A method and system for temperature risk analysis of energy storage in new energy grid connection

Abstract

The present invention discloses a method and system for analyzing temperature risks of energy storage in new energy grid-connected energy, wherein the method comprises: establishing an electrical model, a thermal model, and a risk analysis model of an energy storage battery; analyzing the interactions among the electrical model, the thermal model, and the risk analysis model, and establishing a correlation relationship among the electrical model, the thermal model, and the risk analysis model; establishing a thermal-electrical-risk coupling model of the energy storage battery based on the correlation relationship; operating the thermal-electrical-risk coupling model in a grid-connected scenario and a constant power charge and discharge scenario, respectively, to obtain temperature and performance degradation parameters of the energy storage battery in the grid-connected scenario and the constant power charge and discharge scenario; and analyzing the impact on the degradation performance of the energy storage battery based on the temperature and performance degradation parameters of the energy storage battery in the grid-connected scenario and the constant power charge and discharge scenario.

Description

Technical Field

[0001] The present invention relates to the field of energy storage technology, and more specifically, to a method and system for temperature risk analysis of energy storage in new energy grid connection. Background Art

[0002] In today's era of continuous pursuit of sustainable development and clean energy, energy storage batteries are becoming a key energy storage solution. Energy storage batteries have a wide range of applications, covering various fields. However, it is important to note that the power characteristics of energy storage vary in different scenarios, changing with the needs of the scenario and also having different impacts on its own performance.

[0003] With the rapid development of new energy, the proportion of clean and renewable energy sources such as wind and photovoltaic power generation in the power system is gradually increasing. Due to the influence of natural and climatic conditions, the uncertain output of wind and photovoltaic power has a certain impact on the stable operation of the power system. Therefore, energy storage batteries, which can smooth the fluctuations of renewable energy output, have been widely used in the integration of new energy into the grid.

[0004] In the process of smoothing the volatility of wind power and photovoltaic power generation, the output of energy storage batteries is affected by the supply and demand relationship on the grid side and has uncertainty, resulting in their electrical performance, thermal performance and safety performance being different from those of batteries in conventional scenarios. Therefore, it is very important to analyze the impact of the uncertain output of energy storage on various aspects of itself when connected to the grid. This is of great significance for promoting the application of energy storage in grid connection and further increasing the proportion of new energy in the energy structure.

[0005] While previous studies have analyzed lithium battery aging and failure in detail, these considerations are limited and lack a comprehensive assessment of the three key aspects of energy storage: electrical, thermal, and risk. Furthermore, no analysis has been conducted on the temperature and risk-related damage caused by the uncertain output of grid-connected energy storage.

[0006] Therefore, a technology is needed to achieve comprehensive analysis of energy storage in new energy grid connection. Summary of the Invention

[0007] The technical solution of the present invention provides a method and system for temperature risk analysis of energy storage in renewable energy grid connection, so as to solve the problem of how to conduct comprehensive analysis of energy storage in renewable energy grid connection.

[0008] In order to solve the above problems, the present invention provides a method for analyzing the temperature risk of energy storage in the new energy grid connection, the method comprising:

[0009] Establish electrical models, thermal models, and risk analysis models for energy storage batteries;

[0010] Analyzing the interaction among the electrical model, the thermal model, and the risk analysis model, and establishing a correlation relationship among the electrical model, the thermal model, and the risk analysis model;

[0011] Based on the correlation, a thermal-electrical-risk coupling model of the energy storage battery is established;

[0012] Running the thermal-electrical-risk coupling model in a grid-connected scenario and a constant power charge-discharge scenario respectively to obtain the temperature and performance attenuation parameters of the energy storage battery in the grid-connected scenario and the constant power charge-discharge scenario;

[0013] Based on the temperature and performance attenuation parameters of the energy storage battery in the grid-connected scenario and the constant power charge and discharge scenario, the impact on the attenuation performance of the energy storage battery is analyzed.

[0014] Preferably, establishing an electrical model of the energy storage battery includes:

[0015] The behavior of the energy storage battery is described based on the second-order equivalent circuit model of the energy storage battery, and the SOC of the energy storage battery is calculated:

[0016]

[0017] Where Q is the energy storage battery capacity, i is the battery current, and t is time;

[0018] The open circuit voltage calculation formula is:

[0019]

[0020] Among them, V 0,max is the open circuit voltage at SOC = 100%, β is the electrical model constant obtained by fitting;

[0021] Terminal voltage V t The calculation formula is:

[0022] V t =V0-V1-V2-R0i(t)

[0023] Among them, V0 is the open circuit voltage of the energy storage battery, V1 and V2 are the voltages at both ends of the parallel RC part, and R0 is the internal resistance of the energy storage battery.

[0024] Preferably, establishing a thermal model of the energy storage battery includes:

[0025] The heat generated by the energy storage battery includes reaction heat, polarization heat and ohmic heat; the heat transfer includes convection heat transfer and radiation heat transfer;

[0026] The calculation formula of the reaction heat is:

[0027]

[0028] Where n is the number of moles of electrons, F is the Faraday constant, E is the electromotive force of the battery, and T is the thermodynamic temperature;

[0029] The calculation formula of the polarization heat is:

[0030] q p =I 2 R p

[0031] where q p is polarization heat generation, I is the current flowing through the battery, R p is the polarization resistance;

[0032] The calculation formula of the ohmic heat is:

[0033] q j =I 2 R1

[0034] Among them, q j is ohmic heat generation, R1 is the internal resistance of the battery;

[0035] The calculation formula for the convective heat transfer is:

[0036] q D =h v A(T b -T e )

[0037] Among them, q D is the convection heat dissipation, h v is the convective heat transfer coefficient, A is the convective heat transfer area, T b is the battery temperature, T e is the ambient temperature;

[0038] The calculation formula for the radiation heat transfer is:

[0039] q r =ε r σ r A((T b +273.15) 4 -(T e +273.15) 4

[0040] Among them, q r is the radiation heat dissipation, ε r is the thermal radiation coefficient, σ r is the Stefan-Boltzmann constant, A is the radiation area;.

[0041] Calculate the energy storage battery temperature:

[0042]

[0043] q c =q g +q p +q j

[0044] q s =q D +q r

[0045] Where M is the battery mass, c p is the battery specific heat capacity, q c The heat generated by the battery, q s Transfer heat to the battery.

[0046] Preferably, the establishing of the risk analysis model for the energy storage battery further includes:

[0047] The Arrhenins equation is used to describe the effect of temperature on the chemical reaction rate of energy storage battery degradation. The formula is:

[0048]

[0049] Among them, r represents the chemical reaction rate under the influence of temperature, that is, the capacity decay rate, k is the Boltzmann constant, and A T is the risk analysis model constant, T is the thermodynamic temperature, E a is the activation energy of the temperature-induced degradation mechanism;

[0050] Obtain the accelerated attenuation factor of energy storage a relative to energy storage b in different scenarios:

[0051]

[0052] Among them, AF T is the acceleration factor under the influence of temperature, T a is the energy storage temperature of the experimental group, T b is the energy storage temperature or baseline temperature of the control group;

[0053] The effect of temperature on the increase of internal resistance is calculated based on the semi-empirical model. The calculation formula is:

[0054]

[0055] Among them, R p is the predicted value of internal resistance under the influence of temperature and cycle number, T is temperature, n is the cycle number, S, U, V, W, Z are the parameters to be fitted;

[0056] When only analyzing the internal resistance increase trend or only qualitatively analyzing the internal resistance increase, other fitted parameters are used, and the formula is:

[0057]

[0058] Preferably, analyzing the interaction among the electrical model, the thermal model and the risk analysis model and establishing an association relationship among the electrical model, the thermal model and the risk analysis model includes:

