log, the ESS controller 17 also provides the remaining capacity Capacity2 of the second ESS, the reference remaining capacity Capacity refer and information regarding a second deviation therebetween can be provided to the ESS integrated management device 18.

[0148] Then, the ESS integrated management device 18 calculates the remaining capacity Capacity2 of the second ESS, the reference remaining capacity Capacity refer and information regarding a second deviation therebetween may be output to the graphic user interface via a display.

[0149] Furthermore, the ESS integrated management device 18 can output the time series data regarding the remaining capacity Capacity2 of the second ESS and the time series data regarding the second deviation in the form of graphs via a display.

[0150] After step S210, the process proceeds to step S220.

[0151] In step S220, the ESS controller 17 judges whether or not the reference time interval has elapsed. If the judgment in step S220 is NO, the execution of the process is suspended. On the other hand, if the judgment in step S220 is YES, the ESS controller 17 increments the order index k of the reference time interval by 1 in step S230, and then the process proceeds to step S20, where steps S20 to 80 in FIG. 4a and steps S150 to S210 in FIG. 5 are executed again in the next reference time interval.

[0152] Therefore, the remaining capacity Capacity2 of the second ESS is calculated every time one day, which is the reference time period, elapses, and the remaining capacity Capacity2 of the second ESS and the reference remaining capacity Capacity refer When a second deviation between is equal to or greater than a second threshold, an event log is stored in the memory device 17a, and the event log can be provided to the ESS integrated management device 18.

[0153] Preferably, the above-mentioned embodiment of FIG. 4a and FIG. 4b and the embodiment of FIG. 5 may be simultaneously performed in a reference time interval. Also, an event log may be generated and recorded in the memory device 17a when all the conditions that the first deviation is equal to or greater than the first threshold value and the second deviation is equal to or greater than the second threshold value are satisfied, and may be provided to the ESS integrated management device 18. Also, the ESS integrated management device 18 may output at least one selected from the time series data on the remaining capacity Capacity1 of the first ESS, the time series data on the remaining capacity Capacity2 of the second ESS, the time series data on the first deviation, and the time series data on the second deviation as a graph via a display. This allows the ESS operator to optimally control the ESS usage pattern so as to follow the design usage pattern of the ESS 11. Also, when the design usage pattern has a large cap with the actual usage pattern, the ESS operator may take measures in advance, such as adding an ESS, in consultation with the ESS manufacturer.

[0154] Although the present invention has been described above using limited embodiments and drawings, the present invention is not limited thereto, and it goes without saying that various modifications and variations can be made by a person having ordinary knowledge in the technical field to which the present invention pertains within the equivalent scope of the technical concept of the present invention and the scope of the claims. [Explanation of symbols]

[0155] 10. Remaining Life Prediction System 11 Energy Storage System (ESS) 12 Battery Rack 12a battery cell 13 Rack Controller 13a Memory Devices 15 Current measurement section 16 Temperature measurement section 17 ESS Controller 17a Memory Devices 18 ESS integrated management device 20 Power Conversion System (PCS) 22 Power Grid 23 Power system

Claims

1. A system for predicting remaining capacity of an energy storage system (ESS) including an ESS controller operably coupled to the ESS having a plurality of battery racks and a rack controller, The ESS controller, Obtaining a charging state of the battery rack from the rack controller; determining an actual usage pattern of the ESS, which indicates a change in the state of charge of the ESS for each reference time period; applying the average of the actual usage pattern to an entire end-of-life (EOL) period to determine a remaining capacity of the first ESS at the end of the EOL period; Recording a first deviation between the remaining capacity of the first ESS and a reference remaining capacity. The ESS remaining capacity prediction system is configured as follows.

2. The system for predicting remaining capacity of an ESS according to claim 1 , wherein the reference time period is one day.

3. The ESS controller, Applying the average of the actual usage pattern determined for each reference time period up to the current time point, Apply the usage pattern of the ESS design for the remaining period from the current time to the EOL life. By this, the remaining capacity of the second ESS at the time of the end of life is determined; The ESS remaining capacity prediction system according to claim 1 , configured to record a second deviation between the remaining capacity of the second ESS and a reference remaining capacity.

