Battery energy storage system management method based on multiple energy optimization

Abstract

The invention relates to the technical field of battery energy storage system management, and relates to a battery energy storage system management method based on multiple energy optimization, and the method comprises the steps: obtaining the actual value of each evaluation index corresponding to each to-be-used phase change material, and selecting the phase change material most suitable for each battery unit in a battery energy storage system; packaging a phase change material in a material with good thermal conductivity, and tightly attaching the phase change material to the surface of each battery unit; a plurality of temperature sensors are installed in a battery energy storage system, the temperature of each battery unit corresponding to each monitoring time point is monitored in real time, and the phase change state of a phase change material in each battery unit at each monitoring time point is analyzed; according to the method, the thermal management efficiency of the battery energy storage system can be remarkably improved, and the safety and reliability of the system are enhanced. Through accurate thermal management, the performance of the battery is optimized, the service life is prolonged, and the overall efficiency of the system is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of battery energy storage system management, and relates to a battery energy storage system management method based on multiple energy optimization. Background Art

[0002] With the rapid development of renewable energy, battery energy storage systems are increasingly being used in power systems. These systems play a vital role in regulating grid load, balancing supply and demand, and storing fluctuating renewable energy. However, batteries generate a lot of heat during the charging and discharging process, which causes the battery temperature to rise, which in turn affects its performance and life. High temperatures not only accelerate the aging of battery materials, but may also cause safety hazards such as thermal runaway and battery failure.

[0003] Traditional temperature control methods mostly rely on active cooling systems, such as air cooling or liquid cooling systems. Although these systems can effectively reduce battery temperature, they also increase energy consumption and cost, reducing the overall efficiency of the system. In addition, these methods usually require complex mechanical and control equipment, increasing the complexity and maintenance cost of the system. Summary of the invention

[0004] In view of the above problems existing in the prior art, the present invention provides a battery energy storage system management method based on multiple energy optimization to solve the above technical problems.

[0005] In order to achieve the above purpose and other purposes, the technical solution adopted by the present invention is as follows:

[0006] A first aspect of the present invention provides a battery energy storage system management method based on multiple energy optimization, the method comprising the following steps:

[0007] Step S1, selecting phase change materials: obtaining actual values ​​of each evaluation index corresponding to each phase change material to be used, so as to select the most suitable phase change material for each battery cell in the battery energy storage system;

[0008] Step S2, designing a PCM embedding structure: encapsulating the phase change material in a material with good thermal conductivity and closely fitting it to the surface of each battery cell;

[0009] Step S3, PCM intelligent control: by installing multiple temperature sensors in the battery energy storage system, the temperature of each battery cell corresponding to each monitoring time point is monitored in real time, and the phase change state of the phase change material in each battery cell at each monitoring time point is analyzed;

[0010] Step S4, optimizing the charge and discharge strategy: dynamically adjusting the charge and discharge rate of the battery energy storage system corresponding to the next monitoring time point according to the phase change state of the phase change material in each battery cell at each monitoring time point.

[0011] The specific selection process of selecting the most suitable phase change material for each battery cell in the battery energy storage system is as follows:

[0012] Obtain a total number M of phase change materials to be used, and number them sequentially as 1, 2, ...m, ...M, where m is the number of each phase change material to be used;

[0013] Obtain the actual value of each evaluation index corresponding to each phase change material to be used, and convert the actual value of each evaluation index corresponding to each phase change material to be used in each battery cell into a membership degree according to the characteristics of each evaluation index and the actual operating parameters of each battery cell. b is the number of each evaluation index, the value range of b is 1 to B, B is the total number of evaluation indexes, and k is the number of each battery unit;

[0014] Then construct the membership matrix of each battery cell in represents the membership of the first phase change material to be used in the k-th battery cell to the first, b-th and last evaluation index respectively; Indicates the membership of the mth phase change material to be used in the kth battery cell in the first and last evaluation indicators respectively; represents the membership of the last phase change material to be used in the k-th battery cell to the first, b-th and last evaluation index respectively;

[0015] The weight of each evaluation index is obtained by using the hierarchical analysis method, and the weight vector W = [W1, ...Wb, ...WB] is constructed, where W1, Wb, and WB are the weights of the first, bth, and last evaluation index respectively;

[0016] The weighted average method is used to multiply the weight vector W by the membership matrix of each battery cell, thereby obtaining a comprehensive evaluation vector of each battery cell corresponding to each phase change material to be used, and then obtaining a comprehensive evaluation score of each battery cell corresponding to each phase change material to be used, and arranging them in descending order, and selecting the phase change material to be used with the first comprehensive evaluation score as the most suitable phase change material for each battery cell in the battery energy storage system.