[0059] Analyzing the effect of the electrical model on the thermal model and risk analysis model, the heat generated inside the energy storage battery is mainly polarization heat and ohmic heat. According to the heat generation formula, its size is affected by the current:

[0060] According to the relationship between the reaction rate of degradation caused by the current of the energy storage battery and the battery current It can be seen that the battery capacity decay rate is affected by the battery current, and the number of cycles affects the increase in battery internal resistance; among them, r I is the capacity decay rate caused by current, E I is the activity factor of the current-induced degradation mechanism, A I is the model constant, I is the current flowing through the battery;

[0061] Analyze the effect of the thermal model on the electrical model and risk analysis model. Under different temperatures, the internal electrical parameters of the energy storage battery are also different. The calculation formula of the open circuit voltage under the influence of temperature is:

[0062]

[0063] V 0,max,T =V 0,max (1+λ V (T-T0))

[0064] β T =β[1+λ β (T-T1)]

[0065] Where T is the battery temperature, T0 is the nominal operating temperature of the battery, V 0,T is the open circuit voltage at temperature T, V 0,max,T is the open circuit voltage at temperature T and SOC = 100%, β T is the thermal model constant at temperature T, λ v is the temperature correlation coefficient of the open circuit voltage V0 of the energy storage battery, V 0,max is the open circuit voltage at temperature T0 and SOC=100%, β is the model parameter at temperature T0, λ β is the temperature dependence coefficient of β;

[0066] The calculation formula for the influence of temperature on the internal resistance of the battery is:

[0067] RT =R(1+λ R (T-T0))

[0068] Among them, R T is the resistance at temperature T, R is the internal resistance at temperature T0, λ R is the temperature correlation coefficient of R;

[0069] Analyze the impact of the risk analysis model on the electrical model and thermal model. The performance degradation of the energy storage battery will cause capacity decay and increased internal resistance. Performance degradation leads to increased internal resistance, which will increase battery heat generation.

[0070] According to another aspect of the present invention, a system for analyzing temperature risks of energy storage in renewable energy grid connection is provided, the system comprising:

[0071] Initial unit, used to establish electrical model, thermal model and risk analysis model of energy storage battery;

[0072] an analyzing unit, configured to analyze the interaction among the electrical model, the thermal model, and the risk analysis model, and establish an association relationship among the electrical model, the thermal model, and the risk analysis model;

[0073] An establishing unit, configured to establish a thermal-electrical-risk coupling model of the energy storage battery based on the association relationship;

[0074] An acquisition unit is used to run the thermal-electric-risk coupling model in a grid-connected scenario and a constant power charge and discharge scenario respectively, and obtain the temperature and performance attenuation parameters of the energy storage battery in the grid-connected scenario and the constant power charge and discharge scenario;

[0075] The result unit is used to analyze the influence on the attenuation performance of the energy storage battery based on the temperature and performance attenuation parameters of the energy storage battery in the grid-connected scenario and the constant power charge and discharge scenario.

[0076] Preferably, the initialization unit is used to establish an electrical model of the energy storage battery and is further used to:

[0077] The behavior of the energy storage battery is described based on the second-order equivalent circuit model of the energy storage battery, and the SOC of the energy storage battery is calculated:

[0078]

[0079] Where Q is the energy storage battery capacity, i is the battery current, and t is time;

[0080] The open circuit voltage calculation formula is:

[0081]

[0082] Among them, V 0,max is the open circuit voltage at SOC = 100%, β is the electrical model constant obtained by fitting;

[0083] Terminal voltage V t The calculation formula is:

[0084] V t =V0-V1-V2-R0i(t)

[0085] Among them, V0 is the open circuit voltage of the energy storage battery, V1 and V2 are the voltages at both ends of the parallel RC part, and R0 is the internal resistance of the energy storage battery.

[0086] Preferably, the initialization unit is used to establish a thermal model of the energy storage battery and is further used to:

[0087] The heat generated by the energy storage battery includes reaction heat, polarization heat and ohmic heat; the heat transfer includes convection heat transfer and radiation heat transfer;

[0088] The calculation formula of the reaction heat is:

[0089]

[0090] Where n is the number of moles of electrons, F is the Faraday constant, E is the electromotive force of the battery, and T is the thermodynamic temperature;

[0091] The calculation formula of the polarization heat is:

[0092] q p =I 2 R p

[0093] where q p is polarization heat generation, I is the current flowing through the battery, R p is the polarization resistance;

[0094] The calculation formula of the ohmic heat is:

[0095] q j =I 2 R1

[0096] Among them, q j is ohmic heat generation, R1 is the internal resistance of the battery;

[0097] The calculation formula for the convective heat transfer is:

[0098] q D =h v A(T b -T e )

[0099] Among them, q D is the convection heat dissipation, hv is the convective heat transfer coefficient, A is the convective heat transfer area, T b is the battery temperature, T e is the ambient temperature;

[0100] The calculation formula for the radiation heat transfer is:

[0101] q r =ε r σ r A((T b +273.15) 4 -(T e +273.15) 4

[0102] Among them, q r is the radiation heat dissipation, ε r is the thermal radiation coefficient, σ r is the Stefan-Boltzmann constant, A is the radiation area;.

[0103] Calculate the energy storage battery temperature:

[0104]

[0105] q c =q g +q p +q j

[0106] q s =q D +q r

[0107] Where M is the battery mass, c p is the battery specific heat capacity, q c The heat generated by the battery, q s Transfer heat to the battery.

[0108] Preferably, the initialization unit is used to establish a risk analysis model for the energy storage battery, and is also used to:

[0109] The Arrhenins equation is used to describe the effect of temperature on the chemical reaction rate of energy storage battery degradation. The formula is:

[0110]

[0111] Among them, r represents the chemical reaction rate under the influence of temperature, that is, the capacity decay rate, k is the Boltzmann constant, and A T is the risk analysis model constant, T is the thermodynamic temperature, E a is the activation energy of the temperature-induced degradation mechanism;

[0112] Obtain the accelerated attenuation factor of energy storage a relative to energy storage b in different scenarios:

[0113]

[0114] Among them, AF T is the acceleration factor under the influence of temperature, T a is the energy storage temperature of the experimental group, T b is the energy storage temperature or baseline temperature of the control group;

[0115] The effect of temperature on the increase of internal resistance is calculated based on the semi-empirical model. The calculation formula is:

[0116]

[0117] Among them, R p is the predicted value of internal resistance under the influence of temperature and cycle number, T is temperature, n is the cycle number, S, U, V, W, Z are the parameters to be fitted;

[0118] When only analyzing the internal resistance increase trend or only qualitatively analyzing the internal resistance increase, other fitted parameters are used, and the formula is:

[0119]

[0120] Preferably, the analysis unit is used to analyze the interaction between the electrical model, the thermal model and the risk analysis model, establish an association relationship between the electrical model, the thermal model and the risk analysis model, and is further used to:

[0121] Analyzing the effect of the electrical model on the thermal model and risk analysis model, the heat generated inside the energy storage battery is mainly polarization heat and ohmic heat. According to the heat generation formula, its size is affected by the current:

[0122] According to the relationship between the reaction rate of degradation caused by the current of the energy storage battery and the battery current It can be seen that the battery capacity decay rate is affected by the battery current, and the number of cycles affects the increase in battery internal resistance; among them, r I is the capacity decay rate caused by current, E I is the activity factor of the current-induced degradation mechanism, A I is the model constant, I is the current flowing through the battery;

[0123] Analyze the effect of the thermal model on the electrical model and risk analysis model. Under different temperatures, the internal electrical parameters of the energy storage battery are also different. The calculation formula of the open circuit voltage under the influence of temperature is:

[0124]

[0125] V0,max,T =V 0,max (1+λ V (T-T0))

[0126] β T =β[1+λ β (T-T1)]

[0127] Where T is the battery temperature, T0 is the nominal operating temperature of the battery, V 0,T is the open circuit voltage at temperature T, V 0,max,T is the open circuit voltage at temperature T and SOC = 100%, β T is the thermal model constant at temperature T, λ v is the temperature correlation coefficient of the open circuit voltage V0 of the energy storage battery, V 0,max is the open circuit voltage at temperature T0 and SOC=100%, β is the model parameter at temperature T0, λ β is the temperature dependence coefficient of β;

[0128] The calculation formula for the influence of temperature on the internal resistance of the battery is:

[0129] R T =R(1+λ R (T-T0))

[0130] Among them, R T is the resistance at temperature T, R is the internal resistance at temperature T0, λ R is the temperature correlation coefficient of R;

[0131] Analyze the impact of the risk analysis model on the electrical model and thermal model. The performance degradation of the energy storage battery will cause capacity decay and increased internal resistance. Performance degradation leads to increased internal resistance, which will increase battery heat generation.

