Energy storage device battery preheating control method, computer device and storage medium

Abstract

This application relates to a method for controlling battery preheating in an energy storage device, a computer device, and a storage medium, and relates to the technical field of battery temperature control. This application obtains the thermal impact parameters of the energy storage device, constructs a temperature control equation for the energy storage device based on the thermal impact parameters, and generates control signals for controlling the water supply temperature and air supply temperature based on the thermal impact parameter values ​​at the start of heating. This allows for precise control of the DC fast charging peak power temperature of the energy storage device at the start of heating, shortening the DC fast charging time by ensuring that the battery cells reach peak power, and improving the response speed and accuracy of the energy storage device battery preheating control.

Description

Technical Field

[0001] The present application relates to the technical field of battery temperature control, and in particular to a method for controlling battery preheating of an energy storage device, a computer device, and a storage medium. Background Art

[0002] Batteries in energy storage devices generate heat during discharge. Air or water cooling is typically used to dissipate heat within the device. Furthermore, when the device is in standby mode, the battery temperature drops to room temperature. When the device transitions from standby mode to charging, the low battery temperature can slow the charging rate if the device is located in a low-temperature environment or in an area with prolonged low temperatures. Due to battery characteristics, DC fast charging can only reach peak power when the battery cell temperature is around 25°C. When the battery cell temperature is low, peak power charging is not possible, and the air conditioning system and PTC thermistor (PTC) are activated to heat the battery or energy storage device. This heating process can take up to 60 minutes before the battery cell reaches an operating temperature of approximately 25°C. Considering the winter operating environment of energy storage devices in northern China, shortening the DC fast charging time would improve charging efficiency. However, due to limitations in the air conditioning system and PTC heating, the time required to reach the operating temperature of approximately 25°C cannot be effectively shortened. Therefore, effectively shortening the DC fast charging time has become a pressing technical challenge. Summary of the Invention

[0003] Based on this, a method for controlling battery preheating of an energy storage device, a computer device, and a storage medium are provided to solve the current technical problem that when charging the battery in the energy storage device, the battery cells cannot reach peak power to shorten the DC fast charging time.

[0004] In one aspect, a method for controlling battery preheating of an energy storage device is provided. The energy storage device is provided with a water circulation system and an air conditioning system. The energy storage device includes a cabin surrounded by vertical side panels and a horizontal partition. Batteries are arranged in the cabin. A water circulation pipeline of the water circulation system is arranged in the horizontal partition. The method comprises:

[0005] Acquire thermal impact parameters of the energy storage device, and construct a temperature control equation for the energy storage device based on the thermal impact parameters;

[0006] Obtaining the used power and remaining power of the battery of the energy storage device, and determining whether the energy storage device needs to be charged according to the used power and remaining power of the battery;

[0007] In response to the energy storage device needing to be charged, detecting the real-time temperature of the battery of the energy storage device, calculating the start heating time for the battery to be heated to the DC fast charging peak power temperature according to the real-time temperature of the battery, and taking the difference between the start heating time and the current time as the preheating duration;

[0008] The DC fast charging peak power temperature is used as the target value of the heat impact parameter at the start of the heating time and is input into the energy storage device temperature control equation. The energy storage device temperature control equation generates control signals for controlling the water supply temperature and the air supply temperature during the preheating time, with the goal of minimizing the water supply temperature of the water circulation pipeline and the air supply temperature of the air conditioning system, while minimizing the energy efficiency cost, the demand deviation cost, and the temperature control operation cost.

[0009] According to the control signal, the water circulation system and the air-conditioning system are controlled to raise the temperature inside the energy storage device to the DC fast charging peak power temperature at the start heating time, and the battery of the energy storage device is started to be charged at the start heating time.

[0010] In one embodiment, obtaining the thermal impact parameters of the energy storage device and constructing the temperature control equation of the energy storage device according to the thermal impact parameters includes:

[0011] Classifying the thermal impact parameters into a state vector matrix X and an input vector matrix U;

[0012] Obtain a first coefficient matrix A corresponding to the state vector matrix X and a second coefficient matrix B corresponding to the input vector matrix U according to a thermal resistance and heat capacity energy balance relationship between the parameters in the state vector matrix X and the parameters in the input vector matrix U;

[0013] The state vector matrix X is multiplied by the first coefficient matrix A and then summed with the input vector matrix U multiplied by the second coefficient matrix B to form an energy storage device temperature control equation, and the energy storage device temperature control equation is Q=AX+BU.

[0014] In one embodiment, classifying the thermal impact parameters into a state vector matrix X and an input vector matrix U comprises:

[0015] Obtain the state vector matrix X of the energy storage device, wherein the parameters in the state vector matrix X include the average temperature of the water circulation pipeline in the horizontal partition , dry bulb temperature in the cabin , the temperature inside the vertical side panel and the temperature on the outside of the vertical side panels ,but ;

[0016] Obtain the input vector matrix U of the energy storage device, the parameters in the input vector matrix U include the water supply temperature of the pipeline fluid in the horizontal partition , air supply temperature of the air conditioning system , dry bulb temperature outside the cabin , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin ,but .

