Residual Capacity Prediction System and Method for 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 remaining capacity prediction system and method for an energy storage system (ESS), and more particularly, to a system and method for analyzing the actual usage pattern of an ESS and predicting the remaining capacity of the ESS at the end of life (EOL).

[0002] This application claims priority based on Korean Patent Application No. 10-2021-0131983, filed on October 05, 2021, and the content of the invention described in the priority-based application is incorporated herein as part of this specification.

Background Art

[0003] In recent years, due to environmental pollution problems of fossil fuels, the use of renewable energy such as sunlight, wind power, and geothermal energy has been gradually increasing. Renewable energy is stored in an energy storage system called an ESS. The ESS converts renewable energy into electrical energy and stores it in a battery, and supplies the electrical energy stored in the battery to the power system system.

[0004] In addition to the storage use of renewable energy, the ESS stores electrical energy from the power grid in the battery during time periods when electricity rates are low, such as at home or in factories, and supplies the electrical energy stored in the battery to various electrical devices during the daytime.

[0005] ESS manufacturers design the EOL life by obtaining in advance the usage pattern (charge / discharge pattern), daily usage capacity, and usage period of the ESS. The remaining capacity of the ESS decreases as the usage time becomes longer Decrease The remaining capacity of the ESS refers to the capacity that can be charged or discharged from the ESS. Therefore, when designing the EOL life, the EOL life is designed to be 10 years, 15 years, 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 usage site, the ESS manufacturer regularly conducts a residual capacity test on the ESS. The cycle of the residual capacity test of the ESS is usually one year. The purpose of the residual capacity test is to check whether the end-of-life (EOL) life can be guaranteed based on the test time point.

[0007] For example, if the EOL life is 20 years and the test time point of the residual capacity test is 10 years after the ESS installation time point, it is necessary to check whether the residual capacity of the ESS 10 years later can guarantee the usage capacity desired by the customer.

[0008] If it is confirmed by the inspection that the EOL life cannot be guaranteed, obtain the usage log of the ESS and investigate whether the ESS is properly operated according to the pre-agreed usage pattern.

[0009] If it is confirmed that the customer has used the ESS excessively compared to the usage pattern considered at the time of ESS design, the ESS manufacturer proposes to discuss with the customer to add an ESS to meet the EOL life or to reduce the guaranteed EOL life for the customer.

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

[0011] Therefore, in the technical field to which the present invention belongs, a technology that can achieve the ease and simplification of the residual capacity test work of the ESS is urgently required. Summary of the Invention Problems to be Solved by the Invention

[0012] The present invention has been devised under the background of the prior art as described above, analyzes the usage pattern of an ESS, predicts the remaining capacity of the ESS when the end-of-life (EOL) life has elapsed, records a log regarding the prediction result, and provides it to a customer in real time, thereby aiming to provide an ESS remaining capacity prediction system and method capable of omitting the remaining capacity test process of the ESS.

Means for Solving the Problems

[0013] An ESS remaining capacity prediction system according to one aspect of the present invention for achieving the above technical problem includes an ESS controller operably coupled to an energy storage system (ESS: Energy Storage System) having a plurality of battery racks and a rack controller.

[0014] Preferably, the ESS controller acquires the state of charge of the battery rack from the rack controller, determines the actual usage pattern of the ESS indicating the change in the state of charge of the ESS for each reference time interval, applies the average of the actual usage patterns to the entire period of the end-of-life (EOL) life to determine the remaining capacity of the first ESS at the time when the EOL life has elapsed, and records a first deviation between the remaining capacity of the first ESS and a reference remaining capacity.

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

[0016] In another aspect, the ESS controller applies the average of the actual usage patterns determined for each reference time up to the current time, and applies the designed usage pattern of the ESS for the remaining period of the EOL life from the current time, thereby determining the remaining capacity of the second ESS at the time when the EOL has elapsed, and recording a second deviation between the remaining capacity of the second ESS and a reference remaining capacity.

[0017] In one embodiment, the ESS controller, in the k-th (where k is an index) reference time interval, the temperature T of the battery rack from the rack controllerk and charge-discharge C rate c k are obtained, and using a predefined correlation relationship between the temperature T and the temperature Attenuation rate A T , the temperature T k corresponding temperature Attenuation rate A T , k is determined, and using a predefined correlation relationship between the charge-discharge C rate c and the C rate Attenuation rate A c , the charge-discharge C rate c k corresponding C rate Attenuation rate A c,k is determined, the depth of discharge (Depth Of Discharge: DoD k ) is determined from the actual usage pattern, and using a predefined correlation relationship between the depth of discharge DoD and the depth of discharge Attenuation rate A DoD , the depth of discharge DoD k corresponding depth of discharge Attenuation rate A DoD,k is determined, and may be configured to determine the remaining capacity (Capacity 1 ) of the first ESS using the following formula.

[0018]

Equation

[0019] In other embodiments, in the k-th (k is an index) reference time interval, the ESS controller receives the temperature T of the battery rack from the rack controller kand charge-discharge C rate c k are obtained, and the temperature T and the temperature Attenuation rate A T using a predefined correlation between and the temperature T k corresponding temperature Attenuation rate A T,k is determined, and the charge-discharge C rate c and the C rate Attenuation rate A c using a predefined correlation between and the charge-discharge C rate c k corresponding C rate Attenuation rate A c,k is determined, and the depth of discharge (Depth Of Discharge: DoD k ) is determined from the actual usage pattern, and the depth of discharge DoD and the depth of discharge Attenuation rate A DoD using a predefined correlation between and the depth of discharge DoD k corresponding depth of discharge Attenuation rate A DoD,k is determined, and may be configured to determine the remaining capacity (Capacity 2 ) of the second ESS using the following formula.

[0020]

Equation

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

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

[0023] In yet another aspect, the system according to the present invention further includes an ESS integrated management device operably coupled to the ESS controller, and the ESS controller may be configured to provide the event log to the ESS integrated management device side.

[0024] A method for predicting the remaining capacity of an ESS according to an aspect of the present invention for achieving the above technical problem 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 the remaining capacity of the ESS, the method including: (a) obtaining a state of charge of the battery rack from the rack controller; (b) determining an actual usage pattern of the ESS indicating a change in the state of charge of the ESS for each reference time interval; (c) applying an average of the actual usage patterns over the entire period of the end-of-life (EOL) to determine a first remaining capacity of the ESS at the time of passage of the EOL; and (d) recording a first deviation between the first remaining capacity of the ESS and a reference remaining capacity.