[0132] The technical solution of the present invention provides a method and system for analyzing the temperature risk of energy storage in the grid-connected renewable energy system. The method includes: establishing an electrical model, a thermal model, and a risk analysis model for the energy storage battery; analyzing the interactions between the electrical model, the thermal model, and the risk analysis model, and establishing a correlation between the electrical model, the thermal model, and the risk analysis model; establishing a thermal-electrical-risk coupling model for the energy storage battery based on the correlation; running the thermal-electrical-risk coupling model in a grid-connected scenario and a constant power charge and discharge scenario, respectively, to obtain the temperature and performance degradation parameters of the energy storage battery in the grid-connected scenario and the constant power charge and discharge scenario; and analyzing the impact on the degradation performance of the energy storage battery based on the temperature and performance degradation parameters of the energy storage battery in the grid-connected scenario and the constant power charge and discharge scenario. The technical solution of the present invention fully considers the electrical and thermal characteristics of the energy storage battery, combines the energy storage performance degradation law, establishes a thermal-electrical-risk coupling model for energy storage, and realizes a comprehensive analysis of the energy storage battery. At the same time, combined with the characteristics of wind and solar loads, it simulates the uncertain output of energy storage in the grid-connected scenario, uses the thermal-electrical-risk coupling model to affect the energy storage itself, and realizes a comprehensive assessment of the electrical, thermal, and risk aspects of the energy storage battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0133] A more complete understanding of exemplary embodiments of the present invention may be obtained by referring to the following drawings:

[0134] Figure 1 A flow chart of a method for analyzing temperature risk of energy storage in new energy grid connection according to a preferred embodiment of the present invention;

[0135] Figure 2 This is a flow chart of battery analysis using a thermal-electrical-risk coupled energy storage model in a grid-connected scenario according to a preferred embodiment of the present invention;

[0136] Figure 3 Schematic diagram of a second-order equivalent circuit model of a battery according to a preferred embodiment of the present invention;

[0137] Figure 4 Schematic diagram of a grid-connected energy storage battery model according to a preferred embodiment of the present invention;

[0138] Figure 5 A block diagram of a thermal model of an energy storage battery according to a preferred embodiment of the present invention;

[0139] Figure 6 A block diagram of a risk analysis model for an energy storage battery according to a preferred embodiment of the present invention;

[0140] Figure 7 A block diagram of a thermal-electrical-risk coupling model for energy storage according to a preferred embodiment of the present invention;

[0141] Figure 8A schematic diagram of wind power output according to a preferred embodiment of the present invention;

[0142] Figure 9 A schematic diagram of photovoltaic output according to a preferred embodiment of the present invention;

[0143] Figure 10 A schematic diagram of load size according to a preferred embodiment of the present invention;

[0144] Figure 11 A schematic diagram of energy storage power according to a preferred embodiment of the present invention;

[0145] Figure 12 Schematic diagram of a temperature curve according to a preferred embodiment of the present invention;

[0146] Figure 13 Schematic diagram of capacity fade acceleration factors relative to each other in two scenarios according to a preferred embodiment of the present invention;

[0147] Figure 14 Schematic diagram of capacity fade acceleration factors relative to 25° C. for two scenarios according to a preferred embodiment of the present invention; and

[0148] Figure 15 This is a system structure diagram for temperature risk analysis of energy storage in new energy grid connection according to a preferred embodiment of the present invention. DETAILED DESCRIPTION

[0149] Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to provide a thorough and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments shown in the accompanying drawings is not intended to limit the present invention. In the accompanying drawings, identical elements are denoted by the same reference numerals.

[0150] Unless otherwise specified, the terms used herein (including technical terms) have the meanings commonly understood by those skilled in the art. In addition, it is understood that terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0151] Figure 1 The present invention is a flowchart of a method for analyzing temperature risks of energy storage in new energy grid connection according to a preferred embodiment of the present invention.

[0152] Existing research on the aging and failure of energy storage batteries has achieved some success, but most of these approaches focus on a single aspect, failing to comprehensively evaluate the batteries from the perspectives of electricity, heat, and risk. Furthermore, they fail to analyze the impact of uncertain output on energy storage batteries in grid-connected scenarios. Based on this, the present invention fully considers the electrical and thermal characteristics of energy storage batteries, incorporates the energy storage performance degradation law, establishes a thermal-electrical-risk coupling model for energy storage, and implements a comprehensive analysis of energy storage batteries. Furthermore, by combining the characteristics of wind and solar loads, the present invention simulates the uncertain output of energy storage in grid-connected scenarios, and uses the thermal-electrical-risk coupling model to analyze the impact of the energy storage itself.

[0153] The present invention establishes an electrical model, a thermal model, and a risk analysis model for energy storage batteries, and fully considers the synergistic relationship between the electricity, heat, and risks of energy storage batteries, and establishes a thermal-electrical-risk coupling model for energy storage; according to the relationship between the wind power and photovoltaic output and the load on the grid side, the energy storage power is controlled by the automatic generation control (AGC) system, and the random output of the grid-connected energy storage is simulated. In this scenario, the energy storage thermal-electrical-risk coupling model is simulated to obtain the energy storage temperature and performance degradation related parameter curves, analyze the impact of the uncertain output on the temperature and risk of the energy storage itself, and understand the temperature conditions and aging process of the grid-connected energy storage. At the same time, under the condition of the same input and output power, the thermal-electrical-risk coupling model of the energy storage is controlled to charge and discharge at constant power, and the temperature and performance degradation indicators of the energy storage in the two scenarios are compared to analyze the impact of the uncertainty of the energy storage output on its temperature and risk in the case of grid connection.

[0154] This paper proposes a method for analyzing the temperature and risk of grid-connected energy storage based on a thermal-electrical-risk coupling model. This method has a reasonable theoretical basis, good operability and feasibility, and can realistically simulate the electrical behavior, thermal behavior, and safety status of energy storage in grid-connected scenarios, and analyze the temperature state and aging rate of energy storage under the influence of grid-connected output uncertainty, such as Figure 1 As shown, the method comprises the following steps:

[0155] The present invention provides a method for analyzing temperature risk of energy storage in renewable energy grid connection, the method comprising:

[0156] Step 101: Establish an electrical model, thermal model, and risk analysis model for the energy storage battery; Figure 2 shown.

[0157] The present invention establishes an electrical model of the energy storage battery, and its equivalent circuit model and the energy storage grid control model block diagram are as follows: Figure 3 、 Figure 4 The present invention establishes a thermal model of the energy storage battery, and its model block diagram is shown as follows: Figure 5 The present invention establishes a risk analysis model for energy storage batteries, and its model block diagram is shown as follows: Figure 6 shown.

[0158] Step 102: Analyze the interaction between the electrical model, the thermal model, and the risk analysis model, and establish a correlation relationship between the electrical model, the thermal model, and the risk analysis model;

[0159] The present invention analyzes the interactions among the three major models in the above steps and establishes connections.