[0017] The actual value of each evaluation index corresponding to each phase change material to be used in each battery cell is converted into a membership degree. The specific conversion process is as follows:

[0018] According to the actual operating parameters of each battery cell, extract the historical minimum parameter value of each battery cell corresponding to each evaluation index Average parameter value And the highest parameter value in history

[0019] Define the membership function formula to calculate the membership degree of each phase change material to be used in each battery cell corresponding to each evaluation index Among them SJ mb is the actual value of the bth evaluation index corresponding to the mth phase change material to be used.

[0020] The phase change states of the phase change material in each battery cell at each monitoring time point include solid state, solid-liquid phase change, liquid state, and liquid-solid phase change.

[0021] Analyze the phase change state of the phase change material in each battery cell at each monitoring time point. The specific analysis process is as follows:

[0022] Get the temperature T of each battery cell at each monitoring time point kn , n is the number of each monitoring time point, n = 1, 2, ... N, N is the total number of monitoring time points;

[0023] The phase change temperature, latent heat and thermal conductivity of the phase change material in each battery cell at each monitoring time point are obtained and recorded as CL1 kn , CL2 kn , CL3 kn ;

[0024] Then calculate the state judgment value of the phase change material in each battery cell at each monitoring time point in

[0025] CG k CY k are the specific heat capacities of the phase change material in the kth battery cell corresponding to the solid and liquid states, respectively, and ΔT is the width of the preset phase change temperature interval;

[0026] Based on the state judgment value of the phase change material in each battery cell at each monitoring time point, the phase change state of the phase change material in each battery cell at each monitoring time point is judged. The specific judgment process is as follows:

[0027] If the state judgment value of the phase change material in a battery cell at a certain monitoring time point is 0, it is determined that the phase change state of the phase change material in the battery cell at the monitoring time point is solid;

[0028] If the state judgment value of the phase change material in a battery cell at a certain monitoring time point is 1, it is determined that the phase change state of the phase change material in the battery cell at the monitoring time point is liquid;

[0029] If the state judgment value of the phase change material in a battery cell at a certain monitoring time point is within the interval (0, 0.5), it is determined that the phase change state of the phase change material in the battery cell at the monitoring time point is solid-liquid phase change;

[0030] If the state judgment value of the phase change material in a battery cell at a certain monitoring time point is within the interval [0.5, 1), then it is determined that the phase change state of the phase change material in the battery cell at the monitoring time point is liquid-solid phase change;

[0031] The phase change state of the phase change material in each battery cell at each monitoring time point is obtained according to the above determination method.

[0032] Dynamically adjust the charging rate of the battery energy storage system corresponding to the next monitoring time point. The specific adjustment process is:

[0033] Based on the phase change state of the phase change material in each battery cell at each monitoring time point, a phase change state factor of the phase change material in each battery cell at each monitoring time point is obtained;

[0034] If the phase change state of the phase change material in a battery cell at a certain monitoring time point is solid or liquid, then the phase change state factor ε1 of the phase change material in the battery cell at the monitoring time point is 1; if the phase change state of the phase change material in a battery cell at a certain monitoring time point is solid-liquid phase change or liquid-solid phase change, then the phase change state factor ε2 of the phase change material in the battery cell at the monitoring time point is 0.5; thus, the phase change state factor ε of the phase change material in each battery cell at each monitoring time point is obtained. kn , where ε kn The value is ε1 or ε2;

[0035] Then calculate the charging rate of the battery energy storage system corresponding to the next monitoring time point C max is the maximum charging rate of the battery energy storage system, δ1 and δ2 are the set temperature adjustment coefficients and phase change state adjustment coefficients, respectively, which are used to weigh the effects of temperature deviation and phase change state on the charging rate, T is the optimal operating temperature of the battery cell, T kn is the temperature of the kth battery cell at the nth monitoring time point, ε kn represents the phase change state factor of the phase change material in the kth battery cell at the nth monitoring time point;

[0036] The charging rate of the battery energy storage system corresponding to the next monitoring time point is fed back to the control terminal corresponding to the battery energy storage system, and the control terminal adjusts the charging rate of the battery energy storage system corresponding to the next monitoring time point.

