Thermal management method and system of energy storage system and storage medium

Abstract

The invention relates to the technical field of energy storage, in particular to a thermal management method and system of an energy storage system and a storage medium. The thermal management method of the energy storage system comprises the following steps: predicting the operation state of management equipment, obtaining operation state data of the management equipment in a preset period, and constructing a charging operation state number axis table and a discharging operation state number axis table; and constructing a temperature operation curve of the energy storage system. And correcting to obtain a corrected curve. And judging whether the correction curve exceeds a preset early warning threshold value or not. And judging whether the phase difference time end is less than a preset time length or not, and radiating by using the most economical cooling equipment. Through the method, heat dissipation of the energy storage system can be estimated, so that heat management can be carried out in advance, preparation and cooling time is provided for heat management, cooling is carried out through optimal cooling equipment, cooling energy can be saved to the maximum extent, the energy utilization rate is increased, energy waste is avoided, and the management cost is reduced.

Description

Technical Field

[0001] The present invention relates to the field of energy storage technology, and in particular to a thermal management method, system and storage medium for an energy storage system. Background Art

[0002] Energy storage system is a technology and device that stores energy for future use. This system usually consists of energy storage units, controllers and energy management systems, and can store and release electrical energy in different ways, such as batteries, compressed air, liquid fuels, flywheels, supercapacitors, etc.

[0003] The advantage of energy storage systems is that they can provide functions such as fast start-up, peak load regulation, smooth output, and reduce the volatility of renewable energy. These functions make energy storage systems an important solution that can help power companies manage power grids, reduce dependence on fossil fuels, reduce carbon emissions, and improve energy efficiency.

[0004] At present, there are many kinds of energy storage systems on the market, each with its own advantages and disadvantages. The specific system to choose depends on the specific application scenario and requirements. Some common energy storage systems include lead-acid batteries, lithium-ion batteries, flow batteries, fuel cells, etc.

[0005] Thermal management of energy storage systems is one of the key factors to ensure safe and reliable operation of energy storage systems. If the heat accumulated in the energy storage system cannot be effectively dissipated, it may cause serious consequences such as battery damage, performance degradation, and even fire. The following are several common thermal management technologies: 1. Natural cooling: Use ambient temperature to naturally cool the energy storage system. This is the simplest and most economical method, but it is only suitable for low power density batteries. 2. Forced air cooling: Dissipate heat by forced circulating air flow. This method is suitable for high power density batteries. 3. Water cooling: A system that uses water as a coolant to dissipate heat. This method can provide higher heat dissipation efficiency, but it requires additional energy to heat the water. 4. Phase change material: Use phase change materials (such as organic compounds) to achieve thermal management. This method can provide efficient heat dissipation, but the cost is high. 5. Thermal runaway monitoring: Monitor the heat accumulation in the energy storage system and take measures to prevent overheating when necessary. In summary, different energy storage systems have different thermal management requirements, and appropriate thermal management technologies need to be selected according to actual conditions. At the same time, effective thermal management can also extend the life of the energy storage system and improve its reliability and safety.

[0006] The thermal management of existing energy storage systems directly controls cooling and heat dissipation through temperature detection. At this time, there is no evaluation of the temperature development trend, which can easily cause damage to the energy storage system and waste energy. Summary of the invention

[0007] In order to solve the above technical problems, the present invention provides a thermal management method for an energy storage system, which is used to predict the heat of the energy storage system and perform planned management. The thermal management method for the energy storage system may include: S1. Predict the operating status of the management device, obtain the operating status data of the management device within a preset cycle, and construct a charging operating status digital axis table and a discharging operating status digital axis table based on the operating status data. The management device here is an electrical device connected to the energy storage system and can affect the working status of the energy storage system. It also includes a charging module connected to the energy storage system. In general, we can predict the operating status of each device in a short time based on the operating rules of the electrical equipment connected to the energy storage system. A preset cycle needs to be determined according to the specific time, and the specific needs are based on the heat release delay time of the energy storage system. Of course, other numerical settings are not excluded. The operating status data includes the operating time point of each management device, the operating status at each time point, the operating power and the end time point, etc., so as to obtain the operating status of each management device corresponding to each time point starting from the current time point, etc. The operating status here includes not only power consumption, but also status data that can affect heat dissipation, which will not be described in detail here. The operating status axis table can be a time axis, the length of the axis is a preset period, the unit of the operating status axis table is a unit time point within the preset period, and the operating status within the preset period needs to be implanted into the axis according to the corresponding time point, so that the operating status axis table can be obtained.

[0008] S2. Construct the temperature operation curve of the energy storage system according to the charging operation state axis table and the discharging operation state axis table. The operation state data includes the operation time point of each management device, the operation state at each time point, the operation power and the end time point, etc. The operation state includes the name of each management device and its corresponding operation parameters. The use state of the energy storage system can be obtained according to the various operation parameters corresponding to each different management device.

