Heating control method, device, system and equipment of energy storage system

Abstract

The application discloses a heating control method, device, system and equipment of an energy storage system, and belongs to the technical field of energy storage. The method comprises the following steps: obtaining expected charging and discharging demand information of the energy storage system, and generating an expected charging and discharging power curve based on the expected charging and discharging demand information, wherein the expected charging and discharging power curve is used for representing expected charging power and / or expected discharging power of the energy storage system within an expected charging and discharging window; determining a battery cell target temperature based on the expected charging and discharging power curve, and determining a heating advance based on the battery cell target temperature and a current environment temperature and a current battery cell temperature; and based on the heating advance, controlling the energy storage system to perform a heating operation before the expected charging and discharging window arrives, so that the battery cell temperature reaches the battery cell target temperature, and the energy storage system meets the expected charging and discharging capacity within the expected charging and discharging window. The application realizes the guarantee of the charging and discharging capacity of the energy storage system under low-temperature working conditions and the optimization of heating energy consumption by constructing a prediction-driven heating timing control mechanism.

Description

Technical Field

[0001] This application belongs to the field of energy storage technology, and in particular relates to a heating control method, device, system and equipment for an energy storage system. Background Technology

[0002] With the development of energy storage technology, the application scale of energy storage systems in grid peak shaving and frequency regulation, distributed energy consumption, and integrated photovoltaic and energy storage applications is constantly expanding. At the same time, in order to improve the economic efficiency and energy utilization efficiency of the system, energy storage systems usually need to perform charging or discharging operations in different time windows according to electricity price strategies, photovoltaic output fluctuations, and load demand changes, thereby achieving optimized energy scheduling.

[0003] When operating in low-temperature environments, the performance of battery cells in energy storage systems is affected by temperature, resulting in decreased charge and discharge capacity, increased internal resistance, and reduced usable capacity. To ensure that energy storage systems can still operate normally under low-temperature conditions, related technologies typically use heating devices to raise the temperature of the battery cells, maintaining them within a suitable operating temperature range.

[0004] However, the relevant technologies mainly rely on the current temperature state or fixed time strategy for control, which makes it difficult to adapt to the different temperature requirements of energy storage systems under different operating conditions. This can easily lead to a mismatch between the heating process and the actual operating requirements, thereby affecting the system's operating efficiency and energy utilization. Summary of the Invention

[0005] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a scanning data processing control, energy storage system, device, and medium to solve the problems of fragmented operation, discontinuous interaction, and low efficiency of scanning data adjustment caused by relying on external input devices for interactive control in the existing 3D scanning process. It enables direct, continuous, and real-time interactive control of 3D scanning data through gestures without touching an external terminal.

[0006] In a first aspect, this application provides a heating control method for an energy storage system, comprising: Obtain the expected charge and discharge demand information of the energy storage system, and generate the expected charge and discharge power curve based on the expected charge and discharge demand information. The expected charge and discharge power curve is used to characterize the expected charge and discharge capacity of the energy storage system within the expected charge and discharge window. The target temperature of the battery cell is determined based on the expected charge and discharge power curve, and the heating advance amount is determined based on the target temperature of the battery cell, the current ambient temperature, and the current temperature of the battery cell. Based on the heating advance amount, the energy storage system is controlled to perform a heating operation before the expected charge / discharge window arrives, so that the cell temperature reaches the target cell temperature, so that the energy storage system can meet the expected charge / discharge capacity within the expected charge / discharge window.

[0007] Secondly, this application provides a heating control device for an energy storage system, comprising: The demand acquisition module is used to acquire the expected charging and discharging demand information of the energy storage system, and generate the expected charging and discharging power curve based on the expected charging and discharging demand information. The expected charging and discharging power curve is used to characterize the expected charging and discharging capacity of the energy storage system within the expected charging and discharging window. The temperature calculation module is used to determine the target temperature of the battery cell based on the expected charge and discharge power curve, and to determine the heating advance amount based on the target temperature of the battery cell, the current ambient temperature, and the current temperature of the battery cell. The heating control module is used to control the energy storage system to perform a heating operation before the expected charge / discharge window arrives, based on the heating advance amount, so that the cell temperature reaches the target cell temperature, so that the energy storage system can meet the expected charge / discharge capacity within the expected charge / discharge window.

[0008] Thirdly, this application provides an energy storage system, including: The battery cell module is used to store and release electrical energy, and to change its operating temperature under heating. A heating execution module is used to perform a heating operation on the battery cell module; A processing device for performing the heating control method for the energy storage system as described in the first aspect.

[0009] Fourthly, this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the heating control method of the energy storage system as described in the first aspect above.

[0010] Fifthly, this application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the heating control method for the energy storage system as described in the first aspect above.

[0011] In a sixth aspect, this application provides a chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the heating control method of the energy storage system as described in the first aspect.

[0012] In a seventh aspect, this application provides a computer program product, including a computer program that, when executed by a processor, implements the heating control method for the energy storage system as described in the first aspect above.

[0013] The above-described one or more technical solutions in the embodiments of this application have at least one of the following technical effects: By acquiring the expected charging and discharging demand information of the energy storage system and generating an expected charging and discharging power curve based on this information, the energy storage system can uniformly represent future charging and discharging demands in a time dimension. This transforms the traditional control method based on the current state into a forward-looking regulation method oriented towards future operating conditions. Furthermore, the target temperature of the battery cell is determined based on the expected charging and discharging power curve, establishing a correspondence between battery cell temperature control and future charging and discharging power demands. The heating advance is determined by combining the target temperature of the battery cell, the current ambient temperature, and the current temperature of the battery cell, ensuring that the heating start timing matches the thermal process required for the battery cell to reach the target temperature. This avoids energy waste due to premature heating or insufficient charging and discharging capacity due to delayed heating. Finally, based on the heating advance, the energy storage system is controlled to perform heating operations before the expected charging and discharging window arrives, ensuring that the battery cell temperature reaches the target temperature when the target charging and discharging window arrives. This guarantees that the energy storage system has the corresponding charging and discharging capacity within the expected charging and discharging window, achieving a synergistic improvement in charging and discharging capacity assurance and heating energy consumption optimization under low-temperature environments.

[0014] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0015] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a schematic diagram of the energy storage system provided in the embodiments of this application; Figure 2 This is a schematic flowchart of the heating control method for an energy storage system provided in an embodiment of this application; Figure 3 This is a schematic diagram of the expected charging power curve under one generation method provided in an embodiment of this application; Figure 4 This is a schematic diagram of the expected charging power curve under another generation method provided in the embodiments of this application; Figure 5 This is a schematic diagram of the expected charging power curve under another generation method provided in the embodiments of this application; Figure 6 This is one of the schematic diagrams illustrating the relationship between heating and charging power provided in the embodiments of this application; Figure 7 This is a second schematic diagram illustrating the relationship between heating and charging power provided in the embodiments of this application; Figure 8 This is a schematic diagram illustrating the effect of starting heating at different times on the charge / discharge rate, provided in an embodiment of this application. Figure 9 This is a schematic diagram of the structure of the heating control device of the energy storage system provided in the embodiments of this application; Figure 10 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0016] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments that can be directly obtained based on the embodiments of this application are within the scope of protection of this application.

[0017] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0018] In practical applications, temperature-controlled energy storage systems are typically deployed in low-temperature areas or outdoor environments. Due to the lack of active temperature regulation capabilities, the cells are prone to triggering charge and discharge capacity limiting mechanisms under low-temperature conditions, which leads to a significant decrease in the available capacity of the energy storage system and affects the overall energy output capacity and operating efficiency of the system.