[0037] Dynamically adjust the discharge rate of the battery energy storage system corresponding to the next monitoring time point. The specific adjustment process is:

[0038] Based on the phase change state of the phase change material in each battery cell at each monitoring time point, the discharge rate adjustment coefficient of the phase change material in each battery cell at each monitoring time point is obtained. T knis the temperature of the kth battery cell at the nth monitoring time point, T k ' n is the temperature of the phase change material in the kth battery cell at the nth monitoring time point, XB k is the phase change enthalpy of the phase change material in the kth battery cell, RL k represents the capacity of the kth battery cell, and τ is a preset calculation constant used to prevent the denominator from being zero;

[0039] The discharge rate adjustment coefficients of the phase change materials in each battery cell at each monitoring time point are summed and averaged to obtain the average phase change state influencing factor of the phase change materials in each battery cell at the monitoring time point.

[0040] Then calculate the discharge rate of each battery cell in the battery energy storage system corresponding to the next monitoring time point

[0041] γ kn is the discharge rate of the kth battery cell at the nth monitoring time point, δ3 and δ4 are the predefined ambient temperature influence coefficient and the safety temperature range influence coefficient, respectively, T n ′ is the temperature of the external environment of the battery energy storage system at the nth monitoring time point, and Δσ is the safe temperature threshold allowed by the battery unit during operation;

[0042] The discharge rates of each battery unit in the battery energy storage system corresponding to the next monitoring time point are summarized, summed and averaged to obtain the discharge rate of the battery energy storage system corresponding to the next monitoring time point; and the summed and averaged are fed back to the corresponding control terminal of the battery energy storage system, and the control terminal adjusts the discharge rate of the battery energy storage system corresponding to the next monitoring time point.

[0043] A second aspect of the present invention provides a battery energy storage system management device based on multiple energy optimization, including a processor, a memory and a communication bus;

[0044] The memory stores a computer-readable program executable by the processor;

[0045] The communication bus realizes the connection and communication between the processor and the memory;

[0046] When the processor executes the computer-readable program, it is executed to implement the battery energy storage system management method based on multiple energy optimization as described in the present invention.

[0047] As described above, the battery energy storage system management method based on multiple energy optimization provided by the present invention has at least the following beneficial effects:

[0048] (1) The battery energy storage system management method based on multiple energy optimization provided by the present invention obtains the actual value of each evaluation index corresponding to each phase change material to be used, thereby selecting the most suitable phase change material for each battery cell in the battery energy storage system; encapsulates the phase change material in a material with good thermal conductivity and fits it tightly to the surface of each battery cell; installs multiple temperature sensors in the battery energy storage system, monitors the temperature of each battery cell corresponding to each monitoring time point in real time, and analyzes the phase change state of the phase change material in each battery cell at each monitoring time point; and then dynamically adjusts the charge and discharge rate of the battery energy storage system corresponding to the next monitoring time point. On the one hand, the characteristics of the phase change material directly affect its performance in battery thermal management. Selecting a suitable phase change material can effectively absorb and release heat, maintain the temperature of the battery cell within the optimal range, prevent overheating or overcooling, and thus protect the performance and life of the battery; on the other hand, dynamically adjusting the charge and discharge rate of the battery energy storage system corresponding to the next monitoring time point is an effective means to improve system performance and safety. Through real-time temperature monitoring and phase change state analysis, the charge and discharge rate can be optimized according to the thermal state of the battery to avoid performance degradation or safety hazards caused by battery overheating. Such adjustments can maximize battery efficiency and extend battery life without affecting battery performance.

[0049] (2) The embodiments of the present invention can significantly improve the thermal management efficiency of the battery energy storage system and enhance the safety and reliability of the system. Through precise thermal management, the performance of the battery is optimized, the service life is extended, and the overall efficiency of the system is improved. At the same time, dynamic adjustment of the charge and discharge rate reduces the risk of battery damage due to overheating or overcooling, reduces maintenance and replacement costs, and improves the economy of the system; through thermal management strategies, it can ensure that the battery remains stable and safe at high energy density, thereby promoting the sustainable development of the entire energy storage industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0051] Figure 1 It is a schematic diagram of the connection of each step of the method of the present invention. DETAILED DESCRIPTION

[0052] The above contents in combination with the implementation of the present invention are merely examples and explanations of the concept of the present invention. The technical personnel in the relevant technical field may make various modifications or supplements to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

