Method for re-calibrating state of charge on multi-battery systems

Abstract

A computer-implemented method for controlling an energy storage system is disclosed. The method may comprise: Monitoring the energy storage system for state of charge anomalies, wherein the energy storage system comprises a plurality of battery units. Determining, in response to detecting a state of charge anomaly in at least one battery unit within the plurality of battery units, a cause for the state of charge anomaly. Controlling, based on the determined cause, the at least one battery unit.

Description

[0001] METHOD FOR RE-CALIBRATING STATE OF CHARGE ON MULTI¬

[0002] BATTERY SYSTEMS

[0003] TECHNICAL FIELD

[0004] The present disclosure relates to the field of energy storage systems. Some example embodiments relate to a method for re-calibrating multi-battery systems.

[0005] BACKGROUND

[0006] Controlling an energy storage system may depend on correctly monitoring state of charge (SoC) of battery units within the energy system. Imbalance induced by various factors in the battery units may generate erroneous SoC readings. Such factors may comprise, e.g., inaccurate coulomb counting within a battery management system, varying resistance in cabling between components of the battery units, or quality discrepancies within the battery units.

[0007] Methods for detecting anomalies in SoC readings and analyzing the underlying factors may enable re-calibrating and / or balancing the energy storage system.

[0008] SUMMARY

[0009] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

[0010] Example embodiments of the present disclosure enable a contributionbased analysis of performance of a communication network comprising a plurality of cells. This benefit may be achieved by the features of the independent claims. Further example embodiments are provided in the dependent claims, the detailed description, and the drawings.

[0011] According to a first aspect, a computer-implemented method for controlling an energy storage system is disclosed. The method may comprise: Monitoring the energy storage system for state of charge anomalies, wherein the energy storage system comprises a plurality of battery units. Determining, in response to detecting a state of charge anomaly in at least one battery unit within the plurality of battery units, a cause for the state of charge anomaly. Controlling, based on the determined cause, the at least one battery unit. With such a method, correcting imbalances within the energy storage system may be enabled.

[0012] According to an example embodiment of the first aspect, the determining the cause may comprise: Analyzing time series data comprising values for a plurality of key performance indicators collected from the plurality of battery units. With such a method, imbalances within the system may be corrected based on performance analysis.

[0013] According to an example embodiment of the first aspect, the plurality of key performance indicators may comprise at least one of: state of charge, voltage, current, system load, and temperature. With such a method, various parameters of the system performance may be taken into account in the analysis.

[0014] According to an example embodiment of the first aspect, the determining the cause may comprise: Receiving a battery alarm indicating an error state within the at least one battery unit.

[0015] According to an example embodiment of the first aspect, the determining the cause may further comprise: Sending a command for an investigative action to the at least one battery unit. Monitoring the at least one battery unit for an impact of the investigative action. Refining, based on the monitored impact, the determined cause for the state of charge anomaly. With such a method, further investigation may be utilized to determine causes for state of charge anomalies.

[0016] According to an example embodiment of the first aspect, the sending the command for the investigative action may be performed in response to a criterion being met. With such a method, further conditions for the investigative action may be determined.

[0017] According to an example embodiment of the first aspect, the criterion may comprise: Determining the cause for the state of charge anomaly with a pre-determined level of uncertainty. Determining the cause for the state of charge anomaly as comprising a specific pre-determined cause.

[0018] According to an example embodiment of the first aspect, the investigative action command may comprise a command to start a charging action or a discharging action of the at least one battery unit. With such a method, further information of the energy system may be obtained by starting the charging action or the discharging action.

[0019] According to an example embodiment of the first aspect, the monitoring the energy storage system may comprise monitoring values for at least one of: current, voltage, temperature, system load, physical state of charge, and reported state of charge. With such a method, various parameters indicating an anomalous behavior may be utilized.

[0020] According to an example embodiment of the first aspect, the determined cause may comprise an imbalance within the at least one battery unit. The controlling may comprise sending a command to implement a balancing mechanism. With such a method, a more accurate state of charge reporting may be achieved by correcting the imbalance.

[0021] According to an example embodiment of the first aspect, the balancing mechanism may comprise adjusting voltage. With such a method, the at least one battery unit may be re-calibrated.

[0022] According to an example embodiment of the first aspect, the state of charge anomaly may comprise detecting a plurality of different state of charge values indicated by the plurality of battery units.

