Intelligent temperature control high-low voltage cabinet of new energy storage system

Abstract

The invention provides an intelligent temperature control high-low voltage cabinet of a new energy storage system, and the cabinet comprises a monitoring and early warning assembly which collects the temperature data of each key part in the high-low voltage cabinet in real time through a distributed temperature sensor array, and senses the external environment change of the high-low voltage cabinet in combination with a multi-dimensional environment sensor; meanwhile, abnormal early warning is carried out according to historical temperature data and real-time dynamic states, and potential risks are pre-judged in advance; the temperature control adjusting assembly is automatically switched to a heat dissipation strategy according to the temperature data of the key part, the external environment change data and the equipment load, and the heat dissipation strategy comprises passive heat dissipation, air cooling heat dissipation, liquid cooling heat dissipation and semiconductor cooling; the energy recovery assembly dynamically adjusts operation parameters of heat dissipation equipment in the heat dissipation strategy; heat generated by heat dissipation equipment in the heat dissipation process is converted into heat supply, hot water or electric energy through integrated modular waste heat recovery. According to the invention, full-process automatic management from monitoring and early warning to adjustment and recovery is realized, manual intervention is reduced, and the management efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic temperature control, and particularly to an intelligent temperature-controlled high and low voltage cabinet for a new energy energy storage system. Background Art

[0002] With the rapid development of new energy technologies, the importance of energy storage systems in energy management has become increasingly prominent. One of the core components of the energy storage device in an energy storage system is the high and low voltage cabinet, and its performance is directly related to the operating efficiency and safety of the entire system. However, a large amount of heat is generated during the operation of the energy storage device, especially during high-power output or long-term operation, and temperature control has become a key technical difficulty. If the temperature control is not in place, it may lead to a decline in device performance, a shortened service life, or even safety accidents. Therefore, the development of an intelligent temperature control system that can monitor the temperature changes of the high and low voltage cabinet in real time and perform precise regulation has become an important research direction in the field of new energy energy storage systems.

[0003] Currently, the temperature control technologies for high and low voltage cabinets on the market mainly include passive heat dissipation, air-cooled heat dissipation, and liquid cooling, etc. Passive heat dissipation mainly relies on natural convection and heat conduction, and is suitable for low-power devices, but its heat dissipation efficiency is low; air-cooled heat dissipation improves the heat dissipation effect by installing a fan for forced convection, but it has a large noise and is easily affected by the environment; liquid cooling uses the method of coolant circulation, with a high heat dissipation efficiency, but the system is complex and the maintenance cost is high. In addition, there are also some intelligent temperature control systems combined with temperature sensors in the prior art, but they can often only achieve simple temperature monitoring and alarm functions and cannot perform refined temperature regulation. Passive heat dissipation and air-cooled heat dissipation are difficult to meet the requirements of rapid heat dissipation when facing high-power energy storage systems, resulting in an increase in device temperature and affecting performance; although the existing temperature control systems can monitor the temperature, they lack intelligent regulation capabilities and cannot dynamically adjust the heat dissipation strategy according to the actual temperature changes; the air-cooled heat dissipation system has a large noise during operation and high energy consumption, which does not conform to the design concept of green energy conservation; although the liquid cooling system has a good heat dissipation effect, its structure is complex and the maintenance cost is high, and it is not suitable for large-scale popularization and application.