[0019] To address the aforementioned issues, common solutions in related technologies involve continuously heating or maintaining the battery cell at a sustained temperature by activating heating devices such as heating films or liquid-cooled heating units. This keeps the cell within its chargeable and dischargeable temperature range, thus mitigating the limited energy storage capacity in low-temperature environments to some extent. However, this approach typically relies on continuous heating or empirical heat preservation strategies, failing to coordinate with actual charging and discharging demands. This results in prolonged heating processes and a high proportion of ineffective heating, leading to significant additional energy consumption and impacting the overall operational benefits of the energy storage system.

[0020] In view of this, the present application provides a heating control method for an energy storage system. By predicting and analyzing the expected charging and discharging demand and adjusting the cell temperature in advance in conjunction with the future charging and discharging window, the heating process is matched with the actual operating demand. While ensuring the charging and discharging capacity of the energy storage system in low-temperature environments, the method reduces the additional energy consumption caused by long-term heat preservation, thereby improving the overall operating efficiency and economy of the system.

[0021] The heating control method, energy storage system, electronic device, and readable storage medium of the energy storage system provided in this application will be described in detail below with reference to the accompanying drawings and through embodiments and application scenarios.

[0022] The energy storage systems described in this application include, but are not limited to, one or more of the following: residential energy storage systems, commercial and industrial energy storage systems, integrated photovoltaic and energy storage systems, grid-side energy storage systems, and mobile energy storage devices. These applications are applicable to energy storage scenarios requiring charging and discharging operation in low-temperature environments.

[0023] Of course, it is not limited to this. For example, it can also be a communication base station energy storage system, a microgrid energy storage system, an off-grid power supply energy storage system, and a new energy power generation side supporting energy storage system, etc., which require charging and discharging temperature management under different operation and scheduling conditions. This application does not limit this.

[0024] Figure 1 This is a schematic diagram of the energy storage system provided in an embodiment of this application. The energy storage system provided in this embodiment includes a battery cell module 101, a heating execution module 102, and a processing device 103.

[0025] Among them, the battery cell module 101 is used for storing and releasing electrical energy, and changes its operating temperature under heating.

[0026] In one embodiment, the cell module 101 may include one or more individual cell units and a battery module structure for connecting multiple cell units in series and / or in parallel, thereby forming an energy storage unit that meets preset capacity and power requirements. The operating state of the cell module 101 is affected by ambient temperature, and its charging and discharging capabilities may decrease under low-temperature conditions.

[0027] The heating execution module 102 is used to perform heating operations on the battery cell module to increase the operating temperature of the battery cell module 101 or maintain it within the target temperature range.

[0028] In one embodiment, the heating execution module 102 may include at least one of a heating film, a liquid-cooled heating circuit, an electric heating element, or a thermal management unit, for performing a heating operation to transfer heat to the cell module 101 to achieve regulation and control of the cell temperature.

[0029] For example, the heating operation is performed through a heating film, which is placed on the surface of the battery cell or inside the battery cell module. The heating film converts electrical energy into heat energy through resistance heating and transfers the heat to the battery cell to raise or maintain the temperature of the battery cell.

[0030] For example, the heating operation is performed through a liquid-cooled heating circuit, which exchanges heat with the battery cell through a circulating heating medium to achieve uniform temperature rise of the battery cell and improve the temperature distribution consistency to a certain extent.

[0031] For example, heating operations are performed through a heat pump system, which uses refrigerant circulation to transfer heat from the outside or inside the system to the battery cell side, thereby improving heating efficiency and reducing energy consumption.

[0032] For example, the heating operation is performed by the battery itself, which generates a controllable heating effect by controlling the internal circuit of the battery cell or equivalent circuit, thereby achieving the battery cell's own heating and temperature rise.

[0033] The processing device 103 is used to control the heating of the battery cell module 101 by the heating execution module 102, so as to control the heating process of the battery cell module 101 according to the expected charging and discharging requirements, so that the battery cell module 101 reaches the target temperature of the battery cell before the expected charging and discharging window arrives, and meets the expected charging and discharging capacity within the expected charging and discharging window.

[0034] In one embodiment, the processing device 103 may be part of the Battery Management Unit (BMU) or Energy Management Unit (EMU) in the energy storage system, and is used to execute the calculation and control logic corresponding to the heating control method and output control commands to the heating execution module 102.

[0035] The heating control method for an energy storage system provided in this application embodiment can be executed by a processing device. The processing device can be a standalone electronic device, a processing unit integrated into a control device, energy management system, battery management system, or other operating control unit within the energy storage system, or a computing device deployed in a server, cloud computing platform, edge computing node, or industrial control system.

[0036] In some embodiments, the processing device may include a processor and a memory, wherein the processor is used to execute program instructions stored in the memory to realize heating control of the energy storage system; wherein the processor may be at least one of a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices or control chips.

[0037] In some implementations, the processing device can also be integrated in a modular form within the energy storage device, such as in the control unit of a battery management system (BMS), thermal management control unit (TMCU), or power control system (PCS), for direct control of the heating execution module.

[0038] The heating control method of the energy storage system provided in this application embodiment will be described below, taking the processing device as the execution subject as an example.

[0039] Figure 2 This is a schematic flowchart of the heating control method for an energy storage system provided in an embodiment of this application. Figure 2 As shown, the method includes steps 210 to 240.

[0040] Step 210: Obtain the expected charging and discharging demand information of the energy storage system, and generate the expected charging and discharging power curve based on the expected charging and discharging demand information. The expected charging and discharging power curve is used to characterize the expected charging and discharging capacity of the energy storage system within the expected charging and discharging window.

[0041] The expected charge and discharge demand information is used to characterize the charging and discharging demands of the energy storage system within a preset time range in the future, as well as the corresponding time distribution. This information may include at least one of the following: expected charge and discharge time information, expected power demand information, and expected charge and discharge capacity information. Depending on the charge and discharge demands, the expected charge and discharge power curve may include an expected charging power curve and an expected discharging power curve.

[0042] In some implementations, the expected charging and discharging demand information may include at least one of the following: user-side dispatch instructions, energy storage system operation strategy information, time-of-use electricity price information, and external energy input forecast information.

[0043] Among them, user-side dispatch instructions are used to characterize the user's charging or discharging demand for the energy storage system in the future time period, such as requiring the energy storage system to charge or discharge at a set power within a specified time period; energy storage system operation strategy information is used to characterize the internal energy management strategy of the system, such as peak shaving and valley filling strategy, reserve capacity strategy or economic dispatch strategy; time-of-use electricity price information is used to characterize the changes in electricity prices in different time periods, so as to guide the energy storage system to charge when the electricity price is low and discharge when the electricity price is high; external energy input forecast information is used to characterize the forecast results such as photovoltaic power generation output or load demand.

[0044] After acquiring the aforementioned expected charging and discharging demand information, the processing device performs time alignment and unified expression processing on the demand information from different sources, converting discrete event-based or rule-based demands into a power demand sequence expressed continuously over time. Specifically, the processing device divides the expected charging and discharging window according to a preset time granularity and determines the corresponding target charging power or target discharging power within each time segment, thereby forming an initial power demand sequence.

[0045] Furthermore, the processing device performs smoothing and constraint correction based on the initial power demand sequence to avoid power abrupt changes or situations exceeding the physical capacity of the energy storage system. The processing device can combine the maximum charge / discharge power constraints, state of charge (SOC) constraints, and cell temperature constraints of the energy storage system to trim or redistribute the power values ​​of each time segment, thereby obtaining a target power sequence that meets the system's operational constraints.

[0046] Based on this, the processing device maps the target power sequence into a continuously varying expected charge / discharge power curve over time, which characterizes the power capacity that the energy storage system needs to provide or absorb within the expected charge / discharge window. This expected charge / discharge power curve not only reflects the power variation trend over time but also corresponds to the charge / discharge capacity boundaries required by the energy storage system at each time point, providing a basic input for subsequent determination of the target cell temperature and heating control.

