Energy storage system dehumidification control method, device, equipment and storage medium

Abstract

The present disclosure provides a kind of energy storage system dehumidification control method, device, equipment and storage medium, it is related to energy storage safety control technical field.The method comprises: obtaining the initial environment temperature and initial relative humidity inside the battery cabin of energy storage system, the dew point temperature of energy storage system is calculated;According to the operating state characteristic information, the charging and discharging starting time and target confidence are obtained, and the target dehumidification working condition parameter is determined according to the target confidence;Based on the preset temperature response model, according to the current liquid cooling standby temperature and target liquid cooling working temperature, the liquid cooling water supply temperature of liquid cooling system at different time is predicted;And according to the liquid cooling water supply temperature and dew point temperature, calculate the condensation temperature margin;Based on the preset dehumidification efficiency model, according to initial environment temperature, initial relative humidity and target relative humidity, determine the time required for dehumidification;According to the charging and discharging starting time and the time required for dehumidification, the dehumidification starting time is determined;In response to meeting the preset dehumidification condition, then execute dehumidification.

Description

Technical Field

[0001] This disclosure relates to the field of energy storage safety control technology, and in particular to a dehumidification control method for an energy storage system, a dehumidification control device for an energy storage system, an electronic device, and a computer-readable storage medium. Background Technology

[0002] As a core component of energy storage systems, energy storage containers densely house battery modules, temperature control equipment, and electrical components. Distributed liquid cooling plates are embedded between the battery packs for heat dissipation. However, as energy storage containers are enclosed spaces, condensation will form on the surface of the liquid cooling plates when the surface temperature falls below the dew point of the air inside the container. This can lead to safety hazards such as electrical short circuits, equipment corrosion, and insulation failure. Current dehumidification strategies, however, only activate the dehumidifier after the dew point is reached, which is a passive response. By this time, condensation has already formed, and the risk of condensation cannot be avoided. Summary of the Invention

[0003] This disclosure provides a dehumidification control method, apparatus, equipment, and storage medium for an energy storage system, which at least to some extent overcomes the problem of response lag in existing dehumidification strategies provided in related technologies.

[0004] Other features and advantages of this disclosure will become apparent from the following detailed description, or may be learned in part from practice of this disclosure.

[0005] According to a first aspect of this disclosure, a dehumidification control method for an energy storage system is provided, comprising: acquiring the initial ambient temperature and initial relative humidity inside the battery compartment of the energy storage system, and calculating the dew point temperature of the energy storage system based on the initial ambient temperature and the initial relative humidity; obtaining the charge / discharge start-up time and target confidence level based on the operating state characteristic information of the energy storage system, and determining target dehumidification operating condition parameters based on the target confidence level; predicting the liquid cooling water supply temperature of the liquid cooling system at different times based on a preset temperature response model, according to the current liquid cooling standby temperature and the target liquid cooling operating temperature; calculating the condensation temperature margin based on the liquid cooling water supply temperature and the dew point temperature; determining the dehumidification duration required based on a preset dehumidification efficiency model, according to the initial ambient temperature, the initial relative humidity, and the target relative humidity; determining the dehumidification start-up time based on the charge / discharge start-up time and the dehumidification duration required; and controlling the dehumidifier to operate based on the target dehumidification operating condition parameters in response to meeting preset dehumidification conditions.

[0006] In some embodiments of this disclosure, the operating status characteristic information includes the current charge / discharge plan and historical charge / discharge plan execution data of the energy storage system; obtaining the charge / discharge start time and target confidence level based on the operating status characteristic information of the energy storage system includes: extracting the charge / discharge start time from the current charge / discharge plan; determining a first plan coefficient based on the type of the current charge / discharge plan; determining a second plan coefficient based on the historical charge / discharge plan execution data; and determining the target confidence level based on the first plan coefficient and the second plan coefficient.

[0007] In some embodiments of this disclosure, determining the first planning coefficient based on the type of the current charge / discharge plan includes: determining the first planning coefficient as a first coefficient value in response to the current charge / discharge plan being a defined plan; and determining the first planning coefficient as a second coefficient value in response to the current charge / discharge plan being a preliminary plan, wherein the second coefficient value is less than the first coefficient value.

[0008] In some embodiments of this disclosure, the historical charge-discharge plan execution data includes the total number of scheduling times and the actual number of execution times of the charge-discharge plan; determining the second plan coefficient based on the historical charge-discharge plan execution data includes: calculating the ratio of the actual number of executions to the total number of scheduling times as the second plan coefficient.

[0009] In some embodiments of this disclosure, the operating status feature information includes historical operating data of the energy storage system; obtaining the charge / discharge start-up time and target confidence level based on the operating status feature information of the energy storage system includes: determining the target confidence level of the energy storage system in a target time period based on the historical operating data, and taking the start time of the target time period as the charge / discharge start-up time.

[0010] In some embodiments of this disclosure, the historical operating data includes the charging and discharging start-up status and corresponding charging and discharging modes of the energy storage system at different times on different days within a historical time interval. Determining the target confidence level of the energy storage system in a target time period based on the historical operating data includes: determining the number of charging and discharging start-up days and the total number of statistical days in the target time period based on the charging and discharging start-up status of the energy storage system at different times on different days within a historical time interval; calculating the charging and discharging start-up probability of the energy storage system in the target time period based on the number of charging and discharging start-up days and the total number of statistical days; determining a third coefficient based on the charging and discharging mode of the energy storage system in the target time period; calculating the standard deviation based on the charging and discharging start-up times within the total number of statistical days, and determining a fourth coefficient based on the standard deviation; and determining the target confidence level of the energy storage system in the target time period based on the charging and discharging start-up probability, the third coefficient, and the fourth coefficient.

[0011] In some embodiments of this disclosure, determining the target dehumidification operating condition parameters based on the target confidence level includes: determining the target dehumidification operating condition parameters corresponding to the target confidence interval according to the target confidence interval to which the target confidence level belongs, wherein the target confidence interval is one of a plurality of preset confidence intervals, and one preset confidence interval corresponds to a set of dehumidification operating condition parameters.

[0012] In some embodiments of this disclosure, the formula for the preset temperature response model is as follows: ; in, The temperature of the liquid cooling water supply at time t after the liquid cooling system is started; This refers to the liquid cooling operating temperature of the liquid cooling system. This refers to the liquid cooling standby temperature of the liquid cooling system. Let t be the temperature response time constant of the liquid cooling system, and t be the time after the liquid cooling system starts up.

[0013] In some embodiments of this disclosure, the formula for the preset dehumidification efficiency model is as follows: ; in, This represents the rate of change in relative humidity. This refers to the rated dehumidification capacity of the dehumidifier. The system efficiency coefficient, ranging from 0.4 to 0.7; This is the environmental correction factor, derived from the temperature correction factor. Humidity correction factor Sure; The volume of the battery compartment; For ambient temperature The saturated water vapor density at that point; Among them, temperature correction coefficient Determined by the following formula: ; Humidity correction factor Determined by the following formula: .

[0014] In some embodiments of this disclosure, determining the dehumidification start time based on the charge / discharge start time and the dehumidification duration includes: calculating the difference between the charge / discharge start time and the dehumidification duration as the dehumidification start time.

[0015] In some embodiments of this disclosure, determining the dehumidification start time based on the charge / discharge start time and the required dehumidification time includes: obtaining the liquid cooling pre-start time; determining the liquid cooling start time based on the charge / discharge start time and the liquid cooling pre-start time; and calculating the difference between the liquid cooling start time and the required dehumidification time as the dehumidification start time.

[0016] In some embodiments of this disclosure, determining the dehumidification start time based on the charging / discharging start time and the dehumidification duration includes: determining a buffer time and correcting the dehumidification start time based on the buffer time.

[0017] In some embodiments of this disclosure, satisfying the preset dehumidification conditions includes: the condensation temperature margin is less than a preset safety threshold and the dehumidification start time has been reached and the target confidence level is greater than a preset confidence threshold; or, the risk critical moment has been reached and the dehumidification start time has been reached and the target confidence level is greater than the preset confidence threshold; wherein, the risk critical moment is the moment corresponding to the condensation temperature margin being less than the preset safety threshold.

[0018] In some embodiments of this disclosure, the method further includes: dynamically adjusting the operating parameters of the dehumidifier based on real-time operating data of the energy storage system during the operation of the dehumidifier with the target dehumidification operating parameters.

[0019] In some embodiments of this disclosure, the real-time operating data includes a charge / discharge change plan; wherein, the step of dynamically adjusting the dehumidifier's operating parameters based on the real-time operating data of the energy storage system includes: acquiring the charge / discharge change plan; obtaining the changed charge / discharge start-up time and the changed target confidence level of the energy storage system based on the charge / discharge change plan; and adjusting the dehumidifier's operating parameters based on the changed charge / discharge start-up time and the target confidence level.

[0020] In some embodiments of this disclosure, the real-time operating data includes real-time relative humidity; the step of dynamically adjusting the operating parameters of the dehumidifier based on the real-time operating data of the energy storage system includes: calculating the humidity decrease rate based on the real-time relative humidity, the initial relative humidity, and the dehumidification duration; and controlling the increase of the dehumidification power of the dehumidifier in response to the humidity decrease rate being less than a preset rate threshold.

[0021] In some embodiments of this disclosure, calculating the dew point temperature of the energy storage system based on the initial ambient temperature and the initial relative humidity includes: determining the dew point temperature based on a preset dew point temperature formula, according to the initial ambient temperature and the initial relative humidity.

[0022] According to a second aspect of this disclosure, a dehumidification control device for an energy storage system is provided, comprising: a first determining module configured to acquire the initial ambient temperature and initial relative humidity inside the battery compartment of the energy storage system, and calculate the dew point temperature of the energy storage system based on the initial ambient temperature and the initial relative humidity; a second determining module configured to obtain the charge / discharge start-up time and target confidence level based on the operating state characteristic information of the energy storage system, and determine target dehumidification operating parameters based on the target confidence level; and a margin calculation module configured to calculate the dehumidification parameters based on the current liquid cooling standby temperature and the target liquid cooling operating temperature according to a preset temperature response model. The system includes a temperature prediction module for the liquid cooling system, which predicts the liquid cooling water supply temperature at different times; a dew point temperature prediction module for calculating the condensation temperature margin; a third determination module for determining the required dehumidification time based on a preset dehumidification efficiency model, the initial ambient temperature, the initial relative humidity, and the target relative humidity; a fourth determination module for determining the dehumidification start time based on the charge / discharge start time and the required dehumidification time; and a dehumidification control module for controlling the dehumidifier to operate based on the target dehumidification operating parameters if the condensation temperature margin and the dehumidification start time meet preset dehumidification conditions.

[0023] According to a third aspect of this disclosure, an electronic device is provided, including a processor and a memory, the memory storing a computer program that, when executed by the processor, implements the energy storage system dehumidification control method of the above embodiments.

[0024] According to a fourth aspect of this disclosure, a computer-readable storage medium is also provided, wherein a computer program is stored therein, and when executed by a processor, the computer program implements the energy storage system dehumidification control method of the above embodiments.

[0025] According to a fifth aspect of this disclosure, a computer program product is also provided, comprising a computer program that, when executed by a processor, implements the energy storage system dehumidification control method of any of the above.