[0004] Prior Art One, Application Number: CN202010021291.8 discloses a high and low voltage cabinet that can be remotely monitored, including a cabinet body and a shock-absorbing base; the cabinet body is installed on the shock-absorbing base; temperature sensors and humidity sensors are provided on the inner side walls of the cabinet body; an intake fan and an exhaust fan are respectively provided at the diagonal positions on both sides of the cabinet body, and the intake fan is located below the exhaust fan; a controller and a data switch are provided inside the cabinet body, and the temperature sensors, humidity sensors, intake fan, and exhaust fan are respectively electrically connected to the controller, and the controller is electrically connected to the data switch. Although it facilitates the later maintenance work of the high and low voltage cabinet by the backstage personnel and improves the working ability of the high and low voltage cabinet in a harsh environment; however, it only realizes temperature monitoring and heat dissipation through temperature sensors and simple fans, lacks diversified heat dissipation strategies and dynamic regulation capabilities, and cannot meet the rapid heat dissipation requirements of high-power energy storage systems; it can only perform basic temperature monitoring and cannot perform abnormal early warning and potential risk prediction based on historical data and real-time dynamics.

[0005] Prior Art Two, Application Number: CN201810683737.6 discloses a protection device for a high and low voltage cabinet, including a protection cabinet main body, a door body, a dehumidifier, a fire alarm, and a heat dissipation cavity. A heat dissipation cavity is provided at the center position of the bottom end of the protection cabinet main body, a heat dissipation plate is installed at the bottom end inside the heat dissipation cavity, heat dissipation fans are provided inside the heat dissipation cavity on both sides of the heat dissipation plate, a fireproof barrier layer is provided at the bottom end of the protection cabinet main body, folding screw holes are hinged on both side walls of the fireproof barrier layer, a clamping cavity is provided at the center position inside the protection cabinet main body, fixed buckles are provided on the inner side walls of the clamping cavity, lifting buckles are installed at both ends of the fixed buckles, and a temperature sensor is fixed at the center position of the top end of the clamping cavity. Although it not only improves the safety of the protection device during use, improves the convenience of installation of the high and low voltage cabinet, but also extends the service life of the protection device; however, the heat dissipation efficiency is low and the energy consumption is high. Using traditional heat dissipation fans and heat dissipation plates, the heat dissipation efficiency is limited and the energy consumption is high, which does not conform to the design concept of green energy conservation; the system complexity and maintenance cost are high.

[0006] Prior Art Three, Application No.: CN 202210146987.2 discloses a high and low voltage cabinet with a neat wire arrangement function and its usage method, including a cabinet body. A top shell is arranged at the top of the cabinet body, and a limiting mechanism is arranged at the bottom of the top shell. The limiting mechanism includes a discharge pipe, the top of the discharge pipe is communicated with the top shell, and a bracket is welded on the left side of the rear of the top shell. The present invention is used in combination with the cabinet body, the column, the top shell, the feed pipe, the connecting plate, the electric telescopic rod, the blanking mechanism, the bracket, the fixing frame, the motor, the second bracket, the pulling block, the installation base, the through hole, the temperature and smoke integrated sensor, the threaded rod, the guide groove, the guide rod and the extension mechanism. Although it solves the problems that the existing high and low voltage cabinets with a neat wire arrangement function usually do not have the function of automatically detecting fire and extinguishing targeted fires during use, and usually cannot provide backup energy through light energy in outdoor environments, which may cause certain inconveniences to users; however, it can only perform simple detection and alarm, cannot achieve fine temperature control; and fails to make full use of the waste heat generated during the operation of the equipment, resulting in low energy utilization efficiency.

[0007] Currently, Prior Art One, Prior Art Two and Prior Art Three have problems such as low heat dissipation efficiency, insufficient regulation ability, complex system, high energy consumption and low energy utilization efficiency in the prior art. Therefore, the present invention provides an intelligent temperature-controlled high and low voltage cabinet for a new energy energy storage system. Summary of the Invention

[0008] In order to solve the above technical problems, the present invention provides an intelligent temperature-controlled high and low voltage cabinet for a new energy energy storage system, including:

[0009] A monitoring and warning component, responsible for collecting temperature data of each key part inside the high and low voltage cabinet in real time through a distributed temperature sensor array, and perceiving changes in the external environment of the high and low voltage cabinet in combination with multi-dimensional environmental sensors; at the same time, making an abnormal warning according to the temperature historical data and real-time dynamics, and predicting potential risks in advance;