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

[0026] On the other hand, the method according to the present invention may further include determining a remaining capacity of the second ESS at the end-of-life (EOL) life point by applying an average of the actual usage patterns up to the current time point and applying a usage pattern of the ESS design for the remaining period of the EOL life from the current time point; 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 according to the present invention includes, in the k-th (where k is an index) reference time interval, obtaining the temperature T of the battery rack from the rack controller k and the charge-discharge C rate c k ; determining the temperature rate A corresponding to the temperature T using a predefined correlation between the temperature T and the temperature rate A Attenuation ; determining the C rate corresponding to the charge-discharge C rate c using a predefined correlation between the charge-discharge C rate c and the C rate T rate A k ; determining the depth of discharge (DoD) from the actual usage pattern Attenuation ; determining the discharge depth rate A corresponding to the depth of discharge DoD using a predefined correlation between the depth of discharge DoD and the discharge depth rate A T , k ; and determining the remaining capacity (Capacity Attenuation ) of the first ESS using the following formula, which may be included. c ; determining the discharge depth rate A corresponding to the charge-discharge C rate c using a predefined correlation between the charge-discharge C rate c and the C rate k rate A Attenuation ; determining the depth of discharge (DoD) from the actual usage pattern c,k ; determining the discharge depth rate A corresponding to the depth of discharge DoD using a predefined correlation between the depth of discharge DoD and the discharge depth rate A k ) Attenuation ; determining the discharge depth rate A corresponding to the depth of discharge DoD using a predefined correlation between the depth of discharge DoD and the discharge depth rate A DoD ; determining the remaining capacity (Capacity k ) of the first ESS using the following formula, which may be included. Attenuation ; determining the discharge depth rate A corresponding to the depth of discharge DoD using a predefined correlation between the depth of discharge DoD and the discharge depth rate A DoD,k ; and determining the remaining capacity (Capacity 1 ) of the first ESS using the following formula, which may be included.

[0028]

Equation

[0029] According to other embodiments, the method according to the present invention, in the k-th (where k is an index) reference time interval, the temperature T of the battery rack from the rack controller k and the charge / discharge C-rate c k are obtained, and the pre-defined correlation between the temperature T and the temperature Attenuation rate A T is used to determine the temperature k corresponding to the temperature T Attenuation rate A T,k ; the pre-defined correlation between the charge / discharge C-rate c and the C-rate Attenuation rate A c is used to determine the C-rate k corresponding to the charge / discharge C-rate c Attenuation rate A c,k ; the depth of discharge (Depth Of Discharge: DoD k ) is determined from the actual usage pattern, and the pre-defined correlation between the depth of discharge DoD and the depth of discharge Attenuation rate A DoD is used to determine the depth of discharge k corresponding to the depth of discharge DoD Attenuation rate A DoD,k ; and the remaining capacity (Capacity 2 ) of the second ESS is determined using the following formula, and may include.

[0030]

Equation

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

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

[0033] In yet another aspect, the method according to the present invention may further include the step of providing the event log to the ESS integrated management device side.

Advantages of the Invention

[0034] According to the present invention, by calculating the remaining capacity when the end-of-life (EOL) life has elapsed, considering the actual usage pattern of the ESS and the designed usage pattern of the ESS respectively, and storing and managing it as log information, it is possible to omit the remaining capacity test of the ESS, which is time-consuming and costly. In addition, by providing the customer with the remaining capacity of the ESS when the EOL life has elapsed, it can be useful for managing the ESS usage pattern and ESS expansion, etc. As an example, when the remaining capacity of the ESS at the end of the EOL life is smaller than the designed remaining capacity, the customer can reduce the daily usage capacity of the ESS or add an ESS in advance at an appropriate time. As another example, when the remaining capacity of the ESS at the end of the EOL life is larger than the designed remaining capacity, the daily usage capacity can be increased in order to improve the usage efficiency of the ESS.

[0035] The following drawings attached to this specification illustrate an embodiment of the present invention and serve to further understand the technical idea of the present invention together with the detailed description of the invention to be described later. Therefore, the present invention should not be construed as being limited only to the matters described in such drawings.

Brief Description of the Drawings

[0036]

Figure 1

Figure 2

Figure 3

Figure 4a

Figure 4b

Figure 5

Best Mode for Carrying Out the Invention

[0037] Hereinafter, preferred embodiments 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 the claims should not be construed as being limited to their ordinary or dictionary meanings. The inventor himself must interpret them in accordance with the meaning and concept corresponding to the technical idea of the present invention in accordance with the principle that he can appropriately define the concept of the terms in order to explain the invention in the best way. Therefore, it must be understood that the embodiments described in this specification and the configurations shown in the drawings are only the most preferred embodiment of the present invention and do not represent all of the technical ideas of the present invention. Therefore, there may be various equivalents and modifications that can replace 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] Referring 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 in parallel. The battery cell 12a may be a lithium-ion battery, but the present invention is not limited by the type of cell.

[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 conditioner for temperature adjustment such as a cooling fan.

[0042] The multiple battery racks 12 included in the ESS 11 are charged or discharged by a power conversion system (PCS: Power Conversion System) 20. The PCS 20 receives power supply from a renewable energy generator using sunlight, geothermal energy, wind power, etc. and / or the power grid, stores it in the ESS 11, or discharges the energy stored in the ESS 11 to the power grid and / or the power system 23. It is a system that changes electrical characteristics (frequency, voltage, etc.) and is responsible for AC-DC conversion.

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

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

[0045] The current measurement unit 15 measures the magnitude of the charge / discharge current at regular time intervals while the plurality of 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 input of the charge / discharge current measurement value and records it in the memory device 13a. Also, the rack controller 13 determines the C-rate (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 cell 12a. The current measurement 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 to 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 input of 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 the air conditioner, the rack temperature measurement value can be regarded as the temperature measurement value of the battery cell 12a. Needless to say, it is also possible for the temperature measurement unit 16 to directly measure the temperature of the battery cell 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 into a temperature value using a voltage-temperature conversion look-up table (function).