[0026] In this embodiment, the charging / discharging start-up time is determined by the operating status characteristic information of the energy storage system, and the required dehumidification time is determined based on a preset dehumidification efficiency model. Based on the charging / discharging start-up time and the required dehumidification time, the dehumidification start-up time can be accurately determined, avoiding passive response lag. The temperature response curve after the liquid cooling system starts is simulated based on a preset temperature response model, and the dynamic evolution trend of the condensation temperature margin is tracked in real time, providing a quantitative basis for anti-condensation decisions. The target dehumidification operating parameters are determined based on the target confidence level, enabling fine control of the dehumidifier's operating time, operating time, and operating power. This effectively reduces the risk of condensation while significantly reducing unnecessary energy consumption and extending the dehumidifier's service life. By comprehensively considering whether the condensation temperature margin, target confidence level, and dehumidification start-up time meet the preset dehumidification conditions, the relative humidity in the battery compartment can be reduced to a safe level before the liquid cooling system starts, fundamentally blocking the conditions for condensation formation and significantly improving the environmental adaptability and operational safety of the energy storage system.

[0027] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0028] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. It is obvious that the drawings described below are merely some embodiments of this disclosure, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0029] Figure 1 This diagram illustrates the structure of an energy storage system provided in an embodiment of the present disclosure.

[0030] Figure 2 The diagram shows a flowchart of a dehumidification control method for an energy storage system provided in an embodiment of this disclosure.

[0031] Figure 3 A flowchart illustrating a method for determining the dehumidification start-up time according to an embodiment of this disclosure is shown.

[0032] Figure 4 A flowchart of another dehumidification control method for an energy storage system provided in an embodiment of this disclosure is shown.

[0033] Figure 5 This diagram illustrates a dehumidification control method for an energy storage system according to an embodiment of the present disclosure.

[0034] Figure 6 A flowchart of a target confidence determination method provided by an embodiment of this disclosure is shown.

[0035] Figure 7A flowchart of another dehumidification control method for an energy storage system provided in an embodiment of this disclosure is shown.

[0036] Figure 8 This diagram illustrates a method for dynamically adjusting the operating parameters of a dehumidifier according to an embodiment of the present disclosure.

[0037] Figure 9 This diagram illustrates a method for dynamically adjusting the operating parameters of another dehumidifier according to an embodiment of the present disclosure.

[0038] Figure 10 This illustration shows an example flowchart of a dehumidification control method for an energy storage system provided in an embodiment of the present disclosure.

[0039] Figure 11 This diagram illustrates the structure of a dehumidification control device for an energy storage system provided in an embodiment of the present disclosure.

[0040] Figure 12 This diagram illustrates the structure of an electronic device provided in an embodiment of the present disclosure. Detailed Implementation

[0041] Preferred embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While preferred embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0042] The terms "first" and "second" used in this document are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "multiple" means two or more, unless otherwise explicitly stated.

[0043] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection, an electrical connection, or a connection that allows communication between them; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication between two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0044] The following disclosure provides many different implementations or examples for carrying out different structures of this application. To simplify the disclosure, specific examples of components and arrangements are described below. Of course, these are merely examples and are not intended to limit the scope of this application. Furthermore, reference numerals and / or reference letters may be repeated in different examples; such repetition is for simplification and clarity and does not in itself indicate a relationship between the various implementations and / or arrangements discussed.

[0045] Because the energy we need is highly time- and space-dependent, in order to utilize energy rationally and improve energy efficiency, it is necessary to store one form of energy in the same way or by converting it into another, and then release it in a specific energy form based on future application needs. Currently, the main way to generate green electricity is to develop green energy sources such as photovoltaics and wind power to replace fossil fuels.

[0046] Currently, the generation of green electricity generally relies on solar, wind, and hydropower. However, wind and solar power are generally characterized by strong intermittency and large fluctuations, which can cause grid instability, insufficient power during peak demand periods, and excessive power during off-peak periods. Unstable voltage can also damage the power grid. Therefore, insufficient electricity demand or insufficient grid capacity may lead to the problem of "wind and solar curtailment." Solving these problems requires energy storage. This involves converting electrical energy into other forms of energy through physical or chemical means and storing it. When needed, this energy can be converted back into electrical energy and released. Simply put, energy storage is like a large "power bank," storing electrical energy when solar and wind power are abundant and releasing the stored electricity when needed.

[0047] Taking electrochemical energy storage as an example, this solution provides an energy storage device 110, which is applied to the energy storage system 100. The energy storage device 110 is equipped with a set of chemical batteries, which mainly use the chemical elements in the batteries as energy storage medium. The charging and discharging process is accompanied by the chemical reaction or change of the energy storage medium. Simply put, the electrical energy generated by wind and solar energy is stored in the chemical batteries. When the use of external electrical energy reaches its peak, the stored electrical energy is released for use, or transferred to places with a shortage of electricity for use.

[0048] Current energy storage applications are quite widespread, including generation-side energy storage, grid-side energy storage, and consumption-side energy storage. The corresponding types of energy storage devices 110 include: (1) Large-scale energy storage power stations (including multiple prefabricated energy storage modules) applied to wind power and photovoltaic power stations can help renewable energy power generation meet grid connection requirements and improve the utilization rate of renewable energy. As a high-quality active / reactive power regulation power source on the power supply side, energy storage power stations can achieve load matching of power in time and space, enhance the renewable energy absorption capacity, reduce instantaneous power changes, reduce the impact on the power grid, improve the absorption of new energy power generation, and are of great significance in power grid system backup, alleviating peak load power supply pressure and peak regulation and frequency regulation. (2) The energy storage prefabricated cabin applied on the grid side mainly functions as peak regulation, frequency regulation and grid congestion relief. In terms of peak regulation, it can realize peak shaving and valley filling of electricity load, that is, charging the energy storage battery when the electricity load is low and releasing the stored electricity during the peak electricity load period, thereby achieving a balance between power production and consumption. (3) Small energy storage cabinets applied to the electricity consumption side mainly function as self-consumption of electricity, peak-valley price arbitrage, capacity cost management, and improvement of power supply reliability. Depending on the application scenario, electricity consumption side energy storage can be divided into industrial and commercial energy storage cabinets, household energy storage devices, energy storage charging piles, etc., which are generally used in conjunction with distributed photovoltaics. Industrial and commercial users can use energy storage for peak-valley price arbitrage and capacity cost management. In the electricity market implementing peak-valley pricing, by charging the energy storage system when the electricity price is low and discharging the energy storage system when the electricity price is high, peak-valley price arbitrage can be achieved, reducing electricity costs. In addition, industrial enterprises subject to two-part tariffs can use energy storage systems to store energy during off-peak hours and discharge during peak loads, thereby reducing peak power and the maximum demand declared, achieving the goal of reducing capacity costs. Household photovoltaics with energy storage can improve the level of self-consumption of electricity. Due to high electricity prices and poor power supply stability, the demand for household photovoltaic installations is driven. Given that photovoltaic power generation occurs during the day, while user load is generally higher at night, configuring energy storage can better utilize photovoltaic power, improve self-consumption levels, and reduce electricity costs. Furthermore, energy storage is needed in areas such as communication base stations and data centers for backup power.

[0049] In some embodiments, see Figure 1 , Figure 1 This is a schematic diagram of the structure of an energy storage system 100 according to an embodiment of this application. Figure 1 And this application Figure 1 The embodiments are illustrated using a shared energy storage scenario on the generation / distribution side as an example. The energy storage device in this application is not limited to a prefabricated energy storage module in the generation and distribution energy storage scenario.

[0050] This application provides an energy storage system 100, which includes: a high-voltage cable 120, a first power conversion device 130, a second power conversion device 140, and an energy storage device 110 provided in this application. In some embodiments of the power generation scenario, the second power conversion device 140 can be a wind power conversion device. Since the electricity generated by the wind power conversion device is volatile, random, and intermittent, the unstable electricity output by the wind power conversion device can be stored in the energy storage device 110 through grid connection. The energy storage device 110 is connected to the high-voltage cable 120 and outputs smooth electricity to supply the power consumption side of the distribution network, realizing peak shaving and frequency regulation, and stable grid operation; or, wind power conversion... The power conversion device is always connected to the high-voltage cable 120. Under normal power generation conditions, the power output of the wind power conversion device is supplied to the power consumption side of the distribution network through the high-voltage cable 120. When the current power load is low and the wind power conversion device generates excess power, the excess power is first stored in the energy storage device 110 to reduce wind and solar curtailment rates and improve the problem of new energy power generation consumption. When the power load is high, the power grid issues an instruction to transmit the power stored in the energy storage device 110 together with the high-voltage cable 120 in grid-connected mode to supply power to the power consumption side. This provides the power grid with various services such as peak shaving, frequency regulation, and backup, giving full play to the peak shaving role of the power grid, promoting peak shaving and valley filling, and alleviating the power supply pressure of the power grid.

[0051] In some embodiments on the distribution network side, the first power conversion device 130 can be a photovoltaic panel, and the energy storage device 110 is connected to the photovoltaic panel and installed downstream of the high-voltage cable 120 and between the user load. The electrical energy output by the photovoltaic panel is stored in the energy storage device 110, which can respond in a timely manner to act as a backup power source when the power grid / distribution network fails; or, it can provide power supply support to alleviate line congestion when the high-voltage cable 120 transmission line is blocked, and to delay the economic pressure caused by the expansion of the power grid / distribution capacity when the power grid is planned to be expanded.

[0052] Optionally, the first power conversion device 130 may include, but is not limited to, a photovoltaic panel, and the second power conversion device 140 may include, but is not limited to, a wind power conversion device. The first power conversion device 130 and the second power conversion device 140 can convert at least one of solar energy, light energy, wind energy, thermal energy, tidal energy, biomass energy and mechanical energy into electrical energy.

[0053] Optionally, the energy storage device 110 may include, but is not limited to, energy storage applications such as energy storage power stations, hydropower / thermal / wind power generation systems, solar power generation systems, mobile power systems, smart home systems, or temporary power supply systems, and may also be applied in multiple fields such as data centers, military equipment, aerospace, charging piles, and electric vehicles.

[0054] Optionally, the energy storage device 110 may include battery modules, battery packs, battery clusters, mobile power supplies, energy storage cabinets / prefabricated energy storage compartments, and other battery integrated systems composed of individual battery cells. The actual application form of the energy storage device 110 provided in this application embodiment may be, but is not limited to, the listed products, and may also be other application forms. This application embodiment does not strictly limit the application form of the energy storage device 110.

[0055] Alternatively, the individual battery cell is not limited to at least one of cylindrical, prismatic, prismatic, or other shaped batteries.

[0056] Optionally, the individual battery cell can be a rechargeable battery, which refers to a single battery cell that can be recharged after discharge to activate the active materials and continue to be used. The individual battery cell can be a lithium-ion battery, sodium-ion battery, sodium-lithium-ion battery, lithium metal battery, sodium metal battery, lithium-sulfur battery, magnesium-ion battery, nickel-metal hydride battery, nickel-cadmium battery, lead-acid battery, etc., and this application does not specifically limit its type.

[0057] Energy storage systems, such as energy storage containers, typically employ liquid cooling systems for thermal management of battery clusters. These systems utilize a distributed cooling design, with liquid cooling plates embedded between each layer of the battery pack. The main coolant pipeline runs vertically along the battery cluster, with branch pipes connected at one end to the main pipeline and at the other end horizontally connected to each layer of cooling plates. Low-temperature coolant is circulated through a chiller unit, achieving efficient heat exchange layer by layer from bottom to top. This liquid cooling system ensures uniform temperature across all cells, improving battery system safety and cycle life.

