Device for controlling energy storage system and method for controlling energy storage system

Abstract

A device for controlling an energy storage system disclosed in the present document comprises: a communication unit for receiving an external power generation amount and an internal power consumption amount; a user interface unit for receiving a cost function selection command from a user; and a control unit for determining an objective function on the basis of a cost function selected by the user and performing battery control optimization on the basis of the external power generation amount, the internal power consumption amount, and the objective function. The control unit: performs the battery control optimization on the basis of a first point in time; determines a predicted value of battery charging / discharging power on the basis of the battery control optimization performed at the first point in time; determines a predicted section including the predicted value of the battery charging / discharging power; and performs the battery control optimization again on the basis that the actual value of the battery charging / discharging power is outside the range of the predicted section.

Description

Control device for energy storage system and control method for energy storage system

[0001] Cross-citation with related applications

[0002] This application claims the benefit of priority from Republic of Korea Patent Application No. 10-2023-0110622, filed August 23, 2023, the entire contents of which are incorporated herein by reference.

[0003] Technology field

[0004] The embodiments disclosed in this document relate to a control device for an energy storage system and a control method for an energy storage system.

[0005] An Energy Storage System (ESS) is a device that stores generated electricity in a storage device, such as a battery, and then supplies it when needed, improving the efficiency of power usage. These ESSs can store electricity generated by renewable energy sources like solar and wind power, or transmitted from power plants, in batteries. They store electricity at night when power consumption is low, and use the stored power during the day when power consumption is high.

[0006] In order to effectively distribute the power usage of energy storage systems, efficient scheduling of charging and discharging is required. However, in the past, there was a limitation that errors occurred due to the failure to consider the uncertainty in predicting the amount of renewable energy generation and power consumption.

[0007] According to one embodiment disclosed in this document, in order to increase the efficiency of the energy storage system, a control device for an energy storage system and a control method for an energy storage system are provided that take into account the uncertainty in prediction of renewable energy generation and power consumption.

[0008] The technical problems of the embodiments disclosed in this document are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the descriptions below.

[0009] According to one embodiment, a control device of an energy storage system includes a communication unit that receives an amount of external power produced and an amount of internal power consumed, a user interface unit that receives a cost function selection command from a user, a control unit that determines an objective function based on the cost function selected by the user, and performs battery control optimization based on the amount of external power produced, the amount of internal power consumed, and the objective function, wherein the control unit performs the battery control optimization based on a first point in time, determines a predicted value of battery charge / discharge power based on the battery control optimization performed at the first point in time, determines a predicted interval including the predicted value of the battery charge / discharge power, and performs the battery control optimization again based on an actual value of the battery charge / discharge power being outside a range of the predicted interval.

[0010] The control unit can adjust variables for battery control optimization based on whether the actual value of the battery charge / discharge power falls outside the range of the prediction interval.

[0011] The control unit can perform the battery control optimization again based on the adjusted variables for the battery control optimization.

[0012] The control unit can receive a weight for determining the priority of the cost function from the user through the user interface unit, and determine the objective function as a weighted sum of the weight and the cost function.

[0013] The user interface unit may further include an input unit, and the input unit may be configured as a UI (User Interface) in which the ratio of the weight is adjusted based on the user's input.

[0014] The control unit may recommend the weight to the user based on the fact that the weight has not been input by the user for a preset period of time.

[0015] The control unit can generate combinations that can be generated based on the number of cost functions and the interval information of the weights, and recommend to the user a combination with the lowest power purchase cost among the combinations.

[0016] The above cost function may include a function that minimizes the difference between the backup SOC (State Of Charge) utilized in the home energy storage system and the user's required SOC.

[0017] The above cost function may include a function that minimizes the difference between the current indoor temperature utilized in the home energy storage system and the user's desired temperature.

[0018] The above control unit can modify the charge / discharge schedule based on the battery control optimization performed again, and perform charge / discharge based on the modified charge / discharge schedule.

[0019] A control method of an energy storage system according to one embodiment includes receiving an external power production amount and an internal power consumption amount, receiving a cost function selection command from a user, determining an objective function based on the cost function selected by the user, performing battery control optimization based on the external power production amount, the internal power consumption amount, and the objective function, and performing the battery control optimization includes performing the battery control optimization based on a first point in time, determining a predicted value of battery charge / discharge power based on the battery control optimization performed at the first point in time, determining a predicted interval including the predicted value of the battery charge / discharge power, and performing the battery control optimization again based on an actual value of the battery charge / discharge power being outside a range of the predicted interval.