[0160] Step 103: Based on the correlation relationship, a thermal-electrical-risk coupling model of the energy storage battery is established;

[0161] The present invention establishes an energy storage heat-electricity-risk coupling model in simulink, and its structural block diagram is as follows Figure 7 shown.

[0162] Step 104: Run the thermal-electrical-risk coupling model in the grid-connected scenario and the constant power charge-discharge scenario respectively to obtain the temperature and performance degradation parameters of the energy storage battery in the grid-connected scenario and the constant power charge-discharge scenario;

[0163] The present invention runs the energy storage thermal-electrical-risk coupling model in the grid-connected scenario and the constant power charging and discharging scenario respectively to obtain curves of relevant parameters such as energy storage temperature, capacity decay acceleration factor, and internal resistance increase.

[0164] Step 105: Based on the temperature and performance attenuation parameters of the energy storage battery in the grid-connected scenario and the constant power charge and discharge scenario, analyze the impact on the attenuation performance of the energy storage battery.

[0165] The present invention compares the simulation results under the two conditions, contrasts the temperature curve fluctuation, maximum value and other indicators of reaction temperature characteristics, and evaluates the battery performance degradation rate based on indicators such as capacity decay acceleration factor, and analyzes the additional impact of uncertainty output on the temperature and performance decay characteristics of energy storage batteries relative to constant power charging and discharging. Figure 2 shown.

[0166] Preferably, establishing an electrical model of the energy storage battery includes:

[0167] The behavior of the energy storage battery is described based on the second-order equivalent circuit model of the energy storage battery, and the SOC of the energy storage battery is calculated:

[0168]

[0169] Where Q is the energy storage battery capacity, i is the battery current, and t is time;

[0170] The open circuit voltage calculation formula is:

[0171]

[0172] Among them, V 0,maxis the open circuit voltage at SOC = 100%, β is the electrical model constant obtained by fitting;

[0173] Terminal voltage V t The calculation formula is:

[0174] V t =V0-V1-V2-R0i(t)

[0175] Among them, V0 is the open circuit voltage of the energy storage battery, V1 and V2 are the voltages at both ends of the parallel RC part, and R0 is the internal resistance of the energy storage battery.

[0176] Since the actual electrical characteristics of the battery are very complex, in order to simplify the analysis, when describing the electrical characteristics of the battery, the present invention generally uses the second-order equivalent circuit model of the battery to approximately describe the behavior of the battery. The second-order equivalent circuit model is as follows: Figure 3 shown.

[0177] Among them, V0 is the open circuit voltage of the battery, which is affected by SOC; R0 is the internal resistance of the battery; V t The charge dynamics model uses two parallel RC components to reflect that the battery cannot respond to load changes and requires some time to reach a steady state. V1 and V2 are the voltages across the parallel RC components.

[0178] Step 1-2: Calculate battery-related electrical parameters.

[0179] (1) The SOC calculation formula is:

[0180]

[0181] Where Q is the battery capacity, i is the battery current, and t is time.

[0182] (2) The formula for calculating the open circuit voltage is:

[0183]

[0184] V 0,max is the open circuit voltage when SOC=100%, and β is the model constant obtained by fitting.

[0185] (3) Terminal voltage V t The calculation formula is:

[0186] V t =V0-V1-V2-R0i(t)

[0187] The present invention connects the energy storage electrical model to the grid, and the grid control model block diagram is as follows: Figure 4As shown in the figure, the grid-connected control phase calculates the difference between the grid-side wind and photovoltaic power output and the grid load, and adds a first-order inertia phase to control the charging and discharging behavior and power level of the energy storage battery. Furthermore, the converter uses dual closed-loop PI control with an outer loop voltage and an inner loop current.

[0188] Preferably, establishing a thermal model of the energy storage battery includes:

[0189] The heat generated by energy storage batteries includes reaction heat, polarization heat and ohmic heat; heat transfer includes convection heat transfer and radiation heat transfer;

[0190] The formula for calculating the heat of reaction is:

[0191]

[0192] Where n is the number of moles of electrons, F is the Faraday constant, E is the electromotive force of the battery, and T is the thermodynamic temperature;

[0193] The calculation formula for polarization heat is:

[0194] q p =I 2 R p

[0195] where q p is polarization heat generation, I is the current flowing through the battery, R p is the polarization resistance;

[0196] The formula for calculating ohmic heat is:

[0197] q j =I 2 R1

[0198] Among them, q j is ohmic heat generation, R1 is the internal resistance of the battery;

[0199] The calculation formula for convective heat transfer is:

[0200] q D =h v A(T b -T e )

[0201] Among them, q D is the convection heat dissipation, h v is the convective heat transfer coefficient, A is the convective heat transfer area, T b is the battery temperature, T e is the ambient temperature;

[0202] The calculation formula for radiation heat transfer is:

[0203] q r =ε r σr A((T b +273.15) 4 -(T e +273.15) 4

[0204] Among them, q r is the radiation heat dissipation, ε r is the thermal radiation coefficient, σ r is the Stefan-Boltzmann constant, A is the radiation area;.

[0205] Calculate the energy storage battery temperature:

[0206]

[0207] q c =q g +q p +q j

[0208] q s =q D +q r

[0209] Where M is the battery mass, c p is the battery specific heat capacity, q c The heat generated by the battery, q s Transfer heat to the battery.

[0210] The present invention analyzes the heat generation and heat transfer modes of energy storage batteries, wherein heat generation includes reaction heat, polarization heat and ohmic heat; and heat transfer includes convection heat transfer and radiation heat transfer.

[0211] The present invention calculates the heat generated by the energy storage battery.

[0212] (1) Reaction heat refers to the heat released by chemical reactions during the battery charging and discharging process. Its calculation formula is:

[0213]

[0214] Where n is the number of moles of electrons, F is the Faraday constant, which is approximately 96485C / mol, E is the electromotive force of the battery in J / C, and T is the thermodynamic temperature in K.

[0215] (2) The internal polarization of the battery is usually divided into electrochemical polarization and concentration polarization. Electrochemical polarization mainly comes from the electrochemical reaction process of the battery, and concentration polarization is caused by the concentration gradient of the active substance in the electrolyte. The calculation formula for polarization heat generation is as follows:

[0216] q p =I 2 R p

[0217] where q p is polarization heat generation, I is the current flowing through the battery, R p is the polarization resistance.

[0218] (3) The ohmic heat generated inside the battery is the heat generated by the current flowing through the resistance inside the battery. The formula is:

[0219] q j =I 2 R1

[0220] Among them, q j is ohmic heat generation, and R1 is the internal resistance of the battery.

[0221] The present invention calculates the heat transfer of energy storage batteries.

[0222] (1) Convection is the process of transferring heat through the flow of fluid (such as liquid or gas). Convective heat dissipation occurs on the surface of the battery and is calculated as follows:

[0223] q D =h v A(T b -T e )

[0224] Among them, q D is the convection heat dissipation, h v is the convective heat transfer coefficient, A is the convective heat transfer area, T b is the battery temperature, T e is the ambient temperature.

[0225] (2) Radiation is the process of transferring heat through electromagnetic radiation. Although radiation heat dissipation is relatively small in battery heat transfer, it can reversibly affect the thermal balance of the battery at high temperatures. According to the Stefan-Boltzmann equation, its calculation formula is as follows:

[0226] q r =ε r σ r A((T b +273.15) 4 -(T e +273.15) 4

[0227] Among them, q r is the radiation heat dissipation, ε r is the thermal radiation coefficient, σ r is the Stefan-Boltzmann constant, and A is the radiation area.

[0228] The present invention calculates the temperature of the energy storage battery.