[0058] Energy storage containers are enclosed spaces. When the surface temperature of the liquid cooling plate is lower than the dew point temperature inside the battery compartment, condensation will occur on the surface of the liquid cooling plate. Condensation may lead to safety hazards such as electrical short circuits, equipment corrosion, and insulation failure.

[0059] In related technologies, a real-time response dehumidification control strategy is typically employed, activating the dehumidifier when a condensation risk is detected. When the energy storage system is in standby mode, there is sufficient condensation temperature margin, and the dehumidifier remains in standby mode. However, when the system receives a charge / discharge command, the liquid cooling system activates as the battery cell temperature rises, rapidly reducing the liquid cooling water supply temperature to the liquid cooling operating temperature. This results in insufficient condensation temperature margin, causing condensation to begin on the surface of the liquid cooling plates. The liquid cooling system already carries a condensation risk during the cooling process. It takes approximately 2-5 minutes from the liquid cooling system activation to reaching the liquid cooling operating temperature; approximately 0.5-1 minute from detecting a condensation risk to the dehumidifier activation; and approximately 5-10 minutes from dehumidifier activation to effective dehumidification. When the dehumidifier is activated upon detecting a condensation risk, the actual dehumidification effect takes 5-15 minutes, while the liquid cooling temperature only needs 2-5 minutes to drop. This severe timing mismatch means that dehumidification only becomes effective after condensation has already occurred. Therefore, the real-time response mode carries a risk of response lag.

[0060] To address at least some of the aforementioned technical problems, this disclosure obtains the initial ambient temperature and initial relative humidity inside the battery compartment of the energy storage system, and calculates the dew point temperature of the energy storage system based on the initial ambient temperature and initial relative humidity; obtains the charge / discharge start-up time and target confidence level based on the operating status characteristic information of the energy storage system, and determines the target dehumidification operating parameters based on the target confidence level; predicts the liquid cooling water supply temperature of the liquid cooling system at different times based on a preset temperature response model, according to the current liquid cooling standby temperature and the target liquid cooling operating temperature; calculates the condensation temperature margin based on the liquid cooling water supply temperature and dew point temperature; determines the dehumidification time required based on a preset dehumidification efficiency model, according to the initial ambient temperature, initial relative humidity, and target relative humidity; determines the dehumidification start-up time based on the charge / discharge start-up time and the dehumidification time required; and controls the dehumidifier operation based on the target dehumidification operating parameters in response to meeting the preset dehumidification conditions.

[0061] This disclosure determines the charging and discharging start-up time by utilizing the operational status characteristics of the energy storage system, and determines the required dehumidification time based on a preset dehumidification efficiency model. Based on the charging and discharging start-up time and the required dehumidification time, the dehumidification start-up time can be accurately determined, avoiding passive response lag. A preset temperature response model simulates the temperature response curve after the liquid cooling system starts, tracking the dynamic evolution trend of the condensation temperature margin in real time, providing a quantitative basis for anti-condensation decisions. Target dehumidification operating parameters are determined based on the target confidence level, enabling precise control of the dehumidifier's operating time, operating time, and operating power. This effectively reduces the risk of condensation while significantly reducing unnecessary energy consumption and extending the dehumidifier's service life. By comprehensively considering the condensation temperature margin, target confidence level, and whether the dehumidification start-up time meets the preset dehumidification conditions, the relative humidity inside the battery compartment can be reduced to a safe level before the liquid cooling system starts, fundamentally blocking the conditions for condensation formation and significantly improving the environmental adaptability and operational safety of the energy storage system.

[0062] This disclosure provides a dehumidification control method for an energy storage system, which can be executed by any electronic device with computing power, such as a controller. In some embodiments, the controller can be a liquid-cooled temperature control system for the energy storage system, such as an Energy Management System (EMS). The controller may also include a Programmable Logic Controller (PLC) or a microcontroller, as long as it can perform the corresponding functions.

[0063] Figure 2 This diagram illustrates a dehumidification control method for an energy storage system according to an embodiment of the present disclosure. Figure 2As shown in the embodiments of this disclosure, the dehumidification control method for an energy storage system includes the following steps S202~S212. Wherein: S202. Obtain the initial ambient temperature and initial relative humidity inside the battery compartment of the energy storage system, and calculate the dew point temperature of the energy storage system based on the initial ambient temperature and initial relative humidity.

[0064] Once the energy storage system design is complete, the liquid cooling plate material and the size of the battery compartment are fixed. Therefore, the temperature and humidity inside the battery compartment (i.e., the initial ambient temperature and initial relative humidity) can be used as parameters to determine the dew point temperature of the energy storage system. The initial ambient temperature and initial relative humidity can be obtained by collecting the current temperature and humidity data from a temperature and humidity sensor, or by collecting the temperature and humidity inside the battery compartment at a preset frequency and calculating the arithmetic mean. This disclosure does not specify a particular method for collecting the initial ambient temperature and initial relative humidity. After the temperature and humidity sensor collects the initial ambient temperature and initial relative humidity inside the battery compartment, it can transmit them to the EMS via RS485 communication.

[0065] In some embodiments, calculating the dew point temperature of the energy storage system based on the initial ambient temperature and initial relative humidity in S202 above includes: determining the dew point temperature based on the initial ambient temperature and initial relative humidity according to a preset dew point temperature formula.

[0066] The preset dew point temperature formula can be pre-configured in the EMS. The preset dew point temperature formula can be the Magnus formula, as follows: (Formula 1); (Formula 2); Where T is the ambient temperature; RH is the relative humidity, RH∈(0,100%). is the dew point temperature; a and b are constants, a = 17.27℃, b = 273.7℃.

[0067] It should be noted that other dew point temperature formulas, such as empirical formulas, can also be used to calculate the dew point temperature. When using different methods to calculate the dew point temperature, the required parameters can be adjusted accordingly.

[0068] S204. Based on the operating status characteristic information of the energy storage system, obtain the charging and discharging start-up time and target confidence level, and determine the target dehumidification operating parameters based on the target confidence level.

[0069] Operational status characteristic information may include information that can determine when the energy storage system will start its charging and discharging plan at a certain time in the future, or information that can predict the probability of the energy storage system having a certain charging and discharging at a certain stage in the future.

[0070] The charge / discharge start-up time can be either the expected start-up time of the energy storage system in the future, or the time when the energy storage system may start charging / discharging in the future. Correspondingly, the target confidence level characterizes the degree of certainty that the energy storage system will start charging / discharging, and the target confidence level is positively correlated with the probability of the energy storage system starting at the charge / discharge start-up time. A higher target confidence level indicates a higher probability of the energy storage system starting charging / discharging at the start-up time; a lower target confidence level indicates a lower probability of the energy storage system starting charging / discharging at the start-up time.

[0071] In some embodiments, the operational status characteristic information may include the current charge / discharge plan. The type of the current charge / discharge plan may include a declarative plan and a preliminary plan. A declarative plan is a charge / discharge plan that is highly likely to be executed, while a preliminary plan is a charge / discharge plan whose execution depends on the current system state. The charge / discharge plan can be obtained directly from the EMS or from the scheduling system.

[0072] Once the EMS obtains the current charging and discharging plan of the energy storage system, it can directly extract the charging and discharging start time from the plan. For example, energy storage power station A participates in the electricity spot market and receives a charging and discharging instruction from the dispatch system at 17:00, specifying that 800kW of discharge will begin at 18:00. Based on load forecasting, the EMS automatically generates a plan that anticipates the discharge will be needed at 18:00 today. Both systems will extract the charging and discharging start time as 18:00 today.

[0073] In some embodiments, the operational status characteristic information may further include historical operational data of the energy storage system, which is the charging and discharging data of the energy storage system at different times over a past period. For example, the historical operational data consists of the number of days in the past N days where charging and discharging were initiated during the target time period t and the total number of days N. Based on the probability of initiating charging and discharging during the target time period t, the probability of initiating charging and discharging during the target time period t can be predicted for the current day. For example, if there are 21 days in 30 days where charging and discharging were initiated between 17:00 and 18:00, then the probability of initiating charging and discharging during the 17:00-18:00 time period on the current day is 70%.

[0074] It should be noted that when the startup probability during a given time period is less than the preset startup probability threshold, it indicates that the startup probability during the target time period is low, and dehumidification may not be performed. The preset startup probability threshold can be pre-configured in the EMS, and the specific value can be determined according to actual needs, such as 10%, 20%, 25%, etc. This disclosure does not impose any specific limitations on it.

[0075] After obtaining the charge / discharge start probability for the target time period based on historical operating data, the start time of the target time period can be used as the charge / discharge start time. For example, 17:00 in the above embodiment.

[0076] It should be noted that the methods for determining the charging and discharging start-up time and the target confidence level can also be other methods that can determine or predict the charging and discharging time of the energy storage system, and this disclosure does not specifically limit them.

[0077] In some embodiments, the start time of charging and discharging can be determined by the current charging and discharging plan, the start time of charging and discharging can be predicted by historical operating data, or the start time of charging and discharging can be determined by combining the current charging and discharging plan with historical operating data.

[0078] For example, when the current charging and discharging plan is obtained from the EMS or scheduling system, the charging and discharging start time is directly extracted from the current charging and discharging plan; when the current charging and discharging plan is not obtained or no clear plan is obtained, the charging and discharging start time is predicted through historical operation data.

[0079] In some embodiments, determining the target dehumidification condition parameters based on the target confidence level in S204 above includes: determining the target dehumidification condition parameters corresponding to the target confidence level interval based on the target confidence level interval to which the target confidence level belongs, wherein the target confidence level interval is one of a plurality of preset confidence level intervals, and one preset confidence level interval corresponds to a set of dehumidification condition parameters.

[0080] The number or values ​​of preset confidence intervals and corresponding dehumidification operating parameters can be determined according to actual needs. For example, three preset confidence intervals can be configured: greater than or equal to 80%, 50%-80%, and ≤50%.

[0081] The target dehumidification operating condition parameters may include the dehumidifier's start-up status and dehumidification power, etc. The start-up status may include start-up or standby. The target dehumidification operating condition parameters may also include the trigger mode, which may include strong trigger mode, weak trigger mode, or no trigger.

[0082] When the target confidence interval is greater than or equal to 80%, the target dehumidification operating condition parameter is to perform dehumidification at the first power, such as 100%, 90%, or maximum power, meaning the dehumidifier enters a strong trigger mode. When the target confidence interval is 50%-80%, it indicates uncertainty as to whether the energy storage system will subsequently enter the operating condition. The target dehumidification operating condition parameter is to perform dehumidification at the second power, which is less than the first power, such as 50% or 60%. Therefore, a low-energy-efficiency scheme is adopted to pre-dehumidify the energy storage system, meaning the dehumidifier enters a weak trigger mode. When the target confidence interval is less than or equal to 50%, it indicates a low probability that the energy storage system will subsequently enter the operating condition. The dehumidifier is controlled to standby mode and dehumidification is not performed on the energy storage system, meaning a non-trigger mode.

[0083] In this disclosure, by adapting the correspondence between the target confidence interval to which the target confidence level belongs and the dehumidification operating parameters, the optimal target dehumidification operating parameters are matched adaptively, thereby achieving hierarchical and precise adaptation of the dehumidification strategy for the energy storage battery compartment and deep adaptation with the pre-dehumidification scheme, effectively improving the initial control accuracy and energy-saving operation and maintenance benefits of the energy storage system.