[0020] A control method of an energy storage system according to one embodiment may further include adjusting a variable for optimizing battery control based on whether an actual value of the battery charge / discharge power falls outside the range of the prediction interval.

[0021] A method for controlling an energy storage system according to one embodiment may further include re-performing the battery control optimization based on the adjusted variables for the battery control optimization.

[0022] Determining the above objective function can be accomplished by receiving weights for determining the priority of the cost function from the user through a user interface unit, and determining the objective function as a weighted sum of the weights and the cost function.

[0023] A control method of an energy storage system according to one embodiment may further include adjusting the ratio of the weights based on the user input entered into the input unit included in the user interface unit.

[0024] A control method of an energy storage system according to one embodiment may further include recommending the weight to the user based on the weight not being input by the user for a preset period of time.

[0025] Recommending the weights to the user may include generating combinations that can be generated based on the number of cost functions and the interval information of the weights, and recommending to the user a combination with the lowest power purchase cost among the combinations.

[0026] The above cost function may include a function that minimizes the difference between the backup SOC (State Of Charge) utilized in the home energy storage system and the user's required SOC.

[0027] The above cost function may include a function that minimizes the difference between the current indoor temperature utilized in the home energy storage system and the user's desired temperature.

[0028] A control method of an energy storage system according to one embodiment may further include modifying a charge / discharge schedule based on the battery control optimization performed again, and performing charge / discharge based on the modified charge / discharge schedule.

[0029] According to a control device of an energy storage system according to one embodiment, uncertainty in prediction of renewable energy generation and power consumption can be taken into account to optimize the energy storage system, thereby reducing errors in energy storage system optimization.

[0030] According to a control device of an energy storage system according to one embodiment, the user can select an objective function and weights in the process of optimizing the energy storage system, so that optimization that matches the user's intention is possible.

[0031] Figure 1 schematically illustrates the configuration of a control device and a power management system of an energy storage system according to one embodiment.

[0032] FIG. 2 illustrates a block diagram showing the configuration of an energy storage system control device according to one embodiment.

[0033] FIG. 3 schematically illustrates a flow for determining whether to re-perform optimization in a control unit of an energy storage system control device according to one embodiment.

[0034] FIG. 4 is a graph showing conditions under which an energy storage system is optimized by a control device of an energy storage system according to one embodiment.

[0035] FIG. 5 illustrates a user interface portion of an energy storage system control device according to one embodiment.

[0036] FIG. 6 illustrates a table for recommending weights in an energy storage system control device according to one embodiment.

[0037] Figure 7 illustrates a flowchart of an energy storage system control method according to one embodiment.

[0038] FIG. 8 continues to illustrate a flowchart of an energy storage system control method according to one embodiment of FIG. 7.

[0039] Hereinafter, various embodiments disclosed in this document will be described in detail with reference to the attached drawings. In this document, identical components in the drawings are designated by the same reference numerals, and redundant descriptions of identical components are omitted.

[0040] With respect to the various embodiments disclosed in this document, specific structural and functional descriptions are merely illustrative for the purpose of explaining the embodiments, and the various embodiments disclosed in this document may be implemented in various forms and should not be construed as being limited to the embodiments described in this document.

[0041] The expressions "first," "second," "first," or "second" used in various embodiments may describe various components, regardless of order and / or importance, and do not limit the components. For example, without departing from the scope of the embodiments disclosed herein, a first component may be renamed a second component, and similarly, a second component may also be renamed a first component.

[0042] The terms used in this document are intended solely to describe specific embodiments and may not be intended to limit the scope of other embodiments. Singular expressions may include plural expressions unless the context clearly dictates otherwise.

[0043] All terms used herein, including technical or scientific terms, have the same meaning as commonly understood by those of ordinary skill in the art of the embodiments disclosed herein. Terms defined in commonly used dictionaries may be interpreted as having the same or similar meaning in the context of the relevant technology, and unless explicitly defined herein, they shall not be interpreted in an idealized or overly formal sense. In some cases, even if a term is defined herein, it cannot be interpreted to exclude the embodiments disclosed herein.

[0044] Figure 1 schematically illustrates the configuration of a control device and a power management system of an energy storage system according to one embodiment.

[0045] Referring to FIG. 1, an energy storage system (20) (ESS) may refer to a system that separately stores surplus power in a battery and supplies it when needed, and may refer to a configuration that can solve power supply and demand problems by storing power that is wasted at night and supplying it during peak hours.