[0023] According to an example embodiment of the first aspect, the determined cause may comprise a faulty battery unit within the plurality of battery units. The method may further comprise generating a maintenance notification. With such a method no further investigation is performed in case of detecting a faulty battery unit.

[0024] According to a second aspect, an apparatus may comprise at least one processor and at least one memory including computer program code. The at least one memory and the computer code may be configured to, with the at least one processor, cause the apparatus at least to perform: Monitoring the energy storage system for state of charge anomalies, wherein the energy storage system comprises a plurality of battery units. Determining, in response to detecting a state of charge anomaly in at least one battery unit within the plurality of battery units, a cause for the state of charge anomaly. Controlling, based on the determined cause, the at least one battery unit. According to a third aspect, a computer program product may comprise computer-readable program code configured to, when read and executed by a computer system, cause the computer system at least to perform: Monitoring the energy storage system for state of charge anomalies, wherein the energy storage system comprises a plurality of battery units. Determining, in response to detecting a state of charge anomaly in at least one battery unit within the plurality of battery units, a cause for the state of charge anomaly. Controlling, based on the determined cause, the at least one battery unit.

[0025] Any example embodiment may be combined with one or more other example embodiments. Many of the attendant features will be more readily appreciated as they become better understood by reference to the following detailed description considered in connection with the accompanying drawings.

[0026] DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings, which are included to provide a further understanding of the example embodiments and constitute a part of this specification, illustrate example embodiments and together with the description help to understand the example embodiments. In the drawings:

[0028] FIG. 1 illustrates a schematic block diagram of an example energy storage system;

[0029] FIG. 2 illustrates a schematic flow chart of a re-calibration method according to an example embodiment;

[0030] FIG. 3 illustrates a schematic flow chart of a re-calibration method according to another example embodiment; and

[0031] FIG. 4 illustrates a schematic block diagram of an apparatus configured to practice one or more example embodiments;

[0032] DETAILED DESCRIPTION

[0033] Reference will now be made in detail to example embodiments, examples of which are illustrated in the accompanying drawings. The detailed description provided below in connection with the appended drawings is intended as a description of the present examples and is not intended to represent the only forms in which the present example may be constructed or utilized. The description sets forth the functions of the example and the sequence of steps for constructing and operating the example. However, the same or equivalent functions and sequences may be accomplished by different examples.

[0034] Although the specification may refer to “an”, “one”, or “some” embodiment(s) in several locations, this does not necessarily mean that each such reference is to the same embodiment(s), or that the feature may not apply to other embodiments. Single features of different embodiments may also be combined to provide other embodiments. Furthermore, words “comprising” and “including” should be understood as not limiting the described embodiments / example, and the embodiments / examples may contain also features / structures that have not been specifically mentioned.

[0035] According to an example embodiment, an energy storage system comprising a plurality of battery units (a multi-battery system) is monitored for state of charge anomalies. Causes for detected state of charge anomalies are determined and the plurality of battery units controlled based on the determined cause.

[0036] According to the example embodiment, it is possible to achieve more accurate state of charge reporting within the energy storage system by correcting imbalances within the plurality of battery units. The plurality of battery units may be more efficiently utilized and more accurate controlling of the energy storage system may be enabled. A more stable voltage profile may be provided by the energy storage system for, e.g., telecommunication equipment. Depending on the situation, actions to achieve these benefits may be different.

[0037] FIG. 1 illustrates a schematic representation of an example embodiment of an energy storage system, for which the re-calibration method may be utilized. The energy storage system may be referred to as, e.g., a distributed energy storage system, a virtual power plant, a virtual power plant system, or similar.

[0038] Referring to FIG. 1, an energy storage system 100 comprises a plurality of battery units 104a, 104b, 104c, 104d coupled to a power grid 102 and to a controller 106. The controller may be configured to control the plurality of battery units according to functionalities described below with reference to FIG. 2 and 3. The controller may be implemented as the apparatus 400 illustrated in FIG. 4. The energy storage system 100 further comprises at least one backend equipment 110 comprising a database 112. The backend equipment may be implemented as the apparatus 400 illustrated in FIG. 4. The controller 106 and the backend equipment 110 are connectable over one or more networks 108.

[0039] FIG. 2 illustrates a flowchart according to an example embodiment of a computer-implemented method for controlling the energy storage system 100.