[0084] S206. Based on the preset temperature response model, predict the liquid cooling water supply temperature of the liquid cooling system at different times according to the current liquid cooling standby temperature and the target liquid cooling operating temperature; and calculate the condensation temperature margin according to the liquid cooling water supply temperature and the dew point temperature.

[0085] The preset temperature response model can be stored in the EMS in advance. The preset temperature response model is used to characterize the change trend of the liquid cooling water supply temperature over time after the liquid cooling system is started. In combination with the dew point temperature of the energy storage system, the dynamic evolution trend of the condensation temperature margin can be tracked in real time, thereby providing a quantitative basis for anti-condensation decision-making.

[0086] In some embodiments, the preset temperature response model can be expressed as: (Formula 3); in, The temperature of the liquid cooling water supply at time t after the liquid cooling system is started; This refers to the liquid cooling operating temperature of the liquid cooling system. This refers to the liquid cooling standby temperature of the liquid cooling system. Let t be the temperature response time constant of the liquid cooling system, and t be the time after the liquid cooling system starts up.

[0087] t=0 is the current time. At t=0, .

[0088] As can be seen from Formula 3, the preset temperature response model is based on the time t after the liquid cooling system starts up and the liquid cooling operating temperature. and liquid cooling standby temperature The independent variable is the liquid cooling water supply temperature, and the dependent variable is the liquid cooling operating temperature. It can also be called the liquid cooling target temperature, which is the final target temperature after the liquid cooling system is started. For example, after the liquid cooling system is started, the coolant temperature will be reduced from the liquid cooling standby temperature, such as 30°C, to the liquid cooling operating temperature, such as 20°C.

[0089] In some embodiments, the preset temperature response model can also be stored in the EMS in the form of a two-dimensional data table or a three-dimensional data table. For example, a three-dimensional data table can be constructed containing the liquid cooling standby temperature, the liquid cooling operating temperature, and the liquid cooling system startup time and the liquid cooling water supply temperature. After determining the liquid cooling standby temperature, the liquid cooling operating temperature, and the liquid cooling system startup time, the liquid cooling water supply temperature can be determined by looking up the table or by interpolation.

[0090] In some embodiments, the difference between the liquid cooling water supply temperature and the dew point temperature can be used as the condensation temperature margin, where the condensation temperature margin at time t is... Represented as .

[0091] S208. Based on the preset dehumidification efficiency model, determine the required dehumidification time according to the initial ambient temperature, initial relative humidity and target relative humidity.

[0092] The preset dehumidification efficiency model is a humidity decay quantification prediction model that is pre-calibrated and solidified into the EMS for the characteristics of the sealed space of the battery compartment. The preset dehumidification efficiency model is used to characterize the decay change law of relative humidity with dehumidification time under a fixed battery cluster environment and rated operating parameters. It can accurately predict the dehumidification time required based on the temperature and humidity state inside the battery cluster and the target relative humidity, providing a core basis for calculating the start time of pre-dehumidification and matching the charging and discharging sequence.

[0093] In some embodiments, the formula for the preset dehumidification efficiency model is as follows: (Formula 4); in, This represents the rate of change in relative humidity. This refers to the rated dehumidification capacity of the dehumidifier. The system efficiency coefficient, ranging from 0.4 to 0.7; This is the environmental correction factor, derived from the temperature correction factor. Humidity correction factor Sure, ; The volume of the battery compartment; Initial ambient temperature The saturated water vapor density at that point; Among them, temperature correction coefficient Determined by the following formula: (Formula 5); Humidity correction factor Determined by the following formula: (Formula 6).

[0094] The publicly disclosed method accurately predicts the time required for dehumidification by using a preset dehumidification efficiency model, thereby allowing for the reverse calculation of the optimal dehumidification start-up time. This ensures that the humidity in the battery compartment is stably reduced to a safe threshold before the energy storage charging and discharging starts and the liquid cooling system begins cooling operation, eliminating the risk of condensation at the source. At the same time, it avoids the dehumidifier running idle for a long time in advance, significantly reducing system energy consumption.

[0095] In some embodiments, the preset dehumidification efficiency model can be stored in the EMS in the form of a two-dimensional data table or a three-dimensional data table to achieve lightweight deployment, thereby determining the required dehumidification time by looking up the table or interpolation.

[0096] S210. Determine the dehumidification start time based on the charging / discharging start time and the required dehumidification time.

[0097] In some embodiments, the dehumidification start time is a time before the charge / discharge start time, so as to ensure that dehumidification is completed before the energy storage system starts charging / discharging or before the liquid cooling system starts, and reduce the humidity of the battery cluster to a safe threshold.

[0098] In one feasible implementation, the difference between the charge / discharge start-up time and the dehumidification time is calculated as the dehumidification start-up time. This ensures that the energy storage system completes dehumidification before charge / discharge startup, eliminating the risk of condensation. The dehumidification start-up time can be expressed by the following formula: (Formula 7); in, This is the start time for dehumidification; This is the start-up time for charging and discharging; The time required for dehumidification.

[0099] For example, if the charging / discharging start time is 18:00 and the dehumidification time is 30 minutes, then the dehumidification start time is 17:30.

[0100] like Figure 3 As shown, in another feasible implementation, the above-mentioned S210 determines the dehumidification start time based on the charging / discharging start time and the required dehumidification duration, including: S302, Obtain the liquid cooling pre-start time; S304. Determine the liquid cooling start time based on the charge / discharge start time and the liquid cooling pre-start time; S306. Calculate the difference between the liquid cooling start time and the dehumidification time required, and use it as the dehumidification start time.

[0101] Liquid-cooled pre-start time is used to characterize the time difference between charge / discharge start-up and liquid-cooled start-up, and is a core timing parameter for the pre-control of energy storage systems.

[0102] In this disclosure, the liquid cooling pre-start time can be determined based on the cell temperature. The pre-start time of the liquid cooling system is dynamically matched according to the cell temperature to adapt to the differences in battery heating characteristics and charge / discharge rates, effectively solving problems such as poor adaptability of fixed liquid cooling pre-start time, delayed cooling, or energy waste.

[0103] Once the charging / discharging start time is determined, the cell temperature of each individual cell in the battery cluster is collected before the start time arrives. Based on a preset correspondence table, the liquid cooling pre-start time corresponding to the temperature range of the cell temperature is determined. The preset correspondence table is used to characterize the correspondence between the preset temperature range and the liquid cooling pre-start time, thereby enabling the cooling mode to be activated in advance. This ensures that the liquid cooling system completes the cooling response before the charging / discharging starts, establishes a stable temperature control condition, and effectively avoids the risk of condensation caused by excessively rapid temperature rise of the cells during charging / discharging reconstruction and sudden changes in temperature and humidity in the battery compartment.

[0104] In the preset correspondence table, multiple preset temperature ranges are configured. Each preset temperature range corresponds to a liquid cooling pre-start time. The higher the temperature value of the preset temperature range, the longer the corresponding liquid cooling pre-start time.

[0105] In some embodiments, the liquid cooling pre-start time can also be obtained based on historical operating data of the liquid cooling system, or it can be pre-calibrated through experimental testing. This disclosure does not specifically limit the method for determining the liquid cooling pre-start time.

[0106] It can calculate the charging and discharging start-up time. and liquid cooling pre-start time The difference between them is used as the liquid cooling start-up time. ,Right now .

[0107] The difference between the dehumidification start-up time and the required dehumidification time is calculated as the dehumidification start-up time to ensure that the energy storage system completes dehumidification before the liquid cooling system starts, eliminating the risk of condensation. The dehumidification start-up time can be expressed as: (Formula 8); in, This is the start time for dehumidification; This is the liquid cooling start-up time; The time required for dehumidification; This is the start-up time for charging and discharging. This is the liquid cooling pre-start time.

[0108] For example, if the charging / discharging start time is 18:00, the dehumidification time is 30 minutes, and the liquid cooling pre-start time is 10 minutes, then the dehumidification start time is 17:20.

[0109] In one feasible implementation, S210 determines the dehumidification start time based on the charging / discharging start time and the required dehumidification time, including: determining a buffer time, correcting the dehumidification start time based on the buffer time, and further reducing the probability of condensation risk in the energy storage system by correcting the dehumidification start time through the buffer time.

[0110] The buffer time can be pre-configured in the EMS. The specific value of the buffer time can be determined according to actual needs, such as a buffer time of 5 minutes, 10 minutes, etc.

[0111] After obtaining the dehumidification start-up time using Formula 7 or Formula 8, the dehumidification start-up time can be corrected using the following formula: (Formula 9); in, This is the corrected dehumidification start-up time; The dehumidification start-up time before the correction; This is the buffer time.

[0112] For example, if the dehumidification start time is 17:20 and the buffer time is 10 minutes, then the corrected dehumidification start time is 17:10.

[0113] S212. In response to meeting the preset dehumidification conditions, the dehumidifier is controlled to operate based on the target dehumidification operating parameters.

[0114] After obtaining the dehumidification start time, it can be determined whether the condensation temperature margin and the dehumidification start time meet the preset dehumidification conditions. If so, the dehumidifier is controlled to run based on the target dehumidification operating parameters; otherwise, the dehumidifier is put into standby mode.

[0115] After obtaining the corrected dehumidification start time, it can be determined whether the condensation temperature margin and the corrected dehumidification start time meet the preset dehumidification conditions. If so, the dehumidifier is controlled to run based on the target dehumidification operating parameters; otherwise, the dehumidifier is put into standby mode.

[0116] In some embodiments, satisfying the preset dehumidification conditions includes: the condensation temperature margin is less than a preset safety threshold and the dehumidification start time has been reached and the target confidence level is greater than a preset confidence threshold; or, the risk critical moment has been reached and the dehumidification start time has been reached and the target confidence level is greater than a preset confidence threshold; wherein, the risk critical moment is the moment corresponding to the condensation temperature margin being less than the preset safety threshold.

[0117] The following are situations where the preset dehumidification conditions are not met: the condensation temperature margin is greater than or equal to the preset safety threshold; the dehumidification start time has not been reached; the risk critical moment has not been reached; or the target confidence level is less than the preset confidence threshold.

[0118] This disclosure deeply couples dynamic condensation temperature margin, risk critical moment, target confidence level, and precise dehumidification start-up moment. It can not only complete humidity control in advance before the energy storage system starts charging and discharging, avoiding the risk of condensation during the switching of previous operating conditions, but also adapt to the dynamic operating condition changes after the liquid cooling system starts, and prevent and control the condensation hazards generated during the liquid cooling process in real time. It completely solves the problems of prediction lag, risk omission, and insufficient operating condition adaptation in traditional single-sequence dehumidification control, comprehensively improves the accuracy and reliability of dehumidification in the energy storage battery compartment, and greatly optimizes the overall operational safety and operating condition adaptability of the energy storage system.

[0119] The preset safety threshold and preset reliability threshold can be pre-configured in the EMS. The preset safety threshold can be a fixed value or a range of values, and the value of the preset safety threshold is determined according to actual needs. The preset reliability threshold can also be a fixed value or a range of values, and this disclosure does not limit the specific values. For example, the preset safety threshold can be 2℃ or 3℃, or the preset safety threshold can be between 2℃ and 3℃. The preset reliability threshold can be 50%, or the preset safety threshold can be between 50% and 55%.