[0047] For example, the energy storage system receives the user's expected charging and discharging demand information through a human-machine interface. This user input may include the expected charging and discharging time period and the corresponding charging and discharging power settings within that time period. The expected charging and discharging time period can be set via a time axis selection method, such as the user directly selecting one or more time intervals as charging or discharging windows in the Time-of-Use (TOU) interface. The charging and discharging power can be set by the user for each moment of the selected time period, or a uniform power value can be set as the default power. If no explicit setting is made, the system automatically uses the energy storage system's rated maximum charging and discharging capacity as the default power.

[0048] In one example, the user selects the nighttime low electricity price period as the charging window in the TOU timeline interface and specifies a higher charging power during this period to meet the fast charging needs; at the same time, the user selects the discharge window during the daytime high electricity price period and sets the discharge power to participate in peak shaving and valley filling.

[0049] In another example, the user selects only the time period without specifying the power parameters. The processing device then automatically generates a corresponding recommended charge and discharge power curve based on the current SOC state, temperature state, and rated power capability of the energy storage system. For example, it automatically reduces the initial charging power when the cell temperature is low and gradually increases it to the maximum charging capability after the temperature meets the requirements.

[0050] Based on the user-inputted time period and time-by-time power settings, the processing device converts the discrete interactive input into a power mapping relationship in the form of a time series. This yields the charging or discharging power corresponding to each sampling point within the expected charging / discharging window, thus forming an initial expected charging / discharging power curve. This power curve directly reflects the user's energy scheduling intentions in the time dimension and serves as the input basis for subsequent target temperature calculations and pre-heating control.

[0051] Step 220: Determine the target temperature of the battery cell based on the expected charge and discharge power curve, and determine the heating advance amount based on the target temperature of the battery cell, the current ambient temperature, and the current temperature of the battery cell.

[0052] After obtaining the expected charge and discharge power curve, the processing device determines the target temperature of the battery cell based on the power curve, and further calculates the heating advance amount by combining the ambient temperature and the current temperature of the battery cell.

[0053] In one embodiment, the processing device first performs time-segmented analysis on the expected charge / discharge power curve to identify the power variation characteristics of different time periods within the expected charge / discharge window. For time intervals with higher power, it indicates that the energy storage system needs to provide a higher charge / discharge current capability; for time intervals with lower power, it corresponds to a lower current demand. Based on the correlation between power and current, the processing device converts the expected charge / discharge power curve into a corresponding expected charge / discharge current demand curve.

[0054] Furthermore, based on the mapping relationship between the expected charge / discharge current demand curve and the cell's operating characteristic parameters, the processing device determines the allowable operating temperature range required for the cell to meet the corresponding current capability. Cell operating characteristic parameters may include internal resistance characteristics, rate performance curve, and temperature-capacity decay relationship. Within the allowable operating temperature range, the processing device selects a target temperature that matches the expected charge / discharge current demand, enabling the cell to meet the expected power output or absorption requirements under these temperature conditions, thus obtaining the target cell temperature.

[0055] In one example, when the expected charge / discharge power curve shows that there is a high power discharge demand within a certain period of time, the processing device will correspondingly increase the target temperature setting of the battery cell to reduce the internal resistance of the battery cell and improve the discharge capacity; when the power curve is in a low power operation state, the target temperature setting will be correspondingly reduced so that the system can reduce heating energy consumption while meeting basic performance requirements.

[0056] After determining the target temperature of the battery cell, the processing device combines the current ambient temperature and the current temperature of the battery cell to model and analyze the time response of the heating process. Specifically, based on the temperature difference between the current battery cell temperature and the target temperature, the influence of the ambient temperature on the heat dissipation rate, and the heating capacity parameters of the heating execution unit, the device calculates the temperature rise rate of the battery cell at the current temperature and the temperature rise rate near the target temperature, and determines the heating time required for the battery cell to rise from the current temperature to the target temperature based on the changes in the temperature rise rate.

[0057] Therefore, the processing device uses the heating time as a heating advance amount and is used to determine the heating start time, so that the heating process can complete the temperature rise before the expected charge and discharge window begins, thereby ensuring that the cell is in a thermal state that meets the target power capability when the window arrives.

[0058] The above method enables a step-by-step mapping from the power curve to the temperature target and then to the time lead, aligning the heating control of the energy storage system with the actual scheduling needs in the time dimension, thereby improving the system's response capability and energy utilization efficiency under dynamic load scenarios.

[0059] Step 230: Based on the heating advance amount, control the energy storage system to perform heating operation before the expected charge and discharge window arrives, so that the cell temperature reaches the target cell temperature, so that the energy storage system can meet the expected charge and discharge capacity within the expected charge and discharge window.

[0060] The processing device performs timing control on the heating process of the energy storage system based on the determined heating advance amount, so that the cells reach the target temperature before the expected charge and discharge window arrives.

[0061] In one embodiment, the processing device first determines the heating start time based on the expected start time of the charge / discharge window and the heating advance amount, and generates a heating control timing instruction. This heating control timing instruction instructs the heating execution unit to start the heating operation at a specified time point and to perform power output control according to the target temperature rise curve during the subsequent time period.

[0062] During the heating process, the processing device acquires real-time data on the battery cell temperature and ambient temperature, and performs closed-loop regulation of the heating process based on the current temperature rise rate. When the deviation between the battery cell temperature and the target temperature is detected to be greater than a preset threshold, the processing device controls the heating execution unit to adjust the heating power to increase or decrease the temperature rise rate, so that the battery cell temperature gradually approaches the target temperature curve; when the battery cell temperature is close to the target temperature, the heating power output is reduced to avoid overshoot and reduce energy loss.

[0063] In one example, when the system detects that the next expected charging window will begin during the nighttime low electricity price period, the processing device will calculate the heating start time in advance and automatically activate the heating film or liquid cooling heating circuit before the window begins, so that the cell temperature rises to the target temperature in advance. When the expected charge / discharge window is reached, the cell is already in a thermal state that meets the capability corresponding to the expected charge / discharge power curve, so it can directly enter the charging or discharging process, achieving the "ready to use" operation effect.

[0064] In another embodiment, when there are multiple consecutive or intermittently distributed expected charge and discharge windows, the processing device can also perform segmented optimization control of the heating strategy based on the target temperature and heating advance amount corresponding to different windows, so that the energy storage system can achieve smooth temperature switching between different scheduling cycles and avoid energy consumption fluctuations caused by frequent and large heating.

[0065] The above method realizes a heating execution mechanism that combines time-advance control based on heating advance with temperature closed-loop regulation, so that the battery cell can stably reach the target temperature at the beginning of the expected charge and discharge window, thereby ensuring that the energy storage system can continuously meet the expected charge and discharge capacity requirements.

[0066] It should be noted that the reason why the cell temperature can meet the expected charge and discharge capacity when it reaches the target temperature is because the cell's charge and discharge capacity is closely related to its internal electrochemical reaction rate and equivalent internal resistance, and these parameters all show a significant functional relationship with temperature.

[0067] Specifically, when the battery cell is at a lower temperature, the electrolyte ion migration rate decreases, the charge transport impedance increases, and the equivalent internal resistance rises. This results in a higher voltage drop required for the same power demand, thus limiting the battery cell's voltage or current limits and reducing its output or absorption power capacity. When the battery cell temperature rises to the target temperature, the electrolyte viscosity decreases, the ion diffusion coefficient increases, and the electrode interface reaction impedance decreases. This causes the battery cell's equivalent internal resistance to decrease and tend towards a stable range, allowing it to support higher charge and discharge currents under the same voltage constraints.