[0040] Referring to FIG. 2, the energy storage system is monitored in operation 201 for state of charge (SoC) anomalies. The energy storage system comprises a plurality of battery units. In an example embodiment, the monitoring the energy storage system comprises monitoring values for at least one of: current, voltage, temperature, system load, an physical state of charge, and a reported state of charge. The physical state of charge may be understood as an amount of coulombs truly charged in a lithium cell of a battery unit within the plurality of battery units, thus reflecting a physical reality of the battery unit. The reported state of charge may be understood as a state of charge indicated by a battery unit within the plurality of battery units. It is resolved in operation 202 whether a state of charge anomaly is detected in at least one battery unit within the plurality of battery units. In an example embodiment, the state of charge anomaly comprises detecting a plurality of different state of charge values indicated by the plurality of battery units. If the state of charge anomaly is not detected (operation 202: no), the process continues in operation 201 by monitoring the energy storage system for state of charge anomalies. If the state of charge anomaly is detected (operation 202: yes), a cause for the state of charge anomaly is determined in operation 203. Then the at least one battery unit is controlled in operation 204.

[0041] In an example embodiment, determining the cause for the SoC anomaly comprises analyzing time series data collected from the plurality of battery units. The time series data comprises values for a plurality of key performance indicators (KPIs) collected from the plurality of battery units. In an example embodiment, the plurality of key performance indicators comprises at least one of: state of charge, voltage, current, system load, and temperature. The time series data may be stored in an internal database within the energy storage system or it may be stored in an external database. In an example embodiment, the determined cause for the SoC anomaly comprises an imbalance within the at least one battery unit, and the controlling the at least one battery unit comprises sending a command to the at least one battery unit to implement a balancing mechanism. In an example embodiment, the balancing mechanism comprises adjusting voltage of a rectifier electrically coupled to the at least one battery unit, leading to the at least one battery unit being re-calibrated. In an example embodiment, the balancing mechanism comprises adjusting voltage of the at least one battery unit, leading to the at least one battery unit being recalibrated. In an example embodiment, determining the cause is based on a type of the at least one battery unit. The type may comprise various information on the at least one battery unit, e.g., vendor, version, age, DC-DC converter, chemistry, and / or rectifier type. The cause of the SoC anomaly may be determined by using, e.g., a rule-based logic, data science methods, or a machine learning model.

[0042] In an example embodiment, the cause for the state of charge anomaly may comprise the at least one battery unit having been discharged completely or partly due to, e.g. a power blackout. The timeseries data comprises SoC values and voltage values. Voltage values that have dropped to very low levels such as < 44 V (volts) may indicate that the battery unit is empty due to dischargement. The controlling of the battery may then comprise scheduling a re-calibration and charging the at least one battery back to at least back-up capacity, e.g., once the power has been returned.

[0043] In an example embodiment, high state of charge values with low voltage values may be detected when monitoring the energy storage system. This may occur due to non-accurate current measurements performed by a battery management system which may cause drift in reported state of charge values over time, leading to false reported state of charge values. Thus, the cause for the state of charge anomaly may be the non-accurate current measurements. The time series data comprises voltage values and state of charge values of the plurality of battery units from, e.g., 24 hours with a sampling rate of 2 min. Different voltage values may be categorized as ‘low’, ‘medium’, and ‘high’. A low voltage value may be understood as, e.g., less than 48 V. A high voltage value may be understood as, e.g., more than 51 V. Different SoC values may be categorized as ‘low’, ‘medium’, and ‘high’. A low SoC value may be understood as, e.g., less than 30% of full SoC. A high SoC value may be understood as, e.g., more than 80% of full SoC. in an example embodiment, a fuzzy logic rule engine may be used to determine values for a need for recalibration parameter (“recal need”). The rules may comprise the following: rulel = Rule(voltage[‘high’] & SoC[‘high’], recal_need[‘low’]) rule2= Rule(voltage[‘high’] & SoC[‘low’], recal_need[‘low’]) rule3 = Rule(voltage[‘low’] & SoC[‘high’], recal_need[‘high’]) ruled = Rule(voltage[‘low’] & SoC[‘low’], recal_need[‘medium’]) rule5 = Rule(voltage[‘medium’] & SoC [‘medium'], recal_need[‘low’]) rule6 = Rule(voltage[‘medium’] & SoC[‘low’], recal_need[‘low’]) rule? = Rule(voltage[‘low’] & SoC [‘medium’], recal_need(‘medium’])

[0044] In another example embodiment, a machine learning model may be used to determine values for the need of re-calibration parameter (“recal need”). The machine learning model may be trained using, e.g., a random forest, extreme gradient boosting (XGBoost), or a neural network.