[0120] After the liquid cooling system is started, the liquid cooling water supply temperature From liquid cooling standby temperature Rapidly decreasing, condensation temperature margin It also shrinks accordingly, among which, , This refers to the dew point temperature. When the condensation temperature margin... When the temperature is below the preset safety threshold, there is a risk of condensation. The moment when the value is less than the preset safety threshold is determined as the critical moment of risk. Dehumidification must be completed before the critical moment of risk.

[0121] The dehumidification start time has been reached. This means that the current time of the system has reached the calculated dehumidification start time. For example, if the dehumidification start time is 17:30, when the current time reaches 17:30, it indicates that the dehumidification start time has been reached.

[0122] The critical moment of risk has been reached refers to the critical time point at which the risk of condensation is about to occur. It is later than or equal to the dehumidification start time. The current time is synchronous with the dehumidification start time. For example, if the critical moment of risk is 17:40, when the current time reaches 17:40, it indicates that the critical moment of risk has been reached.

[0123] The dehumidification start-up time and the risk critical time have been reached mean that the energy storage system has reached both the calculated dehumidification start-up time and the critical time when the risk of condensation is about to occur. When the dehumidification start-up time is 17:30, the risk critical time is 17:40, and the current time is 17:40, the preset dehumidification conditions are met if the target confidence level is greater than the preset confidence threshold.

[0124] In this embodiment, the charging / discharging start-up time is determined by the operating status characteristic information of the energy storage system, and the required dehumidification time is determined based on a preset dehumidification efficiency model. Based on the charging / discharging start-up time and the required dehumidification time, the dehumidification start-up time can be accurately determined, avoiding passive response lag. The temperature response curve after the liquid cooling system starts is simulated based on a preset temperature response model, and the dynamic evolution trend of the condensation temperature margin is tracked in real time, providing a quantitative basis for anti-condensation decisions. The target dehumidification operating parameters are determined based on the target confidence level, enabling fine control of the dehumidifier's operating time, operating time, and operating power. This effectively reduces the risk of condensation while significantly reducing unnecessary energy consumption and extending the dehumidifier's service life. By comprehensively considering whether the condensation temperature margin, target confidence level, and dehumidification start-up time meet the preset dehumidification conditions, the relative humidity in the battery compartment can be reduced to a safe level before the liquid cooling system starts, fundamentally blocking the conditions for condensation formation and significantly improving the environmental adaptability and operational safety of the energy storage system.

[0125] Figure 4 A flowchart illustrating another dehumidification control method for an energy storage system provided in an embodiment of this disclosure is shown. Figure 4 As shown, in some embodiments, the operating status characteristic information includes the current charge / discharge plan and historical charge / discharge plan execution data of the energy storage system; the step in S204 above, obtaining the charge / discharge start time and target confidence level based on the operating status characteristic information of the energy storage system, includes: S402. Extract the charge / discharge start time from the current charge / discharge plan; S404. Determine the first plan coefficient based on the type of the current charge / discharge plan; S406. Determine the second plan coefficient based on historical charge and discharge plan execution data; S408. Determine the target confidence level based on the first planning coefficient and the second planning coefficient.

[0126] The current charge / discharge plan refers to the charge / discharge plan to be executed on the current day, which is acquired by the energy storage system. The current charge / discharge plan can be obtained directly from the EMS or from the dispatch system. The type of current charge / discharge plan can include explicit plans or preliminary plans. Explicit plans are charge / discharge plans that are highly likely to be executed, while preliminary plans are charge / discharge plans whose execution depends on the current system state.

[0127] Once the EMS obtains the current charging and discharging plan of the energy storage system, it can directly extract the charging and discharging start time from the plan. For example, energy storage power station A participates in the electricity spot market and receives a charging and discharging instruction from the dispatch system at 17:00, specifying that 800kW of discharge will begin at 18:00. Based on load forecasting, the EMS automatically generates a plan that anticipates the discharge will be needed at 18:00 today. Both systems will extract the charging and discharging start time as 18:00 today.

[0128] Historical charge and discharge plans correspond to the current charge and discharge plans and refer to the charge and discharge plans that the energy storage system has already completed. Historical charge and discharge plan execution data characterizes the completion status of historical charge and discharge plans during execution. Historical charge and discharge plan execution data includes, but is not limited to, the total number of charge and discharge operations received by the energy storage power station within a preset time interval (such as 15 days, 30 days, etc.), the number of times the plan was actually executed as planned, the number of times the plan was canceled, and the number of times the plan was postponed or brought forward.

[0129] In some embodiments, S404 above, determining the first planning coefficient according to the type of the current charge / discharge plan, includes: determining the first planning coefficient as a first coefficient value in response to the current charge / discharge plan being a defined plan; and determining the first planning coefficient as a second coefficient value in response to the current charge / discharge plan being a preliminary plan, wherein the second coefficient value is less than the first coefficient value.

[0130] The first planning coefficient characterizes the certainty coefficient of the plan and is determined based on the type of the current charge / discharge plan. The higher the certainty of the current charge / discharge plan, the larger the value of the first planning coefficient; that is, the first planning coefficient is directly proportional to the certainty of the current charge / discharge plan. For a defined plan, the first planning coefficient takes a first value, such as 0.95 or 0.9; for a preliminary plan, the first planning coefficient takes a second value, such as 0.8 or 0.75.

[0131] It should be noted that the specific values ​​of the first and second coefficients are not specifically limited and can be determined according to actual needs.

[0132] In some embodiments, historical charge / discharge plan execution data includes the total number of scheduling attempts and the actual number of execution attempts. S406 above determines a second plan coefficient based on the historical charge / discharge plan execution data, including: calculating the ratio of the actual number of execution attempts to the total number of scheduling attempts, as the second plan coefficient.

[0133] In some embodiments, the target confidence level is the product of the first planning coefficient and the second planning coefficient. That is, the target confidence level can be expressed as: (Formula 10); in, Target confidence level; The first planning coefficient; This is the coefficient for the second plan.

[0134] For example, energy storage power station A received a total of 28 charging and discharging plans from the dispatch system in the past 30 days. Of these, 26 were actually executed, 1 was cancelled, and 1 was postponed or brought forward. At this time, the second planning coefficient... This charge / discharge plan is a specific plan. Then the target confidence level When the confidence threshold of the strong trigger mode is 0.8, the target dehumidification operating condition parameter is determined as the first dehumidification parameter, such as a dehumidification power of 100%.

[0135] Energy storage power station B received a total of 28 charging and discharging plans from the dispatch system in the past 30 days. Of these, 15 were actually executed, 6 were canceled, and 7 were postponed or brought forward. At this time, the second planning coefficient... This charge / discharge plan is a specific plan. Then the target confidence level When the confidence threshold of the trigger mode is 0.5-0.8, the target dehumidification operating condition parameter is determined as the second dehumidification parameter, such as a dehumidification power of 50%.

[0136] Energy storage power station C received a total of 2 charging and discharging plans from the dispatch system in the past 30 days. Of these, 1 was actually executed, 1 was canceled, and 0 were postponed or brought forward. Because the sample size of energy storage power station C is relatively low, when the number of statistical days is less than a preset threshold (e.g., 7 days), the second planning coefficient is defined. Use the default value, such as 0.7.

[0137] It should be noted that in the above example, the actual executed charge / discharge plan refers to a time deviation of less than 15 minutes between the start time and the scheduled charge / discharge time. That is, if the charge / discharge plan is scheduled for 18:00, then a charge / discharge plan with a start time between 17:45 and 18:15 is determined to be an actually executed charge / discharge plan, and the corresponding actual execution count is incremented by 1.

[0138] A charge / discharge plan whose start time is earlier than the planned charge / discharge time and whose deviation is more than 15 minutes is identified as being advanced; a charge / discharge plan whose start time is later than the planned charge / discharge time and whose deviation is more than 15 minutes is identified as being delayed. The number of times a plan is delayed or advanced is incremented by 1.

[0139] For any charge / discharge plan that was not executed, it is determined to be cancelled, and the corresponding cancellation count is incremented by 1.

[0140] In this embodiment, when the current charge / discharge plan is obtained, the charge / discharge start time can be directly extracted. A first plan coefficient is determined based on the type of the current charge / discharge plan, and a second plan coefficient is determined based on historical charge / discharge plan execution data. The target confidence level is determined based on the first and second plan coefficients. Thus, based on the historical situation of the energy storage system and the current plan, the target confidence level is accurately determined to characterize the response capability of the energy storage system's charge / discharge plan. This effectively improves the accuracy and reliability of the charge / discharge start time prediction, providing a reliable quantitative basis for subsequent dehumidification parameter grading and matching and precise control of dehumidification timing. This improves the accuracy and adaptability of the energy storage system's pre-dehumidification and anti-condensation control.

[0141] Figure 5 This diagram illustrates a flowchart of another dehumidification control method for an energy storage system provided in an embodiment of this disclosure. Figure 5 As shown, in some embodiments, the operating status characteristic information includes historical operating data of the energy storage system; the step in S204 above, obtaining the charging / discharging start-up time and target confidence level based on the operating status characteristic information of the energy storage system, includes: S2042. Based on historical operating data, determine the target confidence level of the energy storage system during the target period, and take the start time of the target period as the charging and discharging start time.

[0142] In some embodiments, historical operating data characterizes the energy storage system's execution of charge and discharge plans within a historical time interval. Based on historical operating data, the charge and discharge start-up status at different times of the current day can be predicted, and the confidence level of the energy storage system at different times of the day can be determined respectively. The target time period is any time period within a day, and the start time of each time period is taken as the charge and discharge start-up time.

[0143] Historical operational data can include the charging and discharging start-up status of the energy storage system at different times on different days within a historical time interval. The historical time interval can be N days prior to the current day, and the different times of each day can be determined based on actual conditions. For example, N is 30 days, and the time periods can be obtained by clustering the historical operational data. For example, historical operational data could be: In the past 30 days, charging and discharging started between 17:00 and 18:00 on 21 days.

[0144] In some embodiments, the charge / discharge start time can be determined based on the current charge / discharge plan, historical operating data, or a combination of both. For example, when the current charge / discharge plan is not available or is not explicitly defined, the charge / discharge start time can be determined based on historical operating data.

[0145] In this embodiment, based on the mining and analysis of historical operating data, the target confidence level and charge / discharge start time of the target period are accurately predicted, ensuring that the confidence level assessment results are consistent with the long-term operating rules of the energy storage system and are true and reliable. By determining the start time of the target period as the charge / discharge start time, a unified judgment benchmark can be established, making the judgment results of the charge / discharge start time more stable. This provides a fixed and reliable benchmark for the pre-dehumidification control method, effectively improving the accuracy and operating stability of the dehumidification control of the energy storage system.

[0146] Figure 6 A flowchart illustrating a target confidence determination method provided by an embodiment of this disclosure is shown. Figure 6 As shown, in some embodiments, historical operating data includes the charging and discharging start-up status of the energy storage system at different times on different days within a historical time interval, and the corresponding charging and discharging modes; S2042 above determines the target confidence level of the energy storage system in the target time period based on the historical operating data, including: S602. Based on the charging and discharging start-up status of the energy storage system at different times and on different days within the historical time interval, determine the number of charging and discharging start-up days and the total number of statistical days in the target period. S604. Calculate the charging and discharging start-up probability of the energy storage system during the target period based on the number of charging and discharging start-up days and the total number of statistical days. S606. Determine the third coefficient based on the charging and discharging mode of the energy storage system during the target period; S608. Calculate the standard deviation based on the charging and discharging start times within the total statistical days, and determine the fourth coefficient based on the standard deviation; S610. Determine the target confidence level of the energy storage system during the target time period based on the charge / discharge start probability, the third coefficient, and the fourth coefficient.