[0010] A temperature control and adjustment component, responsible for automatically switching to a heat dissipation strategy according to the temperature data of the key parts, the external environment change data and the equipment load. The heat dissipation strategies include passive heat dissipation, air-cooled heat dissipation, liquid-cooled heat dissipation and semiconductor cooling;

[0011] An energy recovery component, responsible for dynamically adjusting the operating parameters of the heat dissipation equipment in the heat dissipation strategy; integrating modular waste heat recovery to convert the heat generated by the heat dissipation equipment during the heat dissipation process into heating, hot water or electric energy.

[0012] Optionally, the monitoring and warning component includes:

[0013] The data acquisition and fusion module is responsible for forming a multi-dimensional dynamic data set from the temperature data of key parts inside the high- and low-voltage switchgear and the external environment change information; based on the historical temperature data, a dynamic temperature baseline is constructed for each key part to identify the normal temperature fluctuation range of the equipment at key parts under different working conditions.

[0014] The abnormal feature extraction module is responsible for extracting features from the data in the multi-dimensional dynamic data set, paying attention to the temperature change rate, periodic fluctuations, and the correlation with environmental parameters; at the same time, combining the historical temperature data, abnormal features deviating from the dynamic baseline are identified.

[0015] The risk assessment module is responsible for performing correlation analysis on the extracted abnormal features with environmental data and equipment load information to form a multi-dimensional risk assessment model; according to the risk assessment results, potential risks are classified and warned, and the warning levels are divided into observation level, prevention level, and emergency level from low to high.

[0016] Optionally, the temperature control and regulation component includes:

[0017] The initial strategy setting module is responsible for selecting an appropriate heat dissipation strategy from passive heat dissipation, air-cooled heat dissipation, liquid-cooled heat dissipation, and semiconductor cooling as the initial heat dissipation strategy according to the initial temperature data of key parts, external environment change data, and equipment load during the use of the high- and low-voltage switchgear; at the same time, the upper and lower limits of the temperature data at which each heat dissipation strategy is activated are set according to the external environment change data and equipment load.

[0018] The heat dissipation demand generation module is responsible for obtaining the temperature data of key parts, external environment change data, and equipment load collected at the first time point, the second time point, and the third time point to form three groups of state parameter sets of key parts; analyzing the three groups of state parameter sets to obtain the target heat dissipation demand.

[0019] The demand relationship judgment module is responsible for generating a heat dissipation strategy switching instruction according to the target heat dissipation demand when the initial heat dissipation strategy cannot meet the target heat dissipation demand, and replacing the initial heat dissipation strategy with a new heat dissipation strategy; when the next time point is reached, continue to judge the relationship between the current heat dissipation strategy and the current heat dissipation demand.

[0020] Optionally, the heat dissipation demand generation module includes:

[0021] The trend judgment sub-module is responsible for obtaining the temperature data of key parts from the three groups of state parameter sets, analyzing the temperature data at the three time points to obtain the temperature data trend at the next time point, and judging whether the temperature data trend is increasing or decreasing. If it is decreasing, stop the temperature data analysis and continue to wait for the next time point to judge the temperature data trend.

[0022] The load demand sub-module is responsible for, when the temperature data trend increases, obtaining the external environment change data trend, and obtaining the device load based on the temperature data trend and the external environment change data trend.

[0023] The relationship judgment sub-module is responsible for, when the temperature data exceeds the upper limit of the current heat dissipation strategy, using the current temperature data as the target heat dissipation demand and judging the relationship between the target heat dissipation demand and the initial heat dissipation strategy.

[0024] Optionally, the load demand sub-module includes:

[0025] The weight allocation unit is responsible for obtaining the temperature data trend and the external environment change data trend, and allocating dynamic weights to the variables of each external environment change data according to the different degrees of influence of the external environment change data on the temperature data.

