Energy storage cabinet temperature control method based on cloud platform and temperature-controlled energy storage cabinet

Abstract

The present invention discloses a temperature control method for an energy storage cabinet based on a cloud platform and a temperature-controlled energy storage cabinet, and relates to the technical field of electric energy storage. The energy storage cabinet comprises a cabinet body, an energy storage module, a data acquisition module, a communication module, and a temperature control module. The temperature control method comprises: S1: acquiring environmental parameters and battery status data; S2: determining a temperature adjustment factor of the energy storage cabinet through the battery status data; S3: generating a composite temperature index based on the environmental parameters and the temperature adjustment factor; S4: dividing the energy storage cabinet into regions, determining temperature requirements of different regions according to the composite temperature index, and formulating a temperature control strategy for the energy storage cabinet based on the temperature requirements and the predicted environmental temperature; S5: the cloud platform generates a control instruction based on the temperature control strategy, and sends it to the energy storage cabinet to execute the control instruction. The present invention can realize precise control of the internal temperature of the energy storage cabinet, ensure that the energy storage equipment operates within an optimal temperature range, and improve the energy storage efficiency and the life of the equipment.

Description

Technical Field

[0001] The present invention relates to the technical field of electric energy storage, and more specifically to a temperature control method for an energy storage cabinet based on a cloud platform and a temperature-controlled energy storage cabinet. Background Art

[0002] With the widespread application of renewable energy and the popularity of electric vehicles, energy storage technology has become a hot topic in the energy field. As a key device for electric energy storage, the stability and safety of the performance of energy storage cabinets are crucial to the operation of the power system. Especially in battery energy storage systems, battery temperature management directly affects battery efficiency, life and safety. Therefore, developing a technology that can accurately control the temperature of energy storage cabinets is of great significance to improving the overall performance of energy storage systems. At present, the temperature control technology of energy storage cabinets mainly relies on traditional temperature sensors and simple temperature control algorithms. These technologies can monitor and control the temperature of energy storage cabinets to a certain extent, but there are still the following shortcomings in practical applications:

[0003] On the one hand, existing temperature control strategies mostly use a single or a few sensors to monitor the temperature of the entire energy storage cabinet, and then perform global temperature adjustment based on these limited data. This approach ignores the differences between individual batteries and the complexity of battery status changes over time, resulting in inaccurate temperature control and inability to effectively extend battery life or improve system energy efficiency. On the other hand, the working environment of energy storage cabinets is diverse, from hot deserts to the cold Arctic. Different geographical locations and seasonal changes bring huge temperature difference challenges, and existing control systems often find it difficult to accurately predict and adapt to changes in the external environment in real time, especially under extreme weather conditions. The risk of battery thermal runaway may increase due to control lags. In addition, in large-scale energy storage systems, battery packs are deployed on a large scale. If precise temperature control cannot be performed according to the specific needs of each battery or small area, it may lead to energy waste.

[0004] The existing Chinese patent application with publication number CN116885331A discloses an energy storage battery temperature control system and an energy storage battery cabinet, which includes a cooling cycle, a refrigeration cycle and a dehumidification unit; the cooling cycle is connected in series with a heat dissipation pipeline arranged in the battery compartment of the energy storage power station for dissipating heat from the battery compartment; the refrigeration cycle is used to realize the refrigeration of the first evaporator through the refrigerant circulation; the first evaporator also includes a heat exchange side connected in series in the cooling cycle; the dehumidification unit includes a second evaporator arranged in the battery compartment, and the dehumidification unit realizes the refrigeration of the second evaporator through the refrigerant circulation, so that the water vapor in the battery compartment is liquefied on the second evaporator and discharged from the battery compartment. This invention solves the problem that the traditional energy storage temperature control system cannot adapt to the conditions of different regions and operate efficiently.

[0005] The existing Chinese patent application with publication number CN117954743A discloses a temperature control method for an energy storage battery cabinet, which includes the following steps: Step 1: Turn on the machine and obtain the charging and discharging time; Step 2: If the battery pack temperature is ≤5℃ or the battery pack temperature is ≥35℃, turn on the air conditioner and air conditioning fan in advance; Step 3: If 5℃<battery pack temperature<35℃ and the maximum temperature difference between battery packs Tdiff≥3℃, turn on the air conditioning fan in advance; if the maximum temperature difference between battery packs Tdiff≤3℃, the air conditioner and air conditioning fan will not work; Step 4: During the charging and discharging process, if the battery pack temperature Tmax≥35℃ or the battery pack temperature Tmin≤5℃, turn on the air conditioner and air conditioning fan; Step 5: During the charging and discharging process, if 5℃<battery pack temperature<35℃ and the maximum temperature difference between battery packs is ≥3℃, turn on the air conditioning fan; if the maximum temperature difference between battery packs is ≤3℃, turn off the air conditioner and air conditioning fan. The control method of the invention is perfect, precise, saves electricity, reduces energy consumption and has low cost.