[0147] After obtaining historical operating data, the number of charging / discharging start-up days and the total number of days during the target period are counted. For example, historical operating data shows that charging / discharging started between 17:00 and 18:00 on 21 out of the past 30 days.

[0148] The charge / discharge start-up probability characterizes the start-up probability over a specific time period, referring to the probability of starting during the target time period over a past period. The charge / discharge start-up probability of an energy storage system during the target time period. This is the ratio between the number of charge / discharge start-up days M and the total number of start-up days N, i.e. .

[0149] The third coefficient characterizes the mode matching degree. Historical operating data also includes the charging and discharging modes corresponding to the charging and discharging start-up states. These modes can include strongly regular and weakly regular modes. The operating modes of the energy storage system include peak shaving and valley filling, and frequency regulation. Peak shaving and valley filling correspond to strongly regular modes, while frequency regulation corresponds to weakly regular modes. For strongly regular modes, the third coefficient... For weak regularity patterns, the third coefficient .

[0150] It should be noted that the value of the third coefficient can be adjusted according to actual needs, and this disclosure does not impose specific restrictions on it.

[0151] The fourth coefficient represents the historical consistency coefficient, calculated based on the standard deviation of the start-up time. It can be used to statistically analyze all effective charge / discharge operating periods over the past N days, extracting the actual charge / discharge start-up time corresponding to each operating period. Assuming the number of effective charge / discharge operating periods is n, the extracted actual charge / discharge start-up times are as follows: , … .

[0152] Calculate the average start-up time to characterize the baseline for the normal charge-discharge start-up time of the energy storage system: (Formula 11); in, The average startup time, Let be the i-th actual charging / discharging start time, and n be the number of effective charging / discharging working periods.

[0153] The standard deviation σ can be calculated using the following formula: (Formula 12); in, The standard deviation is used to characterize the degree of fluctuation and dispersion at the start-up time of the energy storage system's charging and discharging. The average startup time, Let be the i-th actual charging / discharging start time, and n be the number of effective charging / discharging working periods.

[0154] According to the preset mapping relationship, the fourth coefficient is matched to the standard deviation σ. The preset mapping relationship represents the correspondence between different standard deviation ranges and the fourth coefficient.

[0155] For example, when σ≤10min, the fourth coefficient is determined to be 0.95; when 10min<σ≤30min, the fourth coefficient is determined to be 0.85; when 30min<σ≤60min, the fourth coefficient is determined to be 0.70; and when σ>60min, the fourth coefficient is determined to be 0.50.

[0156] The target confidence level for the target time period can be expressed as: (Formula 13); in, The target confidence level for the target time period. This represents the probability of the energy storage system starting up during the target time period; It is the third coefficient; It is the fourth coefficient.

[0157] In this embodiment, the general plan mines and analyzes historical operating data to accurately predict the target confidence level for the target period, ensuring that the confidence level assessment results are consistent with the long-term operating patterns of the energy storage system, are true and reliable, and effectively improve the accuracy and operating stability of the dehumidification control of the energy storage system.

[0158] Figure 7 A flowchart illustrating another dehumidification control method for an energy storage system provided in an embodiment of this disclosure is shown. Figure 7 As shown, in some embodiments, the energy storage system dehumidification control method of this disclosure further includes: S214. Based on the real-time operating data of the energy storage system, dynamically adjust the operating parameters of the dehumidifier.

[0159] In some embodiments, real-time operating data may include charge / discharge change plans and / or real-time relative humidity. The aforementioned dynamic adjustment of the dehumidifier's operating parameters includes, but is not limited to, the dehumidifier's operating status and dehumidification power. This disclosure, through monitoring real-time operating data during the dehumidification process, achieves real-time monitoring and dynamic parameter fine-tuning of the entire dehumidification process, improving the accuracy and economy of dehumidification control. Through control logic involving real-time monitoring and dynamic closed-loop adjustment throughout the entire process, it can accurately adapt to the continuous dynamic changes in temperature and humidity of the battery compartment and the equipment's operating status during dehumidification, improving the precision of dehumidification control in the energy storage system.

[0160] like Figure 8 As shown, in some embodiments, the real-time operating data includes a charge / discharge change plan; wherein, the above-mentioned S214 dynamically adjusts the operating parameters of the dehumidifier based on the real-time operating data of the energy storage system, including: S802, Obtain the charge / discharge change plan; S804. Based on the charge and discharge change plan, obtain the charge and discharge start-up time of the energy storage system after the change and the target confidence level after the change; S806. Adjust the dehumidifier's operating parameters according to the changed charge / discharge start-up time and target confidence level.

[0161] In some embodiments, the charge / discharge change plan may include advancing the plan, postponing the plan, or canceling the plan. Cancellation of the plan refers to canceling the current charge / discharge plan.

[0162] "Planning ahead of schedule" or "planning to postpone schedule" refers to advancing or delaying the start time of the charge / discharge cycle based on the current charge / discharge plan. For example, if the start time extracted from the current charge / discharge plan is 18:00; if the start time extracted from the modified charge / discharge plan is 17:30, then the plan will be advanced by 30 minutes; if the start time extracted from the modified charge / discharge plan is 18:15, then the plan will be postponed by 15 minutes.

[0163] The revised charge / discharge start time can be directly extracted from the charge / discharge change plan. The charge / discharge change plan is a defined plan, with the first plan coefficient remaining unchanged. Based on the charge / discharge change plan and historical charge / discharge plan execution data, the second plan coefficient is re-determined. The product of the first plan coefficient and the re-determined second plan coefficient is calculated to obtain the revised target confidence level. The calculation method for the revised target confidence level is similar to that in the aforementioned embodiments, and the similarities will not be repeated here.

[0164] Based on the changed charge / discharge start-up time and target confidence level, the changed target dehumidification operating parameters and dehumidification start-up time can be re-determined. The changed target dehumidification operating parameters, changed dehumidification start-up time and condensation temperature margin can be re-evaluated to see if they meet the preset dehumidification conditions, thereby controlling the operation of the dehumidifier.

[0165] In some embodiments, in response to an earlier-than-expected plan, the dehumidifier is immediately started and / or the dehumidification power is increased; in response to a delayed plan, the start-up of the dehumidifier is paused and / or the dehumidification power is reduced; in response to a cancelled plan, dehumidification of the energy storage system is stopped.

[0166] In this embodiment, when the charging and discharging plan changes, the dehumidification start time is recalculated, and the dehumidifier's operating status is adjusted accordingly. This disclosure can monitor the change events of the charging and discharging plan in real time. Once the plan parameters, running time, or start sequence is adjusted, it will actively link and recalculate the dehumidification duration and start time, and simultaneously correct the dehumidifier's start / stop status, running time, and operating parameters. It can dynamically iterate the dehumidification control logic in real time following the upper-level scheduling plan, effectively solving problems such as dehumidification timing misalignment, over-dehumidification, and under-dehumidification in the plan switching scenario. It avoids the occurrence of humidity control blind spots in the battery compartment during the transition period of operating condition changes, and ensures that the humidity of the battery compartment remains stable within the safe threshold range throughout the process, significantly improving the dynamic response capability and operating condition adaptability of the energy storage dehumidification control system.

[0167] like Figure 9 As shown, in some embodiments, real-time operating data includes real-time relative humidity; the above-described S214 dynamically adjusts the dehumidifier's operating parameters based on the real-time operating data of the energy storage system, including: S902. During the operation of the dehumidifier with the target dehumidification parameters, calculate the humidity decrease rate based on the real-time relative humidity, initial relative humidity, and dehumidification duration. S904. In response to the humidity decrease rate being less than a preset rate threshold, the dehumidification power of the dehumidifier is increased.

[0168] Real-time relative humidity can be collected by temperature and humidity sensors and uploaded to EMS; dehumidification duration is the time from the start of dehumidifier operation based on target dehumidification parameters to the current moment.

[0169] Calculate the difference between the initial relative humidity and the real-time relative humidity to obtain the humidity difference. Calculate the ratio of the humidity difference to the dehumidification time to obtain the humidity decrease rate. For example, if the initial relative humidity is 80%RH, the real-time relative humidity is 50%RH, and the dehumidification time is 20 minutes, the humidity decrease rate is 15%RH / min.

[0170] The preset rate threshold can be pre-configured in the EMS. The preset rate threshold can be a fixed value or a range of values. The value of the preset rate threshold can be determined according to actual needs. For example, the preset rate threshold is 10%RH / min.

[0171] When the rate of humidity decrease is less than the preset rate threshold, the dehumidification power of the dehumidifier can be increased. For example, if the target dehumidification operating condition parameter is a dehumidification power of 90%, when the rate of humidity decrease is less than the preset rate threshold, the dehumidification power of the dehumidifier can be increased to 100%.

[0172] In some embodiments, the dehumidification power of the dehumidifier is reduced in response to a humidity decrease rate exceeding a preset upper limit. When the humidity decrease rate exceeds 30%RH / min, the dehumidification power of the dehumidifier is reduced, for example, from 90% to 50%.

[0173] In this embodiment of the disclosure, during the dehumidification process, real-time relative humidity is monitored to achieve real-time monitoring of the entire dehumidification process and dynamic parameter fine-tuning, thereby improving the accuracy and economy of dehumidification control.

[0174] In some embodiments, after calculating the dew point temperature of the energy storage system, the method further includes: obtaining the current liquid cooling water supply temperature, calculating the current condensation temperature margin based on the current liquid cooling water supply temperature and the dew point temperature; if the current condensation temperature margin is less than or equal to a preset safety threshold, generating a control command, the control command being used to control the start of the dehumidifier; if the current condensation temperature margin is greater than the preset safety threshold, performing the step of obtaining the charging and discharging start-up time and target confidence level based on the operating status characteristic information of the energy storage system.

[0175] When the current condensation temperature margin is less than or equal to the preset safety threshold, dehumidification is started directly to effectively ensure the anti-condensation effect of the energy storage system; when the current condensation temperature margin is greater than the preset safety threshold, the pre-dehumidification process is initiated, thereby reducing the relative humidity in the battery compartment to a safe level before charging and discharging and / or before the liquid cooling system is started, fundamentally blocking the conditions for condensation formation and significantly improving the environmental adaptability and operational safety of the energy storage system.

[0176] To deepen the understanding of the dehumidification control method for the energy storage system disclosed in this paper, the following will be combined with... Figure 10 Please provide an explanation.

[0177] like Figure 10 As shown, a dehumidification control method for an energy storage system includes the following steps: S1001, Real-time monitoring of the initial ambient temperature, initial relative humidity and liquid cooling water supply temperature of the liquid cooling system inside the battery compartment; S1002. Calculate the dew point temperature and the current condensation temperature margin. The dew point temperature is calculated based on the initial ambient temperature and initial relative humidity using a preset dew point temperature calculation formula. The current condensation temperature margin is the difference between the liquid cooling water supply temperature and the dew point temperature. It should be noted that the dehumidifier is started when the current condensation temperature margin is less than or equal to the preset safety threshold; S1003 is executed when the current condensation temperature margin is greater than the preset safety threshold.