[0017] In one embodiment, obtaining a first coefficient matrix A corresponding to the state vector matrix X and a second coefficient matrix B corresponding to the input vector matrix U according to a thermal resistance and heat capacity energy balance relationship between parameters in the state vector matrix X and parameters in the input vector matrix U includes:

[0018] Setting thermal resistance and heat capacity between the parameters in the state vector matrix X and the parameters in the input vector matrix U to form a thermal resistance-heat capacity model;

[0019] The energy balance of various states in the thermal resistance-heat capacity model is written as a set of linear differential equations as follows:

[0020] ,

[0021] ,

[0022] ,

[0023] ;in g wd is the thermal radiation transmittance of the vertical side plate, R1 is the average temperature of the water circulation pipe in the horizontal partition The dry bulb temperature in the cabin The thermal resistance between them, R2 is the air supply temperature of the air conditioning system The dry bulb temperature outside the cabin The thermal resistance between the horizontal partition and the water circulation pipe is R3, which is the average temperature of the water circulation pipe in the horizontal partition. The water supply temperature of the fluid in the pipeline inside the horizontal partition The thermal resistance between the two, R4 is the air supply temperature of the air conditioning system The dry bulb temperature in the cabin The thermal resistance between the two, R5 is the dry bulb temperature in the cabin The temperature of the outer side of the vertical side plate The thermal resistance between the two, R6 is the dry bulb temperature outside the cabin The temperature of the outer side of the vertical side plate The thermal resistance between the two, R7 is the dry bulb temperature in the cabin The temperature of the inner side of the vertical side plate The thermal resistance between is the average temperature of the water circulation pipe in the horizontal partition and the heat capacity between the horizontal partitions, is the temperature of the outer side of the vertical side plate and the heat capacity between the horizontal partitions, is the temperature inside the vertical side plate and the heat capacity between the horizontal partitions, is the dry bulb temperature in the cabin The heat capacity between the horizontal partition;

[0024] The first coefficient matrix A corresponding to the state vector matrix X is obtained as: ;

[0025] The second coefficient matrix B corresponding to the input vector matrix U is obtained as: .

[0026] In one embodiment, minimizing energy efficiency cost, demand deviation cost, and temperature control operation cost includes:

[0027] Set the objective function of the temperature control equation of the energy storage device ,in is the energy efficiency cost at the kth moment, is the demand deviation cost at the kth moment, is the temperature adjustment operation cost at the kth moment, is the weight coefficient of energy efficiency cost, is the weight coefficient of demand deviation cost, is the weight coefficient of temperature control operation cost, is the preheating time, The number of time periods after the preheating time is divided into multiple time periods;

[0028] The energy storage device temperature control equation is combined with the objective function to obtain , after solving, the control signals for controlling the water supply temperature and the air supply temperature are generated.

[0029] In one embodiment, in the objective function,

[0030] The energy efficiency cost at the kth moment is ,in is the heating power value of the unit at the kth moment, is the cooling power value of the unit at the kth moment, is the heating coefficient of the unit, is the cooling coefficient of the unit;

[0031] The demand deviation cost at time k is , , ,in is the deviation between the cabin temperature and the upper limit of thermal comfort temperature at the kth moment, is the deviation between the cabin temperature at the kth moment and the lower limit of thermal comfort temperature;

[0032] The temperature adjustment operation cost at the kth moment is ,in is the cost of energy consumption at the kth moment, is the cost of equipment maintenance and upkeep at the kth moment, is the cost of system scheduling and management at the kth time.

[0033] In one embodiment, obtaining the used power and remaining power of a battery of the energy storage device, and determining whether the energy storage device needs to be charged according to the used power and remaining power of the battery includes:

[0034] Identify the low and peak electricity prices based on the external grid electricity prices, and obtain the low and peak electricity price periods;

[0035] According to the historical electricity consumption data, the normal electricity power P1, the normal electricity consumption duration t1, the peak electricity power P2 and the peak electricity consumption duration t2 are obtained, and the predicted electricity power is P1×t1+P2×t2;

[0036] Obtaining the battery life of the energy storage device according to the remaining power of the battery of the energy storage device and the predicted power consumption;

[0037] If the current time is during the peak electricity price period, and the end time of the battery life is within the peak electricity price period, it is determined that the energy storage device does not need to be charged, and the power supply mode is switched to the external power grid when the remaining power of the battery of the energy storage device is used up;

[0038] If the current time is the peak electricity price period and the end time of the battery life is within the low electricity price period, it is determined that the energy storage device needs to be charged, and the start time of the low electricity price period is used as the charging start time.