[0006] The above prior arts all have the problems mentioned in the background art. They do not consider the temperature differences between different batteries inside the energy storage cabinet and the influence of environmental factors on the temperature of the energy storage cabinet, resulting in insufficient temperature control accuracy and poor temperature control adaptability. Summary of the invention

[0007] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a temperature control method for an energy storage cabinet based on a cloud platform and a temperature-controlled energy storage cabinet. The present invention can improve the refined management of the temperature control of the energy storage cabinet, accurately control the internal temperature of the energy storage cabinet, ensure that the energy storage equipment operates within the optimal temperature range, and improve the energy storage efficiency and equipment life.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] In a first aspect, the present invention provides a temperature control method for an energy storage cabinet based on a cloud platform, which specifically comprises the following steps:

[0010] S1: Obtain environmental parameters and battery status data;

[0011] S2: Determine the temperature adjustment factor of the energy storage cabinet according to the battery status data;

[0012] S3: generating a composite temperature index based on the environmental parameter and the temperature adjustment factor;

[0013] S4: Divide the energy storage cabinet into regions, determine the temperature requirements of different regions according to the composite temperature index, and formulate a temperature control strategy for the energy storage cabinet based on the temperature requirements and the predicted ambient temperature;

[0014] S5: The cloud platform generates a control instruction based on the temperature control strategy, and sends it to the energy storage cabinet to execute the control instruction.

[0015] As a further improvement of the present invention, the temperature adjustment factor includes a temperature adjustment factor of a battery state of charge, and the battery state of charge temperature adjustment factor is determined as follows:

[0016] Configuring a battery state of charge threshold, wherein the battery state of charge threshold includes a battery state of charge high temperature threshold and a battery state of charge low temperature threshold;

[0017] Get the battery state of charge, compare it with the battery state of charge threshold, and calculate the battery state of charge temperature adjustment factor. The calculation formula is as follows:

[0018] ;

[0019] in, represents the battery state of charge temperature adjustment factor of the ith battery, , n represents the total number of batteries in the energy storage cabinet, represents the actual battery state of charge of the ith battery, represents the high temperature threshold of the battery state of charge of the ith battery, represents the low temperature threshold of the battery state of charge of the ith battery, , Represents the weight coefficient.

[0020] As a further improvement of the present invention, the temperature adjustment factor also includes a charge and discharge rate temperature adjustment factor, and the calculation formula of the charge and discharge rate temperature adjustment factor is as follows:

[0021] ;

[0022] in, represents the temperature adjustment factor of the charge and discharge rate of the ith battery, represents the actual charge and discharge rate of the ith battery, represents the maximum safe charge and discharge rate of the ith battery, Represents the weight coefficient.

[0023] As a further improvement of the present invention, the temperature adjustment factor also includes a battery health state temperature adjustment factor, and the determination method of the battery health state temperature adjustment factor includes:

[0024] Acquire battery health status parameters, wherein the battery health status parameters include the number of battery cycles, the growth ratio relative to the initial internal resistance, and the loss ratio relative to the initial capacity;

[0025] Calculate the battery health state value using the battery health state parameter;

[0026] The battery health status temperature adjustment factor is determined based on the battery health status value, and the calculation formula is:

[0027] ;

[0028] in, represents the temperature adjustment factor of the health status of the ith battery, represents the health status threshold of the ith battery, represents the weight coefficient, Represents the health status value of the ith battery.

[0029] As a further improvement of the present invention, the calculation formula for calculating the battery health status value is:

[0030] ;

[0031] Among them, the battery health status value The larger it is, the healthier the battery is. represents the cycle life of the ith battery, represents the number of cycles of the ith battery, represents the growth ratio of the i-th battery relative to the initial internal resistance, represents the loss ratio of the i-th battery relative to the initial capacity, represents the weight coefficient, represents the nonlinear coefficient.

[0032] As a further improvement of the present invention, the environmental parameter includes the real-time temperature of each battery in the energy storage cabinet, and the generation of the composite temperature index specifically includes:

[0033] The real-time temperature of each battery in the energy storage cabinet is obtained, and the composite temperature index of each battery is generated by combining the battery state of charge temperature adjustment factor, charge and discharge rate temperature adjustment factor, and battery health status temperature adjustment factor. The calculation formula is as follows:

[0034] ;

[0035] in, represents the composite temperature index of the ith battery, represents the real-time temperature of the ith battery, Represents an exponential function with the natural constant e as the base.