[0178] S1003. Determine if there is a charging / discharging plan. If yes, proceed to S1004; otherwise, proceed to S1005. S1004. Obtain the current charging / discharging plan from the EMS or scheduling system, and extract the charging / discharging start time; S1005. Predict the charging / discharging start-up time based on historical operating data; S1006, Output charging / discharging start time and target confidence level; S1007. Determine the target dehumidification operating parameters based on the target confidence level; S1008. Determine if the target confidence level is ≥50%. If not, proceed to S1009; if yes, proceed to S1010. S1009, Dehumidification not triggered, continue monitoring, return to S1001; S1010. Based on the preset temperature response model, predict the liquid cooling water supply temperature at different times, and calculate the condensation temperature margin and the critical moment of risk. S1011. Determine the required dehumidification time based on the preset dehumidification efficiency model and the target relative humidity; S1012. Calculate the dehumidification start time; the dehumidification start time can be calculated according to formula 7, formula 8, or formula 9. S1013. Determine whether the preset dehumidification conditions are met; if not, proceed to S1014; if yes, proceed to S1015. The preset dehumidification conditions include: the condensation temperature margin is less than the preset safety threshold and the dehumidification start time has been reached and the target confidence level is greater than the preset confidence level threshold; or, the risk critical moment has been reached and the dehumidification start time has been reached and the target confidence level is greater than the preset confidence level threshold; wherein, the risk critical moment is the moment when the condensation temperature margin is less than the preset safety threshold. S1014. Continuously monitor, wait for timing conditions, and return to S1001; S1015, Dynamic adjustment and real-time correction, responding to changes in charge and discharge plans, and real-time relative humidity correction; S1006 Output control command to end dehumidification. This control command is output when the real-time relative humidity is less than or equal to the target relative humidity.

[0179] Based on the same inventive concept, this disclosure also provides a dehumidification control device for an energy storage system, as shown in the following embodiment. Since the principle by which this device solves the problem is similar to that of the method embodiment described above, the implementation of this device embodiment can refer to the implementation of the method embodiment described above, and repeated details will not be elaborated further.

[0180] Figure 11 This diagram illustrates the structure of a dehumidification control device for an energy storage system according to an embodiment of this disclosure. Figure 11 As shown, in one embodiment, the device includes a first determining module 1110, a second determining module 1120, a surplus calculation module 1130, a third determining module 1140, a fourth determining module 1150, and a dehumidification control module 1160.

[0181] The first determining module 1110 is configured to acquire the initial ambient temperature and initial relative humidity inside the battery compartment of the energy storage system, and calculate the dew point temperature of the energy storage system based on the initial ambient temperature and initial relative humidity. The second determining module 1120 is configured to obtain the charging and discharging start-up time and target confidence level based on the operating status characteristic information of the energy storage system, and determine the target dehumidification operating condition parameters based on the target confidence level. The margin calculation module 1130 is configured to predict the liquid cooling water supply temperature of the liquid cooling system at different times based on the current liquid cooling standby temperature and the target liquid cooling operating temperature, according to the preset temperature response model; and calculate the condensation temperature margin based on the liquid cooling water supply temperature and the dew point temperature. The third determining module 1140 is configured to determine the required dehumidification time based on a preset dehumidification efficiency model, according to the initial ambient temperature, initial relative humidity, and target relative humidity. The fourth determining module 1150 is configured to determine the dehumidification start time based on the charging / discharging start time and the required dehumidification duration; The dehumidification control module 1160 is configured to control the operation of the dehumidifier based on the target dehumidification operating condition parameters in response to the satisfaction of preset dehumidification conditions.

[0182] In some embodiments, the operating status characteristic information includes the current charge and discharge plan and historical charge and discharge plan execution data of the energy storage system; the second determining module 1120 is configured to extract the charge and discharge start time from the current charge and discharge plan; determine a first plan coefficient according to the type of the current charge and discharge plan; determine a second plan coefficient according to the historical charge and discharge plan execution data; and determine a target confidence level according to the first plan coefficient and the second plan coefficient.

[0183] In some embodiments, the second determining module 1120 is configured to determine a first planning coefficient as a first coefficient value in response to the current charging and discharging plan being a defined plan; and to determine a second planning coefficient as a second coefficient value in response to the current charging and discharging plan being a preliminary plan, wherein the second coefficient value is less than the first coefficient value.

[0184] In some embodiments, historical charge-discharge plan execution data includes the total number of scheduling times and the actual number of execution times of the charge-discharge plan; the second determining module 1120 is configured to calculate the ratio of the actual number of execution times to the total number of scheduling times as a second plan coefficient.

[0185] In some embodiments, the operating status characteristic information includes historical operating data of the energy storage system; the second determining module 1120 is configured to determine the target confidence level of the energy storage system in the target time period based on the historical operating data, and take the start time of the target time period as the charging and discharging start time.

[0186] In some embodiments, historical operating data includes the charge / discharge start-up status and corresponding charge / discharge modes of the energy storage system at different times on different days within a historical time interval; the second determining module 1120 is configured to determine the number of charge / discharge start-up days and the total number of statistical days in the target period based on the charge / discharge start-up status of the energy storage system at different times on different days within a historical time interval; calculate the charge / discharge start-up probability of the energy storage system in the target period based on the number of charge / discharge start-up days and the total number of statistical days; determine a third coefficient based on the charge / discharge mode of the energy storage system in the target period; calculate the standard deviation based on the charge / discharge start-up time within the total number of statistical days, and determine a fourth coefficient based on the standard deviation; and determine the target confidence level of the energy storage system in the target period based on the charge / discharge start-up probability, the third coefficient, and the fourth coefficient.

[0187] In some embodiments, the second determining module 1120 is configured to determine the target dehumidification operating condition parameters corresponding to the target confidence interval based on the target confidence interval to which the target confidence level belongs, wherein the target confidence interval is one of a plurality of preset confidence intervals, and a preset confidence interval corresponds to a set of dehumidification operating condition parameters.

[0188] It should be noted that the formula for the preset temperature response model is as follows: ; in, The temperature of the liquid cooling water supply at time t after the liquid cooling system is started; This refers to the liquid cooling operating temperature of the liquid cooling system. This refers to the liquid cooling standby temperature of the liquid cooling system. Let t be the temperature response time constant of the liquid cooling system, and t be the time after the liquid cooling system starts up.

[0189] It should be noted that the formula for the preset dehumidification efficiency model is as follows: ; in, This represents the rate of change in relative humidity. This refers to the rated dehumidification capacity of the dehumidifier. The system efficiency coefficient, taking a value between 0.4 and 0.7; This is the environmental correction factor, derived from the temperature correction factor. Humidity correction factor Sure; The volume of the battery compartment; ambient temperature The saturated water vapor density at that point; Among them, temperature correction coefficient Determined by the following formula: ; Humidity correction factor Determined by the following formula: .

[0190] In some embodiments, the third determining module 1140 is configured to calculate the difference between the charge / discharge start time and the dehumidification time required, as the dehumidification start time.

[0191] In some embodiments, the third determining module 1140 is configured to acquire the liquid cooling pre-start time; determine the liquid cooling start time based on the charge / discharge start time and the liquid cooling pre-start time; and calculate the difference between the liquid cooling start time and the dehumidification time required as the dehumidification start time.

[0192] In some embodiments, the third determining module 1140 is configured to determine a buffer time and adjust the dehumidification start time based on the buffer time.

[0193] In some embodiments, satisfying the preset dehumidification conditions includes: the condensation temperature margin is less than a preset safety threshold and the dehumidification start time has been reached and the target confidence level is greater than a preset confidence threshold; or, the risk critical moment has been reached and the dehumidification start time has been reached and the target confidence level is greater than a preset confidence threshold; wherein, the risk critical moment is the moment corresponding to the condensation temperature margin being less than the preset safety threshold.

[0194] In some embodiments, the device further includes a dehumidification adjustment module (not shown in the figures), which is configured to dynamically adjust the operating parameters of the dehumidifier based on real-time operating data of the energy storage system while the dehumidifier is operating at the target dehumidification operating parameters.

[0195] In some embodiments, the real-time operating data includes a charge / discharge change plan; the dehumidification adjustment module is configured to acquire the charge / discharge change plan; based on the charge / discharge change plan, obtain the changed charge / discharge start-up time and the changed target confidence level of the energy storage system; and adjust the operating parameters of the dehumidifier based on the changed charge / discharge start-up time and target confidence level.

[0196] In some embodiments, the real-time operating data includes real-time relative humidity; the dehumidification adjustment module is configured to calculate the humidity decrease rate based on the real-time relative humidity, the initial relative humidity, and the dehumidification duration; and to control the dehumidification power of the dehumidifier to be increased in response to the humidity decrease rate being less than a preset rate threshold.

[0197] In some embodiments, the first determining module 1110 is configured to determine the dew point temperature based on a preset dew point temperature formula, according to the initial ambient temperature and the initial relative humidity.

[0198] In this embodiment, the charging / discharging start-up time is determined by the operating status characteristic information of the energy storage system, and the required dehumidification time is determined based on a preset dehumidification efficiency model. Based on the charging / discharging start-up time and the required dehumidification time, the dehumidification start-up time can be accurately determined, avoiding passive response lag. The temperature response curve after the liquid cooling system starts is simulated based on a preset temperature response model, and the dynamic evolution trend of the condensation temperature margin is tracked in real time, providing a quantitative basis for anti-condensation decisions. The target dehumidification operating parameters are determined based on the target confidence level, enabling fine control of the dehumidifier's operating time, operating time, and operating power. This effectively reduces the risk of condensation while significantly reducing unnecessary energy consumption and extending the dehumidifier's service life. By comprehensively considering whether the condensation temperature margin, target confidence level, and dehumidification start-up time meet the preset dehumidification conditions, the relative humidity in the battery compartment can be reduced to a safe level before the liquid cooling system starts, fundamentally blocking the conditions for condensation formation and significantly improving the environmental adaptability and operational safety of the energy storage system.

[0199] It should be noted that all relevant content in each scenario designed in the above method embodiments can be referenced from the functional description of the corresponding functional module, and will not be repeated here.

[0200] Those skilled in the art will understand that various aspects of this disclosure can be implemented as a system, method, or program product. Therefore, various aspects of this disclosure can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software aspects, collectively referred to herein as a "circuit," "module," or "system."

[0201] The following reference Figure 12 To describe an electronic device 1200 according to such an embodiment of the present disclosure. Figure 12 The electronic device 1200 shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments disclosed herein.

[0202] In one embodiment, the electronic device 1200 includes a processor and a memory for storing executable instructions of the processor, wherein the processor is configured to perform the above-described energy storage system dehumidification control method by executing the executable instructions.

[0203] like Figure 12 As shown, the electronic device 1200 is manifested in the form of a general-purpose computing device. The components of the electronic device 1200 may include, but are not limited to: at least one processing unit 1210, at least one storage unit 1220, and a bus 1230 connecting different system components (including storage unit 1220 and processing unit 1210).

[0204] The storage unit stores program code, which can be executed by the processing unit 1210, causing the processing unit 1210 to perform the steps described in the "Exemplary Methods" section above according to various exemplary embodiments of this disclosure. For example, the processing unit 1210 can execute the following steps of the above method embodiment: obtain the initial ambient temperature and initial relative humidity inside the battery compartment of the energy storage system, and calculate the dew point temperature of the energy storage system based on the initial ambient temperature and initial relative humidity; obtain the charge / discharge start-up time and target confidence level based on the operating status characteristic information of the energy storage system, and determine the target dehumidification operating condition parameters based on the target confidence level; predict the liquid cooling water supply temperature of the liquid cooling system at different times based on the current liquid cooling standby temperature and the target liquid cooling operating temperature based on the preset temperature response model; calculate the condensation temperature margin based on the liquid cooling water supply temperature and the dew point temperature; determine the dehumidification time required based on the initial ambient temperature, initial relative humidity and target relative humidity based on the preset dehumidification efficiency model; determine the dehumidification start-up time based on the charge / discharge start-up time and the dehumidification time required; and control the dehumidifier to operate based on the target dehumidification operating condition parameters in response to meeting the preset dehumidification conditions.