[0009] S3. Correct the temperature operation curve of the energy storage system and obtain the correction curve. As time goes by, the absolute time point where the origin of the horizontal coordinate of the temperature operation curve of the energy storage system is located is constantly changing. The vertical coordinates corresponding to the temperature operation curve of the energy storage system are all obtained by prediction and calculation, but the endpoint values ​​of the temperature operation curve of the energy storage system can be obtained through detection, which provides the possibility and convenience for correction. Its predicted charge and discharge operation state axis table may change, and the parameters of the energy storage system may also change with changes in temperature and some operating conditions. The predicted charge and discharge operation state axis table may change and can be corrected through real-time calculation, but some parameter changes of the energy storage system cannot be reflected in the predicted operation state axis table, so it is necessary to correct the double error of the operation curve.

[0010] S4. Determine whether the correction curve exceeds a preset warning threshold T 标 If yes, a first-level alarm is issued and S5 is executed. If no, no first-level alarm is issued. The preset warning threshold T 标 It can be set according to the actual situation. It is a horizontal straight line in the coordinate system. When the correction curve exceeds the warning threshold, the two lines intersect.

[0011] S5. Mark the horizontal coordinate of the intersection point as i, and then determine whether i is less than a preset time length i 标 If yes, a second-level alarm is issued and S6 is executed. If no, no second-level alarm is issued. Where i is the time period between the intersection point and the current time point. The preset time length i 标 It can be determined according to the heat dissipation capacity of the heat dissipation device of the energy storage system. S6: Determine whether the correction curve fits the cooling device numbered h to the cooling device and exceeds the preset warning threshold value T 标 , h is the cooling device number of the energy storage system, h=1, 2, ..., H; if yes, select the cooling device numbered h for cooling, if no, execute S7; S7, determine whether the correction curve fits the cooling device numbered h+1 to a curve exceeding a preset warning threshold value T 标 , and then perform analogy calculations. If the correction curve still exceeds the preset warning threshold T for the cooling device numbered H, 标 , then cool down according to the cooling equipment numbered H.

[0012] Preferably: the method for constructing the temperature operation curve of the energy storage system may include: constructing a plane coordinate system, the horizontal axis of the plane coordinate system is a preset period, and the vertical axis is a temperature value, and then calculating the heat dissipation temperature value T of the energy storage system corresponding to each time point in the preset period through an operating state axis table, and then implanting the heat dissipation temperature value T of the energy storage system into the plane coordinate system according to the time point to obtain each heat dissipation temperature value point, and connecting each heat dissipation temperature value point in sequence, so as to obtain the temperature operation curve of the energy storage system.

[0013] Preferably: the heat dissipation temperature value T of the energy storage system is a predicted temperature value in the energy storage system, and its value can be calculated according to the charging operation state axis table and the discharging operation state axis table. , where R is the discharge internal resistance of the energy storage system, R' is the charging internal resistance of the energy storage system, and its specific value can be obtained by testing the charging and discharging state of the energy storage system or by the energy storage system, j is the number of each management device in the discharge operation state axis table at the predicted time point, and J is the total number of discharge management devices at the predicted time point, j=1, 2, ..., J; I j is the operating current of the discharge management device numbered j, IJ 0 is the additional current when J discharge management devices are running. k is the number of each charge management device in the charge operation state axis table at the predicted time point, K is the total number of charge management devices at the predicted time point, k=1, 2, ..., K; I k is the operating current of the charging management device numbered k, I K 1 is the additional current of K charging management devices, I K 1 It can be obtained through experimental detection. ε is the heat dissipation proportional factor, and its value is related to the heat dissipation performance of the energy storage system and the temperature difference. Its value is generally between 0.1-0.8, and can be obtained by checking the information table prepared in advance according to the experiment, and of course it can also be obtained by calculation. C is the average specific heat capacity of the energy storage system, and M is the effective mass of the energy storage system, which can be obtained by heating the energy storage system. S is the effective heat dissipation area of ​​the energy storage system, and its value can be obtained through the equipment parameters of the energy storage system, which will not be described in detail here. The heat dissipation temperature value calculated by this method can fully consider the heat dissipation state when the charging and discharging states are running at the same time, and take into account the heat generation of each current and the influence of the additional current. At the same time, through the influence of the heat dissipation efficiency, the evaluation is more comprehensive, in line with the actual heat dissipation of the energy storage system, and the calculation is accurate.

[0014] Preferably: the additional current I J 0 The obtaining method may include: obtaining the detection current I by detecting the energy storage system 总 , then the additional current of each discharge management device numbered j is Then, each discharge management device is made into a device-additional current compatibility information table, which includes each matching management device, parameter information and corresponding additional current. The additional current can be obtained by searching the compatibility information table through the name and parameter information of each management device.

[0015] Preferably: the method for obtaining the heat dissipation proportional factor ε may include: conducting experiments on the energy storage system in advance, calculating the heat dissipation proportional factor value according to different heat dissipation temperature differences ΔT, so as to obtain the heat dissipation proportional factor values ​​corresponding to different heat dissipation temperature differences ΔT, and then constructing a heat dissipation proportional curve, searching the heat dissipation proportional curve through the heat dissipation temperature difference ΔT, so as to obtain the heat dissipation proportional factor.