[0036] As a further improvement of the present invention, the method of formulating the energy storage cabinet temperature control strategy specifically includes:

[0037] S41: Divide the batteries in the energy storage cabinet into M areas, each area includes The average composite temperature index of all batteries in each area is calculated using the following formula:

[0038] ;

[0039] in, represents the average composite temperature index of all batteries in the jth region, , M is the total number of regions; represents the composite temperature index of the kth battery in the jth region, represents the composite temperature index weight coefficient of the kth battery in the jth region, ;

[0040] S42: traverse each area, determine the temperature requirement of each area, and add a temperature requirement tag according to the temperature requirement, specifically including:

[0041] Configure high temperature threshold and low temperature threshold for each area;

[0042] When the average composite temperature index of a region is greater than the high temperature threshold of the region, the temperature demand of the region is determined to be a cooling demand, and a cooling demand label is added;

[0043] When the average composite temperature index of a region is not greater than the region's high temperature threshold and not less than the region's low temperature threshold, it is determined that the region has no temperature requirement and no label needs to be added;

[0044] When the average composite temperature index of the region is less than the low temperature threshold of the region, the temperature demand of the region is determined to be a heating demand, and a heating demand label is added;

[0045] S43: training a temperature prediction model based on the environmental parameters to obtain an environmental prediction temperature;

[0046] The environmental parameters also include temperature, humidity, and wind speed of the environment outside the energy storage cabinet;

[0047] The temperature prediction model includes an input layer, a hidden layer, and an output layer. The input layer includes 3 neurons, which represent temperature, humidity, and wind speed respectively. The hidden layer has G neurons. The output layer outputs the predicted environmental temperature at a preset time in the future. ;

[0048] S44: Integrate the predicted environmental temperature to formulate temperature control strategies for areas with different temperature requirements in the energy storage cabinet.

[0049] As a further improvement of the present invention, the control instruction includes a temperature control instruction for a cooling demand label area, specifically including the following steps:

[0050] A51: Get the real-time average composite temperature index of the area corresponding to the cooling demand tag;

[0051] A52: Calculate the temperature error term of the jth region using the following formula:

[0052] ;

[0053] in, represents the high temperature error term of the jth region, represents the real-time average composite temperature index of the jth region, represents the maximum target temperature of the jth zone;

[0054] A53: Based on high temperature error term , the control output of the low-temperature refrigerant liquid at the current moment is calculated through the PID controller algorithm ,in, Indicates the flow rate or temperature of low-temperature refrigerant liquid;

[0055] A54: Continuously monitor the real-time average composite temperature index of the jth area, based on The flow rate or temperature of the cryogenic liquid refrigerant is adjusted until the real-time average composite temperature index of the jth zone is reduced to the maximum target temperature corresponding to the zone.

[0056] As a further improvement of the present invention, the control instruction also includes a temperature control instruction for the heating demand label area, specifically including the following steps:

[0057] B51: Get the real-time average composite temperature index of the area corresponding to the heating demand tag;

[0058] B52: Calculate the temperature error term of the jth region. The formula is as follows:

[0059] ;

[0060] in, represents the low temperature error term of the jth region, represents the real-time average composite temperature index of the jth region, represents the minimum target temperature of the jth zone;

[0061] B53: Based on low temperature error term , the control output of the heater at the current moment is calculated by the PID controller algorithm ;in, Indicates the power of the heater;

[0062] B54: Continuously monitor the real-time average composite temperature index of the jth area, based on The power of the heater is adjusted until the real-time average composite temperature index of the jth zone reaches its corresponding minimum target temperature.

[0063] In a second aspect, the present invention provides a temperature-controlled energy storage cabinet based on a cloud platform, comprising a cabinet body, an energy storage module, a data acquisition module, a communication module, and a temperature control module, wherein:

[0064] The energy storage module, data acquisition module, communication module, and temperature control module are placed in the cabinet;

[0065] The energy storage module is used to charge and store energy or discharge the battery module, wherein the battery module is composed of a plurality of batteries connected in series;

[0066] The data acquisition module is used to monitor and collect data;

[0067] The communication module is used to transmit the collected data to the cloud platform and receive the control instructions issued by the cloud platform;

[0068] The temperature control module is used to control the temperature of the battery module based on the control instruction, and includes a heating unit and a cooling unit.

[0069] Beneficial effects of the present invention:

[0070] Through comprehensive analysis of environmental parameters and battery status data, the current operating environment of the energy storage cabinet and the working status of the battery can be accurately reflected. By determining the temperature adjustment factor through multiple factors, the temperature requirements of the energy storage cabinet can be evaluated more comprehensively and accurately.

[0071] By dividing the batteries in the energy storage cabinet into multiple areas and calculating the average composite temperature index and temperature demand label of each area, accurate matching and on-demand allocation of resources are achieved, overcooling or heating is avoided, and the overall energy storage and utilization efficiency is improved, which helps to reduce unnecessary energy consumption and reduce the operating cost of the energy storage cabinet;

[0072] Combined with the predicted environmental temperature information, the temperature control strategy of different areas is optimized, so that the energy storage cabinet can respond to environmental changes in advance, reduce the system response delay caused by temperature changes, and enhance the stability and safety of the energy storage cabinet. Accurate temperature control helps keep the battery within the optimal working range, improves the charging efficiency and equipment service life of the energy storage cabinet, and reduces safety risks caused by overheating or overcooling.