4. When determining the remaining capacity of the first ESS, The ESS controller, in a k-th reference time interval (k is an index), The rack controller detects the temperature of the battery rack (T ｋ ) and charge / discharge C rate (c ｋ ) and Temperature T and temperature decay rate (A Ｔ ) using a predefined correlation between ｋ ) corresponding temperature decay rate (A Ｔ，ｋ ) is determined, Charge / discharge C rate (c) and C rate decay rate (A ｃ ) using a predefined correlation between the charge / discharge C rate (c ｋ ) corresponding C rate decay rate (A ｃ，ｋ ) is determined, A depth of discharge (DoD) is calculated from the actual usage pattern in the k-th reference time period among the actual usage patterns determined for each reference time period. ｋ ) is determined, Depth of Discharge (DoD) and Depth of Discharge Decay Rate (A ＤｏＤ ) using a predefined correlation between the depth of discharge (DoD ｋ ) corresponding to the discharge depth decay rate (A ＤｏＤ，ｋ ) is determined, The remaining capacity (Capacity) of the first ESS is calculated using the following formula: １ 2. The system for predicting remaining capacity of an ESS according to claim 1, further comprising: [0010] (k: order index of the reference time interval, n: number of reference time intervals of the ESS usage period, W: "EOL life / reference time interval", A Ｔ，ｋ : Temperature decay rate in the kth reference time interval, A ｃ，ｋ : C rate decay rate in the kth reference time interval, A ＤｏＤ，ｋ : discharge depth decay rate in the kth reference time interval, A: power conversion efficiency (predefined), B: capacity loss compensation rate (predefined), E: design capacity of ESS (predefined)).

5. When determining the remaining capacity of the second ESS, The ESS controller, in a k-th reference time interval (k is an index), The rack controller detects the temperature of the battery rack (T ｋ ) and charge / discharge C rate (c ｋ ) and Temperature (T) and temperature decay rate (A Ｔ ) using a predefined correlation between ｋ ) corresponding temperature decay rate (A Ｔ，ｋ ) is determined, Charge / discharge C rate (c) and C rate decay rate (A ｃ ) using a predefined correlation between the charge / discharge C rate (c ｋ ) corresponding C rate decay rate (A ｃ，ｋ ) is determined, A depth of discharge (DoD) is calculated from the actual usage pattern in the k-th reference time period among the actual usage patterns determined for each reference time period. ｋ ) is determined, Depth of Discharge (DoD) and Depth of Discharge Decay Rate (A ＤｏＤ ) using a predefined correlation between the depth of discharge (DoD ｋ ) corresponding to the discharge depth decay rate (A ＤｏＤ，ｋ ) is determined, The remaining capacity (Capacity) of the second ESS is calculated using the following formula: ２ 4. The system for predicting remaining capacity of an ESS according to claim 3, further comprising: [0025] (k: order index of the reference time interval, n: number of reference time intervals of the ESS usage period, W: "EOL life / reference time interval", A Ｔ，ｋ : Temperature decay rate in the kth reference time interval, A ｃ，ｋ : C rate decay rate in the kth reference time interval, A ＤｏＤ，ｋ : Discharge depth decay rate in the kth reference time interval, A Ｔ : Temperature decay rate corresponding to the design operating temperature of the ESS, A Ｃ : C-rate decay rate corresponding to the design charge / discharge C-rate of the ESS, A Ｄ０Ｄ : Discharge depth decay rate corresponding to the design discharge depth of the ESS, A: Power conversion efficiency (predefined), B: Capacity loss compensation rate (predefined), E: Design capacity of the ESS (predefined).

6. The ESS remaining capacity prediction system according to claim 1 , wherein the ESS controller records an event log including a time point of the event when an event occurs in which the first deviation is equal to or greater than a first threshold value.

7. The ESS remaining capacity prediction system according to claim 3 , wherein the ESS controller records an event log including a time point of the event when an event occurs in which the second deviation is equal to or greater than a second threshold value.

8. further comprising an ESS integration management device operably coupled to the ESS controller; The ESS remaining capacity prediction system according to claim 6 or 7, wherein the ESS controller provides the event log to an ESS integrated management device.

9. A method for predicting remaining capacity of an Energy Storage System (ESS) having a plurality of battery racks and a rack controller, the method comprising: (a) obtaining a charging status of a battery rack from a rack controller; (b) determining an actual usage pattern of the ESS indicative of a change in the state of charge of the ESS over a reference time period; (c) applying the average of the actual usage pattern to the entire EOL life to determine the remaining capacity of the first ESS at the end of the EOL life; (d) recording a first deviation between the first ESS remaining capacity and a reference remaining capacity; A method for predicting remaining capacity of an ESS, comprising:

10. The method for predicting remaining capacity of an ESS according to claim 9 , wherein the reference time period is one day.