[0016] Preferred: Heat dissipation proportionality factor value , where Q is the theoretical calorific value of the energy storage system, and ΔT is the heat dissipation temperature difference, which can be the difference between the internal temperature of the energy storage system and the ambient temperature, and can be obtained through detection.

[0017] Preferred: Specific theoretical calorific value , where Q' is the power consumption of the energy storage system, and U is the operating voltage of the energy storage system.

[0018] Preferably: the method for constructing a heat dissipation proportion curve may include: constructing a plane coordinate system, the horizontal axis is the heat dissipation temperature difference, the vertical axis is the heat dissipation proportion factor, and then implanting the calculated heat dissipation proportion factor into the plane coordinate system according to the corresponding heat dissipation temperature difference, thereby obtaining the heat dissipation proportion point, and then connecting each heat dissipation proportion point in sequence to obtain the heat dissipation proportion curve.

[0019] Preferably, the method for correcting the temperature operation curve of the energy storage system may include: detecting the internal temperature value T' of the energy storage system, and calculating the heat dissipation temperature value T'' of the energy storage system according to the operation status data at the current time point, and translating the vertical coordinate of the end point of the temperature operation curve of the energy storage system from the heat dissipation temperature value T to T', and adjusting the vertical coordinate point value of the temperature operation curve of the energy storage system according to By scaling and correcting the ratio of the error, the correction curve can be obtained. This method can not only correct the error of the current operating state parameters, but also correct the error in the calculation, so that the two errors can be corrected in an all-round way, making the correction curve more accurate.

[0020] Preferably: the warning threshold ,in is the buffer factor, T 1 It is the tolerance temperature or upper limit temperature of the energy storage system. Its value is generally 0.8-0.95. Of course, other values ​​are not excluded. The smaller the buffer factor is, the better the protection of the energy storage system is. The larger the buffer space is, but the alarm frequency will increase, the cooling cost will be higher, and the management cost will increase. This setting method is a fixed value method and cannot be adjusted according to actual conditions.

[0021] Preferably: the preset warning threshold T 标 The calculation method may also include: calculating the tolerance temperature t of each electrical component in the energy storage system m , where m is the number of each electrical component or electrical material in the energy storage system, and the tolerance temperature t m It can be obtained based on the upper temperature limit of each electrical component or electrical material, and the details are not described here. , where M is the total number of electrical components or electrical materials in the energy storage system, m=1, 2, …, M; t m is the tolerable temperature of each electrical component or material in the energy storage system, δ m It is the weight ratio of the electrical component or electrical material electrical component numbered m. mIt is the heat dissipation ratio coefficient of the electrical component or electrical material numbered m. Its value can be obtained according to the structure of the energy storage system and the material of its peripheral structure. It can be obtained by calculation or experiment. The experimental process is not described here. The preset warning threshold calculated by this method can take into account the tolerance temperature of each electrical component or material, its weight ratio and its heat dissipation ratio coefficient. This calculation method is comprehensive and the calculation result is accurate.

[0022] Preferred: Heat dissipation proportionality coefficient , where n is the number of the electrical component or electrical material m, the number of the material outside the electrical component, and the numbering can be done from the inside to the outside, and the details are not repeated here. n is the thickness of the peripheral material numbered n, is the thermal conductivity of the peripheral material numbered n, S n The effective surface area of ​​the peripheral material numbered n can be obtained through the structure of the energy storage system, which will not be described in detail here. The specific value of the adjustment coefficient can be obtained through the structure of the energy storage system, and its value is generally 0.5-1, which will not be described in detail here. The preset warning threshold calculated by this method takes into account the structure of the energy storage system and the materials of its peripheral structure, and the evaluation is comprehensive and the calculation is accurate.

[0023] Preferably: the preset time length , where T 0 is the cooling target temperature of the energy storage system, which can be the standard operating temperature of the energy storage system, generally 20-50 degrees Celsius, and will not be described in detail here. h is the cooling equipment number of the energy storage system, h=1, 2, ...H; the energy storage system cooling equipment can include air cooling, air conditioning cooling, etc., and the sorting method can be sorted from low to high in terms of cooling capacity. Basically, the cooling capacity and cooling cost are positively correlated, and will not be described in detail here. θ h It is the heat dissipation capacity factor of the cooling device numbered h, which can be obtained by conducting experiments on the cooling capacity of each cooling device. These data are dimensionless data, and Max[] is the maximum value. The specific details are not repeated here. This method processes the temperature difference logarithmically, which can take into account the trend of temperature heat dissipation. The higher the temperature, the stronger the heat dissipation capacity. This calculation method can fully consider the heat dissipation characteristics, with high calculation accuracy and more in line with the actual heat dissipation situation.