[0046] An energy storage system (ESS) (20) can receive and store power from a power grid (21), a renewable energy generation module (22), or an electric vehicle (23), and a battery module included in the energy storage system (ESS) (20) can be configured with a combination of a plurality of battery cells connected in series and in parallel.

[0047] Here, the system power grid (21) may refer to a network connected to a power supplier that generates and supplies electricity. In other words, the system power grid (21) may refer to a network interconnected to supply electricity from power producers to power consumers.

[0048] In addition, the renewable energy generation module (22) may refer to a module that generates electric energy using solar energy, wind energy, geothermal energy, ocean energy, and bio energy.

[0049] The energy storage system (ESS) (20) may further include a power conversion device (not shown), which may convert AC power supplied from a power grid (21) into DC power and store the DC power in a battery module. In addition, the power conversion device (not shown) may convert the output of a battery module or the output of a renewable energy generation module (22) into AC power and supply the AC power to a load (24) or transmit the AC power to a grid.

[0050] The energy storage system control device (1) can control the charging / discharging of the battery module, and can control and manage the voltage, current, temperature, etc. of the battery module to prevent overcharging and overdischarging, etc., and can include, for example, a BMS.

[0051] The energy storage system (20) may be connected to the system power grid (21), a renewable energy generation module (22), an electric vehicle (23), a load (24), and the input / output of the energy storage system (ESS) (20), and may be configured to control the distribution and connection of the mutual input / output according to the power status of the energy storage system (ESS) (20).

[0052] A detailed configuration of an energy storage system control device (1) according to one embodiment is described below in FIG. 2.

[0053] FIG. 2 illustrates a block diagram showing the configuration of an energy storage system control device according to one embodiment.

[0054] Referring to FIG. 2, an energy storage system control device (1) according to one embodiment includes a control unit (100) including at least one processor (110) and memory (120), a communication unit (200), and a user interface unit (300), and can control the energy storage system (20) by communicating with an external device (2) through the communication unit (200).

[0055] An energy storage system control device (1) according to one embodiment may mean any electronic device including a processor (110) and a memory (120).

[0056] The communication unit (200) may include a wireless communication unit (210) and a wired communication unit (220) to communicate with an external device (2). The communication unit (200) may transmit and receive various data related to cost functions and weights from a separately provided user interface unit (300).

[0057] The wireless communication unit (210) may include at least one of a short-range communication module and a long-range communication module.

[0058] The short-range communication module can communicate with an external device (2) adjacent to the energy storage system control device (1) using a short-range communication method. Here, the short-range communication module can utilize one of the following communication methods: Bluetooth, Bluetooth low energy, infrared data association (IrDA), Zigbee, Wi-Fi, Wi-Fi direct, Ultra Wideband (UWB), or near field communication (NFC).

[0059] The remote communication module may include a communication module that performs various types of remote communication, and may include a mobile communication unit (200). The mobile communication unit (200) may transmit and receive a wireless signal with at least one of a base station, an external terminal, and an external device (2) on a mobile communication network. In addition, the remote communication module may communicate with an external device (2) or an external device (2) such as another electronic device through a surrounding access point (AP). The access point (AP) may connect a local area network (LAN) to which the energy storage system control device (1) is connected to a wide area network (WAN) to which a communication server is connected. Accordingly, the energy storage system control device (1) may be connected to the communication server through the wide area network (WAN) and communicate with the external device (2).

[0060] The wired communication unit (220) can connect to a wired communication network and communicate with an external device (2) through the wired communication network. For example, the wired communication unit (220) can connect to a wired communication network through Ethernet (IEEE 802.3 technology standard) or connect to a wired communication network through CAN communication, and transmit and receive data with the external devices (2) through the wired communication network.

[0061] An energy storage system control device (1) according to one embodiment may include a user interface unit (300) having an input unit (310) and an output unit (320).

[0062] The input unit (310) may be implemented as at least one input means such as a touch screen, a push button, a membrane button, a dial, a slider switch, etc., but is not limited thereto.

[0063] The output unit (320) may be implemented as a display means such as a plasma display panel (PDP), a liquid crystal display (LCD) panel, a light emitting diode (LED) panel, an organic light emitting diode (OLED) panel, an active-matrix organic light-emitting diode (AMOLED) panel, and a curved display panel, but is not limited thereto.