[0053] Example 1

[0054] See also Figure 1 As shown, a battery energy storage system management method based on multiple energy optimization includes the following steps:

[0055] Step S1, selecting phase change materials: obtaining actual values ​​of each evaluation index corresponding to each phase change material to be used, so as to select the most suitable phase change material for each battery cell in the battery energy storage system;

[0056] Based on the above solution, the phase change material most suitable for each battery cell in the battery energy storage system is selected, and the specific selection process is as follows:

[0057] Obtain a total number M of phase change materials to be used, and number them sequentially as 1, 2, ...m, ...M, where m is the number of each phase change material to be used;

[0058] Obtain the actual value of each evaluation index corresponding to each phase change material to be used, wherein each evaluation index includes but is not limited to melting point, latent heat, thermal conductivity, density or specific heat capacity; according to the characteristics of each evaluation index and combined with the actual operating parameters of each battery cell, convert the actual value of each evaluation index corresponding to each phase change material to be used in each battery cell into a membership degree b is the number of each evaluation index, the value range of b is 1 to B, B is the total number of evaluation indexes, and k is the number of each battery unit;

[0059] Then construct the membership matrix of each battery cell in represents the membership of the first phase change material to be used in the k-th battery cell to the first, b-th and last evaluation index respectively; Indicates the membership of the mth phase change material to be used in the kth battery cell in the first and last evaluation indicators respectively; represents the membership of the last phase change material to be used in the k-th battery cell to the first, b-th and last evaluation index respectively;

[0060] The weight of each evaluation index is obtained by using the hierarchical analysis method, and the weight vector W = [W1, ...Wb, ...WB] is constructed, where W1, Wb, and WB are the weights of the first, bth, and last evaluation index respectively;

[0061] The weighted average method is used to multiply the weight vector W by the membership matrix of each battery cell, thereby obtaining a comprehensive evaluation vector of each battery cell corresponding to each phase change material to be used, and then obtaining a comprehensive evaluation score of each battery cell corresponding to each phase change material to be used, and arranging them in descending order, and selecting the phase change material to be used with the first comprehensive evaluation score as the most suitable phase change material for each battery cell in the battery energy storage system.

[0062] The comprehensive evaluation vector of each battery cell corresponding to each phase change material to be used is a row vector, in which each element represents an evaluation index score of a PCM, which are summed and averaged to obtain the comprehensive evaluation score of each battery cell corresponding to each phase change material to be used.

[0063] Preferably, based on the above scheme, the actual value of each evaluation index corresponding to each phase change material to be used in each battery cell is converted into a membership degree. The specific conversion process is as follows:

[0064] According to the actual operating parameters of each battery cell, extract the historical minimum parameter value of each battery cell corresponding to each evaluation index Average parameter value And the highest parameter value in history

[0065] Define the membership function formula to calculate the membership degree of each phase change material to be used in each battery cell corresponding to each evaluation index Among them SJ mb is the actual value of the bth evaluation index corresponding to the mth phase change material to be used.

[0066] Step S2, designing a PCM embedding structure: encapsulating the phase change material in a material with good thermal conductivity and closely fitting it to the surface of each battery cell;

[0067] Step S3, PCM intelligent control: by installing multiple temperature sensors in the battery energy storage system, the temperature of each battery cell corresponding to each monitoring time point is monitored in real time, and the phase change state of the phase change material in each battery cell at each monitoring time point is analyzed;

[0068] Preferably, based on the above scheme, the phase change state of the phase change material in each battery cell at each monitoring time point includes solid state, solid-liquid phase change, liquid state and liquid-solid phase change.

[0069] Phase change materials (PCM) used in battery cells are usually used for thermal management to regulate battery temperature. The phase change states of phase change materials are mainly the following:

[0070] 1. Solid state: At low temperatures, PCM is in a solid state, able to absorb heat and gradually heat up;

[0071] 2. Solid-liquid phase change: When the temperature reaches the melting point of the material, PCM begins to change from solid to liquid. In this process, it can absorb a large amount of heat with a small temperature change, which is the key feature of phase change materials for thermal management;

[0072] 3. Liquid: At temperatures above the melting point, the PCM completely transforms into a liquid state and continues to absorb heat, but the efficiency is not as high as during the solid-liquid phase transition;

[0073] 4. Liquid-solid phase change: When the temperature drops, PCM resolidifies from liquid to solid, releasing the heat previously absorbed.