[0024] Preferably: the method for obtaining the fitting curve of the cooling device numbered h by the correction curve may include: performing cooling fitting on each cooling device to obtain a cooling fitting curve, wherein the cooling fitting curve is a curve constructed with the cooling time as the ordinate and the lowered temperature as the ordinate, and different cooling fitting curves can be constructed for different starting temperatures and ambient temperatures, which will not be described in detail here. Then, the cooling fitting curve is implanted into the correction curve coordinate system, and the cooling fitting curve is subtracted from the correction curve, so that the cooling fitting curve can be obtained, and its specific numerical calculation will not be described in detail here.

[0025] The present invention further proposes a thermal management system for an energy storage system, which is used to predict the heat of the energy storage system and perform planned management. The thermal management system for the energy storage system may include: The equipment operation statistics module is used to predict the operating status of the management equipment, obtain the operating status data of the management equipment within a preset cycle, and construct a charging operating status axis table and a discharging operating status axis table based on the operating status data.

[0026] The energy storage system statistics module is used to construct a temperature operation curve of the energy storage system according to the charging operation state axis table and the discharging operation state axis table.

[0027] The operating curve correction module is used to correct the temperature operating curve of the energy storage system and obtain a correction curve.

[0028] The judgment analysis module is used to determine whether the correction curve exceeds a preset warning threshold T 标 If yes, a first-level alarm is issued, if no, no first-level alarm is issued. After receiving the first-level alarm, the horizontal coordinate of the intersection point is calibrated as i, and then it is determined whether i is less than a preset time length i 标 If yes, a second-level alarm is issued. If no, no second-level alarm is issued. It is determined whether the correction curve for the cooling device fitting curve numbered h exceeds the preset warning threshold T. 标 If yes, select the cooling device numbered h for cooling. If no, determine whether the correction curve fits the cooling device numbered h+1 to a curve that exceeds the preset warning threshold T. 标 , and then perform analogy calculations. If the correction curve still exceeds the preset warning threshold T for the cooling device numbered H, 标 , then cool down according to the cooling equipment numbered H.

[0029] As a preferred embodiment of the present invention, a computer readable storage medium stores a computer program. When the program is executed by a processor, the steps of the thermal management method of the energy storage system are implemented. When the thermal management method of the energy storage system is applied, it can be applied in the form of software, such as a program designed to be independently run on a computer readable storage medium. The computer readable storage medium can be a USB flash drive, designed as a USB shield, and the USB flash drive is designed to start the program of the entire method through an external trigger.

[0030] The technical effects and advantages of the present invention are as follows: Through this method, the heat dissipation of the energy storage system can be budgeted, so that heat management can be performed in advance, which provides preparation and cooling time for heat management, and cooling through the optimal cooling equipment can save cooling energy to the maximum extent, improve energy utilization, avoid energy waste, and reduce management costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 A schematic flow chart of the thermal management method for an energy storage system proposed in the present invention.

[0032] Figure 2 This is a schematic diagram of the structure of the thermal management system of the energy storage system proposed by the present invention. DETAILED DESCRIPTION

[0033] Embodiments of the present disclosure are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present disclosure, and are not to be construed as limitations of the present disclosure. On the contrary, the embodiments of the present disclosure include all changes, modifications, and equivalents that fall within the spirit and connotation of the appended claims.

[0034] Example 1 Reference Figure 1 In this embodiment, a thermal management method for an energy storage system is proposed, which is used to predict the heat of the energy storage system and perform planned management. The thermal management method for the energy storage system may include: S1. Predict the operating status of the management device, obtain the operating status data of the management device within a preset cycle, and construct a charging operating status digital axis table and a discharging operating status digital axis table based on the operating status data. The management device here is an electrical device connected to the energy storage system and capable of affecting the working status of the energy storage system, including electrical appliances connected to the energy storage system, such as lighting equipment, refrigeration equipment, motor units, etc., and also includes a charging module connected to the energy storage system. The charging module can be a charging device, a photovoltaic system or other power generation module, which will not be described in detail here. In general, we can predict the operating status of each device in a short time based on the operating rules of the electrical equipment connected to the energy storage system. For example, the energy storage system is an energy storage device for photovoltaic and wind power generation of street lamps. The amount of photovoltaic power generation can be obtained according to the light intensity and light angle of the day, and then the photovoltaic power generation power can be obtained according to the conversion. Then, the wind power generation power and the heat dissipation efficiency caused by wind power in the future period are obtained according to the current wind power generation equipment. The charging power of the energy storage system can be obtained by adding and converting the two. The street lamp does not discharge during the day. According to the usage rules of the street lamp, it can be obtained that the lighting is turned on at 5 pm, and the street lamp is 50w, so that the power of its discharge can be obtained. Of course, this is just a simple example and is not universal. Other situations are not described in detail here. A preset cycle needs to be determined according to the specific time, which can be 0.1min-60min, among which 1-10min is appropriate. The specific needs are based on the heat release delay time of the energy storage system, and of course other numerical settings are not excluded. In general, the predicted cycle time length is not large, and each management device can be predicted. The details are not described here. The operating status data includes the operating time point of each management device, the operating status at each time point, the operating power and the end time point, etc., so as to obtain the operating status of each management device corresponding to each time point from the current time point, etc. The operating status here includes not only power consumption, but also status data that can affect heat dissipation, which is not described here. The operating status axis table can be a time axis, the length of the axis is a preset period, the unit of the operating status axis table is a unit time point within the preset period, and the operating status within the preset period needs to be implanted into the axis according to the corresponding time point, so that the operating status axis table can be obtained.