[0048] The rack controller 13 can determine the charge state of the battery rack 12 while the battery rack 12 is being charged or discharged, and store it in the memory device 13a. The charge state of the battery rack 12 is the value obtained by summing up the charge states of the battery cells 12a. Therefore, after determining the charge states of the plurality of battery cells 12a, the rack controller 13 can determine the sum value thereof as the charge state of the battery rack 12.

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

[0050] In other examples, the rack controller 13 can input information regarding the voltage, charge / discharge current, and temperature of the battery cell 12a into an extended Kalman filter, and determine the state of charge of each battery cell. An extended Kalman filter capable of determining the state of charge from the voltage, charge / discharge current, and temperature of a battery cell is known in the art.

[0051] For an example of estimating the state of charge using an extended Kalman filter, reference can be made to the paper “Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs Parts 1,2 and 3” by Gregory L. Plett (Journal of Power Source 134, 2004, 252 - 261), and the above paper can be adopted 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 conventions) well-known in the ESS technical field, such as the CAN protocol, TCP / IP, Modbus TCP, Modbus RTU, RS - 485, etc.

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

[0055] In addition, the ESS controller 17 may be connected to the 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 technical field. The ESS integrated management device 18 optimally adjusts the charge and discharge amount and charge and discharge time of the ESS 11 by integrally controlling the PCS 20 and the ESS 11. The ESS integrated management device 18 is interlocked with sensors and measuring devices, analyzes the charge and discharge data of the ESS 11, and controls it so that the ESS 11 can be operated with optimal efficiency.

[0056] The ESS controller 17 can periodically obtain the charge state of the battery rack 12 from the rack controller. For this purpose, the ESS controller 17 may send a charge state request message to the rack controller side at regular time intervals. Then, the rack controller 13 may read the charge state of the battery rack 12 from the memory device 13a and send it to the ESS controller side via the communication line. The ESS controller 17 can store the received charge state of the battery rack 12 in the memory device 17a together with a time stamp. As a result, time-series data regarding the charge state 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 may use the following formula 1 to set the average value of the charge states of the battery racks 12 obtained at the same time point as the charge state SOC of the ESS 11 ESS and store it in the memory device 17a. Therefore, the memory device 17a stores time-series data of the charge state SOC of the ESS 11 obtained in the reference time interval. ESS

[0058]

Equation

[0059] Each time a reference time interval elapses, the ESS controller 17 refers to the state of charge SOC ESS stored in the memory device 17a, determines the actual usage pattern of the ESS 11 indicating the change in the state of charge of the ESS during the reference time interval, and can store the actual usage pattern in the memory device 17a.

[0060] Preferably, the reference time interval may be one day. In this case, each time one day elapses, the ESS controller 17 refers to the time-series data of the state of charge SOC ESS periodically stored in the memory device 17a during the most recent 24 hours to determine the actual usage pattern of the ESS 11 indicating the change in the state of charge of the ESS. Optionally, the reference time interval may be set longer or shorter than one day.

[0061] FIG. 2 is a graph showing an example of the 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 intervals, two discharging intervals, and four rest intervals, and shows the change mode of the state of charge SOC ESS of the ESS 11 in the reference time interval.

[0063] The charging period is a period during which charging power is supplied from a renewable energy generator and / or the power grid to the ESS side. The time period corresponding to the charging period is when the power generation efficiency of the renewable energy is high or when the electricity rate of the power grid is low (at night). The discharging period is a period during which discharging power is released from the ESS to the power grid and / or the power system 23. The time period corresponding to the discharging period is the peak time of the power grid 22 or when the power system 23 requires power (e.g., weekly). The time period corresponding to the rest period is a period during which the ESS11 stabilizes after charging or discharging. That is, in the rest period, the battery cell 12a of the battery rack 12 has a state in which the polarization state is eliminated and stabilized. The voltage of the battery cell 12a measured when the rest period ends may be used as the open-circuit voltage when determining the initial value of the state of charge.

[0064] The actual usage pattern A can vary depending on how the operator of the ESS11 operates the usage policy of the ESS11. When a policy for active use of the ESS11 is applied, the discharging period may increase. On the other hand, when a policy for passive use of the ESS11 is applied, the discharging period may decrease and the rest period may be extended.

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

[0066] FIG. 3 is a graph showing an example of the designed usage pattern B of the ESS11 according to an embodiment of the present invention.

[0067] Referring to FIG. 3, the designed usage pattern B of the embodiment is determined based on one day. The designed usage pattern B has a charging period, a discharging period, and a rest period, and shows the aspect of the change in the state of charge SOC of the ESS11 in the reference time period. ESS The EOL life of the ESS11 is determined on the premise that the ESS11 is repeatedly charged and discharged according to the designed usage pattern.

[0068] If the actual usage pattern during the reference time interval is different from the designed 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 intervals. Therefore, when the charge and discharge of ESS11 are repeated in the pattern shown in FIG. 2, ESS11 is used more actively than in the designed usage pattern. Therefore, when the charge and discharge of ESS11 are repeated 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 compared to the case where the charge and discharge are repeated in the designed usage pattern of FIG. 3.

[0069] Preferably, the ESS controller 17 can apply the average of the actual usage patterns determined for each reference time interval over the entire EOL life to determine the remaining capacity of the first ESS at the time when the EOL life has elapsed. The remaining capacity of the first ESS corresponds to the remaining capacity predicted when the charge and discharge are repeated according to the actual usage pattern at the time when the EOL life has elapsed.

[0070] Specifically, in the k-th (where k is an order index and a natural number of 1 or more) reference time interval (one day), the ESS controller 17 obtains the state of charge SOC Rack,k of the battery rack 12, the temperature T k of the battery rack, and the charge and discharge C rate c k from the rack controller periodically and stores them in the memory device 17a.

[0071] Also, the ESS controller 17 uses Equation 1 to calculate the average value of the state of charge SOC Rack,k of the battery rack 12 obtained at the same time point to determine the state of charge SOC ESS of ESS11 and stores it in the memory device 17a.