[0074] Based on the above scheme, the phase change state of the phase change material in each battery cell at each monitoring time point is analyzed. The specific analysis process is as follows:

[0075] Get the temperature T of each battery cell at each monitoring time point kn , n is the number of each monitoring time point, n = 1, 2, ... N, N is the total number of monitoring time points;

[0076] The phase change temperature, latent heat and thermal conductivity of the phase change material in each battery cell at each monitoring time point are obtained and recorded as CL1 kn , CL2 kn , CL3 kn ;

[0077] The phase change temperature of the phase change material in each battery cell at each monitoring time point is obtained, and the specific steps are as follows: first, a high-precision temperature sensor, such as a thermocouple or thermistor, is installed on each battery cell to ensure that the sensor is in good contact with the surface of the phase change material so as to monitor the temperature change in real time; then, during the battery charging and discharging process, temperature data is continuously collected, and the temperature curve is processed by data analysis software to identify the temperature platform stage, which usually corresponds to the phase change temperature; then, the data is smoothed and the rate of change of temperature over time is calculated to determine the exact time point of the phase change; finally, a thermal model of the battery cell is established using a numerical simulation tool (such as finite element analysis), material parameters are input, and the experimental results are verified and optimized, so as to accurately identify the phase change temperature of the phase change material in each battery cell at different monitoring time points;

[0078] The specific steps to obtain the latent heat of the phase change material in each battery cell at each monitoring time point are as follows: First, install high-precision temperature sensors (such as thermocouples or thermistors) and heat flow meters to ensure that they are in good contact with the surface of the phase change material in each battery cell to monitor the temperature and heat flow changes in real time; then, continuously collect temperature and heat flow data during the battery charging and discharging process; then, by analyzing the heat flow data, identify the heat flow platform during the phase change process, and combine the temperature change, use the formula Q = ∫CG k ·dn+CL2kn , Q is the total heat, and the latent heat of the phase change material in each battery cell at each monitoring time point is calculated;

[0079] The thermal conductivity of the phase change material in each battery cell at each monitoring time point is obtained. The specific steps are as follows:

[0080] During the battery charging and discharging process, temperature and heat flow data are continuously collected; then, the thermal conductivity is calculated using Fourier's law of heat conduction through the measured temperature difference and heat flux density.

[0081] Then calculate the state judgment value of the phase change material in each battery cell at each monitoring time point in

[0082] CG k CY k are the specific heat capacities of the phase change material in the kth battery cell corresponding to the solid and liquid states, respectively, and ΔT is the width of the preset phase change temperature range.

[0083] The above calculation formula determines the phase change state of the material by defining the temperature range and latent heat absorption. In this way, the thermal dynamic behavior of the material from solid to liquid (or vice versa) during the phase change of PCM can be captured more accurately;

[0084] Traditional thermal management systems usually rely on fixed temperature thresholds and cannot dynamically respond to the complexity of temperature changes. Using this formula, the state changes of PCM can be monitored in real time within a more detailed temperature range, which is crucial for optimizing the battery thermal management system. By more accurately judging the phase change state, the thermal efficiency of the system can be improved, energy loss can be reduced, and the service life of the battery can be extended. In addition, this method can respond quickly to temperature changes, avoid overheating or overcooling, and improve the safety and reliability of the battery.

[0085] Based on the state judgment value of the phase change material in each battery cell at each monitoring time point, the phase change state of the phase change material in each battery cell at each monitoring time point is judged. The specific judgment process is as follows:

[0086] If the state judgment value of the phase change material in a battery cell at a certain monitoring time point is 0, it is determined that the phase change state of the phase change material in the battery cell at the monitoring time point is solid;

[0087] If the state judgment value of the phase change material in a battery cell at a certain monitoring time point is 1, it is determined that the phase change state of the phase change material in the battery cell at the monitoring time point is liquid;

[0088] If the state judgment value of the phase change material in a battery cell at a certain monitoring time point is within the interval (0, 0.5), it is determined that the phase change state of the phase change material in the battery cell at the monitoring time point is solid-liquid phase change;

[0089] If the state judgment value of the phase change material in a battery cell at a certain monitoring time point is within the interval [0.5, 1), then it is determined that the phase change state of the phase change material in the battery cell at the monitoring time point is liquid-solid phase change;

[0090] The phase change state of the phase change material in each battery cell at each monitoring time point is obtained according to the above determination method.