[0026] The influence quantification unit is responsible for constructing a heat flow balance model of the device based on the first law of thermodynamics to describe the dynamic relationship in the process of heat generation, transfer and dissipation inside the device; introducing external environment variables into the heat flow balance model to quantify the influence on heat transfer.

[0027] The dynamic superposition unit is responsible for predicting the heat distribution and transfer path inside the device through finite element analysis; dynamically superposing the internal temperature data change trend and the external environment change data trend through the heat flow balance model and weight allocation; calculating the device load threshold according to the current heat accumulation speed and distribution of the device after dynamic superposition.

[0028] Optionally, the expression of the heat flow balance model: Internal heat accumulation = Heat generated by the device heat source - Heat dissipated through the heat dissipation mechanism.

[0029] Optionally, the dynamic superposition unit includes:

[0030] The heat analysis sub-unit is responsible for dynamically superposing the internal temperature data change trend and the external environment change data trend to form a comprehensive heat state description; analyzing the heat accumulation speed and its distribution inside the device.

[0031] The adjustment calculation sub-unit is responsible for obtaining the dynamic transfer characteristics of the heat inside the device, combining the potential influence of the external environment change on the heat state of the device, and adjusting the calculation model of the load threshold.

[0032] The threshold determination sub-unit is responsible for establishing a heat accumulation model according to the structural materials and thermal characteristics of the device, calculating the highest temperature reached by the device under specific working conditions; evaluating the heat dissipation capacity of the device under different environmental conditions; determining the highest load threshold within the safe operating range of the device based on the heat accumulation model and heat dissipation capacity evaluation.

[0033] Optionally, the demand relationship judgment module includes:

[0034] The instruction generation sub-module is responsible for matching the heat dissipation strategy according to the target heat dissipation demand, dynamically selecting a new heat dissipation strategy; when the new heat dissipation strategy is selected, generating a corresponding heat dissipation strategy switching instruction;

[0035] The strategy switching sub-module is responsible for, when receiving the heat dissipation strategy switching instruction, asking the initial heat dissipation strategy whether it agrees to be replaced as the switching input terminal, and when the initial heat dissipation strategy agrees to switch, switching the initial heat dissipation strategy to the new heat dissipation strategy as the switching input terminal;

[0036] The closed-loop feedback sub-module is responsible for, after the heat dissipation strategy switching instruction is executed, monitoring the temperature change of the key parts, the fluctuation of the external environment, and the condition of the device load in real time; at the same time, continuing to enter the demand judgment and strategy matching stage of the next time point, forming a closed-loop feedback mechanism.

[0037] Optionally, the instruction includes the specific implementation method of the new heat dissipation strategy, the switching time node, the adjustment of the temperature threshold, and the adaptive adjustment to the change of the external environment.

[0038] Optionally, the instruction generation sub-module includes:

[0039] The node selection unit is responsible for, after the new heat dissipation strategy is determined, designing the function deployment and operation parameter limitation of the heat dissipation device; selecting a switching time node according to the target heat dissipation demand and the real-time state of the device operation, based on the temperature rise rate of the key parts and the dynamic change of the external environment;

[0040] The continuous monitoring unit is responsible for dynamically adjusting the temperature threshold according to the temperature data of the key parts and the device load, resetting the upper and lower limits of the temperature of the key parts; continuously monitoring the change of the external environment, and dynamically optimizing the new heat dissipation strategy;

[0041] The content embedding unit is responsible for embedding the specific implementation method, the switching time node, the temperature threshold adjustment, and the external environment adaptive adjustment into the heat dissipation strategy switching instruction to generate a complete heat dissipation strategy switching instruction.