[0045] The controlling the at least one battery unit may then comprise re-calibrating when the need for re-calibration parameter has value ‘high’, or re-calibrating when the need for re-calibration parameter has value ‘high’ or ‘medium’.

[0046] In an example embodiment, the determined cause comprises a faulty battery unit within the plurality of battery units. The method then further comprises generating a maintenance notification. No balancing mechanism may be needed when the cause for the SoC anomaly is determined to be the faulty battery unit.

[0047] FIG. 3 illustrates a flowchart according to example functionalities for determining the cause for the state of charge anomaly. The functionalities illustrated in FIG. 3 may be carried out within operation 203 in FIG. 2.

[0048] Referring to FIG. 3, a command for an investigative action is sent in operation 301 to the at least one battery unit. In an example embodiment, the sending the command for the investigative action may be performed in response to a criterion being met. In an example embodiment, the criterion may comprise determining the cause for the state of charge anomaly with a pre-determined level of uncertainty. In an example embodiment, the criterion may comprise determining the cause for the state of charge anomaly as comprising a specific pre-determined cause. In an example embodiment, the investigative action may be scheduled to be performed immediately. In an example embodiment, the investigative action may be scheduled to be performed in the future, e.g., within a defined period of time. In an example embodiment, the investigative action may be an action that would be performed in any event even without the command, and then the command for the investigative action comprises a command to monitor the action when it is performed. In an example embodiment, the investigative action may comprise allowing the at least one battery unit to be charged to full capacity while normally a state of charge value exceeding 90% would be avoided. In an example embodiment, the investigative action may comprise starting a charging action of the at least one battery unit. In an example embodiment, the investigative action may comprise starting a charging action of the plurality of the battery units or some battery units within the plurality of battery units. In an example embodiment, the investigative action may comprise starting a discharging action of the at least one battery unit. In an example embodiment, the investigative action may comprise starting a discharging action of the plurality of the battery units or some battery units within the plurality of battery units. The energy system is monitored in operation 302 for an impact of the investigative action. The determined cause for the state of charge anomaly is refined in operation 303 based on the monitored impact of the investigative action.

[0049] In an example embodiment, low state of charge values may be detected when monitoring the energy storage system while the state of charge values do not increase past, e.g., a pre-determined threshold even when high voltage values are detected. The time series data comprises voltage values and state of charge values of the plurality of battery units from, e.g., 24 hours with a sampling rate of 2 min. Analyzing the time series data may not reveal the cause for the state of charge anomaly, e.g., with a sufficient level of certainty, which may be understood as determining the cause for the state of charge anomaly with the pre-determined level of uncertainty. The investigative action may comprise, e.g., initiating charging the at least one battery unit and measuring current while charging. The cause of the state of charge anomaly may comprise the battery management system being imbalanced and thus monitoring low state of charge while the plurality of battery units are truly charged to full capacity. The controlling the at least one battery unit based on monitoring the impact of the investigative action may comprise executing a corrective action. In an example embodiment, the corrective action may comprise, e.g., raising charging voltage of the at least one battery unit temporarily to a level where an overvoltage threshold is triggered. Thus, the battery management system is reset. In an example embodiment, the corrective action may comprise, e.g., raising charging voltage of the at least one battery unit slightly, e.g., to 56 V, to re-engage a charging mode on a DC-DC converter. After executing the corrective action, the at least one battery unit is re-measured to ensure a normal functioning.

[0050] In an example embodiment, different state of charge values may be detected in at least two battery units within the plurality of battery units when monitoring the energy storage system. Different state of charge values indicated by the plurality of battery units may cause the energy storage system not to charge at full capacity. The time series data comprises current values and state of charge values of the plurality of battery units from, e.g., 24 hours with a sampling rate of 2 min. Analyzing the time series data may not reveal the cause for the state of charge anomaly, e.g., with a sufficient level of certainty, which may be understood as determining the cause for the state of charge anomaly with the pre-determined level of uncertainty. The investigative action may comprise, e.g., initiating charging the at least one battery unit and measuring current while charging. The controlling the at least one battery unit based on monitoring the impact of the investigative action may comprise executing a corrective action. The corrective action may comprise, e.g., scheduling the energy storage system to perform a full re-calibration charging the plurality of battery units to full capacity, i.e., 100%. The charging may be performed until a charging current of close to 0 A (amperes) may be measured. In an example embodiment, when the plurality of battery units comprises at least six battery units, measuring a charging current of less than 4 A may be understood as being close to 0 A. Then the at least two battery units may be balanced at 100% state of charge value.