[0091] Step S4, optimizing the charge and discharge strategy: the phase change state of the phase change material in each battery cell at each monitoring time point, dynamically adjusting the charge and discharge rate of the battery energy storage system corresponding to the next monitoring time point.

[0092] Based on the above scheme, the charging rate of the battery energy storage system corresponding to the next monitoring time point is dynamically adjusted. The specific adjustment process is as follows:

[0093] Based on the phase change state of the phase change material in each battery cell at each monitoring time point, a phase change state factor of the phase change material in each battery cell at each monitoring time point is obtained;

[0094] If the phase change state of the phase change material in a battery cell at a certain monitoring time point is solid or liquid, then the phase change state factor ε1 of the phase change material in the battery cell at the monitoring time point is 1; if the phase change state of the phase change material in a battery cell at a certain monitoring time point is solid-liquid phase change or liquid-solid phase change, then the phase change state factor ε2 of the phase change material in the battery cell at the monitoring time point is 0.5; thus, the phase change state factor ε of the phase change material in each battery cell at each monitoring time point is obtained. kn , where ε kn The value is ε1 or ε2;

[0095] Then calculate the charging rate of the battery energy storage system corresponding to the next monitoring time point C max is the maximum charging rate of the battery energy storage system, δ1 and δ2 are the set temperature adjustment coefficients and phase change state adjustment coefficients, respectively, which are used to weigh the effects of temperature deviation and phase change state on the charging rate, T is the optimal operating temperature of the battery cell, T kn is the temperature of the kth battery cell at the nth monitoring time point, ε kn represents the phase change state factor of the phase change material in the kth battery cell at the nth monitoring time point;

[0096] It reflects the degree to which the temperature of each battery cell deviates from the optimal operating temperature. The greater the deviation, the lower the charging rate.

[0097] (1-δ2×ε kn ) is used to adjust the charging rate to reflect the effect of phase change state. When the solid-liquid phase change or liquid-solid phase change occurs, the charging rate is reduced to prevent overcooling or overheating;

[0098] The charging rate of the battery energy storage system corresponding to the next monitoring time point is fed back to the control terminal corresponding to the battery energy storage system, and the control terminal adjusts the charging rate of the battery energy storage system corresponding to the next monitoring time point.

[0099] Based on the above scheme, the discharge rate of the battery energy storage system corresponding to the next monitoring time point is dynamically adjusted. The specific adjustment process is as follows:

[0100] Based on the phase change state of the phase change material in each battery cell at each monitoring time point, the discharge rate adjustment coefficient of the phase change material in each battery cell at each monitoring time point is obtained. T kn is the temperature of the kth battery cell at the nth monitoring time point, T k ' n is the temperature of the phase change material in the kth battery cell at the nth monitoring time point, XB k is the phase change enthalpy of the phase change material in the kth battery cell, RL k represents the capacity of the kth battery cell, and τ is a preset calculation constant used to prevent the denominator from being zero;

[0101] The discharge rate adjustment coefficients of the phase change materials in each battery cell at each monitoring time point are summed and averaged to obtain the average phase change state influencing factor of the phase change materials in each battery cell at the monitoring time point.

[0102] Then calculate the discharge rate of each battery cell in the battery energy storage system corresponding to the next monitoring time point

[0103] γ kn is the discharge rate of the kth battery cell at the nth monitoring time point, δ3 and δ4 are the predefined ambient temperature influence coefficient and the safety temperature range influence coefficient, respectively, T n ′ is the temperature of the external environment of the battery energy storage system at the nth monitoring time point, and Δσ is the safe temperature threshold allowed by the battery unit during operation;

[0104] The temperature of the external environment of the battery energy storage system at each monitoring time point will affect the heat dissipation and overall temperature management of the battery. Therefore, the influence of the ambient temperature needs to be considered when adjusting the battery discharge rate. If the ambient temperature is high, the battery may be more likely to overheat; if the ambient temperature is low, the battery may be more likely to overcool;

[0105] The discharge rates of each battery unit in the battery energy storage system corresponding to the next monitoring time point are summarized, summed and averaged to obtain the discharge rate of the battery energy storage system corresponding to the next monitoring time point; and the summed and averaged are fed back to the corresponding control terminal of the battery energy storage system, and the control terminal adjusts the discharge rate of the battery energy storage system corresponding to the next monitoring time point.