[0072] Through the above process, in the memory device 17a, there are the state of charge SOC ESS of ESS11, the temperature T k of the plurality of battery racks 12, and the charge and 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 may be set as the maximum value, median value, or mode value of the time-series data regarding the temperature T of all the battery racks 12 stored in the memory device 17a. k

[0077] Further, the ESS controller 17 may use a predefined correlation relationship between the charge-discharge C rate c and the C rate Attenuation ratio A c to determine the C rate k ratio A Attenuation corresponding to the charge-discharge C rate c. c,k The correlation relationship between the charge-discharge C rate c and the C rate Attenuation ratio A c may be determined by experiments. That is, charge-discharge cycle experiments on the battery cell 12a are performed under different charge-discharge C rate conditions, and the correlation relationship between the charge-discharge C rate c and the C rate Attenuation ratio A c may be defined as a look-up table or a look-up function.

[0078] The charge-discharge C rate c Attenuation ratio A c,k used when determining the C rate k ratio A k may be set as the average value of the time-series data regarding the charge-discharge C rate c of the plurality of battery racks 12 stored in the memory device 17a, but the present invention is not limited thereto. In a modification, the charge-discharge C rate c k may be set as the maximum value, median value, or mode value of the time-series data regarding the charge-discharge C rate c of the plurality of battery racks 12 stored in the memory device 17a. k

[0079] Further, the ESS controller 17 may use a predefined correlation relationship between the depth of discharge DoD and the depth of discharge Attenuation ratio A DoD to determine the depth of discharge k ratio A Attenuation corresponding to the depth of discharge DoD determined from the actual usage pattern. DoD,k ratio AAttenuation Discharge rate A DoD The correlation with can be determined by experiments. That is, charge-discharge cycle experiments are performed on the battery cell 12a under different depth-of-discharge conditions, and the depth-of-discharge DoD and the depth-of-discharge Attenuation Discharge rate A DoD The correlation with may be defined as a look-up table or a look-up function.

[0080] In addition, the ESS controller 17 can determine the remaining capacity (Capacity 1 ) of the first ESS at the time when the EOL life has elapsed using the following mathematical formula 2, and can store it in the memory device 17a.

[0081]

Equation

[0082] In the mathematical formula 2, the power conversion efficiency A is the power conversion efficiency of the PCS20, and is a value determined in advance according to the performance specifications of the PCS20. The capacity loss compensation rate is a factor considering the power consumption of the rack controller 13, power cable loss, rack-to-rack capacity deviation, cell-to-cell capacity deviation, etc. when the rack controller 13 is supplied with power from the battery rack, and is a pre-defined value. When the reference time unit is 1 day, n is the total number of days of use of the ESS11, and W is the total number of days corresponding to the EOL life. When the usage time of the ESS11 is 10 years and the EOL life is 20 years, n is 365×10 and W is 365×20.

[0083] Also, the ESS controller 17 can record the first deviation between the remaining capacity Capacity of the first ESS and the reference remaining capacity Capacity in the memory device 17a. 1 and the reference remaining capacity Capacity refer in the memory device 17a.

[0084] The reference remaining capacity Capacity refer means the remaining capacity of the ESS at the time when the EOL life has elapsed when the ESS is used over the entire EOL life period according to the designed usage pattern (Figure 3).

[0085] The reference remaining capacity (Capacity refer ) may be calculated in advance based on the following mathematical formula 3, recorded in the memory device 17a, and referred to.

[0086]

Number

[0087] rate A Attenuation may be determined using a pre-defined correlation between the temperature T of the battery rack 12 and the temperature T rate A Attenuation rate A T and. Also, the C-rate Attenuation rate A c may be determined using a pre-defined correlation between the charge / discharge C-rate c of the battery rack 12 and the C-rate Attenuation rate A c and. Also, the depth of discharge Attenuation rate A DoDmay be determined using a predefined correlation between the depth of discharge DoD and the discharge depth Attenuation rate A DoD .

[0088] In addition, when an event occurs in which a first deviation between the remaining capacity Capacity of the first ESS and the reference remaining capacity Capacity is equal to or greater than a first threshold value, the ESS controller 17 can record an event log including the time point of the event occurrence in the memory device 17a. The first threshold value may be set to about 1% to about 10% of the reference remaining capacity Capacity, but the present invention is not limited thereto. 1 and the reference remaining capacity Capacity refer . refer .

[0089] In addition, the ESS controller 17 may be configured to provide the event log to the ESS integrated management device side. Further, the ESS controller 17 can provide information on the remaining capacity Capacity of the first ESS, the reference remaining capacity Capacity 1 , and the first deviation therebetween to the ESS integrated management device 18. refer .

[0090] The ESS integrated management device 18 can output information on the remaining capacity Capacity of the first ESS, the reference remaining capacity Capacity 1 , and the first deviation therebetween to a graphic user interface via a display. refer .

[0091] In addition, the ESS integrated management device 18 can output time-series data regarding the remaining capacity Capacity of the first ESS and time-series data regarding the first deviation in the form of a graph via a display. 1 .

[0092] According to another aspect, the ESS controller 17 applies the average of the actual usage patterns determined in each reference time interval up to the current time point, and applies the usage pattern of the ESS design for the remaining period of the EOL life from the current time point, so as to determine the remaining capacity Capacity of the second ESS at the time when the EOL life has elapsed 2 can be determined.

[0093] Specifically, in the k-th (k is an order index, a natural number of 1 or more) reference time interval (one day), the ESS controller 17 periodically receives the state of charge SOC of the battery rack 12 from the rack controller 13 Rack,k , the temperature T of the battery rack k and the charge and discharge C rate c k and stores them in the memory device 17a.

[0094] In addition, the ESS controller 17 uses Equation 1 to calculate the average value of the state of charge SOC of the battery rack 12 obtained at the same time point, determines the state of charge SOC of the ESS11, and stores it in the memory device 17a. Rack,k ESS

[0095] After the above process, the memory device 17a stores time series data related to the state of charge SOC of the ESS11 ESS , the temperature T of the plurality of battery racks 12 k and the charge and discharge C rate c k .

[0096] The ESS controller 17 uses the time series data related to the state of charge SOC of the ESS11 calculated in the k-th reference time interval to determine the actual usage pattern of the ESS11 (see Figure 2), and stores it in the memory device 17a. ESS

[0097] In addition, the ESS controller 17 determines the depth of discharge DoD from the actual usage pattern determined in the k-th reference time interval. The depth of discharge DoD k kcorresponds to the value obtained by summing up the change amounts of the state of charge in each discharge period in the actual usage pattern. The more actively the ESS11 is used, the deeper the depth of discharge DoD k increases. On the contrary, the more passively the ESS11 is used, the deeper the depth of discharge DoD k decreases.