[0068] Therefore, the target temperature essentially corresponds to the temperature boundary point where the cell's internal resistance and rate performance meet the constraints under the expected charge / discharge current demand. When the cell temperature reaches this target temperature, the cell's available charge / discharge power capability matches the demand capability corresponding to the expected charge / discharge power curve, thereby ensuring that the energy storage system can stably output or absorb the corresponding power within the expected charge / discharge window, meeting the expected charge / discharge capability requirements.

[0069] The heating control method for an energy storage system provided in this application improves the temperature control of the energy storage system from static threshold control to predictive control based on future power demand by acquiring the expected charging and discharging demand information of the energy storage system and generating the expected charging and discharging power curve. This allows discrete scheduling requirements or operating intentions to be structured into a power expression in the time dimension, enabling the energy storage system to have a unified representation of future charging and discharging behavior, providing a quantitative basis for subsequent temperature control strategies, and thus improving the matching between heating control and actual operating conditions. Based on this, the target temperature of the battery cell is determined based on the expected charging and discharging power curve, transforming the battery cell temperature control from the traditional fixed threshold control method to target constraint control that matches future power demand. Furthermore, by combining the target temperature of the battery cell, the current ambient temperature, and the current temperature of the battery cell to determine the heating advance, the heating behavior no longer depends on fixed time or simple temperature threshold triggering, but matches the thermal process required to reach the target temperature. This achieves dynamic optimization of the heating start timing, thereby avoiding ineffective energy consumption due to premature heating or insufficient charging and discharging capacity due to late heating, and improving the time matching accuracy of the temperature control strategy. Furthermore, by controlling the energy storage system to perform heating operations based on the heating advance amount before the expected charge and discharge window arrives, the cell temperature reaches the target cell temperature when the window arrives, thereby ensuring that the energy storage system has the corresponding charge and discharge capabilities during the actual charge and discharge phase, improving system availability and operational reliability, reducing ineffective heating time, and improving overall energy utilization efficiency and operational economy.

[0070] In one embodiment, the generation method of the expected charge and discharge power curve has multi-source input characteristics. The processing device can adaptively select or integrate multiple generation paths according to different application scenarios to improve the applicability and scheduling matching capability of the power curve. This includes: generating the expected charge and discharge power curve based on the expected charge and discharge time and expected charge and discharge capacity set by the user; using the scheduling power curve of the energy storage system as the expected charge and discharge power curve, wherein the scheduling power curve is determined based on the time-of-use electricity price curve; or, generating the power demand curve based on historical photovoltaic power generation data and load data through learning and prediction.

[0071] In a user interaction scenario, the user inputs the expected charging and discharging times and corresponding expected charging and discharging capabilities through a human-computer interaction interface. Specifically, this involves selecting one or more charging or discharging time periods on the time axis interface and setting a target power value for the selected time periods. When the user does not explicitly input power parameters, the processing device defaults to using the rated maximum charging and discharging capability of the energy storage system as the initial power value, and can dynamically correct this default value based on cell temperature, SOC status, and system safety constraints. Based on the above input, the processing device generates a power sequence corresponding one-to-one with the time axis and further forms a continuous expected charging and discharging power curve.

[0072] For example, such as Figure 3 The diagram shown illustrates the user interface and power setting process. Figure 3 The system uses a time axis to display charging and discharging scheduling areas for different time intervals. Users can select intervals on the time axis to divide charging and discharging tasks into different time periods and set target power values ​​within the corresponding intervals (t1, t2). When no explicit power setting is received, the system automatically fills the selected interval with a default power value and generates a continuous power curve based on this, thus realizing the conversion from discrete interactive input to a continuous power scheduling curve. Based on the above input, the processing device generates a power sequence that corresponds one-to-one with the time axis and further forms a continuous expected charging and discharging power curve.

[0073] In another embodiment, the processing device uses the dispatch power curve of the energy storage system as the expected charge / discharge power curve. The dispatch power curve is determined by the time-of-use electricity price curve; that is, based on the changes in electricity prices at different times, low-price periods are mapped to charging power increase intervals, and high-price periods to discharging power increase intervals, thus forming a power dispatch curve consistent with the economic optimization objective. This method is suitable for periodic dispatch or electricity market participation scenarios, enabling the energy storage system to achieve revenue optimization while ensuring constraints.

[0074] For example, such as Figure 4 The figure shown is a schematic diagram of generating energy storage dispatch power curves based on time-of-use pricing. Figure 4 The horizontal axis represents time, while the vertical axes correspond to the electricity price change curve and the energy storage power dispatch curve, respectively. The electricity price curve exhibits time-segmented fluctuations. The system divides charging and discharging strategies based on the high and low electricity price intervals: during low electricity price periods, a charging power enhancement interval is generated, prioritizing charging operations for the energy storage system; during high electricity price periods, a discharging power enhancement interval is generated, allowing the energy storage system to discharge for economic gain; when the electricity price is in the middle level or transitional range, a power balance or low-power operation interval is generated, thus forming a continuous dispatch power curve. For example, the electricity price curve switches between price intervals at key time nodes t1 and t2, dividing the entire time axis into different price intervals. Within the low electricity price interval corresponding to t1 to t2, the system generates a charging power enhancement strategy, keeping the energy storage system in a charging state; after t2, when entering the high electricity price interval, a discharging power enhancement strategy is generated, allowing the energy storage system to discharge; at the boundaries between different price intervals, the power curve exhibits a smooth transition to avoid abrupt dispatch changes. In this way, the processing device maps the time-of-use electricity price curve into a time-continuous scheduling power curve, and uses it as the input of the expected charging and discharging power curve for subsequent heating control and operation scheduling of the energy storage system.

[0075] In another embodiment, for scenarios where photovoltaic output and load changes are highly uncertain, the processing device learns and predicts based on historical photovoltaic power generation data and load data to generate a power demand curve. Specifically, the processing device performs time series modeling on historical photovoltaic power sequences and load power sequences to obtain photovoltaic output prediction curves and load demand prediction curves for future periods. Based on the difference between the two, it determines the net power change trend, thereby identifying potential charging and discharging windows and corresponding power demands, and generating an expected charging and discharging power curve that changes over time.

[0076] like Figure 5 The diagram shown is a schematic of the expected charge / discharge power curve generated by learning and predicting based on historical data, as well as the identification of the charge / discharge window. Figure 5 The horizontal axis represents time t, and the vertical axis represents the change in power, where the curves... This represents the net power change process after deducting the system constraint threshold M. The system uses this curve to perform window identification on the time axis. When the value gradually rises from below zero and first exceeds the threshold condition at t1, it is determined to enter the valid charging window; when The charging window ends when the power decreases and falls below the threshold at t2, thus obtaining a continuous time interval (t1, t2). Within the window (t1, t2), the system generates a corresponding expected charging power curve based on the net power margin. This power curve characterizes the actual charging capacity of the energy storage system at each time point after deducting system safety constraints and heating power consumption. In this way, the system transforms the predicted photovoltaic output and load demand into a schedulable, time-continuous power curve, and further maps it to the operation control input of the energy storage system. Through the above method, the processing device realizes a complete link from historical data learning and prediction, net power analysis, window identification to the generation of expected charge and discharge power curves, providing a basic input for subsequent determination of cell target temperature and advance heating control.

[0077] In one alternative implementation, the three methods described above can be used individually or combined and weighted according to the application scenario. For example, the scheduling requirements input by the user, the TOU economic curve, and the photovoltaic prediction results can be considered simultaneously. The final expected charge and discharge power curve can be generated by weighted superposition or priority adjudication to improve the robustness and adaptability of curve generation.