[0064] The user interface unit (300) can provide an interface that connects the input unit (310) and the output unit (320) to the processor (110) to enable data transmission and reception.

[0065] The memory (120) can store various information required for driving the energy storage system control device (1). Specifically, the memory (120) can store an operating system and a program required for driving the energy storage system control device (1), or store data required for driving the energy storage system control device (1).

[0066] Specifically, the memory (120) can store various programs related to the power generation amount of the renewable energy generation module (22) and the consumption amount used in the load (24) or electric vehicle (23). In addition, the memory (120) can also store various battery data such as voltage, current, temperature, and characteristic value data of each battery cell.

[0067] Additionally, the memory (120) can store a cost function selected by the user and can store a combination of a cost function and a weight for recommending a weight.

[0068] The memory (120) may include volatile memory (120) such as Static Random Access Memory (S-RAM) and Dynamic Random Access Memory (D-RAM) for temporarily storing data. In addition, the memory (120) may include nonvolatile memory (120) such as Read Only Memory (ROM), Erasable Programmable Read Only Memory (EPROM), and Electrically Erasable Programmable Read Only Memory (EEPROM) for long-term storage of data.

[0069] The processor (110) outputs a control signal to control the overall energy storage system control device (1). The processor (110) may include one or more central processing units (CPUs) and graphics processing units (GPUs). In this case, the processor (110) may be implemented as an array of a plurality of logic gates, or may be implemented as a combination of a general-purpose microprocessor (110) and a memory (120) storing a program that can be executed on the microprocessor (110).

[0070] The aforementioned memory (120) and processor (110) may be included in the control unit (100), and the control unit (100) may control the aforementioned components to determine abnormal battery data among the battery data.

[0071] Specifically, the control unit (100) can determine an objective function based on a cost function selected by the user, and perform battery control optimization based on external power production, internal power consumption, and the objective function.

[0072] In addition, the control unit (100) may perform the battery control optimization based on a first point in time, determine a predicted value of battery charge / discharge power based on the battery control optimization performed at the first point in time, determine a predicted interval including the predicted value of battery charge / discharge power, and perform battery control optimization again based on the actual value of battery charge / discharge power being outside the range of the predicted interval.

[0073] In addition, the control unit (100) can adjust variables for battery control optimization based on whether the actual value of the battery charge / discharge power is outside the range of the prediction interval, and the control unit (100) can perform battery control optimization again based on the adjusted variables for battery control optimization.

[0074] Additionally, the control unit (100) can modify the charge / discharge schedule based on the battery control optimization performed again, and perform charge / discharge based on the modified charge / discharge schedule.

[0075] In addition, the control unit (100) can receive weights for determining the priority of the cost function from the user through the user interface unit (300), and determine the objective function as a weighted sum of the weights and the cost function.

[0076] In addition, the control unit (100) can recommend weights to the user based on the fact that no weights have been input by the user for a preset period of time, and the control unit (100) can generate combinations that can be generated based on the number of cost functions and the interval information of the weights, and recommend to the user the combination with the lowest power purchase cost among the generated combinations.

[0077] Accordingly, the energy storage system control device (1) according to one embodiment can reduce uncertainty that may occur in the battery optimization process and optimize the charge / discharge schedule of the energy storage system (ESS) (20) by considering the user's intention, thereby improving the reliability of optimization and increasing user satisfaction, which has a significant effect.

[0078] FIG. 3 schematically illustrates a flow for determining whether to re-perform optimization in a control unit of an energy storage system control device according to one embodiment.

[0079] Referring to FIG. 3, the control unit (100) of the energy storage system control device (1) according to one embodiment can determine whether to re-perform battery optimal control based on external power production, internal power consumption, and cost function.

[0080] Specifically, external power generation may refer to the amount of power generated from the system power grid (21), renewable energy generation modules (22), and electric vehicles (23), internal power consumption may refer to the amount of power consumed by the system power grid (21), electric vehicles (23), and loads (24), and the cost function may refer to a function that is received from a user through an input unit (310) and minimizes an error.

[0081] Thereafter, the weight determination unit (101) of the control unit (100) can determine the weight based on whether a command to select a weight has been input from the user.

[0082] Specifically, when a user inputs a weight through the input unit (310), the control unit (100) can determine the input weight as a weight for generating an objective function.

[0083] On the other hand, if the user does not input weights through the input unit (310), the control unit (100) can recommend weights to the user, generate combinations that can be generated based on the number of cost functions and the interval information of the weights, and recommend the weights of the combination with the lowest power purchase cost among the generated combinations to the user. This will be described later in FIG. 6.