[0229] Ignore the uneven heat generation of the battery, consider the temperature of the entire battery to be uniform, write the heat balance equation, and solve for the battery temperature.

[0230]

[0231] q c =q g +q p +q j

[0232] q s =q D +q r

[0233] Where M is the battery mass, c p is the battery specific heat capacity, q c The heat generated by the battery, q s Transfer heat to the battery.

[0234] Preferably, establishing a risk analysis model for energy storage batteries further includes:

[0235] The Arrhenins equation is used to describe the effect of temperature on the chemical reaction rate of energy storage battery degradation. The formula is:

[0236]

[0237] Among them, r represents the chemical reaction rate under the influence of temperature, that is, the capacity decay rate, k is the Boltzmann constant, and A T is the risk analysis model constant, T is the thermodynamic temperature, E a is the activation energy of the temperature-induced degradation mechanism;

[0238] Obtain the accelerated attenuation factor of energy storage a relative to energy storage b in different scenarios:

[0239]

[0240] Among them, AF T is the acceleration factor under the influence of temperature, T a is the energy storage temperature of the experimental group, T b is the energy storage temperature or baseline temperature of the control group;

[0241] The effect of temperature on the increase of internal resistance is calculated based on the semi-empirical model. The calculation formula is:

[0242]

[0243] Among them, R p is the predicted value of internal resistance under the influence of temperature and cycle number, T is temperature, n is the cycle number, S, U, V, W, Z are the parameters to be fitted;

[0244] When only analyzing the internal resistance increase trend or only qualitatively analyzing the internal resistance increase, other fitted parameters are used, and the formula is:

[0245]

[0246] The capacity of the present invention is an indicator of the energy storage capacity of the battery. The Arrhenins equation is used to describe the effect of temperature on the chemical reaction rate of energy storage degradation. The formula is as follows:

[0247]

[0248] Among them, r T It represents the chemical reaction rate under the influence of temperature, that is, the capacity attenuation rate, k is the Boltzmann constant, A T is the model constant, T is the thermodynamic temperature, E a is the activation energy of the temperature-induced degradation mechanism.

[0249] Based on the formula, the present invention can calculate the accelerated attenuation factor of energy storage a relative to energy storage b in different scenarios.

[0250]

[0251] Among them, AF T is the acceleration factor under the influence of temperature, T a is the energy storage temperature of the experimental group, T b is the control group energy storage temperature or the reference temperature. This paper can be used to solve the accelerated attenuation factors of grid-connected energy storage and constant power charge and discharge energy storage relative to each other, as well as the accelerated attenuation factors of the two relative to the reference temperature.

[0252] Internal resistance is an indicator of battery output power. This paper uses a semi-empirical model to calculate the effect of temperature on the increase in internal resistance. The calculation formula is as follows:

[0253]

[0254] Among them, R p is the predicted value of internal resistance under the influence of temperature and cycle number, T is temperature, n is the cycle number, S, U, V, W, and Z are the parameters to be fitted.

[0255] When only analyzing the internal resistance increase trend or only qualitatively analyzing the internal resistance increase, other fitted parameters can be used. The formula is as follows:

[0256]

[0257] Preferably, analyzing the interaction between the electrical model, the thermal model, and the risk analysis model, and establishing a correlation relationship between the electrical model, the thermal model, and the risk analysis model, includes:

[0258] Analyzing the effect of the electrical model on the thermal model and risk analysis model, the heat generated inside the energy storage battery is mainly polarization heat and ohmic heat. According to the heat generation formula, its size is affected by the current:

[0259] According to the relationship between the reaction rate of degradation caused by the current of the energy storage battery and the battery current It can be seen that the battery capacity decay rate is affected by the battery current, and the number of cycles affects the increase in battery internal resistance; among them, r I is the capacity decay rate caused by current, E I is the activity factor of the current-induced degradation mechanism, A I is the model constant, I is the current flowing through the battery;

[0260] Analyze the effect of the thermal model on the electrical model and risk analysis model. Under different temperatures, the internal electrical parameters of the energy storage battery are also different. The calculation formula of the open circuit voltage under the influence of temperature is:

[0261]

[0262] V 0,max,T =V 0,max (1+λ V (T-T0))

[0263] β T =β[1+λ β (T-T1)]

[0264] Where T is the battery temperature, T0 is the nominal operating temperature of the battery, V 0,T is the open circuit voltage at temperature T, V 0,max,T is the open circuit voltage at temperature T and SOC = 100%, β T is the thermal model constant at temperature T, λ v is the temperature correlation coefficient of the open circuit voltage V0 of the energy storage battery, V 0,max is the open circuit voltage at temperature T0 and SOC=100%, β is the model parameter at temperature T0, λ β is the temperature dependence coefficient of β;

[0265] The calculation formula for the influence of temperature on the internal resistance of the battery is:

[0266] R T =R(1+λ R (T-T0))

[0267] Among them, R T is the resistance at temperature T, R is the internal resistance at temperature T0, λ R is the temperature correlation coefficient of R;

[0268] Analyze the impact of the risk analysis model on the electrical model and thermal model. The performance degradation of the energy storage battery will cause capacity decay and increased internal resistance. Performance degradation leads to increased internal resistance, which will increase battery heat generation.

[0269] The present invention analyzes the effect of the electrical model on the thermal model and the risk analysis model.

[0270] (1) The heat generated inside the battery is mainly polarization heat and ohmic heat. According to the heat generation formula, its size is affected by the current.

[0271] (2) According to the relationship formula between the reaction rate of degradation caused by battery current and battery current It can be seen that the battery capacity decay rate is affected by the battery current, and the number of cycles affects the increase in battery internal resistance.

[0272] The present invention analyzes the effect of the thermal model on the electrical model and the risk analysis model.

[0273] (1) The electrical parameters inside the battery are different at different temperatures.

[0274] The calculation formula of open circuit voltage under the influence of temperature is:

[0275]

[0276] V 0,max,T =V 0,max (1+λ V (T-T0))

[0277] β T =β[1+λ β (T-T1)]

[0278] Where T is the battery temperature, T0 is the nominal operating temperature of the battery, V 0,T is the open circuit voltage at temperature T, V 0,max,T is the open circuit voltage at temperature T and SOC = 100%, β T is the model constant at temperature T, λ v is the temperature dependence coefficient of V0, V 0,max is the open circuit voltage at temperature T0 and SOC=100%, β is the model parameter at temperature T0, λ β is the temperature dependence coefficient of β.

[0279] The calculation formula for the influence of temperature on the internal resistance of the battery is:

[0280] R T =R(1+λ R (T-T0))

[0281] R Tis the resistance at temperature T, R is the internal resistance at temperature T0, λ R is the temperature dependence coefficient of R.

[0282] (2) Temperature is the main factor affecting battery performance aging. From the risk analysis model in step 2, it can be seen that capacity attenuation and internal resistance increase are both related to temperature.

[0283] The present invention analyzes the effect of the risk analysis model on the electrical model and the thermal model.

[0284] (1) Battery performance degradation will cause capacity decay and internal resistance increase. The specific formula is shown in step 3.

[0285] (2) Performance degradation leads to increased internal resistance, which will increase battery heat generation.

[0286] A comprehensive analysis and calculation of the electrical characteristics, thermal characteristics and risk-related performance indicators of the energy storage system were carried out, and the mutual influence between electricity, heat and risk was fully considered. A thermal-electricity-risk coupling model of energy storage was established, which can effectively respond to changes in various external conditions of energy storage and realize comprehensive analysis of energy storage under various working conditions.

[0287] By running the energy storage thermal-electric-risk coupling model under the influence of uncertain output and constant power charging and discharging scenarios, and comparing the differences in parameters such as temperature and capacity decay acceleration factor, it is possible to show the impact of random output on the relevant characteristics of the energy storage itself.