[0042] The monitoring and early warning component of the present invention collects the temperature data of each key part inside the high-voltage and low-voltage cabinets in real time through a distributed temperature sensor array, and combines multi-dimensional environmental sensors to sense the external environmental changes of the high-voltage and low-voltage cabinets; at the same time, according to the temperature historical data and real-time dynamics, it conducts abnormal early warning and anticipates potential risks in advance; the temperature control and regulation component automatically switches to a heat dissipation strategy according to the temperature data of the key parts, external environmental change data, and equipment load, and the heat dissipation strategy includes passive heat dissipation, air-cooled heat dissipation, liquid-cooled heat dissipation, and semiconductor cooling; the energy recovery component dynamically adjusts the operating parameters of the heat dissipation equipment in the heat dissipation strategy; the integrated modular waste heat recovery converts the heat generated by the heat dissipation equipment during the heat dissipation process into heating, hot water, or electric energy. Through the above solutions, the monitoring and early warning component can timely detect abnormalities and anticipate risks in advance by collecting temperature data in real time and multi-dimensional environmental perception, effectively avoiding equipment failures or safety hazards caused by excessive temperature or environmental changes. The temperature control and regulation component automatically switches to the most suitable heat dissipation strategy according to the equipment load and internal and external environmental data, ensuring that the temperature of the key parts is always within the ideal range, improving the heat dissipation efficiency and reducing energy consumption. The energy recovery component converts the waste heat generated during the heat dissipation process into heating, hot water, or electric energy, realizing the cascaded utilization of energy, reducing energy waste, and conforming to the concept of green and sustainable development.

[0043] Other features and advantages of the present invention will be described in the following description, and, in part, will be obvious from the description, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained by the structures specifically pointed out in the written description and the drawings.

[0044] The technical solutions of the present invention will be further described in detail below through the drawings and embodiments. Description of the Drawings

[0045] The drawings are used to provide a further understanding of the present invention and constitute a part of the description. They are used together with the embodiments of the present invention to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0046] Figure 1 It is the block diagram of the intelligent temperature-controlled high-voltage and low-voltage cabinet of the new energy energy storage system in Embodiment 1 of the present invention;

[0047] Figure 2 It is the schematic diagram of the intelligent temperature-controlled high-voltage and low-voltage cabinet of the new energy energy storage system in Embodiment 1 of the present invention;

[0048] Figure 3 It is the block diagram of the monitoring and early warning component in Embodiment 2 of the present invention;

[0049] Figure 4 It is the block diagram of the temperature control and regulation component in Embodiment 3 of the present invention;

[0050] Figure 5This is the block diagram of the energy recovery component in Embodiment 9 of the present invention. Detailed implementation manners

[0051] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only for the purpose of illustrating and explaining the present invention, and are not used to limit the present invention.

[0052] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the embodiments of the present application. In the embodiments of the present application, the singular forms "a", "the" and "said" are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0053] When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. On the contrary, they are only examples of devices and methods consistent with some aspects of the present application. In the description of the present application, it should be understood that the terms "first", "second", "third", etc. are only used to distinguish similar objects, and do not have to be used to describe a specific order or sequence, nor can they be understood as indicating or implying relative importance. For those of ordinary skill in the art, the specific meanings of the above terms in the present application can be understood according to specific circumstances.

[0054] Embodiment 1: As Figure 1 shown, the embodiment of the present invention provides an intelligent temperature-controlled high and low voltage cabinet for a new energy energy storage system, including:

[0055] A monitoring and early warning component, responsible for collecting the temperature data of each key part inside the high and low voltage cabinet in real time through a distributed temperature sensor array, and perceiving the external environment changes of the high and low voltage cabinet in combination with multi-dimensional environmental sensors; at the same time, according to the temperature historical data and real-time dynamics, it conducts abnormal early warning and anticipates potential risks in advance;

[0056] A temperature control and adjustment component, responsible for automatically switching to a heat dissipation strategy according to the temperature data of the key parts, the external environment change data and the device load. The heat dissipation strategies include passive heat dissipation, air-cooled heat dissipation, liquid-cooled heat dissipation and semiconductor cooling;

[0057] An energy recovery component, responsible for dynamically adjusting the operating parameters of the heat dissipation devices in the heat dissipation strategy; integrating modular waste heat recovery to convert the heat generated by the heat dissipation devices during the heat dissipation process into heating, hot water or electric energy.