[0084] Afterwards, the objective function determination unit (102) of the control unit (100) can determine the objective function based on the weights and cost function selected by the user, and the cost function (J n ) can be configured in various ways based on the user's intention as follows.

[0085]

[0086]

[0087]

[0088]

[0089]

[0090]

[0091]

[0092] Specifically, mathematical expression 1 may mean a cost function that minimizes net power usage, mathematical expression 2 may mean a cost function for peak shaving that minimizes peak load (24), and mathematical expression 3 may mean a cost function that minimizes internal resistance in relation to battery performance degradation.

[0093] In addition, mathematical expression 4 may mean a cost function that minimizes a rapid change in SOC (State Of Charge) in relation to battery performance degradation, and mathematical expression 5 may mean a cost function that minimizes a deviation between battery cells.

[0094] In addition, mathematical expressions 6 and 7 may refer to cost functions utilized in a home energy storage system (20), and mathematical expression 6 may refer to a cost function that minimizes the difference between a back up SOC (State Of Charge) and a user's required SOC in order to maintain a back up SOC (State Of Charge) utilized in a home energy storage system, and mathematical expression 7 may refer to a cost function that minimizes the difference between the current indoor temperature and the user's required temperature.

[0095] At this time, f in the cost function may mean a function related to the degree of degradation of the battery cell, and g in the cost function may mean a function related to the user's inconvenience.

[0096] The control unit (100) can receive a command to select a cost function from the user, and can determine the objective function (Min.Z) as in the following mathematical expression 8 by using the weighted sum of the selected cost function and the weights.

[0097]

[0098] At this time, is a state variable, may include, is a control variable may include.

[0099] In the cost function and objective function can mean the amount of power [kW] taken from the grid at a specific time k, can mean the output power of the energy storage device at a specific time k, can mean the SOC of the energy storage device at a specific time k. Also, in the cost function and objective function, is the temperature of the energy storage device at a specific time k[ ] can mean, can mean the indoor humidity [%] inside the home at a specific time k, may mean the power usage time ($ / kWh) based on the power cost at a specific time k, can mean the internal resistance [ohm] at a specific time k, can mean the capacity [Ah] at a specific time k, is the weight being traded off (0<=w 1 , … , w j ) can mean.

[0100] Thereafter, the optimization unit (103) of the control unit (100) can perform battery optimization based on the external power production, internal power consumption, and the determined objective function. In this case, battery optimization may mean determining a charge / discharge schedule so that the determined objective function has a minimum value.

[0101] After performing optimization, the control unit (100) can determine whether optimization needs to be re-performed in the optimization re-performation judgment unit (104).

[0102] Specifically, the control unit (100) may perform battery control optimization based on a first point in time, determine a predicted value of battery charge / discharge power based on the battery control optimization performed at the first point in time, determine a predicted interval including the predicted value of battery charge / discharge power, and perform battery control optimization again based on the actual value of battery charge / discharge power being outside the range of the predicted interval.

[0103] That is, the control unit (100) can determine a point in time one day prior to the second point in time, which is the point in time when actual battery charging and discharging is performed, as the first point in time, and perform optimization in advance at the first point in time. Thereafter, the control unit (100) can determine a predicted value of the charging and discharging power at the second point in time based on the optimization result.

[0104] At this time, when the second point in time is reached, the control unit (100) can receive the actual value of the charge / discharge power from the energy storage system (20), and the control unit (100) can perform battery control optimization again when the actual value of the charge / discharge power is outside a preset reference range (e.g., a 95% range of the predicted error).

[0105] An energy storage system control device (1) according to one embodiment can reduce the error between a predicted value and an actual value, thereby minimizing uncertainty and reducing cost loss.

[0106] The control unit (100) can notify the user by transmitting the optimization result to the user terminal and server device based on the optimization being re-performed.

[0107] FIG. 4 is a graph showing conditions under which an energy storage system is optimized by an energy storage system control device according to one embodiment.

[0108] Referring to FIG. 4, the control unit (100) can determine the difference between the actual value (a) and the predicted value (b) of the charge / discharge power as an error (d). The energy storage system control device (1) according to the present disclosure can operate for the purpose of minimizing the error (d) between the actual value (a) and the predicted value (b).

[0109] At this time, the control unit (100) can determine a prediction interval ⓒ including a predicted value of the charge / discharge power, and if the control unit (100) determines that the actual value (a) of the charge / discharge power exceeds the range of the predicted interval (c), the control unit (100) can re-perform battery optimization.