[0288] The energy storage heat-electricity-risk coupling model can not only be applied to energy storage analysis in wind power and photovoltaic AGC system control scenarios, but also has wide adaptability and can be used for comprehensive analysis of the electricity, heat and risk aspects of energy storage systems in various scenarios, providing a powerful tool for comprehensive analysis of energy storage systems.

[0289] The present invention verifies the effectiveness of the method by analyzing the temperature and risk of energy storage in a wind-solar-storage grid-connected system.

[0290] Obtain the power curve of wind power output, photovoltaic output and load size in the wind-solar-storage grid-connected system for one day, and obtain the output power of the energy storage battery under the control of the AGC system, such as Figures 8 to 11 shown.

[0291] The simulation time of the present invention is 1 day. The battery parameters are selected from the data built into the "Battery (Table-Based)" module. The battery parameters with Part number U27_36XP, Manufacturer Valence, and Battery Type Lithium-ion (rated voltage 38.4V, rated capacity 50A*hr, and other parameters are not listed due to space reasons) are selected.

[0292] The ambient temperature is a random number between 295K and 300K.

[0293] At the same time, the positive and negative parts of the energy storage power curve are integrated respectively to obtain the charge and discharge amount of the energy storage battery under AGC control in one day. The absolute values ​​are added and then divided by time to obtain the power of the constant power energy storage battery under the same energy storage charge and discharge amount under AGC control in one day. The charge and discharge time is determined according to the ratio of the charge and discharge amount. The formula is as follows:

[0294]

[0295]

[0296]

[0297] Among them, P h E is the power of constant power charging and discharging energy storage battery; c is the charge capacity, E d is the discharge capacity (E c 、E d are all positive values), t is the time of one day (86400 seconds), t c Battery charging time, t d is the battery discharge time.

[0298] A one-day simulation of grid-connected energy storage and constant power charge and discharge energy storage was conducted to compare the temperature and performance degradation characteristics of the two cases. The simulation results are as follows: Figure 12-14 shown.

[0299] By comparing the temperature curves under two scenarios, it can be seen that compared with constant power charge and discharge batteries, the temperature curve of grid-connected energy storage fluctuates greatly under the influence of impact current and current fluctuations. During high-power discharge, excessively high temperatures occur, with the highest temperature reaching 83°C. Excessive temperature not only accelerates battery aging, but also faces the risk of thermal runaway.

[0300] The capacity decay acceleration factors in the two scenarios relative to each other show that the capacity decay rate is not linearly related to temperature. When the temperature of the grid-connected energy storage is high, the capacity decay rate doubles, and the acceleration factor of the grid-connected energy storage relative to the constant power charge and discharge energy storage reaches a maximum of 8.21, meaning that the capacity decay rate is 8.21 times that of the constant power charge and discharge energy storage. While the acceleration factor of the constant power charge and discharge battery relative to the grid-connected energy storage does exceed 1 in some regions, the acceleration factor is generally small, reaching a maximum of only 2.67. This shows that the uncertain output of the grid-connected energy storage accelerates the capacity decay of the electric energy.

[0301] In order to more intuitively display the impact of uncertain output on the aging rate of charging performance, the present invention calculates the acceleration factor of energy storage under two scenarios relative to 25 degrees Celsius. It can be seen that the maximum acceleration factor of grid-connected energy storage is 26.33, that is, its decay rate is 26.33 times that at 25 degrees Celsius; the maximum value of constant power charge and discharge battery is only 3.79. Taking the average value of the two curves, it can be obtained that the average acceleration factor of grid-connected energy storage is 6.89, and that of constant power battery energy storage is 3.61, that is, the average decay rate of grid-connected energy storage is 1.91 times that of constant power battery energy storage, and its lifespan is only 0.53 of that of constant power charge and discharge battery. This can provide an intuitive understanding of the role of uncertain output in accelerating battery capacity decay.

[0302] like Figure 15 As shown, the present invention provides a system for analyzing temperature risks of energy storage in new energy grid connection, the system comprising:

[0303] Initialization unit 1501, used to establish an electrical model, a thermal model, and a risk analysis model of the energy storage battery;

[0304] An analysis unit 1502 is configured to analyze the interaction between the electrical model, the thermal model, and the risk analysis model, and establish a correlation relationship between the electrical model, the thermal model, and the risk analysis model;

[0305] An establishing unit 1503 is used to establish a thermal-electrical-risk coupling model of the energy storage battery based on the association relationship;

[0306] An acquisition unit 1504 is configured to run a thermal-electrical-risk coupling model in a grid-connected scenario and a constant power charge-discharge scenario, respectively, to acquire temperature and performance degradation parameters of the energy storage battery in the grid-connected scenario and the constant power charge-discharge scenario;

[0307] The result unit 1505 is used to analyze the influence on the attenuation performance of the energy storage battery based on the temperature and performance attenuation parameters of the energy storage battery in the grid-connected scenario and the constant power charge and discharge scenario.

[0308] Preferably, the initialization unit 1501 is used to establish an electrical model of the energy storage battery and is also used to:

[0309] The behavior of the energy storage battery is described based on the second-order equivalent circuit model of the energy storage battery, and the SOC of the energy storage battery is calculated:

[0310]

[0311] Where Q is the energy storage battery capacity, i is the battery current, and t is time;

[0312] The open circuit voltage calculation formula is:

[0313]

[0314] Among them, V 0,max is the open circuit voltage at SOC = 100%, β is the electrical model constant obtained by fitting;

[0315] Terminal voltage V t The calculation formula is:

[0316] V t =V0-V1-V2-R0i(t)

[0317] Among them, V0 is the open circuit voltage of the energy storage battery, V1 and V2 are the voltages at both ends of the parallel RC part, and R0 is the internal resistance of the energy storage battery.

[0318] Preferably, the initialization unit 1501 is used to establish a thermal model of the energy storage battery and is also used to:

[0319] The heat generated by energy storage batteries includes reaction heat, polarization heat and ohmic heat; heat transfer includes convection heat transfer and radiation heat transfer;

[0320] The formula for calculating the heat of reaction is:

[0321]

[0322] Where n is the number of moles of electrons, F is the Faraday constant, E is the electromotive force of the battery, and T is the thermodynamic temperature;

[0323] The calculation formula for polarization heat is:

[0324] q p =I 2 R p

[0325] where q p is polarization heat generation, I is the current flowing through the battery, R p is the polarization resistance;

[0326] The formula for calculating ohmic heat is:

[0327] q j =I 2 R1

[0328] Among them, q j is ohmic heat generation, R1 is the internal resistance of the battery;

[0329] The calculation formula for convective heat transfer is:

[0330] q D =h v A(T b -T e )

[0331] Among them, q Dis the convection heat dissipation, h v is the convective heat transfer coefficient, A is the convective heat transfer area, T b is the battery temperature, T e is the ambient temperature;

[0332] The calculation formula for radiation heat transfer is:

[0333] q r =ε r σ r A((T b +273.15) 4 -(T e +273.15) 4

[0334] Among them, q r is the radiation heat dissipation, ε r is the thermal radiation coefficient, σ r is the Stefan-Boltzmann constant, A is the radiation area;.

[0335] Calculate the energy storage battery temperature:

[0336]

[0337] q c =q g +q p +q j

[0338] q s =q D +q r

[0339] Where M is the battery mass, c p is the battery specific heat capacity, q c The heat generated by the battery, q s Transfer heat to the battery.