[0098] Also, the ESS controller 17 determines, in substantially the same manner as described above, the temperature k rate A corresponding to the temperature T of the battery rack Attenuation the C-rate T,k rate A corresponding to the charge / discharge C-rate c k and the depth of discharge Attenuation rate A corresponding to the depth of discharge DoD determined from the actual usage pattern c,k k Attenuation can be determined. DoD,k

[0099] Also, the ESS controller 17 can determine the remaining capacity Capacity of the second ESS at the time when the EOL life has elapsed using the following mathematical formula 4 and store it in the memory device 17a. 2

[0100] [Number] (k: sequential 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 Attenuation rate in the k-th reference time interval, A c,k : C-rate Attenuation rate in the k-th reference time interval, A DoD,k : depth of discharge Attenuation rate in the k-th reference time interval, A T : temperature Attenuation rate corresponding to the designed operating temperature of the ESS, A c : C-rate Attenuation rate corresponding to the designed charge / discharge C-rate of the ESS, A D0D : depth of discharge Attenuation corresponding to the designed depth of discharge of the ESS​​​Rate, A: Power conversion efficiency (pre-defined), B: Capacity loss compensation rate (pre-defined), E: Design capacity of ESS (pre-defined))

[0101] In Equation 4, the power conversion efficiency A is the power conversion efficiency of PCS20 and is a value determined in advance according to the performance specifications of PCS20. The capacity loss compensation rate is a factor that takes into account the power consumption of the rack controller 13, power cable loss, deviation of the capacity between racks, deviation of the capacity between cells, etc. when the rack controller 13 receives power supply from the battery rack, and is a pre-defined value. When the reference time unit is 1 day, n is the total number of days of use of ESS11, and W is the total number of days corresponding to the EOL life. If the usage time of ESS11 is 10 years and the EOL life is 20 years, then n is 365×10 and W is 365×20.

[0102] Also, the ESS controller 17 can record the second deviation between the remaining capacity Capacity of the second ESS 2 and the reference remaining capacity Capacity refer in the memory device 17a.

[0103] Also, when an event occurs in which the second deviation between the remaining capacity Capacity of the second ESS 2 and the reference remaining capacity Capacity refer is equal to or greater than the second threshold value, the ESS controller 17 can record an event log including the time point of the event occurrence in the memory device 17a. The second threshold value can be set to a value of about 1% to about 10% of the reference remaining capacity Capacity refer , but the present invention is not limited thereto.

[0104] The ESS controller 17 may also be configured to provide the event log to the ESS integrated management device side. Also, the ESS controller 17, the remaining capacity Capacity of the second ESS 2 , the reference remaining capacity Capacity referAnd information regarding a second deviation between these can be provided to the ESS integrated management device 18.

[0105] The ESS integrated management device 18 can output information regarding the remaining capacity Capacity of the second ESS, 2 a reference remaining capacity Capacity, refer and a second deviation therebetween to a graphic user interface via a display.

[0106] Also, the ESS integrated management device 18 can output time-series data regarding the remaining capacity Capacity of the second ESS 2 and time-series data regarding the second deviation in a graph format via a display.

[0107] According to the above-described embodiment of the present invention, by calculating the remaining capacity at the end of the EOL life in consideration of the actual usage pattern of the ESS and the designed usage pattern of the ESS, respectively, and storing and managing it as log information,

[0108] it is possible to omit a remaining capacity test of the ESS that takes a lot of time and cost.

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

[0110] As another example, when the remaining capacity of the ESS at the end of the EOL life is larger than the reference remaining capacity, in order to improve the usage efficiency of the ESS, the depth of discharge DoD per day can be increased.

[0111] In the present invention, the ESS controller 17 may selectively include a processor, an application-specific integrated circuit (ASIC), other chip sets, logic circuits, registers, communication modems, data processing devices, etc., which are known in the art, in order to execute various control logics.

[0112] The memory devices 13a and 17a are not particularly limited in type as long as they are media capable of recording and erasing information. For example, the memory devices 13a and 17a may be hard disks, RAMs, ROMs, EEPROMs, registers, or flash memories.

[0113] The memory devices 13a and 17a can store, update, erase, and transmit a program including control logic executed by the controller, and / or a pre-defined look-up table, function, parameter, chemical / physical / electrical constant, etc. that are generated when the control logic is executed.

[0114] At least one of the control logics of the ESS controller 17 is combined, and the combined control logic can be created in a computer-readable code system and stored in the memory device 17a. The code system may be distributed and stored and executed on a computer connected by a network. Also, functional programs, codes, and code segments for realizing the combined control logic can be easily inferred by a programmer in the technical field to which the present invention belongs.

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

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

[0117] The steps shown in FIGS. 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 extended or shortened compared to one day.

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

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

[0120] Subsequently, in step S30, the ESS controller 17 sets the average value of the state of charge SOC Rack,k of the battery rack 12 acquired at the same time as the state of charge SOC ESS of the ESS11 and stores it in the memory device 17a. Thereby, time-series data regarding the state of charge SOC ESS of the ESS11 determined in the reference time interval is stored in the memory device 17a.

[0121] Next, in step S40, the ESS controller 17 determines the actual usage pattern of the ESS11 indicating the change in the state of charge of the ESS from the time-series data of the state of charge SOC ESS stored in the memory device 17a and stores the actual usage pattern in the memory device 17a.

[0122] Subsequently, in step S50, the ESS controller 17 determines the depth of discharge DoD k from the actual usage pattern determined in the k-th reference time interval.

[0123] Next, in step S60, the ESS controller 17 uses a predefined correlation between the temperature T and the temperature Attenuation rate A T to determine the temperature k rate A Attenuation corresponding to the temperature T of the battery rack 12. The temperature T,k rate A Attenuation used for the determination may be the average value, median value, maximum value, mode value, etc. of the temperatures of a plurality of battery racks 12. T,k The temperature T k referred to at the time of determining the rate A may be the average value, median value, maximum value, mode value, etc. of the temperatures of a plurality of battery racks 12.