[0110] That is, the control unit (100) can perform optimization at the first point in time and derive the expected charge / discharge schedule (f) from the already performed charge / discharge schedule (e). At this time, the control unit (100) can derive the predicted value (b) and predicted interval (c) of the charge / discharge power by the predicted charge / discharge schedule (f). At this time, if the actual value (a) of the charge / discharge power at the second point in time is determined to exceed the range of the predicted interval (c), the charge / discharge can be performed by the corrected charge / discharge schedule (g).

[0111] The control unit (100) can determine the prediction interval (c), which serves as a basis for determining whether the actual value (a) of the charge / discharge power exceeds the range of the prediction interval (c), as shown in the following mathematical expression 9.

[0112]

[0113] At this time, is the mean of the predictor variables, is the value of the predicted response variable, is the value of the predictor variable, is the standard deviation of the predictor variable, is the standard deviation of the error term, can mean the percentile of the t-distribution with n-2 degrees of freedom.

[0114] In this way, the control unit (100) can determine a prediction interval and use it as a basis for re-performing battery optimization.

[0115] FIG. 5 illustrates a user interface portion of an energy storage system control device according to one embodiment.

[0116] Referring to FIG. 5, the input unit (310) of the energy storage system control device (1) according to one embodiment may be configured as a UI (User Interface) in which the ratio of weights is adjusted based on a user's input.

[0117] Accordingly, the user can manipulate the UI according to the purpose of using the energy storage system (20), and there is an effect of easily performing cost function and weight adjustment according to the UI manipulation.

[0118] At this time, the UI can have a structure that maintains the sum of the weights to be 1. The UI structure can be applied in various ways, such as circular or bar shapes, and is not restricted by shape. Furthermore, the method by which the user adjusts the weights through the UI can include dragging and numeric input, and there are no restrictions on the method as long as the weights can be adjusted.

[0119] As in Fig. 5, the user can determine the weight for minimizing power cost (a) as 0.3, the weight for minimizing peak shaving (b) to minimize peak load (24) as 0.2, and the weight for minimizing battery degradation (c) as 0.5.

[0120] According to this, the objective function can be determined as shown in mathematical expression 10 below.

[0121]

[0122] If the user does not set a weight, the control unit (100) can recommend a weight as shown in FIG. 6, and the default value can be set to 1 for minimizing power costs, such as the purpose of installing the energy storage system (20).

[0123] FIG. 6 illustrates a table for recommending weights in an energy storage system control device according to one embodiment.

[0124] Referring to FIG. 6, the control unit (100) may recommend weights based on the fact that no command for inputting weights has been received from the user. Specifically, the control unit (100) may generate combinations that can be generated based on the number of cost functions and the interval information of the weights, and recommend the combination with the lowest power purchase cost among the combinations to the user.

[0125] That is, as shown in the table of Fig. 6, when the number of cost functions constituting the objective function is n, and the minimum change unit of the weight is 0.1, and the changeable weight range is w, the control unit (100) is w n By calculating all combinations, the weight of the case that minimizes the total cost can be recommended to the user. At this time, the cost can be calculated based on the power used in the energy storage system (20) and the power rate that varies over time.

[0126] For example, if the number of cost functions is 3, and the minimum change unit of the weight is 0.1, and the changeable weight range is 8 (8 ranges from 0.1 to 0.8), then all possible combinations are 8. 3 A total of 512 combinations are determined.

[0127] At this time, assuming that the total cost C1 in Fig. 6 is the minimum cost among all cases, the control unit (100) can recommend to the user w1 corresponding to case 1 among 512 combinations as 0.1, w2 as 0.1, and w3 as 0.8. If there are multiple combinations with the same cost, they can be recommended arbitrarily.

[0128] According to an energy storage system control device (1) according to one embodiment, convenience is increased because weights are recommended based on the minimum cost even when the user does not set weights.

[0129] FIG. 7 illustrates a flowchart of a method for controlling an energy storage device according to one embodiment, and FIG. 8 continues the flowchart of a method for controlling an energy storage device according to one embodiment from FIG. 7.

[0130] Referring to Fig. 7, the control unit (100) can receive external power production and internal power consumption through the communication unit (200) (700). In addition, the control unit (100) can receive a cost function selection command for selecting a cost function from the user (710). Although Fig. 7 illustrates receiving external power production and internal power consumption and receiving a cost function selection command, these operations can be performed in parallel, and there is no restriction on the order.