[0073] In addition, the use of cloud platforms for data storage, processing and generation of control instructions enables remote monitoring and intelligent management of energy storage cabinets, reduces the need for manual intervention, reduces management costs, and reduces energy waste caused by human factors. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] Figure 1 It is a flow chart of the temperature control method of the energy storage cabinet based on the cloud platform;

[0075] Figure 2 A flow chart of determining the temperature control strategy for the energy storage cabinet temperature control method based on the cloud platform;

[0076] Figure 3 This is a schematic diagram of the temperature-controlled energy storage cabinet structure based on the cloud platform. DETAILED DESCRIPTION

[0077] In order to make the purpose, technical solution and advantages of the embodiment of the present invention clearer, the technical solution of the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings of the embodiment of the present invention. Obviously, the described embodiment is a part of the embodiment of the present invention, not all of the embodiments. Based on the described embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0078] Unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0079] In order to keep the following description of the embodiments of the present invention clear and concise, detailed descriptions of well-known functions and well-known components are omitted.

[0080] Example 1

[0081] refer to Figure 1 to Figure 2 As shown, a specific implementation of the energy storage cabinet temperature control method based on a cloud platform of the present invention is shown, which specifically includes the following steps:

[0082] S1: Obtain environmental parameters and battery status data;

[0083] The environmental parameters include environmental parameters inside the energy storage cabinet and environmental parameters outside the energy storage cabinet;

[0084] The environmental parameters in the energy storage cabinet include the temperature of each battery in the energy storage cabinet;

[0085] Environmental parameters outside the energy storage cabinet include temperature, humidity, and wind speed;

[0086] The battery status data includes the battery state of charge, charge and discharge rate, and battery health status of each battery in the energy storage cabinet;

[0087] The battery state of charge can be read through the battery management system. The battery is more likely to heat up at a high battery state of charge, and the cooling requirement is greater at this time; heating may be more required at a low battery state of charge; as the state of charge increases, the critical safety temperature of the lithium-ion battery will decrease, which means that when the battery state of charge is high, the battery may more easily reach its safety temperature limit during operation, thereby increasing the risk of thermal runaway. Obtaining the battery state of charge helps to evaluate the safe temperature range of the battery in its current state, so that the ambient temperature in the energy storage cabinet can be controlled more accurately to prevent the battery from thermal runaway due to excessive temperature;

[0088] The charge and discharge rate is calculated by reading the actual current value through the current sensor and comparing it with the rated capacity of the battery. The charge and discharge rate will affect the battery temperature. Too fast charging speed and too high discharge rate will cause the battery temperature to rise.

[0089] The health status of the battery is indirectly estimated by detecting the battery's cycle coefficient, internal resistance change, and capacity attenuation indicators. Aging batteries are more prone to overheating.

[0090] S2: Determine the temperature adjustment factor of the energy storage cabinet based on the battery status data;

[0091] The temperature adjustment factors include the temperature adjustment factor of the battery state of charge, the temperature adjustment factor of the charge and discharge rate, and the temperature adjustment factor of the battery health state, wherein:

[0092] The battery state of charge temperature adjustment factor is determined as follows:

[0093] Configure battery state of charge thresholds, including battery state of charge high temperature threshold and battery state of charge low temperature threshold;

[0094] Obtain the battery state of charge and compare it with the battery state of charge threshold to calculate the state of charge adjustment factor. The calculation formula is as follows:

[0095] ;

[0096] in, represents the battery state of charge temperature adjustment factor of the ith battery, , n represents the total number of batteries in the energy storage cabinet, represents the actual battery state of charge of the ith battery, represents the high temperature threshold of the battery state of charge of the ith battery, represents the low temperature threshold of the battery state of charge of the ith battery, , Represents the weight coefficient, which is set based on experience.

[0097] The calculation formula of the charge and discharge rate temperature adjustment factor is as follows:

[0098] ;

[0099] in, represents the temperature adjustment factor of the charge and discharge rate of the ith battery, represents the actual charge and discharge rate of the ith battery, represents the maximum safe charge and discharge rate of the ith battery, Represents the weight coefficient, which is set based on experience.

[0100] Temperature adjustment factors for determining battery health status include:

[0101] The battery health status value is obtained based on the number of battery cycles, the growth ratio relative to the initial internal resistance, and the loss ratio relative to the initial capacity. The calculation formula is:

[0102] ;

[0103] in, Represents the health status value of the ith battery. The larger the health status value of the battery, the healthier the battery. represents the cycle life of the ith battery, represents the number of cycles of the ith battery, It represents the growth ratio of the i-th battery relative to the initial internal resistance, which is calculated by regularly measuring the internal resistance of the battery; It represents the loss ratio of the i-th battery relative to the initial capacity. By performing a complete charge and discharge cycle, the discharge capacity is calculated, and then the inverse of the capacity retention rate is calculated compared with the rated capacity of the battery. Represents the weight coefficient, which is set based on experience. Represents the nonlinear coefficient, which is set based on experience;

[0104] The battery health status temperature adjustment factor is determined based on the battery health status value, and the calculation formula is:

[0105] ;

[0106] in, represents the temperature adjustment factor of the health status of the ith battery, represents the health status threshold of the ith battery, Represents the weight coefficient, which is set based on experience.