[0124] Subsequently, in step S70, the ESS controller 17 uses a predefined correlation between the charge / discharge C rate c and the C rate Attenuation rate A c to determine the C rate k rate A Attenuation corresponding to the charge / discharge C rate c of the battery rack 12. The C rate c,k rate A Attenuation used for the determination may be the average value, median value, maximum value, mode value, etc. of the C rates of a plurality of battery racks 12. c,k The C rate c k referred to at the time of determining the rate A may be the average value, median value, maximum value, mode value, etc. of the C rates of a plurality of battery racks 12.

[0125] Next, in step S80, the ESS controller 17 uses a predefined correlation between the depth of discharge DoD and the depth of discharge Attenuation rate A DoD to determine the depth of discharge k rate A Attenuation corresponding to the depth of discharge DoD determined from the actual usage pattern. DoD,k The ESS controller 17 determines the rate A.

[0126] Subsequently, in step S90, the ESS controller 17 applies 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 period, and uses the following formula 2 to determine the remaining capacity Capacity 1 of the first ESS at the time when the EOL life has elapsed, and stores it in the memory device 17a.

[0127] [Number] (k: Ordinal index of the reference time interval, n: Number of reference time intervals in the ESS usage period, W: "EOL life / reference time interval", A T,k : Temperature in the k-th reference time interval Attenuation Rate, A c,k : C-rate in the k-th reference time interval Attenuation Rate, A DoD,k : Depth of discharge in the k-th reference time interval Attenuation Rate, A: Power conversion efficiency (pre-defined), B: Capacity loss compensation rate (pre-defined), E: Design capacity of the ESS (pre-defined))

[0128] Next, in step S100, the ESS controller 17 determines the first deviation between the remaining capacity Capacity of the first ESS 1 and the reference remaining capacity Capacity refer and stores it in the memory device 17a.

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

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

[0131] Next, in step S120, the ESS controller 17 provides the event log to the ESS integrated management device side. Along with the provision of the event log, the ESS controller 17 can provide information on the remaining capacity Capacity of the first ESS, the reference remaining capacity Capacity, and the first deviation therebetween to the ESS integrated management device 18. 1 and the reference remaining capacity Capacity refer and information on the first deviation therebetween to the ESS integrated management device 18.

[0132] Then, the ESS integrated management device 18 can output information on the remaining capacity Capacity of the first ESS, the reference remaining capacity Capacity, and the first deviation therebetween to the graphic user interface via the display. 1 and the reference remaining capacity Capacity refer and information on the first deviation therebetween to the graphic user interface via the display.

[0133] In addition, the ESS integrated management device 18 can output time-series data regarding the remaining capacity Capacity of the first ESS and time-series data regarding the first deviation in the form of a graph via the display. 1 and time-series data regarding the first deviation in the form of a graph via the display.

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

[0135] In step S130, the ESS controller 17 determines whether or not a 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 sequential index k of the reference time interval by 1 in step S140, and then the process proceeds to step S20, and steps S20 to 120 are executed again in the next reference time interval.

[0136] Therefore, every time one day, which is the reference time interval, elapses, the remaining capacity Capacity of the first ESS is calculated, and the remaining capacity Capacity of the first ESS, 1 the remaining capacity Capacity of the first ESS, 1 and the reference remaining capacity Capacity referWhen the first deviation from [something] is greater than or equal to the first threshold value, the 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 the flow of the ESS remaining capacity prediction method according to another embodiment of the present invention.

[0138] In another embodiment, the ESS controller 17 performs the same steps S10 to S80 in FIG. 4a, and then selectively performs steps S150 to S230 in FIG. 5.

[0139] In step S150, the ESS controller 17 uses a predefined correlation between the temperature T and the temperature Attenuation rate A T to determine the temperature Attenuation rate A T corresponding to the designed operating temperature of the ESS 11.

[0140] Next, in step S160, using a predefined correlation between the charge-discharge C rate c and the C rate Attenuation rate A c the C rate Attenuation rate A c corresponding to the designed charge-discharge C rate of the ESS 11 is determined.

[0141] Next, in step S170, using a predefined correlation between the depth of discharge DoD and the depth of discharge Attenuation rate A DoD the depth of discharge Attenuation rate A DoD corresponding to the designed depth of discharge DoD of the ESS 11 is determined.

[0142] Next, in step S180, the ESS controller 17 applies the condition that the average of the actual usage patterns determined for each reference time interval up to the current time is applied, and the designed usage pattern of the ESS is applied for the remaining period of the EOL life from the current time, and the second remaining capacity Capacity of the ESS at the time of passing the EOL life is calculated by the following formula 42 can be determined.

[0143]

Number

[0144] Next, in step S190, the ESS controller 17 determines a second deviation between the remaining capacity Capacity of the second ESS 2 and the reference remaining capacity Capacity refer and stores it in the memory device 17a.

[0145] The reference remaining capacity Capacity refer means the remaining capacity of the ESS at the time when the EOL life has elapsed when the ESS11 is used over the entire EOL life period according to the designed usage pattern of the ESS11.

[0146] Next, in step S200, the ESS controller 17 determines a second deviation between the remaining capacity Capacity of the second ESS 2 and the reference remaining capacity Capacity referWhen an event occurs in which a second deviation from [a certain value] becomes equal to or greater than a second threshold value, an event log including the time point of the event occurrence can be stored in the memory device 17a. The second threshold value may be set to about 1% to about 10% of the reference remaining capacity Capacity refer but the present invention is not limited thereto.

[0147] Next, in step S210, the ESS controller 17 provides the event log to the ESS integrated management device side. Along with the provision of the event log, the ESS controller 17 can provide information regarding the remaining capacity Capacity 2 of the second ESS, the reference remaining capacity Capacity refer and the second deviation therebetween to the ESS integrated management device 18.

[0148] Then, the ESS integrated management device 18 can output information regarding the remaining capacity Capacity 2 of the second ESS, the reference remaining capacity Capacity refer and the second deviation therebetween to a graphic user interface via a display.

[0149] Also, the ESS integrated management device 18 can output time-series data regarding the remaining capacity Capacity 2 of the second ESS and time-series data regarding the second deviation in the form of a graph via a display.

[0150] Proceed to step S220 after step S210.