[0039] If the current time is within the low electricity price period, it is determined that the energy storage device needs to be charged.

[0040] In one embodiment, generating a control signal for controlling the water supply temperature and the air supply temperature during the preheating time includes:

[0041] monitoring a parameter value X(k) of the state vector matrix X of the energy storage device at the current k-th moment, and obtaining a predicted parameter value X(k+1|k) of the state vector matrix X at the k+1-th moment based on the parameter value X(k) of the state vector matrix X at the current k-th moment;

[0042] Get the comfortable temperature in the cabin at the current k-th moment: , the preheating time is divided into multiple time periods and the cabin temperature is adjusted step by step. From the current kth moment onwards, the cabin comfort temperature corresponding to the i-th time period within the preheating time is , set the cabin comfort temperature adjustment mode to ;

[0043] Set the dry bulb temperature outside the cabin at the current k-th moment , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin The collection is , the dry-bulb temperature outside the cabin corresponding to the i-th time period within the preheating time from the current k-th moment onwards , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin The collection is , set the dry bulb temperature outside the cabin , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin The collection adjustment method is ;

[0044] Based on the comfortable temperature adjustment method in the cabin and the dry bulb temperature outside the compartment , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin Collection adjustment method , obtaining the predicted parameter value of the input vector matrix U of the energy storage device at the k+1th moment;

[0045] A control signal for controlling the water supply temperature and the air supply temperature during the preheating time is generated according to the predicted parameter value of the input vector matrix U at the k+1th moment.

[0046] On the other hand, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the energy storage device battery preheating control method when executing the computer program.

[0047] On the other hand, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the energy storage device battery preheating control method are implemented.

[0048] The above-mentioned energy storage device battery preheating control method, computer device and storage medium obtain the heat influence parameters of the energy storage device, construct the energy storage device temperature control equation according to the heat influence parameters, and generate control signals for controlling the water supply temperature and the air supply temperature based on the heat influence parameter values ​​at the start time of heating, thereby achieving precise control of the DC fast charging peak power temperature of the energy storage device at the start time of heating, shortening the DC fast charging time by achieving the peak power of the battery cell, and improving the response speed and accuracy of the energy storage device battery preheating control. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0050] Figure 1 This is a flow chart of a method for controlling preheating of a battery in an energy storage device according to an embodiment of the present application;

[0051] Figure 2 This is a structural block diagram of a thermal resistance-heat capacity model in one embodiment of the present application;

[0052] Figure 3 This is a control logic diagram based on model predictive control in one embodiment of the present application;

[0053] Figure 4 This is a diagram of the internal structure of a computer device in one embodiment of the present application. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0055] In one embodiment, Figure 1 As shown, a method for controlling battery preheating of an energy storage device is provided. The energy storage device is provided with a water circulation system and an air conditioning system. The energy storage device includes a cabin surrounded by vertical side panels and horizontal partitions. Batteries are arranged in the cabin. The water circulation pipeline of the water circulation system is arranged in the horizontal partition. The method includes:

[0056] S1. Obtaining thermal impact parameters of the energy storage device and constructing a temperature control equation for the energy storage device according to the thermal impact parameters;

[0057] S2. Obtaining the used power and remaining power of the battery of the energy storage device, and determining whether the energy storage device needs to be charged according to the used power and remaining power of the battery;

[0058] S3. In response to the energy storage device needing to be charged, detecting the real-time temperature of the battery of the energy storage device, calculating the start heating time for the battery to be heated to the DC fast charging peak power temperature according to the real-time temperature of the battery, and taking the difference between the start heating time and the current time as the preheating duration;

[0059] S4. Using the DC fast charge peak power temperature as the target value of the heat impact parameter at the start of the heating time and inputting it into the energy storage device temperature control equation, the energy storage device temperature control equation generating control signals for controlling the water supply temperature and the air supply temperature during the preheating time, with the goal of minimizing the water supply temperature of the water circulation pipeline and the air supply temperature of the air conditioning system, while minimizing the energy efficiency cost, the demand deviation cost, and the temperature control operation cost;

[0060] S5. Control the water circulation system and the air-conditioning system according to the control signal to raise the temperature inside the energy storage device to the DC fast charging peak power temperature at the start heating time, and start charging the battery of the energy storage device at the start heating time.

[0061] Specifically, by obtaining the thermal influence parameters of the energy storage device, a temperature control equation for the energy storage device is constructed according to the thermal influence parameters. Based on the values ​​of the thermal influence parameters at the start of heating, a control signal for controlling the water supply temperature and the air supply temperature can be generated, thereby achieving precise control of the DC fast charging peak power temperature of the energy storage device at the start of heating, achieving the peak power of the battery cell to shorten the DC fast charging time, and improving the response speed and accuracy of the battery preheating control of the energy storage device.