[0035] S2. Construct the temperature operation curve of the energy storage system according to the charging operation state axis table and the discharging operation state axis table. The operation state data includes the operation time point of each management device, the operation state at each time point, the operation power and the end time point, etc. The operation state includes the name of each management device and its corresponding operation parameters. The use state of the energy storage system can be obtained according to the various operation parameters corresponding to each different management device. For example, a management device is a fan. The fan is turned on at 11 o'clock, which is the first gear of heat dissipation. The operating parameters of the first gear of heat dissipation are power of 20W, and it is planned to be turned off at 11:10, etc. Of course, this is just a simple example and is not universal. Other situations are not described here. The method for constructing the temperature operation curve of the energy storage system may include: constructing a plane coordinate system, the horizontal axis of the plane coordinate system is a preset period, and the vertical axis is a temperature value, and then calculating the energy storage system heat dissipation temperature value T corresponding to each time point in the preset period through the operation state axis table, and then implanting the energy storage system heat dissipation temperature value T into the plane coordinate system according to the time point to obtain each heat dissipation temperature value point, and connecting each heat dissipation temperature value point in sequence, so as to obtain the energy storage system temperature operation curve. The energy storage system heat dissipation temperature value T is the predicted temperature value in the energy storage system, and its value can be calculated according to the charging operation state axis table and the discharging operation state axis table. The energy storage system heat dissipation temperature value , where R is the discharge internal resistance of the energy storage system, and R' is the charging internal resistance of the energy storage system. The specific value can be obtained by testing the charging and discharging state of the energy storage system or by the energy storage system. The specific test process is a prior art and will not be described here. j is the number of each management device in the discharge operation state axis table at the predicted time point, and J is the total number of discharge management devices at the predicted time point, j=1, 2, ..., J; I j is the operating current of the discharge management device numbered j, I J 0 is the additional current when J discharge management devices are running. Its specific value can be obtained through experiments. In an ideal state, its value is zero. However, in actual situations, the superposition of multiple currents will increase the current load of the circuit. Therefore, by setting the additional current, the impact of the current on the energy storage system can be better evaluated, avoiding the calculation error caused by the change of the current value due to the circuit load, and improving the accuracy of the prediction. The additional current I J 0 The energy storage system can be tested by discharging the corresponding management equipment and parameters, and the detection current I can be obtained by detecting the energy storage system. 总 , then the additional current of each discharge management device numbered j is , and then make each discharge management device into a device-additional current compatibility information table, which includes each matching management device, parameter information and corresponding additional current. When performing calculations, the name and parameter information of each management device are used to search the compatibility information table to obtain the additional current. k is the number of each charging management device in the charging operation status axis table at the predicted time point, K is the total number of charging management devices at the predicted time point, k=1, 2, ..., K; I k is the operating current of the charging management device numbered k, I K 1 is the additional current of K charging management devices. At this time, each charging management device can be a plurality of solar panels, wind power generation modules, etc., and its prediction can be predicted according to the power generation law. K 1 It can be obtained through experimental testing, and the details are not described here. ε is the heat dissipation proportional factor, and its value is related to the heat dissipation performance of the energy storage system and the temperature difference. Its value is generally between 0.1-0.8. It can be obtained by checking the information table prepared in advance based on the experiment, or by calculation. When obtained by calculation, the heat dissipation proportional factor , where Q is the theoretical calorific value of the energy storage system. Its value can be obtained through experiments on the energy storage system, and of course it can also be obtained through calculation. The specific theoretical calorific value is , where Q' is the power consumption of the energy storage system, and U is the operating voltage of the energy storage system, and its specific value is not repeated here. ΔT is the heat dissipation temperature difference, which can be the difference between the internal temperature of the energy storage system and the ambient temperature, which can be obtained by detection, C is the average specific heat capacity of the energy storage system, and M is the effective mass of the energy storage system, which can be obtained by heating the energy storage system. It is a prior art and is not repeated here. Specifically, the energy storage system can be tested in advance, and calculations can be performed according to different heat dissipation temperature differences ΔT, so that the heat dissipation proportional factors corresponding to different heat dissipation temperature differences ΔT can be obtained, and then a heat dissipation proportional curve can be constructed. The heat dissipation proportional curve construction method may include: constructing a plane coordinate system, the horizontal axis is the heat dissipation temperature difference, and the vertical axis is the heat dissipation proportional factor, and then the calculated heat dissipation proportional factor is implanted into the plane coordinate system according to the corresponding heat dissipation temperature difference, so as to obtain the heat dissipation proportional point, and then the heat dissipation proportional points are connected in sequence to obtain the heat dissipation proportional curve. The heat dissipation proportional curve is searched by the heat dissipation temperature difference to obtain the heat dissipation proportional factor. S is the effective heat dissipation area of ​​the energy storage system, and its value can be obtained through the equipment parameters of the energy storage system, which is not repeated here. The heat dissipation temperature value calculated by this method can fully consider the heat dissipation state when the charging and discharging states are running at the same time, and take into account the heat generation of each current and the influence of the additional current. At the same time, through the influence of the heat dissipation efficiency, the evaluation is more comprehensive, in line with the actual heat dissipation of the energy storage system, and the calculation is accurate.