[0106] Example 2

[0107] A battery energy storage system management device based on multiple energy optimization, including a processor, a memory and a communication bus;

[0108] The memory stores a computer-readable program executable by the processor;

[0109] The communication bus realizes the connection and communication between the processor and the memory;

[0110] When the processor executes the computer-readable program, it is executed to implement the battery energy storage system management method based on multiple energy optimization as described in the present invention.

[0111] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0112] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0113] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A battery energy storage system management method based on multiple energy optimization, characterized in that: The method includes: Step S1, selecting phase change materials: obtaining actual values ​​of each evaluation index corresponding to each phase change material to be used, so as to select the most suitable phase change material for each battery cell in the battery energy storage system; Step S2, designing a PCM embedding structure: encapsulating the phase change material in a material with good thermal conductivity and closely fitting it to the surface of each battery cell; Step S3, PCM intelligent control: by installing multiple temperature sensors in the battery energy storage system, the temperature of each battery cell corresponding to each monitoring time point is monitored in real time, and the phase change state of the phase change material in each battery cell at each monitoring time point is analyzed; Step S4, optimizing the charge and discharge strategy: dynamically adjusting the charge and discharge rate of the battery energy storage system corresponding to the next monitoring time point according to the phase change state of the phase change material in each battery cell at each monitoring time point.

2. The battery energy storage system management method based on multiple energy optimization according to claim 1 is characterized in that: The specific selection process of selecting the most suitable phase change material for each battery cell in the battery energy storage system is as follows: Obtain a total number M of phase change materials to be used, and number them sequentially as 1, 2, ...m, ...M, where m is the number of each phase change material to be used; Obtain the actual value of each evaluation index corresponding to each phase change material to be used, and convert the actual value of each evaluation index corresponding to each phase change material to be used in each battery cell into a membership degree according to the characteristics of each evaluation index and the actual operating parameters of each battery cell. b is the number of each evaluation index, the value range of b is 1 to B, B is the total number of evaluation indexes, and k is the number of each battery unit; Then construct the membership matrix of each battery cell in represents the membership of the first phase change material to be used in the k-th battery cell to the first, b-th and last evaluation index respectively; Indicates the membership of the mth phase change material to be used in the kth battery cell in the first and last evaluation indicators respectively; represents the membership of the last phase change material to be used in the k-th battery cell to the first, b-th and last evaluation index respectively; The weight of each evaluation index is obtained by using the hierarchical analysis method, and the weight vector W = [W1, ...Wb, ...WB] is constructed, where W1, Wb, and WB are the weights of the first, bth, and last evaluation index respectively; The weighted average method is used to multiply the weight vector W by the membership matrix of each battery cell, thereby obtaining a comprehensive evaluation vector of each battery cell corresponding to each phase change material to be used, and then obtaining a comprehensive evaluation score of each battery cell corresponding to each phase change material to be used, and arranging them in descending order, and selecting the phase change material to be used with the first comprehensive evaluation score as the most suitable phase change material for each battery cell in the battery energy storage system.

3. The battery energy storage system management method based on multiple energy optimization according to claim 2 is characterized in that: The actual value of each evaluation index corresponding to each phase change material to be used in each battery cell is converted into a membership degree. The specific conversion process is as follows: According to the actual operating parameters of each battery cell, extract the historical minimum parameter value of each evaluation index corresponding to each battery cell Average parameter value And the highest parameter value in history Define the membership function formula to calculate the membership degree of each phase change material to be used in each battery cell corresponding to each evaluation index Among them SJ mb is the actual value of the bth evaluation index corresponding to the mth phase change material to be used.

4. The battery energy storage system management method based on multiple energy optimization according to claim 1 is characterized in that: The phase change states of the phase change material in each battery cell at each monitoring time point include solid state, solid-liquid phase change, liquid state, and liquid-solid phase change.