[0340] Preferably, the initialization unit 1501 is used to establish a risk analysis model for the energy storage battery, and is also used to:

[0341] The Arrhenins equation is used to describe the effect of temperature on the chemical reaction rate of energy storage battery degradation. The formula is:

[0342]

[0343] Among them, r represents the chemical reaction rate under the influence of temperature, that is, the capacity decay rate, k is the Boltzmann constant, and A T is the risk analysis model constant, T is the thermodynamic temperature, E a is the activation energy of the temperature-induced degradation mechanism;

[0344] Obtain the accelerated attenuation factor of energy storage a relative to energy storage b in different scenarios:

[0345]

[0346] Among them, AF T is the acceleration factor under the influence of temperature, T a is the energy storage temperature of the experimental group, T b is the energy storage temperature or baseline temperature of the control group;

[0347] The effect of temperature on the increase of internal resistance is calculated based on the semi-empirical model. The calculation formula is:

[0348]

[0349] Among them, R p is the predicted value of internal resistance under the influence of temperature and cycle number, T is temperature, n is the cycle number, S, U, V, W, Z are the parameters to be fitted;

[0350] When only analyzing the internal resistance increase trend or only qualitatively analyzing the internal resistance increase, other fitted parameters are used, and the formula is:

[0351]

[0352] Preferably, the analysis unit 1502 is configured to analyze the interaction between the electrical model, the thermal model, and the risk analysis model, establish an association relationship between the electrical model, the thermal model, and the risk analysis model, and further configured to:

[0353] Analyzing the effect of the electrical model on the thermal model and risk analysis model, the heat generated inside the energy storage battery is mainly polarization heat and ohmic heat. According to the heat generation formula, its size is affected by the current:

[0354] According to the relationship between the reaction rate of degradation caused by the current of the energy storage battery and the battery current It can be seen that the battery capacity decay rate is affected by the battery current, and the number of cycles affects the increase in battery internal resistance; among them, r I is the capacity decay rate caused by current, E I is the activity factor of the current-induced degradation mechanism, A I is the model constant, I is the current flowing through the battery;

[0355] Analyze the effect of the thermal model on the electrical model and risk analysis model. Under different temperatures, the internal electrical parameters of the energy storage battery are also different. The calculation formula of the open circuit voltage under the influence of temperature is:

[0356]

[0357] V 0,max,T=V 0,max (1+λ V (T-T0))

[0358] β T =β[1+λ β (T-T1)]

[0359] Where T is the battery temperature, T0 is the nominal operating temperature of the battery, V 0,T is the open circuit voltage at temperature T, V 0,max,T is the open circuit voltage at temperature T and SOC = 100%, β T is the thermal model constant at temperature T, λ v is the temperature correlation coefficient of the open circuit voltage V0 of the energy storage battery, V 0,max is the open circuit voltage at temperature T0 and SOC=100%, β is the model parameter at temperature T0, λ β is the temperature dependence coefficient of β;

[0360] The calculation formula for the influence of temperature on the internal resistance of the battery is:

[0361] R T =R(1+λ R (T-T0))

[0362] Among them, R T is the resistance at temperature T, R is the internal resistance at temperature T0, λ R is the temperature correlation coefficient of R;

[0363] Analyze the impact of the risk analysis model on the electrical model and thermal model. The performance degradation of the energy storage battery will cause capacity decay and increased internal resistance. Performance degradation leads to increased internal resistance, which will increase battery heat generation.

[0364] A system for analyzing temperature risks of energy storage in a new energy grid-connected system according to a preferred embodiment of the present invention corresponds to a method for analyzing temperature risks of energy storage in a new energy grid-connected system according to another preferred embodiment of the present invention, and will not be described in detail here.

[0365] It will be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention may be implemented in various computer languages, for example, the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0366] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0367] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0368] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0369] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0370] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

[0371] The invention has been described above with reference to a few embodiments. However, it is readily apparent to a person skilled in the art that other embodiments than the ones disclosed above are equally within the scope of the invention, as defined by the appended patent claims.

[0372] Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to "a / the [means, component, etc.]" are to be interpreted openly as referring to at least one instance of the means, component, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not necessarily need to be performed in the exact order disclosed, unless explicitly stated otherwise.

Claims

1. A method for analyzing temperature risk of energy storage in renewable energy grid connection, the method comprising: Establish electrical models, thermal models, and risk analysis models for energy storage batteries; Analyzing the interaction among the electrical model, the thermal model, and the risk analysis model, and establishing a correlation relationship among the electrical model, the thermal model, and the risk analysis model; Based on the correlation, a thermal-electrical-risk coupling model of the energy storage battery is established; Running the thermal-electrical-risk coupling model in a grid-connected scenario and a constant power charge-discharge scenario respectively to obtain the temperature and performance attenuation parameters of the energy storage battery in the grid-connected scenario and the constant power charge-discharge scenario; Based on the temperature and performance attenuation parameters of the energy storage battery in the grid-connected scenario and the constant power charge and discharge scenario, the impact on the attenuation performance of the energy storage battery is analyzed.

2. The method according to claim 1, wherein establishing an electrical model of the energy storage battery comprises: The behavior of the energy storage battery is described based on the second-order equivalent circuit model of the energy storage battery, and the SOC of the energy storage battery is calculated: Where Q is the energy storage battery capacity, i is the battery current, and t is time; The open circuit voltage calculation formula is: Among them, V 0,max is the open circuit voltage at SOC = 100%, β is the electrical model constant obtained by fitting; Terminal voltage V t The calculation formula is: In t =V0-V1-V 2- R0i(t) Among them, V0 is the open circuit voltage of the energy storage battery, V1 and V2 are the voltages at both ends of the parallel RC part, and R0 is the internal resistance of the energy storage battery.

3. The method according to claim 1, wherein establishing a thermal model of the energy storage battery comprises: The heat generated by the energy storage battery includes reaction heat, polarization heat and ohmic heat; the heat transfer includes convection heat transfer and radiation heat transfer; The calculation formula of the reaction heat is: Where n is the number of moles of electrons, F is the Faraday constant, E is the electromotive force of the battery, and T is the thermodynamic temperature; The calculation formula of the polarization heat is: q p =I 2 R p where q p is polarization heat generation, I is the current flowing through the battery, R p is the polarization resistance; The calculation formula of the ohmic heat is: q j =I 2 R1 Among them, q j is ohmic heat generation, R1 is the internal resistance of the battery; The calculation formula for the convective heat transfer is: q D =h v A(T b -T e ) Among them, q D is the convection heat dissipation, h v is the convective heat transfer coefficient, A is the convective heat transfer area, T b is the battery temperature, T e is the ambient temperature; The calculation formula for the radiation heat transfer is: q r =e r s r A((T b +273.15) 4 -(T e +273.15) 4 Among them, q r is the radiation heat dissipation, ε r is the thermal radiation coefficient, σ r is the Stefan-Boltzmann constant, A is the radiation area; Calculate the energy storage battery temperature: q c =q g +q p+ q j q s =q D+ q r Where M is the battery mass, c p is the battery specific heat capacity, q c The heat generated by the battery, q s Transfer heat to the battery.