[0131] Thereafter, the control unit (100) can determine whether a weight input for determining the priority of the cost function has been received from the user (720).

[0132] If the control unit (100) determines that no weight input for determining the priority of the cost function has been received from the user (No of 720), it can generate all combinations that can be generated based on the number of cost functions and the interval information of the weights (730).

[0133] The control unit (100) may recommend to the user the weights included in the combination with the lowest power purchase cost among the generated combinations (740). Thereafter, the control unit (100) may receive a weight input for determining the priority of the cost function from the user (example of 720) or, if the user selects the recommended weights, determine the objective function based on the selected weights and the cost function (750).

[0134] Continuing with reference to Figure 8, battery control optimization can be performed at a first point in time (800) based on external power production, internal power consumption, and the objective function. As described above, the first point in time may refer to a point in time one day prior to the actual charging and discharging.

[0135] The control unit (100) can determine a predicted value and predicted interval of battery charge / discharge power based on the battery control optimization performed at the first point in time (810). The control unit (100) can determine whether the actual value of the battery charge / discharge power exceeds the predicted interval range (820).

[0136] If the control unit (100) determines that the actual value of the battery charge / discharge power exceeds the predicted interval range (example of 820), it can adjust variables for battery control optimization (830) and perform battery control optimization again based on the adjusted variables (840).

[0137] In this way, the energy storage system control device (1) according to one embodiment can eliminate uncertainty in the process of performing battery control optimization, thereby enabling efficient and user-friendly charge / discharge schedule management.

[0138] Meanwhile, the disclosed embodiments may be implemented in the form of a recording medium storing computer-executable instructions. The instructions may be stored in the form of program code, and when executed by a processor, may generate program modules to perform the operations of the disclosed embodiments. The recording medium may be implemented as a computer-readable recording medium.

[0139] Computer-readable storage media include all types of storage media that store instructions that can be deciphered by a computer. Examples include read-only memory (ROM), random access memory (RAM), magnetic tape, magnetic disks, flash memory, and optical data storage devices.

[0140] Additionally, a computer-readable recording medium may be provided in the form of a non-transitory storage medium. Here, the term "non-transitory storage medium" simply means a tangible device that does not contain signals (e.g., electromagnetic waves). This term does not distinguish between cases where data is permanently stored in the storage medium and cases where data is temporarily stored. For example, a "non-transitory storage medium" may include a buffer in which data is temporarily stored.

[0141] According to one embodiment, the method according to various embodiments disclosed in the present document may be provided as included in a computer program product. The computer program product may be traded as a product between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable recording medium (e.g., compact disc read only memory (CD-ROM)), or may be distributed online (e.g., downloaded or uploaded) via an application store (e.g., Play Store™) or directly between two user devices (e.g., smartphones). In the case of online distribution, at least a portion of the computer program product (e.g., downloadable app) may be at least temporarily stored or temporarily generated in a machine-readable recording medium, such as a memory (102) of a manufacturer's server, an application store's server, or a relay server.

[0142] Although all components constituting the embodiments disclosed in this document have been described as being combined or operating in combination as one, the embodiments disclosed in this document are not necessarily limited to such embodiments. That is, within the scope of the purpose of the embodiments disclosed in this document, all of the components may be selectively combined and operated one or more times.

[0143] Furthermore, terms such as "include," "comprise," or "have" described above, unless specifically stated otherwise, imply that the corresponding component may be present, and therefore should be interpreted to include other components rather than excluding other components. All terms, including technical or scientific terms, have the same meaning as commonly understood by a person of ordinary skill in the art to which the embodiments disclosed in this document pertain, unless otherwise defined. Commonly used terms, such as terms defined in dictionaries, should be interpreted to be consistent with the contextual meaning of the relevant technology, and shall not be interpreted in an idealized or overly formal sense, unless explicitly defined in this document.

[0144] The above description is merely an illustrative description of the technical idea disclosed in this document, and those skilled in the art to which the embodiments disclosed in this document pertain may make various modifications and variations without departing from the essential characteristics of the embodiments disclosed in this document. Therefore, the embodiments disclosed in this document are not intended to limit the technical idea of ​​the embodiments disclosed in this document, but to explain it, and the scope of the technical idea disclosed in this document is not limited by these embodiments. The scope of protection of the technical idea disclosed in this document should be interpreted by the claims below, and all technical ideas within a scope equivalent thereto should be interpreted as being included in the scope of rights of this document.