[0062] In this embodiment, obtaining the thermal influence parameters of the energy storage device and constructing the temperature control equation of the energy storage device according to the thermal influence parameters includes:

[0063] Classifying the thermal impact parameters into a state vector matrix X and an input vector matrix U;

[0064] Obtain a first coefficient matrix A corresponding to the state vector matrix X and a second coefficient matrix B corresponding to the input vector matrix U according to a thermal resistance and heat capacity energy balance relationship between the parameters in the state vector matrix X and the parameters in the input vector matrix U;

[0065] The state vector matrix X is multiplied by the first coefficient matrix A and then summed with the input vector matrix U multiplied by the second coefficient matrix B to form an energy storage device temperature control equation, and the energy storage device temperature control equation is Q=AX+BU.

[0066] This embodiment constructs a thermally activated building system control model corresponding to the energy storage device, classifies the thermally affected parameters in the model into a state vector matrix X and an input vector matrix U, and uses the thermal resistance and heat capacity energy balance relationship between the parameters to obtain a first coefficient matrix A corresponding to the state vector matrix X and a second coefficient matrix B corresponding to the input vector matrix U. This can form an accurate temperature control equation for the energy storage device. Based on the values ​​of the thermally affected parameters at the start of heating, control signals for controlling the water supply temperature and the supply air temperature can be generated, thereby achieving precise control of the DC fast charging peak power temperature of the energy storage device at the start of heating.

[0067] In this embodiment, classifying the thermal impact parameters into a state vector matrix X and an input vector matrix U includes:

[0068] Obtain the state vector matrix X of the energy storage device, wherein the parameters in the state vector matrix X include the average temperature of the water circulation pipeline in the horizontal partition , dry bulb temperature in the cabin , the temperature inside the vertical side panel and the temperature on the outside of the vertical side panels ,but ;

[0069] Obtain the input vector matrix U of the energy storage device, the parameters in the input vector matrix U include the water supply temperature of the pipeline fluid in the horizontal partition , air supply temperature of the air conditioning system , dry bulb temperature outside the cabin , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin ,but .

[0070] Among them, the average temperature of the water circulation pipe in the horizontal partition is , dry bulb temperature in the cabin , the temperature inside the vertical side panel and the temperature on the outside of the vertical side panels , water supply temperature of the fluid in the horizontal partition pipe , air supply temperature of the air conditioning system , dry bulb temperature outside the cabin The unit is ℃, the heat dissipation of the battery in the cabin and the intensity of heat radiation outside the cabin The unit is W.

[0071] In this embodiment, obtaining a first coefficient matrix A corresponding to the state vector matrix X and a second coefficient matrix B corresponding to the input vector matrix U according to a thermal resistance and heat capacity energy balance relationship between the parameters in the state vector matrix X and the parameters in the input vector matrix U includes:

[0072] Thermal resistance and heat capacity are set between the parameters in the state vector matrix X and the parameters in the input vector matrix U to form a thermal resistance-heat capacity model; the thermal resistance-heat capacity model is as follows Figure 2 As shown;

[0073] The energy balance of various states in the thermal resistance-heat capacity model is written as a set of linear differential equations as follows:

[0074] ,

[0075] ,

[0076] ,

[0077] ;in g wd is the thermal radiation transmittance of the vertical side plate, R1 is the average temperature of the water circulation pipe in the horizontal partition The dry bulb temperature in the cabin The thermal resistance between them, R2 is the air supply temperature of the air conditioning system The dry bulb temperature outside the cabin The thermal resistance between the horizontal partition and the water circulation pipe is R3, which is the average temperature of the water circulation pipe in the horizontal partition. The water supply temperature of the fluid in the pipeline inside the horizontal partition The thermal resistance between the two, R4 is the air supply temperature of the air conditioning system The dry bulb temperature in the cabin The thermal resistance between the two, R5 is the dry bulb temperature in the cabin The temperature of the outer side of the vertical side plate The thermal resistance between the two, R6 is the dry bulb temperature outside the cabin The temperature of the outer side of the vertical side plate The thermal resistance between the two, R7 is the dry bulb temperature in the cabin The temperature of the inner side of the vertical side plate The thermal resistance between is the average temperature of the water circulation pipe in the horizontal partition and the heat capacity between the horizontal partitions, is the temperature of the outer side of the vertical side plate and the heat capacity between the horizontal partitions, is the temperature inside the vertical side plate and the heat capacity between the horizontal partitions, is the dry bulb temperature in the cabin The heat capacity between the horizontal partition;

[0078] The first coefficient matrix A corresponding to the state vector matrix X is obtained as: ;

[0079] The second coefficient matrix B corresponding to the input vector matrix U is obtained as: .