[0078] By employing the aforementioned multi-source expected charge and discharge power curve generation method, the energy storage system can flexibly construct power demand models under different application scenarios. On the one hand, through user-interactive input, the power curve can directly reflect the user's scheduling intentions, improving system controllability and interpretability. On the other hand, through the scheduling curve generation method based on time-of-use pricing, the energy storage system can optimize economic benefits. Furthermore, through prediction methods based on historical photovoltaic and load data, the system possesses adaptive capabilities to uncertain energy inputs. Therefore, it is possible to achieve multi-scenario adaptive generation of expected charge and discharge power curves, improving the scheduling accuracy and operational stability of the energy storage system under complex operating conditions, and providing a more reliable input basis for subsequent determination of target cell temperature and advance heating control.

[0079] In one embodiment, the process of learning and predicting based on historical photovoltaic power generation data and load data is applied to scenarios of integrated photovoltaic and energy storage systems or energy storage systems with uncertain external energy input. Specifically, learning and predicting based on historical photovoltaic power generation data and load data to generate power demand curves includes: generating photovoltaic power curves and load power curves based on historical photovoltaic power data and historical load power data; calculating the power difference based on the photovoltaic power curves and load power curves, whereby the power difference characterizes the net power available for charging and discharging of the energy storage system within different time periods; determining a time period that meets a preset threshold condition based on the power difference as the expected charging and discharging window, and determining the expected charging power and / or expected discharging power within the expected charging and discharging window to generate an expected charging and discharging power curve; determining the corresponding charging current and / or discharging current based on the expected charging and discharging power curve, and determining the target temperature of the battery cell based on the cell's operating characteristic parameters.

[0080] The processing device first performs time series alignment processing on the historical operating data to obtain historical photovoltaic power data and historical load power data. Then, it performs noise reduction, outlier removal, and time granularity unification processing on the data to ensure the stability and consistency of subsequent prediction results.

[0081] After data preprocessing, the processing unit uses a learning model to model and predict historical photovoltaic power and load power data, generating photovoltaic power curves and load power curves for future time periods. The photovoltaic power curve represents the renewable energy input capacity at different points in time, while the load power curve represents the changing trend of external electricity demand.

[0082] In one embodiment, for uncertain scenarios where the charging and discharging capabilities and timing of the photovoltaic-storage system cannot be predicted, the processing device employs an AI (Artificial Intelligence) learning method based on historical data to further extrapolate and analyze the photovoltaic power curve and the load power curve, thereby obtaining the following information:

[0083]

[0084] In the formula, The photovoltaic power curve represents the predicted power generation of the photovoltaic system at time t. The load power curve represents the predicted power demand of the system load at time t. It is used to characterize the time-varying power prediction mapping relationship learned from historical operating data, and to output the photovoltaic power or load power prediction value at the corresponding moment. It can represent time series prediction models (such as LSTM, Transformer, etc.), regression models, statistical learning models or other fitting functions.

[0085] Furthermore, the processing device calculates the power difference at each time step based on the photovoltaic power curve and the load power curve to obtain the net power curve. This net power curve is used to characterize the surplus or deficit power state of the system in each time period without considering the regulation of the energy storage system. When the net power is positive, it indicates that there is surplus power that can be used to charge the energy storage system; when the net power is negative, it indicates that the energy storage system needs to discharge to support the system.

[0086] In one implementation, net power is defined as:

[0087] In the formula, The net power difference represents the effective power margin or deficit that the system can use for energy storage charging and discharging at time t. The expected charge / discharge power represents the target power that the energy storage system can achieve at time t, under the condition of satisfying system constraints (including heating power consumption, etc.). It can also characterize the impact of the energy storage system's heating power on the available power.

[0088] In one embodiment, the processing device performs threshold screening on the net power curve to determine the time period that meets the preset threshold conditions as the expected charge / discharge window. For example, when the net power is continuously higher than a preset positive threshold, it is determined to be a potential charging window; when the net power is continuously lower than a preset negative threshold, it is determined to be a potential discharging window. This method can effectively filter out the impact of short-term fluctuations on scheduling decisions.

[0089] For example, the processing device performs threshold screening on the net power curve when When the value is greater than a preset threshold M, it indicates that there is sufficient surplus power available for charging the energy storage system during that time period, thus allowing for the selection of systems that meet the criteria. The time interval is used as the expected charging and discharging window, which includes (t1, t2), (t3, t4)...(tn-1, tn).

[0090] After determining the expected charge / discharge window, the processing device further determines the corresponding expected charging power and / or expected discharging power within each window, and generates an expected charge / discharge power curve that changes over time. In a specific example, when the photovoltaic output is significantly higher than the load demand during the midday period, it is identified as a charging window, and a higher charging power curve is generated; when the load is consistently higher than the photovoltaic output at night, a discharging power curve is generated to meet the power supply demand on the load side.

[0091] Based on this, the processing device calculates the corresponding charging current and / or discharging current based on the expected charging and discharging power curve, and determines the target temperature of the battery cell by combining the cell's operating characteristic parameters, including rate performance, internal resistance characteristics, and temperature-performance relationship, so that the battery cell has the thermal state to meet the power output or absorption capacity under the corresponding current requirements.

[0092] Therefore, by jointly predicting photovoltaic output and load demand and introducing net power difference analysis, the system can automatically identify potential charging and discharging windows, improving the foresight of scheduling. Furthermore, by converting the prediction results into charging and discharging power curves and linking them with the calculation of current demand and target cell temperature, the power prediction results can directly serve thermal management control, significantly improving the adaptability of the energy storage system under photovoltaic fluctuations and load uncertainties. This achieves closed-loop linkage from energy prediction to thermal state control, improving the overall system operating efficiency and the accuracy of charging and discharging capacity matching.

[0093] In some embodiments, determining the heating advance amount based on the target temperature of the battery cell, the current ambient temperature, and the current temperature of the battery cell includes: determining the temperature rise requirement required for the battery cell to reach the target temperature based on the temperature difference between the current temperature of the battery cell and the target temperature of the battery cell; determining the basic heat dissipation conditions of the battery cell based on the current ambient temperature; determining a first temperature rise rate of the battery cell at the current battery cell temperature and a second temperature rise rate at the target temperature of the battery cell based on the heating capacity parameters of the heating unit and the basic heat dissipation conditions; determining the heating time required for the battery cell to heat to the target temperature from the current moment based on the first temperature rise rate and the second temperature rise rate, and using the heating time as the heating advance amount.

[0094] The processing device performs dynamic calculations by combining the current state of the battery cell with the target state in order to accurately predict the timing of heating start-up.

[0095] In one embodiment, the processing device first acquires the current temperature and the target temperature of the battery cell, and calculates the temperature difference between them to characterize the temperature rise required for the battery cell to transition from its current thermal state to the target thermal state. This temperature difference reflects the energy level that the battery cell needs to increase and is a fundamental parameter for determining the heating time.

[0096] Furthermore, the processing device determines the basic heat dissipation conditions of the battery cell based on the current ambient temperature. Specifically, the lower the ambient temperature, the higher the rate at which the battery cell dissipates heat to the outside; conversely, the higher the ambient temperature, the relatively weaker the heat dissipation capacity. These basic heat dissipation conditions characterize the external factors influencing heat loss of the battery cell during the heating process, thereby affecting the actual temperature rise efficiency.

[0097] Based on this, the processing device combines the heating capacity parameters of the heating unit with the basic heat dissipation conditions to perform thermodynamic modeling of the cell's temperature rise process. The processing device can calculate the first temperature rise rate of the cell at the current cell temperature and the second temperature rise rate near the target cell temperature, using both parameters. The first temperature rise rate characterizes the actual temperature rise capability when the cell temperature is low in the initial heating stage, while the second temperature rise rate characterizes the change in temperature rise capability due to changes in heat loss and the approach of thermal equilibrium as the target temperature nears.