5. The battery energy storage system management method based on multiple energy optimization according to claim 4 is characterized in that: Analyze the phase change state of the phase change material in each battery cell at each monitoring time point. The specific analysis process is as follows: Get the temperature T of each battery cell at each monitoring time point kn , n is the number of each monitoring time point, n = 1, 2, ... N, N is the total number of monitoring time points; The phase change temperature, latent heat and thermal conductivity of the phase change material in each battery cell at each monitoring time point are obtained and recorded as CL1 kn , CL2 kn , CL3 kn ; Then calculate the state judgment value of the phase change material in each battery cell at each monitoring time point in CG k CY k are the specific heat capacities of the phase change material in the kth battery cell corresponding to the solid and liquid states, respectively, and ΔT is the width of the preset phase change temperature interval; Based on the state judgment value of the phase change material in each battery cell at each monitoring time point, the phase change state of the phase change material in each battery cell at each monitoring time point is judged. The specific judgment process is as follows: If the state judgment value of the phase change material in a battery cell at a certain monitoring time point is 0, it is determined that the phase change state of the phase change material in the battery cell at the monitoring time point is solid; If the state judgment value of the phase change material in a battery cell at a certain monitoring time point is 1, it is determined that the phase change state of the phase change material in the battery cell at the monitoring time point is liquid; If the state judgment value of the phase change material in a battery cell at a certain monitoring time point is within the interval (0, 0.5), it is determined that the phase change state of the phase change material in the battery cell at the monitoring time point is solid-liquid phase change; If the state judgment value of the phase change material in a battery cell at a certain monitoring time point is within the interval [0.5, 1), then it is determined that the phase change state of the phase change material in the battery cell at the monitoring time point is liquid-solid phase change; The phase change state of the phase change material in each battery cell at each monitoring time point is obtained according to the above determination method.

6. The battery energy storage system management method based on multiple energy optimization according to claim 1, characterized in that: Dynamically adjust the charging rate of the battery energy storage system corresponding to the next monitoring time point. The specific adjustment process is as follows: Based on the phase change state of the phase change material in each battery cell at each monitoring time point, a phase change state factor of the phase change material in each battery cell at each monitoring time point is obtained; Then calculate the charging rate of the battery energy storage system corresponding to the next monitoring time point C max is the maximum charging rate of the battery energy storage system, δ1 and δ2 are the set temperature adjustment coefficients and phase change state adjustment coefficients, respectively, which are used to weigh the effects of temperature deviation and phase change state on the charging rate, T is the optimal operating temperature of the battery cell, T kn is the temperature of the kth battery cell at the nth monitoring time point, ε kn represents the phase change state factor of the phase change material in the kth battery cell at the nth monitoring time point; The charging rate of the battery energy storage system corresponding to the next monitoring time point is fed back to the control terminal corresponding to the battery energy storage system, and the control terminal adjusts the charging rate of the battery energy storage system corresponding to the next monitoring time point.

7. The battery energy storage system management method based on multiple energy optimization according to claim 6 is characterized in that: Dynamically adjust the discharge rate of the battery energy storage system corresponding to the next monitoring time point. The specific adjustment process is: Based on the phase change state of the phase change material in each battery cell at each monitoring time point, the discharge rate adjustment coefficient of the phase change material in each battery cell at each monitoring time point is obtained. T k ' n is the temperature of the phase change material in the kth battery cell at the nth monitoring time point, XB k is the phase change enthalpy of the phase change material in the kth battery cell, RL k represents the capacity of the kth battery cell, and τ is a preset calculation constant used to prevent the denominator from being zero; The discharge rate adjustment coefficients of the phase change materials in each battery cell at each monitoring time point are summed and averaged to obtain the average phase change state influencing factor of the phase change materials in each battery cell at the monitoring time point. Then calculate the discharge rate of each battery cell in the battery energy storage system corresponding to the next monitoring time point γ kn is the discharge rate of the kth battery cell at the nth monitoring time point, δ3 and δ4 are the predefined ambient temperature influence coefficient and safety temperature range influence coefficient respectively, T n ′ is the temperature of the external environment of the battery energy storage system at the nth monitoring time point, and Δσ is the safe temperature threshold allowed by the battery unit during operation; The discharge rates of each battery unit in the battery energy storage system corresponding to the next monitoring time point are summarized, summed and averaged to obtain the discharge rate of the battery energy storage system corresponding to the next monitoring time point; and the summed and averaged are fed back to the corresponding control terminal of the battery energy storage system, and the control terminal adjusts the discharge rate of the battery energy storage system corresponding to the next monitoring time point.

8. A battery energy storage system management device based on multiple energy optimization, characterized in that: It is implemented based on the battery energy storage system management method based on multiple energy optimization as described in any one of claims 1 to 7, and includes a processor, a memory and a communication bus; The memory stores a computer-readable program executable by the processor; The communication bus realizes the connection and communication between the processor and the memory; When the processor executes the computer-readable program, it is executed to implement the battery energy storage system management method based on multiple energy optimization as described in any one of claims 1-7.

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