[0080] In the formula, is the heat capacity between building components (J / kg·℃); is the thermal resistance between building components (°C / W).

[0081] It is understandable that after obtaining the values ​​of the first coefficient matrix A corresponding to the state vector matrix X and the second coefficient matrix B corresponding to the input vector matrix U, the energy storage device temperature control equation Q=AX+BU can be solved in theory.

[0082] In this embodiment, the goal of minimizing energy efficiency cost, demand deviation cost, and temperature control operation cost includes:

[0083] The objective function corresponding to the temperature control equation of the energy storage device is formed by setting the lowest water supply temperature of the pipeline fluid in the horizontal partition and minimizing the energy efficiency cost, demand deviation cost, and temperature adjustment operation cost. ,in is the energy efficiency cost at the kth moment, is the demand deviation cost at the kth moment, is the temperature adjustment operation cost at the kth moment, is the weight coefficient of energy efficiency cost, is the weight coefficient of demand deviation cost, is the weight coefficient of temperature control operation cost, is the preheating time, The number of time periods after the preheating time is divided into multiple time periods;

[0084] The energy storage device temperature control equation is combined with the objective function to obtain , after solving, the control signals for controlling the water supply temperature and the air supply temperature are generated.

[0085] Among them, in the objective function,

[0086] The energy efficiency cost at the kth moment is ,in is the heating power value of the unit at the kth moment, is the cooling power value of the unit at the kth moment, is the heating coefficient of the unit, is the cooling coefficient of the unit (the unit is an air source heat pump and a variable frequency fan);

[0087] The demand deviation cost at time k is , , ,in is the deviation between the cabin temperature and the upper limit of thermal comfort temperature at the kth moment, is the deviation between the cabin temperature at the kth moment and the lower limit of thermal comfort temperature;

[0088] The temperature adjustment operation cost at the kth moment is ,in is the cost of energy consumption at the kth moment, is the cost of equipment maintenance and upkeep at the kth moment, is the cost of system scheduling and management at the kth time.

[0089] Wherein, it is preferred that the preheating time is 24 hours, which is divided into 24 time periods, each time period is 1 hour, If it is 24, it means the forecast will be made 24 hours from now. The unit is W 2 ); Demand deviation cost Unit is ℃ 2 ; Temperature control operation cost The unit is Yuan.

[0090] In this embodiment, obtaining the used power and remaining power of the battery of the energy storage device, and determining whether the energy storage device needs to be charged according to the used power and remaining power of the battery includes:

[0091] Identify the low and peak electricity prices based on the external grid electricity prices, and obtain the low and peak electricity price periods;

[0092] According to the historical electricity consumption data, the normal electricity power P1, the normal electricity consumption duration t1, the peak electricity power P2 and the peak electricity consumption duration t2 are obtained, and the predicted electricity power is P1×t1+P2×t2;

[0093] Obtaining the battery life of the energy storage device according to the remaining power of the battery of the energy storage device and the predicted power consumption;

[0094] If the current time is during the peak electricity price period, and the end time of the battery life is within the peak electricity price period, it is determined that the energy storage device does not need to be charged, and the power supply mode is switched to the external power grid when the remaining power of the battery of the energy storage device is used up;

[0095] If the current time is the peak electricity price period and the end time of the battery life is within the low electricity price period, it is determined that the energy storage device needs to be charged, and the start time of the low electricity price period is used as the charging start time.

[0096] If the current time is within the low electricity price period, it is determined that the energy storage device needs to be charged.

[0097] In this embodiment, generating a control signal for controlling the water supply temperature and the air supply temperature during the preheating time includes:

[0098] monitoring a parameter value X(k) of the state vector matrix X of the energy storage device at the current k-th moment, and obtaining a predicted parameter value X(k+1|k) of the state vector matrix X at the k+1-th moment based on the parameter value X(k) of the state vector matrix X at the current k-th moment;

[0099] Get the comfortable temperature in the cabin at the current k-th moment: , the preheating time is divided into multiple time periods and the cabin temperature is adjusted step by step. From the current kth moment onwards, the cabin comfort temperature corresponding to the i-th time period within the preheating time is , set the cabin comfort temperature adjustment mode to ;

[0100] Set the dry bulb temperature outside the cabin at the current k-th moment , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin The collection is , the dry-bulb temperature outside the cabin corresponding to the i-th time period within the preheating time from the current k-th moment onwards , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin The collection is , set the dry bulb temperature outside the cabin , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin The collection adjustment method is ;

[0101] Based on the comfortable temperature adjustment method in the cabin and the dry bulb temperature outside the compartment , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin Collection adjustment method , obtaining the predicted parameter value of the input vector matrix U of the energy storage device at the k+1th moment;

[0102] A control signal for controlling the water supply temperature and the air supply temperature during the preheating time is generated according to the predicted parameter value of the input vector matrix U at the k+1th moment.