[0107] S3: generating a composite temperature index based on the environmental parameter and the temperature adjustment factor;

[0108] The environmental parameters include the temperature of each battery in the energy storage cabinet,

[0109] The calculation formula for generating the composite temperature index is:

[0110] ;

[0111] in, represents the composite temperature index of the ith battery, represents the real-time temperature of the ith battery, It represents the exponential function with the natural constant e as the base;

[0112] S4: Divide the energy storage cabinet into regions, determine the temperature requirements of different regions according to the composite temperature index, and formulate a temperature control strategy for the energy storage cabinet based on the temperature requirements and the predicted ambient temperature;

[0113] The method of formulating the energy storage cabinet temperature control strategy specifically includes:

[0114] S41: Divide the batteries in the energy storage cabinet into M areas, each area includes The average composite temperature index of all batteries in each area is calculated as:

[0115]

[0116] in, represents the average composite temperature index of all batteries in the jth region, , M is the total number of regions; represents the composite temperature index of the kth battery in the jth region, represents the composite temperature index weight coefficient of the kth battery in the jth region, ;

[0117] S42: traverse each divided area, determine the temperature requirement of each area, and add a temperature requirement label according to the temperature requirement, specifically including:

[0118] Configure high temperature threshold and low temperature threshold for each area;

[0119] When the average composite temperature index of a region is greater than the high temperature threshold of the region, the temperature demand of the region is determined to be a cooling demand, and a cooling demand label is added;

[0120] When the average composite temperature index of a region is not greater than the region's high temperature threshold and not less than the region's low temperature threshold, it is determined that the region has no temperature requirement and no label needs to be added;

[0121] When the average composite temperature index of the region is less than the low temperature threshold of the region, the temperature demand of the region is determined to be a heating demand, and a heating demand label is added;

[0122] S43: Training a temperature prediction model based on the environmental parameters to obtain the predicted environmental temperature, specifically including:

[0123] The predicted environmental temperature is obtained through a temperature prediction model, which includes an input layer, a hidden layer, and an output layer. The input layer includes 3 neurons, which represent temperature, humidity, and wind speed respectively. The hidden layer has G neurons. The output layer outputs the predicted environmental temperature at a preset time in the future. , wherein the future preset time may be 30 minutes, 1 hour or 2 hours, etc., which is set by those skilled in the art;

[0124] S44: integrating the predicted environmental temperature to formulate temperature control strategies for areas corresponding to different temperature requirements in the energy storage cabinet; the temperature control strategies include cooling demand control strategies and heating demand control strategies;

[0125] Adjustments to the cooling demand control strategy include:

[0126] When the predicted ambient temperature at a preset time in the future is higher than the current temperature, the flow rate or temperature of the low-temperature liquid refrigerant is increased for all batteries in the area corresponding to the cooling demand label;

[0127] When the predicted ambient temperature at a preset time in the future is lower than the current temperature, the flow rate or temperature of the cryogenic liquid refrigerant is reduced for all batteries in the area corresponding to the cooling demand label;

[0128] Adjustments to the heating demand control strategy include:

[0129] When the predicted ambient temperature at a preset time in the future is higher than the current temperature, the heater power is reduced for all batteries in the area corresponding to the heating demand label;

[0130] When the predicted ambient temperature at a preset time in the future is lower than the current temperature, the heater power is increased for all batteries in the area corresponding to the heating demand label;

[0131] S5: The cloud platform generates a control instruction based on the temperature control strategy, and sends it to the energy storage cabinet to execute the control instruction.

[0132] The control instructions include control instructions for the area corresponding to the cooling demand tag and the area corresponding to the heating demand tag, specifically including:

[0133] Determining the control instructions for the area corresponding to the cooling requirement tag specifically includes the following steps:

[0134] A51: Get the real-time average composite temperature index of the area corresponding to the cooling demand tag;

[0135] A52: Calculate the temperature error term of the jth region using the following formula:

[0136] ;

[0137] in, represents the high temperature error term of the jth region, represents the real-time average composite temperature index of the jth region, represents the maximum target temperature of the jth zone;

[0138] A53: Design of a PID controller for a temperature-controlled energy storage cabinet based on the high temperature error term , the PID controller calculates the control output of the low-temperature refrigerant liquid at the current moment ,in, Indicates the flow rate or temperature of cryogenic liquid refrigerant;

[0139] A54: Continuously monitor the real-time average composite temperature index of the jth area, based on The flow rate or temperature of the cryogenic liquid refrigerant is adjusted until the real-time average composite temperature index of the jth zone is reduced to the maximum target temperature corresponding to the zone.