[0036] S3. Correct the temperature operation curve of the energy storage system and obtain a corrected curve. As time goes by, the absolute time point where the origin of the horizontal coordinate of the temperature operation curve of the energy storage system is located is constantly changing. The vertical coordinates corresponding to the temperature operation curve of the energy storage system are all obtained by prediction and calculation, but the endpoint values ​​of the temperature operation curve of the energy storage system can be obtained through detection, which makes correction possible and convenient. Its predicted charge and discharge operation state axis table may change, and the parameters of the energy storage system may also change with changes in temperature and some operating conditions. The predicted charge and discharge operation state axis table may change and can be corrected through real-time calculation, but some parameter changes of the energy storage system cannot be reflected by the predicted operation state axis table, so it is necessary to correct the double error of the operation curve. The correction method of the temperature operation curve of the energy storage system may include: detecting the internal temperature value T' of the energy storage system, and calculating the heat dissipation temperature value T'' of the energy storage system according to the operating state data at the current time point, and translating the endpoint vertical coordinate of the temperature operation curve of the energy storage system from the heat dissipation temperature value T to T', and adjusting the vertical coordinate point value of the temperature operation curve of the energy storage system according to By scaling and correcting the ratio of the error, the correction curve can be obtained. This method can not only correct the error of the current operating state parameters, but also correct the error in the calculation, so that the two errors can be corrected in an all-round way, making the correction curve more accurate.

[0037] S4. Determine whether the correction curve exceeds a preset warning threshold T 标 If yes, a first-level alarm is issued and S5 is executed. If no, no first-level alarm is issued. The preset warning threshold T 标 It can be set according to the actual situation. It is a horizontal straight line in the coordinate system. When the correction curve exceeds the warning threshold, the two lines intersect. In general, it is necessary to consider the tolerance temperature or upper limit temperature T of the energy storage system. 1 In general, the warning threshold ,in The buffer factor is generally 0.8-0.95. Of course, other values ​​are not excluded. The smaller the buffer factor is, the better the protection of the energy storage system is, and the larger the buffer space is. However, the alarm frequency will increase, the cooling cost will be higher, and the management cost will increase. This setting method is a fixed value method and cannot be adjusted according to actual conditions. The preset warning threshold T 标 The calculation method may also include: calculating the tolerance temperature t of each electrical component in the energy storage system m , where m is the number of each electrical component or electrical material in the energy storage system, and the tolerance temperature t mIt can be obtained based on the upper temperature limit of each electrical component or electrical material, and the details are not described here. , where M is the total number of electrical components or electrical materials in the energy storage system, m=1, 2, …, M; t m is the tolerable temperature of each electrical component or material in the energy storage system, δ m It is the weight ratio of the electrical component or electrical material electrical component numbered m, which can be preset according to the importance of the electrical component or electrical material electrical component in the energy storage system, and the details are not repeated here. m It is the heat dissipation proportional coefficient of the electrical component or electrical material numbered m. Its value can be obtained based on the structure of the energy storage system and the material of its peripheral structure. It can be obtained specifically through calculation or experiment. The experimental process is not described here. The preset warning threshold calculated by this method can take into account the tolerance temperature of each electrical component or material, its weight ratio and its heat dissipation proportional coefficient. This calculation method is comprehensive and the calculation result is accurate. Heat dissipation proportional factor , where n is the number of the electrical component or electrical material m, the number of the material outside the electrical component, and the numbering can be done from the inside to the outside, and the details are not repeated here. n is the thickness of the peripheral material numbered n, is the thermal conductivity of the peripheral material numbered n, S n The effective surface area of ​​the peripheral material numbered n can be obtained through the structure of the energy storage system, which will not be described in detail here. The specific value of the adjustment coefficient can be obtained through the structure of the energy storage system, and its value is generally 0.5-1, which will not be described in detail here. The preset warning threshold calculated by this method takes into account the structure of the energy storage system and the materials of its peripheral structure, and the evaluation is comprehensive and the calculation is accurate.