[0103] exist Figure 3 If the comfortable temperature in the cabin at the current k-th moment is , the comfortable temperature in the cabin corresponding to the i-th time period during the preheating time after the k-th moment is , that is, the cabin comfort temperature adjustment method learned by the MPC controller is ; If the dry-bulb temperature outside the cabin at the current kth moment is , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin The collection is , then the dry bulb temperature outside the cabin corresponding to the i-th time period during the preheating time after the k-th time is , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin The collection is , which is the dry bulb temperature outside the cabin known to the MPC controller , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin The collection adjustment method is The preheating time is divided into Hp time periods, and the value of i is 1≤i≤Hp.

[0104] Wherein, the water circulation system includes a variable frequency water pump, the air conditioning system includes a variable frequency fan, and an MPC controller is provided for controlling the variable frequency water pump and the variable frequency fan according to the control signal.

[0105] In this embodiment, controlling the variable frequency water pump and the variable frequency fan according to the control signal includes:

[0106] Obtain the state vector matrix X value at the current moment, the energy storage device temperature control equation value at the current moment, and the heat impact energy storage device temperature control equation value at the start of heating, and obtain the heat impact parameter value at the start of heating;

[0107] Dividing the preheating time into a plurality of time periods according to the current state vector matrix X value, the current energy storage device temperature control equation value, the heat impact energy storage device temperature control equation value at the start of heating, and the heat impact parameter value at the start of heating, generating an input vector matrix U value corresponding to each time period, and generating a control signal corresponding to each time period from the input vector matrix U value corresponding to each time period;

[0108] The control signal of each time period is sent to the variable frequency water pump and the variable frequency fan in chronological order.

[0109] In the above-mentioned energy storage device battery preheating control method, a heat-activated building system control model is constructed by corresponding to the energy storage device, and the heat-affected parameters in the model are classified into a state vector matrix X and an input vector matrix U. The thermal resistance and heat capacity energy balance relationship between the parameters is used to obtain the first coefficient matrix A corresponding to the state vector matrix X and the second coefficient matrix B corresponding to the input vector matrix U. This can form an accurate temperature control equation for the energy storage device. Based on the values ​​of the heat-affected parameters at the start time of heating, control signals for controlling the water supply temperature and the supply air temperature can be generated, thereby achieving precise control of the DC fast charging peak power temperature of the energy storage device at the start time of heating, and avoiding the problems of slow response speed and low precision in the energy storage device battery preheating control.

[0110] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store energy storage device battery preheating control data. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for controlling energy storage device battery preheating is implemented.

[0111] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0112] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the following steps are performed:

[0113] Acquire thermal impact parameters of the energy storage device, and construct a temperature control equation for the energy storage device based on the thermal impact parameters;

[0114] Obtaining the used power and remaining power of the battery of the energy storage device, and determining whether the energy storage device needs to be charged according to the used power and remaining power of the battery;

[0115] In response to the energy storage device needing to be charged, detecting the real-time temperature of the battery of the energy storage device, calculating the start heating time for the battery to be heated to the DC fast charging peak power temperature according to the real-time temperature of the battery, and taking the difference between the start heating time and the current time as the preheating duration;

[0116] The DC fast charging peak power temperature is used as the target value of the heat impact parameter at the start of the heating time and is input into the energy storage device temperature control equation. The energy storage device temperature control equation generates control signals for controlling the water supply temperature and the air supply temperature during the preheating time, with the goal of minimizing the water supply temperature of the water circulation pipeline and the air supply temperature of the air conditioning system, while minimizing the energy efficiency cost, the demand deviation cost, and the temperature control operation cost.

[0117] According to the control signal, the water circulation system and the air-conditioning system are controlled to raise the temperature inside the energy storage device to the DC fast charging peak power temperature at the start heating time, and the battery of the energy storage device is started to be charged at the start heating time.

[0118] For specific limitations on the steps implemented when the processor executes the computer program, please refer to the above limitations on the method for controlling battery preheating of the energy storage device, which will not be repeated here.

[0119] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0120] Acquire thermal impact parameters of the energy storage device, and construct a temperature control equation for the energy storage device based on the thermal impact parameters;

[0121] Obtaining the used power and remaining power of the battery of the energy storage device, and determining whether the energy storage device needs to be charged according to the used power and remaining power of the battery;

[0122] In response to the energy storage device needing to be charged, detecting the real-time temperature of the battery of the energy storage device, calculating the start heating time for the battery to be heated to the DC fast charging peak power temperature according to the real-time temperature of the battery, and taking the difference between the start heating time and the current time as the preheating duration;

[0123] The DC fast charging peak power temperature is used as the target value of the heat impact parameter at the start of the heating time and is input into the energy storage device temperature control equation. The energy storage device temperature control equation generates control signals for controlling the water supply temperature and the air supply temperature during the preheating time, with the goal of minimizing the water supply temperature of the water circulation pipeline and the air supply temperature of the air conditioning system, while minimizing the energy efficiency cost, the demand deviation cost, and the temperature control operation cost.