[0140] Determining the control instructions for the area corresponding to the heating demand tag specifically includes the following steps:

[0141] B51: Get the real-time average composite temperature index of the area corresponding to the heating demand tag;

[0142] B52: Calculate the temperature error term of the jth region. The formula is as follows:

[0143] ;

[0144] in, represents the low temperature error term of the jth region, represents the real-time average composite temperature index of the jth region, represents the minimum target temperature of the jth region; the temperature error term includes a high temperature error term and a low temperature error term;

[0145] B53: Design of PID controller for temperature-controlled energy storage cabinet based on low temperature error term , the control output of the heater at the current moment is calculated by the PID controller algorithm ;in, Indicates the power of the heater;

[0146] B54: Continuously monitor the real-time average composite temperature index of the jth area, based on The power of the heater is adjusted until the real-time average composite temperature index of the jth zone reaches the minimum target temperature corresponding to its zone.

[0147] Among them, the PID controller algorithm will calculate the control output based on the error, and specifically control the output through the parameter settings of the proportional term, integral term and differential term. The control output of this embodiment is the temperature and flow rate of the low-temperature refrigerant liquid or the power of the heater. The parameter settings of the proportional term, integral term and differential term are based on the specific characteristics and requirements of the temperature-controlled energy storage cabinet, and are preliminarily set through on-site debugging and empirical formulas, and are optimized and adjusted during the control process.

[0148] Example 2

[0149] refer to Figure 3 As shown, this embodiment is the second embodiment of the present invention; based on the same inventive concept as embodiment 1, this embodiment introduces a specific implementation of a temperature-controlled energy storage cabinet based on a cloud platform, including a cabinet body, an energy storage module, a data acquisition module, a communication module, and a temperature control module;

[0150] The energy storage module, temperature control module and communication module are placed in the cabinet;

[0151] The energy storage module is used to charge and store energy or discharge a battery module, and the battery module is composed of a plurality of batteries connected in series;

[0152] The data acquisition module is used to monitor and collect data, including collecting environmental parameters and battery status data;

[0153] The temperature control module is used to control the temperature of the battery module so that the energy storage cabinet is in an optimal temperature range, and includes a heating unit and a cooling unit, wherein:

[0154] The heating unit is used to heat the battery module to ensure that the battery can maintain a suitable operating temperature range in a low-temperature environment, reduce performance degradation caused by low temperature, and prevent the battery from being damaged due to overcooling;

[0155] The cooling unit is used to cool the battery module through low-temperature liquid refrigerant to prevent the battery from overheating under high temperature conditions, effectively control the battery temperature, and ensure that it operates within a safe and efficient temperature range;

[0156] The communication module is used to transmit the collected data to the cloud platform and receive control instructions issued by the cloud platform; the control instructions include controlling the temperature and flow rate of the low-temperature refrigerant liquid and the power of the heater.

[0157] Working principle and its effect:

[0158] Through comprehensive analysis of environmental parameters and battery status data, the current operating environment of the energy storage cabinet and the working status of the battery can be accurately reflected. By determining the temperature adjustment factor through multiple factors, the temperature requirements of the energy storage cabinet can be evaluated more comprehensively and accurately.

[0159] By dividing the batteries in the energy storage cabinet into multiple areas and calculating the average composite temperature index and temperature demand label of each area, accurate matching and on-demand allocation of resources are achieved, overcooling or heating is avoided, and the overall energy storage and utilization efficiency is improved, which helps to reduce unnecessary energy consumption and reduce the operating cost of the energy storage cabinet;

[0160] Combined with the predicted environmental temperature information, the temperature control strategy of different areas is optimized, so that the energy storage cabinet can respond to environmental changes in advance, reduce the system response delay caused by temperature changes, and enhance the stability and safety of the energy storage cabinet. Accurate temperature control helps keep the battery within the optimal working range, improves the charging efficiency and equipment service life of the energy storage cabinet, and reduces safety risks caused by overheating or overcooling.

[0161] In addition, the use of cloud platforms for data storage, processing and generation of control instructions enables remote monitoring and intelligent management of energy storage cabinets, reduces the need for manual intervention, reduces management costs, and reduces energy waste caused by human factors.

[0162] In addition, although exemplary embodiments have been described in the present invention, the scope includes any and all embodiments based on the present invention with equivalent elements, modifications, omissions, combinations (e.g., various embodiments intersecting schemes), adaptations or changes. The elements in the claims will be interpreted broadly based on the language adopted in the claims, and are not limited to the examples described in this specification or during the execution of this application, and the examples will be interpreted as non-exclusive. Therefore, this specification and examples are intended to be considered as examples only, and the true scope and spirit are indicated by the claims and the full scope of their equivalents.