[0038] S5. Mark the horizontal coordinate of the intersection point as i, and then determine whether i is less than a preset time length i 标 If yes, a second-level alarm is issued and S6 is executed. If no, no second-level alarm is issued. Where i is the time period between the intersection point and the current time point. The preset time length i 标 It can be determined according to the heat dissipation capacity of the heat dissipation equipment of the energy storage system. The specific value is generally 0.5min-5min. This fixed time limit is relatively mechanical and cannot be adjusted organically according to specific circumstances, which is easy to waste energy. , where T 0is the cooling target temperature of the energy storage system, which can be the standard operating temperature of the energy storage system, generally 20-50 degrees Celsius, and will not be described in detail here. h is the cooling equipment number of the energy storage system, h=1, 2, ...H; the energy storage system cooling equipment can include air cooling, air conditioning cooling, etc., and the sorting method can be sorted from low to high in terms of cooling capacity. Basically, the cooling capacity and cooling cost are positively correlated, and will not be described in detail here. θ h It is the heat dissipation capacity factor of the cooling device numbered h, which can be obtained by conducting experiments on the cooling capacity of each cooling device. These data are dimensionless data, and Max[] is the maximum value. The specific details are not repeated here. This method processes the temperature difference logarithmically, which can take into account the trend of temperature heat dissipation. The higher the temperature, the stronger the heat dissipation capacity. This calculation method can fully consider the heat dissipation characteristics, with high calculation accuracy and more in line with the actual heat dissipation situation.

[0039] S6. Determine whether the correction curve for the cooling device fitting curve numbered h exceeds the preset warning threshold value T 标 If not, select the cooling device numbered h for cooling; if yes, execute S7; S7, determine whether the correction curve fits the cooling device numbered h+1 to a curve exceeding a preset warning threshold value T 标 , and then perform analogy calculations. If the correction curve still exceeds the preset warning threshold T for the cooling device numbered H, 标 , then the temperature is cooled according to the cooling device numbered H. The method for obtaining the correction curve fitting curve for the cooling device numbered h may include performing cooling fitting on each cooling device to obtain a cooling fitting curve. The cooling fitting curve is a curve constructed with the cooling time as the ordinate and the lowered temperature as the ordinate. Different cooling fitting curves can be constructed for different starting temperatures and ambient temperatures, which will not be described in detail here. Then the cooling fitting curve is implanted into the correction curve coordinate system, and the cooling fitting curve is subtracted from the correction curve to obtain the cooling fitting curve, and its specific numerical calculation is not described here. Through this method, the heat dissipation of the energy storage system can be budgeted, so that heat management can be performed in advance, which provides preparation and cooling time for heat management, and cooling through the optimal cooling equipment can save cooling energy to the maximum extent, improve energy utilization, avoid energy waste, and reduce management costs.

[0040] Embodiment 2 The present invention further proposes a thermal management system for an energy storage system, which is used to predict the heat of the energy storage system and perform planned management. The thermal management system for the energy storage system may include: The equipment operation statistics module is used to predict the operating status of the management equipment, obtain the operating status data of the management equipment within a preset cycle, and construct a charging operating status axis table and a discharging operating status axis table based on the operating status data.

[0041] The energy storage system statistics module is used to construct a temperature operation curve of the energy storage system according to the charging operation state axis table and the discharging operation state axis table.

[0042] The operating curve correction module is used to correct the temperature operating curve of the energy storage system and obtain a correction curve.

[0043] The judgment analysis module is used to determine whether the correction curve exceeds a preset warning threshold T 标 If yes, a first-level alarm is issued, if no, no first-level alarm is issued. After receiving the first-level alarm, the horizontal coordinate of the intersection point is calibrated as i, and then it is determined whether i is less than a preset time length i 标 If yes, a second-level alarm is issued. If no, no second-level alarm is issued. It is determined whether the correction curve for the cooling device fitting curve numbered h exceeds the preset warning threshold T. 标 If not, select the cooling device numbered h for cooling. If yes, determine whether the correction curve fits the cooling device numbered h+1 to a curve that exceeds the preset warning threshold T. 标 , and then perform analogy calculations. If the correction curve still exceeds the preset warning threshold T for the cooling device numbered H, 标 , then cool down according to the cooling equipment numbered H.

[0044] Embodiment 3 As a preferred embodiment of the present invention, a computer-readable storage medium stores a computer program. When the program is executed by a processor, the steps of the thermal management method of the energy storage system are implemented. When the thermal management method of the energy storage system is applied, it can be applied in the form of software, such as a program designed to be independently run by a computer-readable storage medium. The computer-readable storage medium can be a U disk, designed as a U shield, and the U disk is designed to start the program of the entire method through an external trigger.

[0045] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution disclosed in this application can be achieved, and this document is not limited here.