[0051] In an example embodiment, a state of charge value of 0% may be detected in the at least one battery unit when monitoring the energy storage system even though the at least one battery unit is being charged at a high charging current. The investigative action may comprise lowering the output voltage to, e.g., 44 V to discharge the at least one battery unit completely. Then the at least one battery unit may be balanced at 0% state of charge value.

[0052] In an example embodiment, a state of charge value of 100% may be detected in the plurality of battery units when monitoring the energy storage system even though it is possible to continuously charge the plurality of battery units using a high current. The investigative action may comprise maintaining charging until the charging current decreases to close to 0 A. Then the plurality of battery units will be balanced at 100% state of charge.

[0053] FIG. 4 illustrates an example embodiment of an apparatus 400 configured to perform operations of one or more example embodiments, e.g., functionalities described above with reference to FIG. 2 and 3. The apparatus 400 may be for example used to implement the controller 106. The apparatus 400 may comprise at least one processor 402. The at least one processor 402 may comprise, for example, one or more of various processing devices or processor circuitry, such as for example a co-processor, a microprocessor, a controller, a digital signal processor (DSP), a processing circuitry with or without an accompanying DSP, or various other processing devices including integrated circuits such as, for example, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a microcontroller unit (MCU), a hardware accelerator, a special-purpose computer chip, or the like.

[0054] The apparatus 400 may further comprise at least one memory 404. The at least one memory 404 may be configured to store, for example, computer program code or the like, for example operating system software and application software. The at least one memory 404 may comprise one or more volatile memory devices, one or more non-volatile memory devices, and / or a combination thereof. For example, the at least one memory 404 may be embodied as magnetic storage devices (such as hard disk drives, floppy disks, magnetic tapes, etc.), optical magnetic storage devices, or semiconductor memories (such as mask ROM, PROM (programmable ROM), EPROM (erasable PROM), flash ROM, RAM (random access memory), etc.).

[0055] The apparatus 400 may further comprise a communication interface 208 configured to enable apparatus 400 to transmit and / or receive information to / ffom other devices, functions, or entities. The apparatus 400 may further comprise a user interface 410, for example for providing user output by the apparatus, such as for example visual and / or audible signal(s), for example by speaker(s), display(s), light(s), or the like. The user interface 410 may be used for example for outputting indication(s) of, e.g., performance to a human user.

[0056] When the apparatus 400 is configured to implement some functionality, some component and / or components of the apparatus 400, such as for example the at least one processor 402 and / or the at least one memory 404, may be configured to implement this functionality. Furthermore, when the at least one processor 402 is configured to implement some functionality, this functionality may be implemented using program code 406 comprised, for example, in the at least one memory 404.

[0057] The functionality described herein may be performed, at least in part, by one or more computer program product components such as for example software components. According to an example embodiment, the apparatus 400 comprises a processor or processor circuitry, such as for example a microcontroller, configured by the program code when executed to execute the embodiments of the operations and functionality described. A computer program or a computer program product may therefore comprise instructions for causing, when executed, the apparatus 400 to perform the method(s) described herein. Alternatively, or in addition, the functionality described herein may be performed, at least in part, by one or more hardware logic components. For example, and without limitation, illustrative types of hardware logic components that may be used include Field-programmable Gate Arrays (FPGAs), application-specific Integrated Circuits (ASICs), application-specific Standard Products (ASSPs), System-on-a-chip systems (SOCs), Complex Programmable Logic Devices (CPLDs), Graphics Processing Units (GPUs).

[0058] The apparatus 400 comprises means for performing at least one method described herein. In one example, the means comprises the at least one processor 402, the at least one memory 404 including the program code 406 configured to, when executed by the at least one processor, cause the apparatus 400 to perform the method.

[0059] The apparatus 400 may comprise a computing device such as for example an access point, an access node, a base station, a server, a network device, a network function device, or the like. Although the apparatus 400 is illustrated as a single device it is appreciated that, wherever applicable, functions of the apparatus 400 may be distributed to a plurality of devices, for example to implement example embodiments as a cloud computing service.

[0060] Although the subject matter has been described in language specific to structural features and / or acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example embodiments of implementing the claims and other equivalent features and acts are intended to be within the scope of the claims.

[0061] It will be understood that the benefits and advantages described above may relate to one example embodiment or may relate to several example embodiments. The example embodiments are not limited to those that solve any or all of the stated problems or those that have any or all of the stated benefits and advantages. It will further be understood that reference to 'an' item may refer to one or more of those items.