[0124] According to the control signal, the water circulation system and the air-conditioning system are controlled to raise the temperature inside the energy storage device to the DC fast charging peak power temperature at the start heating time, and the battery of the energy storage device is started to be charged at the start heating time.

[0125] For specific limitations on the steps implemented when the computer program is executed by the processor, please refer to the above limitations on the method for controlling battery preheating of an energy storage device, which will not be repeated here.

[0126] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0127] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0128] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for controlling battery preheating of an energy storage device, characterized in that: The energy storage device is provided with a water circulation system and an air conditioning system. The energy storage device includes a cabin surrounded by vertical side panels and horizontal partitions. A battery is arranged in the cabin. The water circulation pipeline of the water circulation system is arranged in the horizontal partition. The method includes: Acquire thermal impact parameters of the energy storage device, and construct a temperature control equation for the energy storage device based on the thermal impact parameters; Obtaining the used power and remaining power of the battery of the energy storage device, and determining whether the energy storage device needs to be charged according to the used power and remaining power of the battery; In response to the energy storage device needing to be charged, detecting the real-time temperature of the battery of the energy storage device, calculating the start heating time for the battery to be heated to the DC fast charging peak power temperature according to the real-time temperature of the battery, and taking the difference between the start heating time and the current time as the preheating duration; The DC fast charging peak power temperature is used as the target value of the heat impact parameter at the start of the heating time and is input into the energy storage device temperature control equation. The energy storage device temperature control equation generates control signals for controlling the water supply temperature and the air supply temperature during the preheating time, with the goal of minimizing the water supply temperature of the water circulation pipeline and the air supply temperature of the air conditioning system, while minimizing the energy efficiency cost, the demand deviation cost, and the temperature control operation cost. Controlling the water circulation system and the air conditioning system according to the control signal to raise the temperature in the energy storage device to the DC fast charging peak power temperature at the start heating time, and starting to charge the battery of the energy storage device at the start heating time; The step of obtaining the thermal influence parameters of the energy storage device and constructing the temperature control equation of the energy storage device according to the thermal influence parameters includes: Classifying the thermal impact parameters into a state vector matrix X and an input vector matrix U; Obtain a first coefficient matrix A corresponding to the state vector matrix X and a second coefficient matrix B corresponding to the input vector matrix U according to a thermal resistance and heat capacity energy balance relationship between the parameters in the state vector matrix X and the parameters in the input vector matrix U; The state vector matrix X is multiplied by the first coefficient matrix A and the sum is multiplied by the input vector matrix U is multiplied by the second coefficient matrix B to form a temperature control equation for the energy storage device, wherein the temperature control equation for the energy storage device is Q=AX+BU; The classifying of the thermal impact parameters into a state vector matrix X and an input vector matrix U includes: Obtain the state vector matrix X of the energy storage device, wherein the parameters in the state vector matrix X include the average temperature of the water circulation pipeline in the horizontal partition , dry bulb temperature in the cabin , the temperature inside the vertical side panel and the temperature on the outside of the vertical side panels ,but ; Obtain the input vector matrix U of the energy storage device, the parameters in the input vector matrix U include the water supply temperature of the pipeline fluid in the horizontal partition , air supply temperature of the air conditioning system , dry bulb temperature outside the cabin , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin ,but .