[0151] In step S220, the ESS controller 17 determines whether the reference time interval has elapsed. If the determination in step S220 is NO, the execution of the process is suspended. On the other hand, if the determination in step S220 is YES, the ESS controller 17 increments the sequence index k of the reference time interval by 1 in step S230, and then the process proceeds to step S20, and steps S20 to S80 in FIG. 4a and steps S150 to S210 in FIG. 5 are executed again in the next reference time interval.

[0152] Therefore, every time one day, which is the reference time interval, elapses, the remaining capacity Capacity of the second ESS 2 is calculated, and when the second deviation between the remaining capacity Capacity of the second ESS 2 and the reference remaining capacity Capacity refer is greater than or equal to the second threshold value, an event log is stored in the memory device 17a and can be provided to the ESS integrated management device 18.

[0153] Preferably, the above-described embodiments of FIGS. 4a and 4b and the embodiment of FIG. 5 may be implemented simultaneously in the reference time interval. Also, the event log may be generated and recorded in the memory device 17a and provided to the ESS integrated management device 18 when all the conditions that the first deviation is greater than or equal to the first threshold value and the second deviation is also greater than or equal to the second threshold value are satisfied. Further, the ESS integrated management device 18 can output at least one selected from the time-series data regarding the remaining capacity Capacity of the first ESS 1 , the time-series data regarding the remaining capacity Capacity of the second ESS 2 , the time-series data regarding the first deviation, and the time-series data regarding the second deviation as a graph via a display. Thereby, the ESS operator can optimally control the ESS usage pattern so as to follow the usage pattern designed for ESS11. Also, when the designed usage pattern has a large gap from the actual usage pattern, the ESS operator can take measures such as consulting with the ESS manufacturer to add ESS in advance.

[0154] As described above, the present invention has been described with reference to limited embodiments and drawings. However, the present invention is not limited thereto, and it goes without saying that various modifications and variations can be made by those with ordinary knowledge in the technical field to which the present invention pertains within the equivalent scope of the technical idea and claims of the present invention.

Explanation of Reference Numerals

[0155] 10 Remaining life prediction system 11 Energy storage system (ESS) 12 Battery rack 12a Battery cell 13 Rack controller 13a Memory device 15 Current measurement unit 16 Temperature measurement unit 17 ESS controller 17a Memory device 18 ESS integrated management device 20 Power conversion system (PCS) 22 Power grid 23 Power system

Claims

1. An ESS remaining capacity prediction system including an ESS controller operably coupled to an energy storage system (ESS) having a plurality of battery racks and a rack controller, wherein the ESS controller, acquires the state of charge of the battery rack from the rack controller, determines an actual usage pattern of the ESS indicating a change in the state of charge of the ESS for each reference time interval, applies the average of the actual usage patterns determined for each reference time interval over the entire end-of-life (EOL) lifetime to determine the remaining capacity of the first ESS at the time when the EOL lifetime has elapsed, records a first deviation between the remaining capacity of the first ESS and a reference remaining capacity is configured as an ESS remaining capacity prediction system.

2. The ESS remaining capacity prediction system according to claim 1, wherein the reference time interval is one day.

3. The ESS controller, applies the average of the actual usage patterns determined for each reference time interval up to the current time, applies the designed usage pattern of the ESS for the remaining period of the EOL lifetime from the current time to thereby determine the remaining capacity of the second ESS at the time when the EOL lifetime has elapsed, is configured to record a second deviation between the remaining capacity of the second ESS and a reference remaining capacity, according to the ESS remaining capacity prediction system of claim 1.

4. When determining the remaining capacity of the first ESS, the ESS controller, at the k-th (where k is an index) reference time interval, The temperature (T ｋ ) and charge-discharge C-rate (c ｋ ) of the battery rack are acquired from the rack controller, Using a predefined correlation between the temperature T and the temperature decay rate (A Ｔ ), the temperature decay rate (A ｋ ) corresponding to the temperature (T Ｔ，ｋ ) is determined, Charge-discharge C-rate (c) and C-rate attenuation rate (A ｃ ), using a predefined correlation between them, the C-rate attenuation rate (A ｋ ) corresponding to the charge-discharge C-rate (c ｃ，ｋ ) is determined, Of the actual usage patterns determined for each of the reference time intervals, the depth of discharge (DoD) is determined from the actual usage pattern in the k-th reference time interval ｋ ) and Using a predefined correlation between the depth of discharge (DoD) and the depth of discharge attenuation rate (A ＤｏＤ ), the depth of discharge attenuation rate (A ｋ ) corresponding to the depth of discharge (DoD ＤｏＤ，ｋ ) is determined, The remaining capacity (Capacity １ ) of the first ESS is determined using the following formula. The ESS remaining capacity prediction system according to claim 1: 【Number 1】 (k: sequential 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 k-th reference time interval, A ｃ，ｋ : C-rate decay rate in the k-th reference time interval, A ＤｏＤ，ｋ : depth of discharge decay rate in the k-th reference time interval, A: power conversion efficiency (pre-defined), B: capacity loss compensation rate (pre-defined), E: designed capacity of the ESS (pre-defined)).

5. When determining the remaining capacity of the second ESS, the ESS controller, at the k-th (where k is an index) reference time interval, The temperature (T ｋ ) and charge-discharge C-rate (c ｋ ) of the battery rack are acquired from the rack controller, Using a predefined correlation between temperature (T) and temperature decay rate (A Ｔ ), the temperature decay rate (A ｋ ) corresponding to temperature (T Ｔ，ｋ ) is determined, Charge and discharge C-rate (c) and C-rate attenuation rate (A ｃ ), using a predefined correlation between them, the C-rate attenuation rate (A ｋ ) corresponding to the charge and discharge C-rate (c ｃ，ｋ ) is determined, Of the actual usage patterns determined for each of the reference time intervals, the depth of discharge (DoD) is determined from the actual usage pattern in the k-th reference time interval. ｋ ) is determined, Using a predefined correlation between the depth of discharge (DoD) and the depth of discharge decay rate (A ＤｏＤ ), the depth of discharge decay rate (A ｋ ) corresponding to the depth of discharge (DoD ＤｏＤ，ｋ ) is determined, Determining the remaining capacity of the second ESS using the following formula (Capacity ２ ), the ESS remaining capacity prediction system according to claim 3: 【Number 2】 (k: sequential 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 k-th reference time interval, A ｃ，ｋ : C-rate decay rate in the k-th reference time interval, A ＤｏＤ，ｋ : depth of discharge decay rate in the k-th reference time interval, A Ｔ : temperature decay rate corresponding to the designed operating temperature of the ESS, A Ｃ : C-rate decay rate corresponding to the designed charge / discharge C-rate of the ESS, A Ｄ０Ｄ : depth of discharge decay rate corresponding to the designed depth of discharge of the ESS, A: power conversion efficiency (pre-defined), B: capacity loss compensation rate (pre-defined), E: designed capacity of the ESS (pre-defined)).