[0098] In one embodiment, the processing device performs segmented equivalent modeling of the entire heating process based on the first temperature rise rate and the second temperature rise rate. By comprehensively calculating the temperature rise rate in different temperature ranges, it determines the total heating time required for the cell to heat from the current temperature to the target temperature and uses this time as the heating advance.

[0099] For example, let the current ambient temperature be Ta, the target temperature of the battery cell be T2, the current temperature of the battery cell be T1, the specific heat capacity of the battery cell be C, the energy consumption coefficient of the heating film be k1, the system heat transfer coefficient be k2, and the mass of the battery cell be m. Then the temperature rise rates of the battery cell under different temperature conditions are as follows: The first temperature rise rate V1 at the current temperature T1 is:

[0100] The second temperature rise rate V2 near the target temperature T2 is:

[0101] Based on the first temperature rise rate and the second temperature rise rate, the processing device performs equivalent averaging on the entire heating process and determines the heating time t required for the battery cell to heat from the current temperature to the target temperature, where:

[0102] Therefore, the processing device uses the heating time t as the heating advance amount.

[0103] In one example, when the ambient temperature is low, the heat dissipation item Increasing the temperature rise rate (V1) causes the first temperature rise rate (V2) to decrease, which in turn increases the heating advance time (t). When the ambient temperature is high, the heat dissipation effect is weakened, and V1 and V2 increase synchronously, resulting in a corresponding decrease in the heating advance time, thereby achieving adaptive adjustment of the heating start-up time.

[0104] The processing device initiates heating control before the expected charge / discharge window arrives, based on the heating advance amount, so that the battery cell reaches the target temperature at the beginning of the window, thereby realizing the "ready to charge and use" operation state of the energy storage system.

[0105] By employing the above method, the calculation of heating advance not only considers the thermal inertia of the battery cell itself, but also comprehensively considers the environmental heat dissipation and changes in the heating unit's capacity. This makes the heating control more closely match the actual thermal dynamic process, enabling heating timing prediction based on the battery cell's thermal dynamic process, rather than using fixed time or empirical parameters for control. The heating advance can adaptively reflect the differences in thermal response across different temperature ranges, thereby improving the calculation accuracy of the heating start-up time. This effectively avoids underheating or overheating problems caused by changes in ambient temperature or fluctuations in heating efficiency, ensuring that the battery cell stably reaches the target temperature before the expected charge / discharge window arrives, thus improving the matching degree of the energy storage system's charge / discharge capacity and overall operational stability.

[0106] In some embodiments, determining the target temperature of the battery cell based on the expected charge-discharge power curve includes: determining the expected charging current and / or expected discharging current based on the expected charge-discharge power curve; determining the allowable operating temperature range of the battery cell under the corresponding charge-discharge current condition based on the expected charging current and / or expected discharging current, wherein the allowable operating temperature range is used to characterize the temperature range in which the battery cell meets the charge-discharge capability under the target charge-discharge current; and determining the target temperature corresponding to the expected charge-discharge current as the target temperature of the battery cell within the allowable operating temperature range.

[0107] The determination of the target temperature of the battery cell is based on the mapping relationship between the current demand and the thermo-electric coupling characteristics of the battery cell. By converting the expected power demand into a current constraint, and then further into a temperature constraint, the target temperature can be quantitatively determined.

[0108] Specifically, the processing device first determines the expected charging current and / or expected discharging current based on the expected charging and discharging power curves. This current can be calculated using the power-voltage relationship, thereby converting the power-level scheduling requirements into the cell's electrical-level operational requirements.

[0109] In one embodiment, the processing device determines the allowable operating temperature range of the battery cell under corresponding charge and discharge current conditions based on the expected charging current and / or expected discharging current, combined with the cell's rate performance curve and internal resistance characteristics. The allowable operating temperature range characterizes the temperature range within which the battery cell can meet voltage constraints and maintain stable charge and discharge efficiency under that current condition.

[0110] In this process, the processing device can correspond to different temperature boundaries according to different current levels. For example, high-rate discharge corresponds to a higher minimum operating temperature threshold to reduce internal resistance and avoid rapid voltage drop; low-rate charging corresponds to a more relaxed temperature range, thereby allowing for lower thermal management requirements.

[0111] After determining the allowable operating temperature range, the processing device selects a target temperature within this range that matches the expected charge / discharge current as the target temperature for the battery cell. Specifically, the target temperature can be comprehensively optimized based on the current magnitude, power duration, and battery cell aging status to meet current power requirements while also optimizing thermal management energy consumption.

[0112] In one example, when the expected charge / discharge current is high, the system selects a target temperature close to the upper limit of the allowable operating temperature range to reduce internal resistance and improve power capability; when the expected current is low, it selects a temperature point in the middle or lower of the range to reduce heating energy consumption.

[0113] By employing the above methods, the energy storage system can map power demand step by step to current demand, and further to temperature constraint ranges, thereby achieving refined control of electro-thermal coupling. Furthermore, by introducing the concept of allowable operating temperature range, a direct correlation is established between cell rate performance and thermal state, so that the determination of target temperature no longer relies on empirical settings, but is calculated based on the actual operating capacity boundary of the cell. This improves the accuracy and reliability of target temperature setting, thereby enhancing the adaptability of the energy storage system under different power conditions. It enables the cell to meet charge and discharge capacity requirements while reducing the risk of overheating, and improves overall energy efficiency and operational stability.

[0114] In the aforementioned embodiments, the energy storage system mainly operates based on the preheating mode, that is, the processing device performs pre-predictive control on the heating start time based on the expected charge and discharge power curve, the target temperature of the battery cell, and the heating advance amount, so that the battery cell reaches the target temperature before the expected charge and discharge window arrives, thereby achieving proactive protection of the expected charge and discharge capacity.

[0115] In one embodiment, the energy storage system can also be configured with a normal heating mode for heating control in scenarios where predictive control is not available or applicable. This mode is mainly used to meet thermal management control requirements under deterministic time nodes (such as user-specified time periods) or fixed scheduling needs.

[0116] In normal heating mode, the processing device no longer relies on advance prediction as the core control basis, but directly triggers and controls the heating process based on a preset charge / discharge power curve or a preset time node. The preset charge / discharge power curve can be the system's default scheduling curve or a historical experience curve, and the preset time node can be a fixed heating time set by the user or a time window specified in the system's operating strategy.

[0117] In one embodiment, when the system is in normal heating mode, the processing device directly controls the heating execution unit to start the heating operation before entering the preset time node or when the specified time node is reached, so that the cell temperature is raised to the preset target temperature or maintained within the preset temperature range, so as to meet the basic charging and discharging requirements within the specified time period.

[0118] In one implementation, the normal heating mode can be used in scenarios that do not rely on forecast information, such as when the user only specifies that the energy storage system needs to have basic charging and discharging capabilities for a certain period of time, without providing a specific power curve. In this case, the processing device controls the heating according to a preset power limit or the system's rated capacity, so that the system is in a usable state at the beginning of the target time period.

[0119] In one embodiment, the system can dynamically switch between normal heating mode and preheating mode. When the system detects uncertainty in the scheduling plan or lack of prediction information, it automatically switches to normal heating mode to ensure basic operational capabilities.

[0120] In one embodiment, the energy storage system is equipped with a multi-mode heating control mechanism to select a preheating mode or a non-preheating mode according to different scheduling needs, so as to adapt to the thermal management needs under different operating strategies.