[0163] The above description is intended to be illustrative rather than restrictive. For example, the above examples (or one or more schemes thereof) may be used in combination with each other. For example, a person of ordinary skill in the art may use other embodiments when reading the above description. In addition, in the above-mentioned specific embodiments, various features may be grouped together to simplify the present invention. This should not be interpreted as an intention that a disclosed feature that is not required to be protected is necessary for any claim. On the contrary, the subject matter of the present invention may be less than all the features of a particular disclosed embodiment. Thus, the claims are incorporated herein into the specific embodiments as examples or embodiments, wherein each claim is independently a separate embodiment, and it is considered that these embodiments may be combined with each other in various combinations or arrangements. The scope of the present invention should be determined with reference to the appended claims and the full scope of equivalent forms granted by these claims.

[0164] The above embodiments are only exemplary embodiments of the present invention and are not intended to limit the present invention. The protection scope of the present invention is defined by the claims. Those skilled in the art may make various modifications or equivalent substitutions to the present invention within the essence and protection scope of the present invention, and such modifications or equivalent substitutions shall also be deemed to fall within the protection scope of the present invention.

Claims

1. A temperature control method for energy storage cabinet based on a cloud platform, characterized in that: The specific steps include: S1: Obtain environmental parameters and battery status data; S2: Determine the temperature adjustment factor of the energy storage cabinet according to the battery status data; The temperature adjustment factor includes a battery health state temperature adjustment factor, and the battery health state temperature adjustment factor is determined in the following manner: Acquire battery health status parameters, wherein the battery health status parameters include the number of battery cycles, the growth ratio relative to the initial internal resistance, and the loss ratio relative to the initial capacity; Calculate the battery health state value using the battery health state parameter; determining a battery state of health temperature adjustment factor based on the battery state of health value; S3: generating a composite temperature index based on the environmental parameter and the temperature adjustment factor; S4: Divide the energy storage cabinet into regions, determine the temperature requirements of different regions according to the composite temperature index, and formulate a temperature control strategy for the energy storage cabinet based on the temperature requirements and the predicted ambient temperature; S5: The cloud platform generates a control instruction based on the temperature control strategy, and sends it to the energy storage cabinet to execute the control instruction; The environmental parameters include the real-time temperature of each battery in the energy storage cabinet. The generation of the composite temperature index specifically includes: The real-time temperature of each battery in the energy storage cabinet is obtained, and the composite temperature index of each battery is generated by combining the battery state of charge temperature adjustment factor, charge and discharge rate temperature adjustment factor, and battery health state temperature adjustment factor. The calculation formula of the composite temperature index is as follows: ； in, represents the composite temperature index of the ith battery, represents the real-time temperature of the ith battery, represents the temperature adjustment factor of the charge and discharge rate of the ith battery, represents the battery state of charge temperature adjustment factor of the ith battery, represents the temperature adjustment factor of the health status of the ith battery, represents an exponential function with the natural constant e as the base, , n represents the total number of batteries in the energy storage cabinet; The method of formulating the energy storage cabinet temperature control strategy includes: Divide the batteries in the energy storage cabinet into multiple areas, calculate the average composite temperature index of all batteries in each area; traverse each area, determine the temperature requirement of each area, and add a temperature requirement label according to the temperature requirement; train the temperature prediction model based on the environmental parameters to obtain the environmental prediction temperature; integrate the environmental prediction temperature to formulate the temperature control strategy for the areas with different temperature requirements in the energy storage cabinet; The calculation formula for calculating the average composite temperature index of all batteries in each area is as follows: ； in, represents the average composite temperature index of all batteries in the jth region, , M is the total number of regions; represents the composite temperature index of the kth battery in the jth region, represents the composite temperature index weight coefficient of the kth battery in the jth region, , The total number of batteries for each region.

2. The temperature control method of energy storage cabinet based on cloud platform according to claim 1 is characterized in that: The temperature adjustment factor also includes a temperature adjustment factor of the battery state of charge. The battery state of charge temperature adjustment factor is determined as follows: Configuring a battery state of charge threshold, wherein the battery state of charge threshold includes a battery state of charge high temperature threshold and a battery state of charge low temperature threshold; Get the battery state of charge, compare it with the battery state of charge threshold, and calculate the battery state of charge temperature adjustment factor. The calculation formula is as follows: ； in, represents the battery state of charge temperature adjustment factor of the ith battery, , n represents the total number of batteries in the energy storage cabinet, represents the actual battery state of charge of the ith battery, represents the high temperature threshold of the battery state of charge of the ith battery, represents the low temperature threshold of the battery state of charge of the ith battery, , Represents the weight coefficient.

3. The temperature control method of the energy storage cabinet based on the cloud platform according to claim 2 is characterized in that: The temperature adjustment factor also includes a charge and discharge rate temperature adjustment factor, and the calculation formula of the charge and discharge rate temperature adjustment factor is as follows: ； in, represents the temperature adjustment factor of the charge and discharge rate of the ith battery, represents the actual charge and discharge rate of the ith battery, represents the maximum safe charge and discharge rate of the ith battery, Represents the weight coefficient.