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

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

8. further includes an ESS integrated management device operably coupled to the ESS controller, The ESS controller provides the event log to the ESS integrated management device side, according to the ESS remaining capacity prediction system of claim 6 or 7.

9. A method for an ESS controller operably coupled to an ESS (Energy Storage System) having a plurality of battery racks and a rack controller to predict the remaining capacity of the ESS, comprising: (a) obtaining the state of charge of the battery rack from the rack controller; (b) determining an actual usage pattern of the ESS indicating the change in the state of charge of the ESS for each reference time interval; (c) applying the average of the actual usage patterns determined for each reference time interval over the entire EOL life to determine the remaining capacity of the first ESS at the time when the EOL life has elapsed; (d) recording a first deviation between the remaining capacity of the first ESS and a reference remaining capacity; A method for predicting the remaining capacity of an ESS, comprising the steps above.

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

11. Applying the average of the actual usage patterns determined for each reference time interval up to the current time, and applying the designed usage pattern of the ESS for the remaining period of the EOL life from the current time to determine the remaining capacity of the second ESS at the time when the EOL life has elapsed; recording a second deviation between the remaining capacity of the second ESS and the reference remaining capacity; The method for predicting the remaining capacity of an ESS according to claim 9, further comprising the steps above.

12. When determining the remaining capacity of the first ESS, in the k-th (k is an index) reference time interval, The step of obtaining the temperature (T ｋ ), and charge / discharge C rate (c ｋ ) of the battery rack from the rack controller; Temperature (T) and temperature decay rate (A Ｔ ) using a predefined correlation between them, the temperature decay rate (A ｋ ) corresponding to the temperature (T Ｔ，ｋ ) and determining the temperature decay rate (A Charge-discharge C-rate (c) and C-rate attenuation rate (A ｃ ), using a predefined correlation between them, the charge-discharge C-rate (c ｋ ), and determining the C-rate attenuation rate (A ｃ，ｋ ) corresponding to it; Of the actual usage patterns determined for each of the reference time intervals, the depth of discharge (DoD) from the actual usage pattern in the k-th reference time interval ｋ ), and a step of determining Using a predefined correlation between the depth of discharge (DoD) and the depth of discharge decay rate (A ＤｏＤ ), determining the depth of discharge decay rate (A ｋ ) corresponding to the depth of discharge (DoD ＤｏＤ，ｋ ); Determining the remaining capacity (Capacity １ ) of the first ESS using the following formula; The method for predicting the remaining capacity of an ESS according to claim 9, comprising: 【Number 3】 (k: sequential index of the reference time interval, n: number of reference time intervals of the ESS usage period, W: "EOL / reference time interval", A Ｔ，ｋ : temperature decay rate in the k-th reference time interval, A ｃ，ｋ : C-rate decay rate in the k-th reference time interval, A ＤｏＤ，ｋ : depth of discharge decay rate in the k-th reference time interval, A: power conversion efficiency (pre-defined), B: capacity loss compensation rate (pre-defined), E: designed capacity of the ESS (pre-defined)).

13. When determining the remaining capacity of the second ESS, in the k-th (k is an index) reference time interval, The step of obtaining the temperature (T ｋ ), and the charge / discharge C rate (c ｋ ) of the battery rack from the rack controller; Using a predefined correlation between temperature (T) and temperature decay rate (A Ｔ ), determining the temperature decay rate (A ｋ ) corresponding to temperature (T Ｔ，ｋ ); Charge-discharge C rate (c) and C rate attenuation rate (A ｃ ), using a predefined correlation between them, the charge-discharge C rate (c ｋ ), determining the C rate attenuation rate (A ｃ，ｋ ) corresponding thereto; Of the actual usage patterns determined for each of the reference time intervals, the depth of discharge (DoD) from the actual usage pattern in the k-th reference time interval ｋ ) determining step; Using a predefined correlation between the depth of discharge (DoD) and the depth of discharge decay rate (A ＤｏＤ ), determining the depth of discharge decay rate (A ｋ ) corresponding to the depth of discharge (DoD ＤｏＤ，ｋ ); Determining the remaining capacity (Capacity ２ ) of the second ESS using the following formula; The method for predicting the remaining capacity of an ESS according to claim 11, comprising: 【Number 4】 (k: sequential index of reference time intervals, n: number of reference time intervals in the ESS usage period, W: "EOL life / reference time interval", A Ｔ，ｋ : temperature decay rate in the k-th reference time interval, A ｃ，ｋ : C-rate decay rate in the k-th reference time interval, A ＤｏＤ，ｋ : depth of discharge decay rate in the k-th reference time interval, A Ｔ : temperature decay rate corresponding to the designed operating temperature of the ESS, A Ｃ : C-rate decay rate corresponding to the designed charge / discharge C-rate of the ESS, A Ｄ０Ｄ : depth of discharge decay rate corresponding to the designed depth of discharge of the ESS, A: power conversion efficiency (pre-defined), B: capacity loss compensation rate (pre-defined), E: designed capacity of the ESS (pre-defined)).

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

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

16. The method further comprises providing the event log, the reference remaining capacity, the remaining capacity of the first ESS, and the first deviation to the ESS integrated management device side. The ESS integrated management device is connected to the ESS controller and is 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 the remaining capacity of an ESS according to claim 14. **Claim 17** Further including the step of providing the event log, the reference remaining capacity, the remaining capacity of the second ESS, and the second deviation to the ESS integrated management device side. The ESS integrated management device is connected to the ESS controller and is 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 the remaining capacity of an ESS according to claim 15. **Claim 18** A computer program including instructions for causing the ESS controller to execute the method for predicting the remaining capacity of an ESS according to any one of claims 9 to 15.

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