[0062] The steps or operations of the methods described herein may be carried out in any suitable order, or simultaneously where appropriate. Additionally, individual blocks may be deleted from any of the methods without departing from the scope of the subject matter described herein. Aspects of any of the example embodiments described above may be combined with aspects of any of the other example embodiments described to form further example embodiments without losing the effect sought.

[0063] It will be understood that the above description is given by way of example embodiments only and that various modifications may be made by those skilled in the art. The above specification, example embodiments and data provide a complete description of the structure and use of exemplary embodiments. Although various example embodiments have been described above with a certain degree of particularity, or with reference to one or more individual embodiments, those skilled in the art could make numerous alterations to the disclosed example embodiments without departing from scope of this specification.

Claims

CLAIMS1. A computer-implemented method for controlling an energy storage system, comprising: monitoring (201) the energy storage system for state of charge anomalies, wherein the energy storage system comprises a plurality of battery units; determining (203), in response to detecting (202) a state of charge anomaly in at least one battery unit within the plurality of battery units, a cause for the state of charge anomaly, wherein the cause is determined based on a type of the at least one battery unit; and controlling (204), based on the determined cause, the at least one battery unit, wherein the determined cause comprises an imbalance within the at least one battery unit, and the controlling comprises sending a command to implement a balancing mechanism, wherein the balancing mechanism comprises adjusting voltage of a rectifier electrically coupled to the at least one battery unit.

2. A method according to claim 1, wherein the determining the cause comprises: analyzing time series data comprising values for a plurality of key performance indicators collected from the plurality of battery units.

3. A method according to claim 2, wherein the plurality of key performance indicators comprises at least one of: state of charge, voltage, current, system load, and temperature.

4. A method according to claim 2 or 3, wherein the determining the cause further comprises: receiving a battery alarm indicating an error state within the at least one battery unit.

5. A method according to any of claims 2 to 4, wherein the determining the cause further comprises: sending (301) a command for an investigative action to the at least one battery unit;monitoring (302) the at least one battery unit for an impact of the investigative action; and refining (303), based on the monitored impact, the determined cause for the state of charge anomaly.

6. A method according to claim 5, wherein the sending the command for the investigative action is performed in response to a criterion being met.

7. A method according to claim 6, wherein the criterion comprises determining the cause for the state of charge anomaly with a pre-determined level of uncertainty or the cause for the state of charge anomaly as comprising a specific pre-determined cause.

8. A method according to any of claims 5 to 7, wherein the investigative action command comprises a command to start a charging action or a discharging action of the at least one battery unit.

9. A method according to any of claims 1 to 8, wherein the monitoring the energy storage system comprises monitoring values for at least one of: current, voltage, temperature, system load, physical state of charge, and reported state of charge.10.. A method according to any of claims 1 to 9, wherein the state of charge anomaly comprises detecting a plurality of different state of charge values indicated by the plurality of battery units.

11. A method according to claim 1 , wherein the determined cause comprises a faulty battery unit within the plurality of battery units, and wherein the method further comprises generating a maintenance notification.

12. An apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and computer program code being configured to, with the at least oneprocessor, cause the apparatus at least to perform: monitoring the energy storage system for state of charge anomalies, wherein the energy storage system comprises a plurality of battery units; determining, in response to detecting a state of charge anomaly in at least one battery unit within the plurality of battery units, a cause for the state of charge anomaly, wherein the cause is determined based on a type of the at least one battery unit; and controlling, based on the determined cause, the at least one battery unit, wherein the determined cause comprises an imbalance within the at least one battery unit, and the controlling comprises sending a command to implement a balancing mechanism, wherein the balancing mechanism comprises adjusting voltage of a rectifier electrically coupled to the at least one battery unit.

13. A computer program product comprising a computer-readable program code configured to, when read and executed by a computer system, cause the computer system at least to perform: monitoring the energy storage system for state of charge anomalies, wherein the energy storage system comprises a plurality of battery units; determining, in response to detecting a state of charge anomaly in at least one battery unit within the plurality of battery units, a cause for the state of charge anomaly, wherein the cause is determined based on a type of the at least one battery unit; and controlling, based on the determined cause, the at least one battery unit, wherein the determined cause comprises an imbalance within the at least one battery unit, and the controlling comprises sending a command to implement a balancing mechanism, wherein the balancing mechanism comprises adjusting voltage of a rectifier electrically coupled to the at least one battery unit.

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