4. The method according to claim 1, wherein establishing a risk analysis model for an energy storage battery further comprises: The Arrhenins equation is used to describe the effect of temperature on the chemical reaction rate of energy storage battery degradation. The formula is: Among them, r represents the chemical reaction rate under the influence of temperature, that is, the capacity decay rate, k is the Boltzmann constant, and A T is the risk analysis model constant, T is the thermodynamic temperature, E a is the activation energy of the temperature-induced degradation mechanism; Obtain the accelerated attenuation factor of energy storage a relative to energy storage b in different scenarios: Among them, AF T is the acceleration factor under the influence of temperature, T a is the energy storage temperature of the experimental group, T b is the energy storage temperature or baseline temperature of the control group; The effect of temperature on the increase of internal resistance is calculated based on the semi-empirical model. The calculation formula is: Among them, R p is the predicted value of internal resistance under the influence of temperature and cycle number, T is temperature, n is the cycle number, S, U, V, W, Z are the parameters to be fitted; When only analyzing the internal resistance increase trend or only qualitatively analyzing the internal resistance increase, other fitted parameters are used, and the formula is:

5. The method according to claim 1, wherein analyzing the interaction among the electrical model, the thermal model, and the risk analysis model and establishing an association relationship among the electrical model, the thermal model, and the risk analysis model comprises: Analyzing the effect of the electrical model on the thermal model and risk analysis model, the heat generated inside the energy storage battery is mainly polarization heat and ohmic heat. According to the heat generation formula, its size is affected by the current: According to the relationship between the reaction rate of degradation caused by the current of the energy storage battery and the battery current It can be seen that the battery capacity decay rate is affected by the battery current, and the number of cycles affects the increase in battery internal resistance; among them, r I is the capacity decay rate caused by current, E I is the activity factor of the current-induced degradation mechanism, A I is the model constant, I is the current flowing through the battery; Analyze the effect of the thermal model on the electrical model and risk analysis model. Under different temperatures, the internal electrical parameters of the energy storage battery are also different. The calculation formula of the open circuit voltage under the influence of temperature is: Where T is the battery temperature, T0 is the nominal operating temperature of the battery, V 0,T is the open circuit voltage at temperature T, V 0,max,T is the open circuit voltage at temperature T and SOC = 100%, β T is the thermal model constant at temperature T, λ v is the temperature correlation coefficient of the open circuit voltage V0 of the energy storage battery, V 0,max is the open circuit voltage at temperature T0 and SOC=100%, β is the model parameter at temperature T0, λ β is the temperature dependence coefficient of β; The calculation formula for the influence of temperature on the internal resistance of the battery is: Among them, R T is the resistance at temperature T, R is the internal resistance at temperature T0, λ R is the temperature correlation coefficient of R; Analyze the impact of the risk analysis model on the electrical model and thermal model. The performance degradation of the energy storage battery will cause capacity decay and increased internal resistance. Performance degradation leads to increased internal resistance, which will increase battery heat generation.

6. A system for analyzing temperature risk of energy storage in renewable energy grid connection, the system comprising: Initial unit, used to establish electrical model, thermal model and risk analysis model of energy storage battery; an analyzing unit, configured to analyze the interaction among the electrical model, the thermal model, and the risk analysis model, and establish an association relationship among the electrical model, the thermal model, and the risk analysis model; An establishing unit, configured to establish a thermal-electrical-risk coupling model of the energy storage battery based on the association relationship; An acquisition unit is used to run the thermal-electric-risk coupling model in a grid-connected scenario and a constant power charge and discharge scenario respectively, and obtain the temperature and performance attenuation parameters of the energy storage battery in the grid-connected scenario and the constant power charge and discharge scenario; The result unit is used to analyze the influence on the attenuation performance of the energy storage battery based on the temperature and performance attenuation parameters of the energy storage battery in the grid-connected scenario and the constant power charge and discharge scenario.

7. The system according to claim 6, wherein the initialization unit is used to establish an electrical model of the energy storage battery, and is further used to: The behavior of the energy storage battery is described based on the second-order equivalent circuit model of the energy storage battery, and the SOC of the energy storage battery is calculated: in, Q is the energy storage battery capacity, i is the battery current, and t is the time; The open circuit voltage calculation formula is: Among them, V 0,max is the open circuit voltage at SOC = 100%, β is the electrical model constant obtained by fitting; Terminal voltage V t The calculation formula is: Among them, V0 is the open circuit voltage of the energy storage battery, V1 and V2 are the voltages at both ends of the parallel RC part, and R0 is the internal resistance of the energy storage battery.

8. The system according to claim 6, wherein the initialization unit is used to establish a thermal model of the energy storage battery, and is further used to: The heat generation of the energy storage battery includes: Reaction heat, polarization heat and ohmic heat; heat transfer includes convection heat transfer and radiation heat transfer; The calculation formula of the reaction heat is: Where n is the number of moles of electrons, F is the Faraday constant, E is the electromotive force of the battery, and T is the thermodynamic temperature; The calculation formula of the polarization heat is: where q p is polarization heat generation, I is the current flowing through the battery, R p is the polarization resistance; The calculation formula of the ohmic heat is: Among them, q j is ohmic heat generation, R1 is the internal resistance of the battery; The calculation formula for the convective heat transfer is: Among them, q D is the convection heat dissipation, h v is the convective heat transfer coefficient, A is the convective heat transfer area, T b is the battery temperature, T e is the ambient temperature; The calculation formula for the radiation heat transfer is: Among them, q r is the radiation heat dissipation, ε r is the thermal radiation coefficient, σ r is the Stefan-Boltzmann constant, A is the radiation area;. Calculate the energy storage battery temperature: Where M is the battery mass, c p is the battery specific heat capacity, q c The heat generated by the battery, q s Transfer heat to the battery.

9. The system according to claim 6, wherein the initialization unit is used to establish a risk analysis model for the energy storage battery, and is further used to: The Arrhenins equation is used to describe the effect of temperature on the chemical reaction rate of energy storage battery degradation. The formula is: in, r represents the chemical reaction rate under the influence of temperature, that is, the capacity decay rate, k is the Boltzmann constant, A T is the risk analysis model constant, T is the thermodynamic temperature, E a is the activation energy of the temperature-induced degradation mechanism; Obtain the accelerated attenuation factor of energy storage a relative to energy storage b in different scenarios: Among them, AF T is the acceleration factor under the influence of temperature, T a is the energy storage temperature of the experimental group, T b is the energy storage temperature or baseline temperature of the control group; The effect of temperature on the increase of internal resistance is calculated based on the semi-empirical model. The calculation formula is: Among them, R p is the predicted value of internal resistance under the influence of temperature and cycle number, T is temperature, n is the cycle number, S, U, V, W, Z are the parameters to be fitted; When only analyzing the internal resistance increase trend or only qualitatively analyzing the internal resistance increase, other fitted parameters are used, and the formula is:

10. The system according to claim 6, wherein the analysis unit is configured to analyze the interaction between the electrical model, the thermal model, and the risk analysis model, establish an association relationship between the electrical model, the thermal model, and the risk analysis model, and further configured to: Analyzing the effect of the electrical model on the thermal model and risk analysis model, the heat generated inside the energy storage battery is mainly polarization heat and ohmic heat. According to the heat generation formula, its size is affected by the current: According to the relationship between the reaction rate of degradation caused by the current of the energy storage battery and the battery current It can be seen that the battery capacity decay rate is affected by the battery current, and the number of cycles affects the increase in battery internal resistance; r I is the capacity decay rate caused by current, E I is the activity factor of the current-induced degradation mechanism, A I is the model constant, I is the current flowing through the battery; Analyze the effect of the thermal model on the electrical model and risk analysis model. Under different temperatures, the internal electrical parameters of the energy storage battery are also different. The calculation formula of the open circuit voltage under the influence of temperature is: Where T is the battery temperature, T0 is the nominal operating temperature of the battery, V 0,T is the open circuit voltage at temperature T, V 0,max,T is the open circuit voltage at temperature T and SOC = 100%, β T is the thermal model constant at temperature T, λ v is the temperature correlation coefficient of the open circuit voltage V0 of the energy storage battery, V 0,max is the open circuit voltage at temperature T0 and SOC=100%, β is the model parameter at temperature T0, λ β is the temperature dependence coefficient of β; The calculation formula for the influence of temperature on the internal resistance of the battery is: Among them, R T is the resistance at temperature T, R is the internal resistance at temperature T0, λ R is the temperature correlation coefficient of R; Analyze the impact of the risk analysis model on the electrical model and thermal model. The performance degradation of the energy storage battery will cause capacity decay and increased internal resistance. Performance degradation leads to increased internal resistance, which will increase battery heat generation.

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