[0205] Storage unit 1220 may include readable media in the form of volatile storage units, such as random access memory (RAM) 12201 and / or cache memory 12202, and may further include read-only memory (ROM) 12203.

[0206] Storage unit 1220 may also include a program / utility 12204 having a set (at least one) of program modules 12205, such program modules 12205 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0207] Bus 1230 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0208] Electronic device 1200 can also communicate with one or more external devices 1240 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with the electronic device 1200, and / or with any device that enables the electronic device 1200 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 1250. Furthermore, electronic device 1200 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 1260. Figure 12 As shown, network adapter 1260 communicates with other modules of electronic device 1200 via bus 1230. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with electronic device 1200, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0209] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0210] In particular, according to embodiments of the present disclosure, the processes described above with reference to the flowcharts can be implemented as a computer program product, which includes a computer program that, when executed by a processor, implements the steps described in the "Exemplary Methods" section above according to various exemplary implementations of the present disclosure.

[0211] In exemplary embodiments of this disclosure, a computer-readable storage medium is also provided, having a computer program stored thereon that, when executed by a processor, implements the steps described in the "Exemplary Methods" section above according to various exemplary embodiments of this disclosure. This computer-readable storage medium may be a readable signal medium or a readable storage medium.

[0212] In some possible implementations, various aspects of this disclosure can also be implemented as a program product comprising a computer program that, when executed by a processor, implements the equalization control method of any of the above embodiments. In one possible embodiment, the program product includes program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps described in the "Exemplary Methods" section of this specification according to various exemplary embodiments of this disclosure.

[0213] More specific examples of computer-readable storage media in this disclosure may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0214] In this disclosure, a computer-readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of transmitting, propagating, or transmitting a program for use by or in connection with an instruction execution system, apparatus, or device.

[0215] Optionally, the program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0216] In practice, program code for performing the operations of this disclosure can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0217] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0218] Furthermore, although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0219] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, mobile terminal, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0220] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the appended claims.

Claims

1. A dehumidification control method for an energy storage system, characterized in that, include: The initial ambient temperature and initial relative humidity inside the battery compartment of the energy storage system are obtained, and the dew point temperature of the energy storage system is calculated based on the initial ambient temperature and the initial relative humidity. Based on the operating status characteristic information of the energy storage system, the charging and discharging start-up time and target confidence level are obtained, and the target dehumidification operating condition parameters are determined based on the target confidence level. Based on the preset temperature response model, the liquid cooling water supply temperature of the liquid cooling system at different times is predicted according to the current liquid cooling standby temperature and the target liquid cooling operating temperature. And calculate the condensation temperature margin based on the liquid cooling water supply temperature and the dew point temperature; Based on a preset dehumidification efficiency model, the required dehumidification time is determined according to the initial ambient temperature, the initial relative humidity, and the target relative humidity. The dehumidification start time is determined based on the charging / discharging start time and the dehumidification duration required. In response to meeting the preset dehumidification conditions, the dehumidifier is controlled to operate based on the target dehumidification operating parameters to achieve pre-dehumidification.

2. The method according to claim 1, characterized in that, The operational status characteristic information includes the current charging and discharging plan and historical charging and discharging plan execution data of the energy storage system; The step of obtaining the charging / discharging start-up time and target confidence level based on the operating state characteristic information of the energy storage system includes: Extract the charge / discharge start time from the current charge / discharge plan; Determine the first plan coefficient based on the type of the current charge / discharge plan; The second plan coefficient is determined based on the historical charge / discharge plan execution data. The target confidence level is determined based on the first planning coefficient and the second planning coefficient.

3. The method according to claim 2, characterized in that, The step of determining the first plan coefficient based on the type of the current charge / discharge plan includes: In response to the fact that the current charge / discharge plan is a defined plan, the first plan coefficient is determined to be a first coefficient value; In response to the fact that the current charge / discharge plan is a preliminary plan, the first plan coefficient is determined to be a second coefficient value, and the second coefficient value is less than the first coefficient value.

4. The method according to claim 2, characterized in that, The historical charge / discharge plan execution data includes the total number of scheduling times and the actual number of execution times for the charge / discharge plan; The step of determining the second plan coefficient based on the historical charge-discharge plan execution data includes: The ratio of the actual number of executions to the total number of schedulings is calculated and used as the second planning coefficient.

5. The method according to claim 1 or 2, characterized in that, The operational status characteristic information includes the historical operational data of the energy storage system; The step of obtaining the charging / discharging start-up time and target confidence level based on the operating state characteristic information of the energy storage system includes: Based on the historical operating data, the target confidence level of the energy storage system in the target time period is determined, and the start time of the target time period is taken as the charging and discharging start time.

6. The method according to claim 5, characterized in that, The historical operating data includes the charging and discharging start-up status of the energy storage system on different days and at different times within a historical time interval, and the corresponding charging and discharging modes. Determining the target confidence level of the energy storage system for a target time period based on the historical operating data includes: Based on the charging and discharging start-up status of the energy storage system at different times of different days within a historical time interval, determine the number of charging and discharging start-up days and the total number of statistical days in the target period. Based on the number of charge / discharge start-up days and the total number of statistical days, calculate the charge / discharge start-up probability of the energy storage system during the target time period. The third coefficient is determined based on the charging and discharging mode of the energy storage system during the target time period; Calculate the standard deviation based on the charging and discharging start times within the total statistical days, and determine the fourth coefficient based on the standard deviation; The target confidence level of the energy storage system during the target time period is determined based on the charge / discharge start probability, the third coefficient, and the fourth coefficient.

7. The method according to claim 1, characterized in that, The step of determining the target dehumidification operating parameters based on the target confidence level includes: Based on the target confidence interval to which the target confidence level belongs, the target dehumidification operating condition parameters corresponding to the target confidence interval are determined, wherein the target confidence interval is one of a plurality of preset confidence intervals, and one preset confidence interval corresponds to a set of dehumidification operating condition parameters.

8. The method according to claim 1, characterized in that, The formula for the preset temperature response model is as follows: ； in, The temperature of the liquid cooling water supply at time t after the liquid cooling system is started; This refers to the liquid cooling operating temperature of the liquid cooling system. This refers to the liquid cooling standby temperature of the liquid cooling system. Let t be the temperature response time constant of the liquid cooling system, and t be the time after the liquid cooling system starts up.

9. The method according to claim 1, characterized in that, The formula for the preset dehumidification efficiency model is as follows: ； in, This represents the rate of change in relative humidity. This refers to the rated dehumidification capacity of the dehumidifier. The system efficiency coefficient, ranging from 0.4 to 0.7; This is the environmental correction factor, derived from the temperature correction factor. Humidity correction factor Sure; The volume of the battery compartment; For ambient temperature The saturated water vapor density at that point; Among them, temperature correction coefficient Determined by the following formula: ； Humidity correction factor Determined by the following formula: 。 10. The method according to claim 1, characterized in that, The step of determining the dehumidification start time based on the charging / discharging start time and the required dehumidification duration includes: The difference between the charging / discharging start time and the dehumidification time required is calculated and used as the dehumidification start time.

11. The method according to claim 1, characterized in that, The step of determining the dehumidification start time based on the charging / discharging start time and the required dehumidification duration includes: Obtain the liquid cooling pre-start time; The liquid cooling start time is determined based on the charge / discharge start time and the liquid cooling pre-start time; The difference between the liquid cooling start-up time and the dehumidification time required is calculated and used as the dehumidification start-up time.

12. The method according to claim 10 or 11, characterized in that, The dehumidification start time is determined based on the charging / discharging start time and the required dehumidification duration, including: Determine the buffer time, and adjust the dehumidification start time accordingly.

13. The method according to claim 1, characterized in that, The conditions for satisfying the preset dehumidification include: The condensation temperature margin is less than the preset safety threshold, the dehumidification start time has been reached, and the target confidence level is greater than the preset confidence threshold. Alternatively, the critical risk moment has been reached and the dehumidification start-up moment has been reached, and the target confidence level is greater than the preset confidence threshold. The critical moment of risk is the moment when the condensation temperature margin is less than the preset safety threshold.

14. The method according to claim 1, characterized in that, The method further includes: The operating parameters of the dehumidifier are dynamically adjusted based on the real-time operating data of the energy storage system.

15. The method according to claim 14, characterized in that, The real-time operating data includes charge / discharge change plans; The step of dynamically adjusting the dehumidifier's operating parameters based on the real-time operating data of the energy storage system includes: Obtain the charge / discharge change plan; Based on the charge and discharge change plan, the changed charge and discharge start-up time and the changed target confidence level of the energy storage system are obtained; The operating parameters of the dehumidifier are adjusted according to the changed charge / discharge start-up time and target confidence level.

16. The method according to claim 14, characterized in that, The real-time operating data includes real-time relative humidity; The step of dynamically adjusting the dehumidifier's operating parameters based on the real-time operating data of the energy storage system includes: During the operation of the dehumidifier with the target dehumidification parameters, the humidity decrease rate is calculated based on the real-time relative humidity, the initial relative humidity, and the dehumidification duration. In response to the humidity decrease rate being less than a preset rate threshold, the dehumidification power of the dehumidifier is controlled to be increased.

17. The method according to claim 1, characterized in that, The step of calculating the dew point temperature of the energy storage system based on the initial ambient temperature and the initial relative humidity includes: Based on a preset dew point temperature formula, the dew point temperature is determined according to the initial ambient temperature and the initial relative humidity.

18. A dehumidification control device for an energy storage system, characterized in that, include: The first determining module is configured to acquire the initial ambient temperature and initial relative humidity inside the battery compartment of the energy storage system, and calculate the dew point temperature of the energy storage system based on the initial ambient temperature and the initial relative humidity. The second determining module is configured to obtain the charging and discharging start-up time and target confidence level based on the operating status characteristic information of the energy storage system, and determine the target dehumidification operating condition parameters based on the target confidence level. The margin calculation module is configured to predict the liquid cooling water supply temperature of the liquid cooling system at different times based on the preset temperature response model, according to the current liquid cooling standby temperature and the target liquid cooling operating temperature. And calculate the condensation temperature margin based on the liquid cooling water supply temperature and the dew point temperature; The third determining module is configured to determine the required dehumidification time based on a preset dehumidification efficiency model, according to the initial ambient temperature, the initial relative humidity, and the target relative humidity. The fourth determining module is configured to determine the dehumidification start time based on the charging / discharging start time and the dehumidification duration required. The dehumidification control module is configured to control the dehumidifier to operate based on the target dehumidification operating condition parameters in response to the condensation temperature margin and the dehumidification start time meeting the preset dehumidification conditions, so as to achieve pre-dehumidification.

19. An electronic device, characterized in that, It includes a processor and a memory, the memory storing a computer program that, when executed by the processor, implements the dehumidification control method for an energy storage system as described in any one of claims 1-17.

20. A computer-readable storage medium, characterized in that, It stores a computer program, which, when executed by a processor, implements the dehumidification control method for the energy storage system according to any one of claims 1-17.

Images