11. Applying the average of the actual usage pattern determined for each reference time period up to the current time point, Apply the usage pattern of the ESS design for the remaining period from the current time to the EOL life. determining a remaining capacity of the second ESS at the time of the EOL life elapse by recording a second deviation between the remaining capacity of the second ESS and a reference remaining capacity; The method for predicting remaining capacity of an ESS according to claim 9, further comprising:

12. When determining the remaining capacity of the first ESS, In the kth reference time interval (k is an index), The rack controller detects the temperature of the battery rack (T ｋ ) and charge / discharge C rate (c ｋ ) and Temperature (T) and temperature decay rate (A Ｔ ) using a predefined correlation between ｋ ) corresponding temperature decay rate (A Ｔ，ｋ ) Charge / discharge C rate (c) and C rate decay rate (A ｃ ) using a predefined correlation between the charge / discharge C rate (c ｋ ) corresponding C rate decay rate (A ｃ，ｋ ) A depth of discharge (DoD) is calculated from the actual usage pattern in the k-th reference time period among the actual usage patterns determined for each reference time period. ｋ ) Depth of Discharge (DoD) and Depth of Discharge Decay Rate (A ＤｏＤ ) using a predefined correlation between the depth of discharge (DoD ｋ ) corresponding to the discharge depth decay rate (A ＤｏＤ，ｋ ) The remaining capacity (Capacity) of the first ESS is calculated using the following formula: １ ) The method for predicting remaining capacity of an ESS according to claim 9, comprising: [0030] (k: order index of the reference time interval, n: number of reference time intervals in the ESS usage period, W: "EOL / reference time interval", A Ｔ，ｋ : Temperature decay rate in the kth reference time interval, A ｃ，ｋ : C rate decay rate in the kth reference time interval, A ＤｏＤ，ｋ : discharge depth decay rate in the kth reference time interval, A: power conversion efficiency (predefined), B: capacity loss compensation rate (predefined), E: design capacity of ESS (predefined)).

13. When determining the remaining capacity of the second ESS, In the kth reference time interval (k is an index), The rack controller detects the temperature of the battery rack (T ｋ ) and charge / discharge C rate (c ｋ ) and Temperature (T) and temperature decay rate (A Ｔ ) using a predefined correlation between ｋ ) corresponding temperature decay rate (A Ｔ，ｋ ) Charge / discharge C rate (c) and C rate decay rate (A ｃ ) using a predefined correlation between the charge / discharge C rate (c ｋ ) corresponding C rate decay rate (A ｃ，ｋ ) A depth of discharge (DoD) is calculated from the actual usage pattern in the k-th reference time period among the actual usage patterns determined for each reference time period. ｋ ) Depth of Discharge (DoD) and Depth of Discharge Decay Rate (A ＤｏＤ ) using a predefined correlation between the depth of discharge (DoD ｋ ) corresponding to the discharge depth decay rate (A ＤｏＤ，ｋ ) The remaining capacity (Capacity) of the second ESS is calculated using the following formula: ２ ) The method for predicting remaining capacity of an ESS according to claim 11, comprising: [0045] (k: order index of the reference time interval, n: number of reference time intervals of the ESS usage period, W: "EOL life / reference time interval", A Ｔ，ｋ : Temperature decay rate in the kth reference time interval, A ｃ，ｋ : C rate decay rate in the kth reference time interval, A ＤｏＤ，ｋ : Discharge depth decay rate in the kth reference time interval, A Ｔ : Temperature decay rate corresponding to the design operating temperature of the ESS, A Ｃ : C-rate decay rate corresponding to the design charge / discharge C-rate of the ESS, A Ｄ０Ｄ : Discharge depth decay rate corresponding to the design discharge depth of the ESS, A: Power conversion efficiency (predefined), B: Capacity loss compensation rate (predefined), E: Design capacity of the ESS (predefined).

14. The method for predicting remaining capacity of an ESS according to claim 9 , further comprising the step of recording an event log including a time point of an event occurrence when an event occurs in which the first deviation is equal to or greater than a first threshold value.

15. The method for predicting remaining capacity of an ESS according to claim 11, further comprising the step of recording an event log including a time point of an event occurrence when an event occurs in which the second deviation is equal to or greater than a second threshold value.

16. providing the event log, the reference remaining capacity, the remaining capacity of the first ESS, and the first deviation to an ESS integrated management device; The ESS integrated management device is connected to the ESS controller and configured to output the reference remaining capacity, the remaining capacity of the first ESS, and the first deviation to a graphical user interface. The method for predicting remaining capacity of an ESS according to claim 14.

17. The method further includes a step of providing the event log, the reference remaining capacity, the second ESS remaining capacity, and the second deviation to an ESS integrated management device, The ESS integrated management device is connected to the ESS controller and configured to output the reference remaining capacity, the remaining capacity of the second ESS, and the second deviation to a graphical user interface. The method for predicting remaining capacity of an ESS according to claim 15.

18. A computer program comprising instructions for causing the ESS controller to execute the method for predicting remaining capacity of an ESS according to any one of claims 9 to 15.

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