[0121] When preheating is enabled, the processing device predicts the heating process required for the battery cell to reach the expected charge and discharge capacity based on the expected charge and discharge power curve and the target temperature of the battery cell. It determines the heating start time so that the heating process is completed before the expected charge and discharge window arrives. This ensures that the battery cell has the temperature conditions to meet the expected charge and discharge capacity at the beginning of the window, achieving the "charge and use immediately" operation effect.

[0122] In the non-preheating mode (power-disabled preheating mode), the processing device does not perform window pre-prediction, but performs real-time heating control based on the preset charge and discharge power curve or preset time node, and triggers heating execution at the specified time to meet the user's set heating requirements at the time point.

[0123] like Figure 6As shown, in the preheating mode, the processing device determines the heating start time based on the relationship between the current heating capacity of the battery cell and the expected charging capacity. When heating is started at time t0, since the battery cell's charging capacity can exceed the expected charging capacity before the charging window t2 under the action of heating, there is no need to start heating at time t0. When heating is started at time t1, the battery cell's charging capacity exactly matches the expected charging capacity at time t2. At this time, the heating advance time δT is the time difference between t2 and t1, and heating is stopped at time t2, allowing the battery cell to enter the working state that meets the charging capacity requirements.

[0124] like Figure 7 As shown, in the non-preheating mode, the processing device does not perform heating advance prediction. Instead, it directly controls heating based on a preset charge / discharge power curve or a preset time node. Heating is initiated when the specified time node t2 is reached, allowing the cell charging capacity to gradually increase from that moment and track the preset power demand to meet the user's heating requirements at the specified time. This method achieves differentiated scheduling of the cell heating process under different control strategies, enabling the system to flexibly switch between predictive-driven and time-triggered modes, thereby improving the adaptability and operational reliability of the energy storage system in complex application scenarios.

[0125] After explaining the multi-mode heating control method, heating advance calculation method, and target temperature determination method based on the expected charge and discharge power curve of the energy storage system in the embodiments of this application, in order to further explain the impact of different heating start times on the matching relationship of cell charge and discharge capabilities and energy utilization efficiency, the overall control mechanism of the embodiments of this application will be comprehensively explained below with reference to the accompanying drawings.

[0126] like Figure 8 The diagram shows the matching relationship between the cell's charge / discharge capacity and the expected charge / discharge capacity at different heating start-up times. Figure 8 The horizontal axis represents time t, and key time nodes t0, t1, and t2 are marked. The vertical axis represents the charge and discharge rate capability of the battery cell. The upper half represents the process of charging capability change, and the lower half represents the process of discharging capability change. The dashed line represents the expected charge and discharge capability demand curve, and the solid line represents the actual capability evolution curve of the battery cell at different heating start-up times.

[0127] When the system starts heating at time t0, the charging capacity of the battery cell gradually increases during the heating process, and reaches or even exceeds the expected charging capacity requirement at time t2. However, due to the early start time of heating, the battery cell has already completed the capacity ramp-up that exceeds the requirement before time t2, resulting in redundant heat accumulation before the target scheduling window arrives, which leads to energy waste and unnecessary thermal management losses.

[0128] When the system starts heating at time t1, the cell charging capacity gradually increases during the heating process and reaches the expected charging capacity requirement at time t2. This achieves precise alignment between the cell capacity curve and the expected capacity curve at the target time point, thereby avoiding premature overcharging and energy redundancy and achieving optimal utilization of heating energy.

[0129] A similar pattern can be observed during the change in discharge capability. Different heating start times will cause the cell discharge capability improvement curve to deviate from the expected discharge capability curve to varying degrees. Premature heating will lead to an early redundant increase in capability, while adaptive start-up can achieve capability matching at the target time.

[0130] Therefore, it can be seen that the core of the embodiments of this application lies in transforming the heating control of the energy storage system from traditional time-triggered heating to capacity-driven predictive heating control. That is, by accurately selecting the heating start time, the process of improving the cell capacity is matched with the expected charge and discharge demand at the target time point. The heating start time no longer depends on a fixed empirical time, but is derived by reverse deduction based on the time required to reach the target charge and discharge capacity, thereby realizing the pre-scheduling control of the cell thermal state, thus avoiding thermal redundancy and energy waste caused by premature heating, and avoiding insufficient capacity caused by late heating.

[0131] Compared with related technologies, the embodiments of this application introduce a heating start-up timing optimization mechanism, which enables the cell heating process to not only meet the target charge and discharge capacity requirements, but also further meet the energy utilization optimality constraints in the time dimension. This significantly reduces ineffective heating time and heat loss, improves the overall energy efficiency of the energy storage system, and enhances the system's precise response capability and operational economy in dynamic scheduling scenarios.

[0132] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0133] The heating control method for an energy storage system provided in this application can be executed by a heating control device for the energy storage system. This application uses the example of a heating control device executing the heating control method for the energy storage system to illustrate the heating control device for the energy storage system provided in this application.

[0134] Figure 9 This is a schematic diagram of the heating control device of the energy storage system provided in the embodiments of this application. Figure 9 As shown, the heating control device 900 of the energy storage system includes: a demand acquisition module 901, a temperature calculation module 902, and a heating control module 903.

[0135] The demand acquisition module 901 is used to acquire the expected charge and discharge demand information of the energy storage system and generate the expected charge and discharge power curve based on the expected charge and discharge demand information. The expected charge and discharge power curve is used to characterize the expected charge and discharge capacity of the energy storage system within the expected charge and discharge window.

[0136] The temperature calculation module 902 is used to determine the target temperature of the battery cell based on the expected charge and discharge power curve, and to determine the heating advance amount based on the target temperature of the battery cell, the current ambient temperature, and the current temperature of the battery cell.

[0137] The heating control module 903 is used to control the energy storage system to perform heating operations before the expected charge and discharge window arrives, based on the heating advance amount, so that the cell temperature reaches the target cell temperature, so that the energy storage system can meet the expected charge and discharge capacity within the expected charge and discharge window.

[0138] In one embodiment, the expected charge / discharge power curve is generated based on at least one of the following methods: generating the expected charge / discharge power curve according to the expected charge / discharge time and expected charge / discharge capacity set by the user; using the scheduling power curve of the energy storage system as the expected charge / discharge power curve, wherein the scheduling power curve is determined based on the time-of-use electricity price curve; or generating the power demand curve based on learning and prediction of historical photovoltaic power generation data and load data.

[0139] In one embodiment, the demand acquisition module is further configured to perform learning and prediction based on historical photovoltaic power data and historical load power data to generate photovoltaic power curves and load power curves; calculate the power difference based on the photovoltaic power curves and load power curves, the power difference being used to characterize the net power available for charging and discharging of the energy storage system within different time periods; determine the time period that meets the preset threshold conditions based on the power difference as the expected charging and discharging window, and determine the expected charging power and / or expected discharging power within the expected charging and discharging window to generate the expected charging and discharging power curve; determine the corresponding charging current and / or discharging current based on the expected charging and discharging power curve, and determine the target temperature of the battery cell based on the battery cell operating characteristic parameters.

[0140] In one embodiment, the temperature calculation module is further configured to determine the temperature rise required for the battery cell to reach the target temperature based on the temperature difference between the current temperature of the battery cell and the target temperature of the battery cell; determine the basic heat dissipation conditions of the battery cell based on the current ambient temperature; determine the first temperature rise rate of the battery cell at the current battery cell temperature and the second temperature rise rate at the target temperature of the battery cell based on the heating capacity parameters of the heating unit and the basic heat dissipation conditions; and determine the heating time required for the battery cell to heat up to the target temperature from the current moment based on the first temperature rise rate and the second temperature rise rate, and use the heating time as the heating advance amount.