4. The temperature control method of the energy storage cabinet based on the cloud platform according to claim 3 is characterized in that: The calculation formula for determining the battery health state temperature adjustment factor based on the battery health state value is: ； in, represents the temperature adjustment factor of the health status of the ith battery, represents the health status threshold of the ith battery, represents the weight coefficient, Represents the health status value of the ith battery.

5. The cloud platform-based energy storage cabinet temperature control method according to claim 4 is characterized in that: The calculation formula of the battery health status value is: ； Among them, the battery health status value The larger it is, the healthier the battery is. represents the cycle life of the ith battery, represents the number of cycles of the ith battery, represents the growth ratio of the i-th battery relative to the initial internal resistance, represents the loss ratio of the i-th battery relative to the initial capacity, represents the weight coefficient, represents the nonlinear coefficient.

6. The cloud platform-based energy storage cabinet temperature control method according to claim 5, characterized in that: The method of formulating the energy storage cabinet temperature control strategy specifically includes: S41: Divide the batteries in the energy storage cabinet into M areas, each area includes For each battery, calculate the average composite temperature index of all batteries in each area; S42: traverse each area, determine the temperature requirement of each area, and add a temperature requirement tag according to the temperature requirement, specifically including: Configure high temperature threshold and low temperature threshold for each area; When the average composite temperature index of a region is greater than the high temperature threshold of the region, the temperature demand of the region is determined to be a cooling demand, and a cooling demand label is added; When the average composite temperature index of a region is not greater than the region's high temperature threshold and not less than the region's low temperature threshold, it is determined that the region has no temperature requirement and no label needs to be added; When the average composite temperature index of the region is less than the low temperature threshold of the region, the temperature demand of the region is determined to be a heating demand, and a heating demand label is added; S43: training a temperature prediction model based on the environmental parameters to obtain an environmental prediction temperature; The environmental parameters also include temperature, humidity, and wind speed of the environment outside the energy storage cabinet; The temperature prediction model includes an input layer, a hidden layer, and an output layer. The input layer includes 3 neurons, which represent temperature, humidity, and wind speed respectively. The hidden layer has G neurons. The output layer outputs the predicted environmental temperature at a preset time in the future. ; S44: Integrate the predicted environmental temperature to formulate temperature control strategies for areas with different temperature requirements in the energy storage cabinet.

7. The cloud platform-based energy storage cabinet temperature control method according to claim 6, characterized in that: The control instruction includes a temperature control instruction for the area corresponding to the cooling requirement tag, specifically including the following steps: A51: Get the real-time average composite temperature index of the area corresponding to the cooling demand tag; A52: Calculate the temperature error term of the jth region using the following formula: ； in, represents the high temperature error term of the jth region, represents the real-time average composite temperature index of the jth region, represents the maximum target temperature of the jth zone; A53: Based on high temperature error term , the control output of the low-temperature refrigerant liquid at the current moment is calculated through the PID controller algorithm ,in, Indicates the flow rate or temperature of low-temperature refrigerant liquid; A54: Continuously monitor the real-time average composite temperature index of the jth area, based on The flow rate or temperature of the cryogenic liquid refrigerant is adjusted until the real-time average composite temperature index of the jth zone is reduced to the maximum target temperature corresponding to the zone.

8. The cloud platform-based energy storage cabinet temperature control method according to claim 7, characterized in that: The control instruction also includes a temperature control instruction for the area corresponding to the heating demand tag, specifically including the following steps: B51: Get the real-time average composite temperature index of the area corresponding to the heating demand tag; B52: Calculate the temperature error term of the jth region. The formula is as follows: ； in, represents the low temperature error term of the jth region, represents the minimum target temperature of the jth zone; B53: Based on low temperature error term , the control output of the heater at the current moment is calculated by the PID controller algorithm ;in Indicates the power of the heater; B54: Continuously monitor the real-time average composite temperature index of the jth area, based on The power of the heater is adjusted until the real-time average composite temperature index of the jth zone reaches the minimum target temperature corresponding to its zone.

9. A temperature-controlled energy storage cabinet based on a cloud platform, used to implement the temperature-controlled energy storage cabinet method based on a cloud platform as described in any one of claims 1 to 8, characterized in that: include: Cabinet, energy storage module, data acquisition module, communication module, temperature control module, including: The energy storage module, data acquisition module, communication module, and temperature control module are placed in the cabinet; The energy storage module is used to charge and store energy or discharge the battery module, wherein the battery module is composed of a plurality of batteries connected in series; The data acquisition module is used to monitor and collect data; The communication module is used to transmit the collected data to the cloud platform and receive the control instructions issued by the cloud platform; The temperature control module is used to control the temperature of the battery module based on the control instruction, and the temperature control module includes a heating unit and a cooling unit.

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