2. The energy storage device battery preheating control method according to claim 1, characterized in that: The step of obtaining a first coefficient matrix A corresponding to the state vector matrix X and a second coefficient matrix B corresponding to the input vector matrix U according to a thermal resistance and heat capacity energy balance relationship between the parameters in the state vector matrix X and the parameters in the input vector matrix U includes: Setting thermal resistance and heat capacity between the parameters in the state vector matrix X and the parameters in the input vector matrix U to form a thermal resistance-heat capacity model; The energy balance of various states in the thermal resistance-heat capacity model is written as a set of linear differential equations as follows: ， ， ， Where gwd is the thermal radiation transmittance of the vertical side plate, R1 is the average temperature of the water circulation pipe in the horizontal partition The dry bulb temperature in the cabin The thermal resistance between them, R2 is the air supply temperature of the air conditioning system The dry bulb temperature outside the cabin The thermal resistance between the horizontal partition and the water circulation pipe is R3, which is the average temperature of the water circulation pipe in the horizontal partition. The water supply temperature of the fluid in the pipeline inside the horizontal partition The thermal resistance between the two, R4 is the air supply temperature of the air conditioning system The dry bulb temperature in the cabin The thermal resistance between the two, R5 is the dry bulb temperature in the cabin The temperature of the outer side of the vertical side plate The thermal resistance between the two, R6 is the dry bulb temperature outside the cabin The temperature of the outer side of the vertical side plate The thermal resistance between the two, R7 is the dry bulb temperature in the cabin The temperature of the inner side of the vertical side plate The thermal resistance between is the average temperature of the water circulation pipe in the horizontal partition and the heat capacity between the horizontal partitions, is the temperature of the outer side of the vertical side plate and the heat capacity between the horizontal partitions, is the temperature inside the vertical side plate and the heat capacity between the horizontal partitions, is the dry bulb temperature in the cabin The heat capacity between the horizontal partition; The first coefficient matrix A corresponding to the state vector matrix X is obtained as: ； The second coefficient matrix B corresponding to the input vector matrix U is obtained as: 。 3. The energy storage device battery preheating control method according to claim 2, characterized in that: The goal of minimizing energy efficiency costs, demand deviation costs, and temperature control operating costs includes: Set the objective function of the temperature control equation of the energy storage device ,in is the energy efficiency cost at the kth moment, is the demand deviation cost at the kth moment, is the temperature adjustment operation cost at the kth moment, is the weight coefficient of energy efficiency cost, is the weight coefficient of demand deviation cost, is the weight coefficient of temperature control operation cost, is the preheating time, The number of time periods after the preheating time is divided into multiple time periods; The energy storage device temperature control equation is combined with the objective function to obtain , after solving, the control signals for controlling the water supply temperature and the air supply temperature are generated.

4. The energy storage device battery preheating control method according to claim 3, characterized in that: In the objective function, The energy efficiency cost at the kth moment is ,in is the heating power value of the unit at the kth moment, is the cooling power value of the unit at the kth moment, is the heating coefficient of the unit, is the cooling coefficient of the unit; The demand deviation cost at time k is , , ,in is the deviation between the cabin temperature and the upper limit of thermal comfort temperature at the kth moment, is the deviation between the cabin temperature at the kth moment and the lower limit of thermal comfort temperature; The temperature adjustment operation cost at the kth moment is ,in is the cost of energy consumption at the kth moment, is the cost of equipment maintenance and upkeep at the kth moment, is the cost of system scheduling and management at the kth time.

5. The energy storage device battery preheating control method according to claim 1, characterized in that: The obtaining of the used power and the remaining power of the battery of the energy storage device, and determining whether the energy storage device needs to be charged according to the used power and the remaining power of the battery includes: Identify the low and peak electricity prices based on the external grid electricity prices, and obtain the low and peak electricity price periods; According to the historical electricity consumption data, the normal electricity power P1, the normal electricity consumption duration t1, the peak electricity power P2 and the peak electricity consumption duration t2 are obtained, and the predicted electricity power is P1×t1+P2×t2; Obtaining the battery life of the energy storage device according to the remaining power of the battery of the energy storage device and the predicted power consumption; If the current time is during the peak electricity price period, and the end time of the battery life is within the peak electricity price period, it is determined that the energy storage device does not need to be charged, and the power supply mode is switched to the external power grid when the remaining power of the battery of the energy storage device is used up; If the current time is during the peak electricity price period and the end time of the battery life is during the low electricity price period, it is determined that the energy storage device needs to be charged, and the start time of the low electricity price period is used as the charging start time; If the current time is within the low electricity price period, it is determined that the energy storage device needs to be charged.

6. The energy storage device battery preheating control method according to claim 1, characterized in that: The generating of the control signal for controlling the water supply temperature and the air supply temperature during the preheating time comprises: monitoring a parameter value X(k) of the state vector matrix X of the energy storage device at the current k-th moment, and obtaining a predicted parameter value X(k+1|k) of the state vector matrix X at the k+1-th moment based on the parameter value X(k) of the state vector matrix X at the current k-th moment; Get the comfortable temperature in the cabin at the current k-th moment: , the preheating time is divided into multiple time periods and the cabin temperature is adjusted step by step. From the current kth moment onwards, the cabin comfort temperature corresponding to the i-th time period within the preheating time is , set the cabin comfort temperature adjustment mode to ; Set the dry bulb temperature outside the cabin at the current k-th moment , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin The collection is , the dry-bulb temperature outside the cabin corresponding to the i-th time period within the preheating time from the current k-th moment onwards , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin The collection is , set the dry bulb temperature outside the cabin , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin The collection adjustment method is ; Based on the comfortable temperature adjustment method in the cabin and the dry bulb temperature outside the compartment , heat dissipation of batteries in the cabin and the intensity of heat radiation outside the cabin Collection adjustment method , obtaining the predicted parameter value of the input vector matrix U of the energy storage device at the k+1th moment; A control signal for controlling the water supply temperature and the air supply temperature during the preheating time is generated according to the predicted parameter value of the input vector matrix U at the k+1th moment.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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