[0046] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A thermal management method for an energy storage system, characterized in that: The thermal management method of the energy storage system comprises: S1. Predicting the operating status of the management device, obtaining the operating status data of the management device within a preset cycle, and constructing a charging operating status axis table and a discharging operating status axis table according to the operating status data; S2. constructing a temperature operation curve of the energy storage system according to the charging operation state axis table and the discharging operation state axis table; S3, correcting the temperature operation curve of the energy storage system and obtaining a corrected curve; S4. Determine whether the correction curve exceeds a preset warning threshold T 标 If yes, a first-level alarm is issued and S5 is executed; if no, a first-level alarm is not issued; S5. Mark the horizontal coordinate of the intersection point as i, and then determine whether i is less than a preset time length i 标 If yes, a second-level alarm is issued and S6 is executed; if no, no second-level alarm is issued; S6. Determine whether the correction curve for the cooling device fitting curve numbered h exceeds the preset warning threshold value T 标 , h is the cooling device number of the energy storage system, h=1, 2, ..., H; the sorting method is to sort the cooling capacity from low to high. If no, select the cooling device numbered h for cooling. If yes, execute S7; S7, determine whether the correction curve fits the cooling device numbered h+1 to a curve exceeding a preset warning threshold value T 标 , and then perform analogy calculations. If the correction curve still exceeds the preset warning threshold T for the cooling device numbered H, 标 , then cool down according to the cooling device or combination numbered H.

2. The thermal management method of the energy storage system according to claim 1, characterized in that: The method for correcting the temperature operation curve of the energy storage system includes: detecting and obtaining an internal temperature value T' of the energy storage system, and calculating a heat dissipation temperature value T'' of the energy storage system according to the operation status data at the current time point, and translating the endpoint ordinate of the temperature operation curve of the energy storage system from the heat dissipation temperature value T to T', and scaling and correcting the ordinate point value of the temperature operation curve of the energy storage system according to a preset ratio to obtain a correction curve.

3. The thermal management method of the energy storage system according to claim 2, characterized in that: The preset ratio is .

4. The thermal management method of the energy storage system according to claim 1, characterized in that: The warning threshold ,in is the buffer factor, and T1 is the tolerance temperature or upper limit temperature of the energy storage system.

5. The thermal management method of the energy storage system according to claim 1, characterized in that: The preset warning threshold T 标 The calculation method includes: preset warning threshold , where m is the serial number of each electrical component or electrical material in the energy storage system, M is the total number of each electrical component or electrical material in the energy storage system, m=1, 2, ..., M; t m is the tolerable temperature of each electrical component or electrical material in the energy storage system; m It is the weight ratio of the electrical component or electrical material electrical component numbered m; m It is the heat dissipation proportional coefficient of the electrical component numbered m or the electrical material electrical component.

6. The thermal management method of the energy storage system according to claim 5, characterized in that: Heat dissipation ratio coefficient , where n is the number of the electrical component or electrical material, the number of the material surrounding the electrical component; b n is the thickness of the peripheral material numbered n, is the thermal conductivity of the peripheral material numbered n, S n is the effective surface area of ​​the peripheral material numbered n; is the adjustment factor.

7. The thermal management method of the energy storage system according to claim 1, characterized in that: The preset time length , where T0 is the cooling target temperature of the energy storage system; h=1, 2, …H; θ h It is the heat dissipation capacity factor of the cooling device numbered h; Max[] is the maximum value.

8. The thermal management method of the energy storage system according to claim 1, characterized in that: The method for obtaining the fitting curve of the cooling device numbered h by the correction curve includes: performing cooling fitting on each cooling device to obtain the cooling fitting curve, the cooling fitting curve is a curve constructed with the cooling time as the vertical coordinate and the lowering temperature as the vertical coordinate; then implanting the cooling fitting curve into the correction curve coordinate system, and subtracting the cooling fitting curve from the correction curve to obtain the cooling fitting curve.

9. A thermal management system for an energy storage system, characterized in that: The thermal management system of the energy storage system comprises: The equipment operation statistics module is used to predict the operation status of the management equipment, obtain the operation status data of the management equipment within a preset period, and construct a charging operation status axis table and a discharging operation status axis table according to the operation status data; An energy storage system statistics module, which is used to construct a temperature operation curve of the energy storage system according to a charging operation state axis table and a discharging operation state axis table; An operating curve correction module, which is used to correct the temperature operating curve of the energy storage system and obtain a correction curve; The judgment analysis module is used to judge whether the correction curve exceeds a preset warning threshold T 标 If yes, a first-level alarm is issued, if no, no first-level alarm is issued; the horizontal coordinate of the intersection point is calibrated as i, and then it is determined whether i is less than a preset time length i 标 If yes, a second-level alarm is issued, if no, no second-level alarm is issued; determine whether the correction curve for the cooling device fitting curve numbered h exceeds the preset warning threshold T 标 If not, select the cooling device numbered h for cooling. If yes, determine whether the correction curve fits the cooling device numbered h+1 to a curve that exceeds the preset warning threshold T. 标 , and then perform analogy calculations. If the correction curve still exceeds the preset warning threshold T for the cooling device numbered H, 标 , then cool down according to the cooling equipment or combination numbered H.

10. A computer-readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the steps of the thermal management method for an energy storage system according to any one of claims 1 to 8 are implemented.

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