[0141] In one embodiment, the temperature calculation module is further configured to determine the expected charging current and / or expected discharging current based on the expected charging and discharging power curve; based on the expected charging current and / or expected discharging current, determine the allowable operating temperature range of the battery cell under the corresponding charging and discharging current conditions, wherein the allowable operating temperature range is used to characterize the temperature range within which the battery cell meets the charging and discharging capability under the target charging and discharging current; and within the allowable operating temperature range, determine the target temperature corresponding to the expected charging and discharging current as the target temperature of the battery cell.

[0142] In one embodiment, the energy storage system is configured with a preheating mode and a normal heating mode. The heating control module is also used to control the energy storage system to perform heating in the normal heating mode according to a preset charge and discharge power curve or a preset time node, so as to meet the heating demand for a specified time period.

[0143] The heating control device of the energy storage system in this application embodiment can be an electronic device or a component of an electronic device, such as an integrated circuit or a chip. The electronic device can be a server, industrial control equipment, energy storage system control equipment, energy management equipment, vehicle control terminal, computer equipment, gateway equipment, or other electronic devices with data processing and control functions, or it can be the processing device described in the above embodiments.

[0144] The heating control device for the energy storage system provided in this application embodiment can realize the various processes implemented in the above-described heating control method embodiment for the energy storage system and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0145] Figure 10 This is a schematic diagram of the structure of the electronic device provided in an embodiment of this application. For example... Figure 10 As shown, this application embodiment also provides an electronic device 1000, including a processor 1001, a memory 1002, and a computer program stored in the memory 1002 and executable on the processor 1001. When the program is executed by the processor 1001, it implements the various processes of the above-described heating control method embodiment for the energy storage system and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0146] This application provides a non-transitory computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described heating control method embodiment for the energy storage system and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0147] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable media, such as computer read-only memory (ROM), random-access memory (RAM), magnetic disks, or optical disks.

[0148] The computer-readable storage medium may include: read-only memory (ROM), random-access memory (RAM), magnetic disk or optical disk, etc.

[0149] This application provides a computer program product, including a computer program that, when executed by a processor, implements the heating control method of the energy storage system described above.

[0150] This application provides a chip that includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-described heating control method embodiment for the energy storage system, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0151] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0152] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0153] From the above description of the embodiments, it is clear that the methods described in the embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases, the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the related technology, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0154] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the above-described embodiments. The above-described embodiments are merely illustrative and not restrictive. Under the guidance of this application, many other forms can be made without departing from the spirit and scope of the claims, and all of them are within the protection scope of this application.

[0155] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0156] Although embodiments of this application have been shown and described, it is understood that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.

Claims

1. A heating control method for an energy storage system, characterized in that, include: Obtain the expected charge and discharge demand information of the energy storage system, and generate the expected charge and discharge power curve based on the expected charge and discharge demand information. The expected charge and discharge power curve is used to characterize the expected charge and discharge capacity of the energy storage system within the expected charge and discharge window. The target temperature of the battery cell is determined based on the expected charge and discharge power curve, and the heating advance amount is determined based on the target temperature of the battery cell, the current ambient temperature, and the current temperature of the battery cell. Based on the heating advance amount, the energy storage system is controlled to perform a heating operation before the expected charge / discharge window arrives, so that the cell temperature reaches the target cell temperature, so that the energy storage system can meet the expected charge / discharge capacity within the expected charge / discharge window.

2. The heating control method for an energy storage system according to claim 1, characterized in that, The expected charge / discharge power curve is generated based on at least one of the following methods: Based on the user's set expected charging and discharging times and expected charging and discharging capabilities, an expected charging and discharging power curve is generated. The scheduled power curve of the energy storage system is used as the expected charge / discharge power curve, which is determined based on the time-of-use electricity price curve; or Power demand curves are generated by learning and predicting based on historical photovoltaic power generation and load data.

3. The heating control method for an energy storage system according to claim 2, characterized in that, The process of learning and predicting based on historical photovoltaic power generation data and load data to generate a power demand curve includes: Based on historical photovoltaic power data and historical load power data, learning and prediction are performed to generate photovoltaic power curves and load power curves. The power difference is calculated based on the photovoltaic power curve and the load power curve. The power difference is used to characterize the net power available for charging and discharging of the energy storage system in different time periods. Based on the power difference, a time period that meets the preset threshold condition is determined as the expected charge and discharge window, and the expected charging power and / or expected discharging power within the expected charge and discharge window are determined to generate the expected charge and discharge power curve. The corresponding charging current and / or discharging current are determined based on the expected charging and discharging power curve, and the target temperature of the battery cell is determined based on the battery cell operating characteristic parameters.

4. The heating control method for an energy storage system according to claim 1, characterized in that, The determination of the heating advance amount based on the target temperature of the battery cell, the current ambient temperature, and the current temperature of the battery cell includes: Based on the temperature difference between the current temperature of the battery cell and the target temperature of the battery cell, determine the temperature rise required for the battery cell to reach the target temperature; Determine the basic heat dissipation conditions of the battery cell based on the current ambient temperature; Based on the heating capacity parameters of the heating unit and the basic heat dissipation conditions, the first temperature rise rate of the battery cell at the current battery cell temperature and the second temperature rise rate at the target battery cell temperature are determined respectively. Based on the first temperature rise rate and the second temperature rise rate, the heating time required for the battery cell to heat up to the target temperature from the current moment is determined, and the heating time is used as the heating advance amount.

5. The heating control method for an energy storage system according to claim 1, characterized in that, Determining the target temperature of the battery cell based on the expected charge / discharge power curve includes: Determine the expected charging current and / or expected discharging current based on the expected charging and discharging power curves; Based on the expected charging current and / or expected discharging current, the allowable operating temperature range of the battery cell under the corresponding charging and discharging current conditions is determined. The allowable operating temperature range is used to characterize the temperature range within which the battery cell meets the charging and discharging capability under the target charging and discharging current. Within the allowable operating temperature range, the target temperature corresponding to the expected charge / discharge current is determined as the target temperature of the battery cell.

6. The heating control method for an energy storage system according to claim 1, characterized in that, The energy storage system is configured with a preheating mode and a normal heating mode, and the method further includes: In normal heating mode, the energy storage system is controlled to perform heating according to the preset charge and discharge power curve or preset time node to meet the heating demand for a specified time period.

7. The heating control method for an energy storage system according to any one of claims 1 to 6, characterized in that, The heating operation is performed by at least one of the following: heating film, liquid cooling heating circuit, heat pump system, or battery self-heating method.

8. The heating control method for an energy storage system according to any one of claims 1 to 6, characterized in that, The energy storage system includes at least one of the following: residential energy storage system, industrial and commercial energy storage system, photovoltaic-energy storage integrated system, or grid-side energy storage system.

9. A heating control device for an energy storage system, characterized in that, include: The demand acquisition module is used to acquire the expected charging and discharging demand information of the energy storage system, and generate the expected charging and discharging power curve based on the expected charging and discharging demand information. The expected charging and discharging power curve is used to characterize the expected charging and discharging capacity of the energy storage system within the expected charging and discharging window. The temperature calculation module is used to determine the target temperature of the battery cell based on the expected charge and discharge power curve, and to determine the heating advance amount based on the target temperature of the battery cell, the current ambient temperature, and the current temperature of the battery cell. The heating control module is used to control the energy storage system to perform a heating operation before the expected charge / discharge window arrives, based on the heating advance amount, so that the cell temperature reaches the target cell temperature, so that the energy storage system can meet the expected charge / discharge capacity within the expected charge / discharge window.

10. An energy storage system, characterized in that, include: The battery cell module is used to store and release electrical energy, and to change its operating temperature under heating. A heating execution module is used to perform a heating operation on the battery cell module; A processing device for performing the heating control method of the energy storage system as described in any one of claims 1-8.

11. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the heating control method for the energy storage system as described in any one of claims 1-8.

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