Claims

1. A communication unit that receives the amount of external power produced and the amount of internal power consumed; A user interface section that receives a cost function selection command from the user; A control unit that determines an objective function based on a cost function selected from the user and performs battery control optimization based on the external power production amount, the internal power consumption amount, and the objective function; The above control unit, The above battery control optimization is performed based on the first point in time, Determine the predicted value of battery charge / discharge power based on the battery control optimization performed at the first point in time, A control device of an energy storage system that determines a prediction interval including a predicted value of the battery charge / discharge power, and re-performs the battery control optimization based on whether the actual value of the battery charge / discharge power falls outside the range of the prediction interval.

2. In claim 1, The above control unit, A control device of an energy storage system that adjusts variables for battery control optimization based on whether the actual value of the battery charge / discharge power falls outside the range of the prediction interval.

3. In claim 2, The above control unit, A control device of an energy storage system that performs battery control optimization again based on the adjusted variables for the above battery control optimization.

4. In claim 1, The above control unit, A control device of an energy storage system that receives weights for determining the priority of the cost function from the user through the user interface unit and determines the objective function as a weighted sum of the weights and the cost function.

5. In claim 4, The above user interface section further includes an input section; The above input section, A control device of an energy storage system comprising a UI (User Interface) in which the ratio of the weights is adjusted based on the user's input.

6. In claim 4, The above control unit, A control device of an energy storage system that recommends the weight to the user based on the weight not being input by the user for a preset period of time.

7. In claim 6, The above control unit, A control device of an energy storage system that generates combinations that can be generated based on the number of cost functions and the interval information of the weights, and recommends to a user a combination with the lowest power purchase cost among the combinations.

8. In claim 1, The above cost function is, A control device of an energy storage system including a function for minimizing the difference between a backup SOC (State Of Charge) utilized in a home energy storage system and a user's required SOC.

9. In claim 1, The above cost function is, A control device of an energy storage system comprising a function for minimizing the difference between the current indoor temperature utilized in the home energy storage system and the user's desired temperature.

10. In claim 1, The above control unit, A control device of an energy storage system that modifies a charge / discharge schedule based on the battery control optimization performed again and performs charge / discharge based on the modified charge / discharge schedule.

11. Receive external power generation and internal power consumption; Receive a cost function selection command from the user; Determine the objective function based on the cost function selected from the above user; Perform battery control optimization based on the external power production amount, the internal power consumption amount, and the objective function; Performing the above battery control optimization is as follows: The battery control optimization is performed based on the first point in time; Determine a predicted value of battery charge / discharge power based on the battery control optimization performed at the first point in time; Determine a prediction interval including a predicted value of the above battery charge / discharge power; A control method for an energy storage system, comprising: re-performing the battery control optimization based on the actual value of the battery charge / discharge power being outside the range of the prediction interval; 12. In claim 11, A control method for an energy storage system, further comprising: adjusting a variable for optimizing battery control based on whether the actual value of the battery charge / discharge power falls outside the range of the prediction interval.

13. In claim 12, A control method of an energy storage system, further comprising: re-performing the battery control optimization based on the adjusted variables for the battery control optimization.

14. In claim 11, Determining the above objective function is: A control method of an energy storage system that receives weights for determining the priority of the cost function from the user through a user interface unit and determines the objective function as a weighted sum of the weights and the cost function.

15. In claim 14, A control method of an energy storage system, further comprising: adjusting the ratio of the weight based on the user input entered into the input unit included in the user interface unit.

16. In claim 14, A control method of an energy storage system, further comprising: recommending the weight to the user based on the weight not being input by the user for a preset period of time.

17. In claim 16, Recommending the above weights to the above user is: A control method for an energy storage system that generates combinations that can be generated based on the number of cost functions and the interval information of the weights, and recommends to a user a combination with the lowest power purchase cost among the combinations.

18. In claim 11, The above cost function is, A control method for an energy storage system including a function for minimizing the difference between a backup SOC (State Of Charge) utilized in a home energy storage system and a user's required SOC.

19. In claim 11, The above cost function is, A control method for an energy storage system, comprising a function for minimizing the difference between the current indoor temperature utilized in the home energy storage system and the user's desired temperature.

20. In claim 11, A control method of an energy storage system further comprising: modifying a charge / discharge schedule based on the battery control optimization performed again, and performing charge / discharge based on the modified charge / discharge schedule.

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