[0058] The working principle and beneficial effects of the above technical solution are as follows: The monitoring and early warning component of this embodiment collects the temperature data of each key part inside the high-voltage and low-voltage cabinets in real time through a distributed temperature sensor array, and combines multi-dimensional environmental sensors to perceive the changes in the external environment of the high-voltage and low-voltage cabinets; at the same time, according to the temperature historical data and real-time dynamics, it conducts abnormal early warning and anticipates potential risks in advance; the temperature control and regulation component automatically switches to a heat dissipation strategy according to the temperature data of the key parts, the external environment change data, and the equipment load. The heat dissipation strategy includes passive heat dissipation, air-cooled heat dissipation, liquid-cooled heat dissipation, and semiconductor cooling; the energy recovery component dynamically adjusts the operating parameters of the heat dissipation equipment in the heat dissipation strategy; the integrated modular waste heat recovery converts the heat generated by the heat dissipation equipment during the heat dissipation process into heating, hot water, or electric energy (for the specific principle, please refer to Appendix Figure 2 ). Through real-time collection of temperature data and multi-dimensional environmental perception, the monitoring and early warning component of the above solution can detect abnormalities in time, anticipate risks in advance, and effectively avoid equipment failures or safety hazards caused by excessive temperature or environmental changes. According to the equipment load and internal and external environment data, the temperature control and regulation component automatically switches to the most suitable heat dissipation strategy to ensure that the temperature of the key parts is always within the ideal range, which not only improves the heat dissipation efficiency but also reduces energy consumption. The energy recovery component converts the waste heat generated during the heat dissipation process into heating, hot water, or electric energy, realizing the cascade utilization of energy, reducing energy waste, and conforming to the concept of green and sustainable development.

[0059] In summary, the intelligent linkage operation of each module in this embodiment enables the equipment to operate stably under different working conditions, extends the service life of the equipment, and reduces the maintenance cost; it realizes the full-process automated management from monitoring, early warning to regulation and recovery, reduces manual intervention, improves the management efficiency, and provides a more convenient user experience; it not only ensures the safety and reliability of the equipment but also creates higher economic value and environmental benefits for users through energy conservation, environmental protection, and intelligent management.

[0060] Embodiment 2: As Figure 3 shown, based on Embodiment 1, the monitoring and early warning component provided by the embodiment of the present invention includes:

[0061] A data acquisition and fusion module, which is responsible for forming a multi-dimensional dynamic data set from the temperature data of the key parts inside the high-voltage and low-voltage cabinets and the external environment change information; based on the temperature historical data, it constructs a dynamic temperature baseline for each key part to identify the normal temperature fluctuation range of the equipment at each key part under different working conditions;

[0062] An abnormal feature extraction module, which is responsible for extracting features from the data of the multi-dimensional dynamic data set, paying attention to the temperature change rate, periodic fluctuations, and the correlation with environmental parameters; at the same time, in combination with the temperature historical data, it identifies the abnormal features that deviate from the dynamic baseline;

[0063] The risk assessment module is responsible for associating and analyzing the extracted abnormal features with environmental data and equipment load information to form a multi-dimensional risk assessment model; according to the risk assessment results, it classifies and warns of potential risks, and the warning levels are divided into observation level, prevention level, and emergency level from low to high.

[0064] Among them, in the expression of the multi-dimensional risk assessment model:

[0065]

[0066]

[0067] In the formula, R(i,t) represents the risk assessment value of the i-th key part at time t; F(i,t) represents the abnormal feature value of the i-th key part at time t; E(t) represents the environmental parameter at time t; L(t) represents the equipment load information at time t; λ1, λ2, λ3, λ4, λ5 represent weight coefficients used to balance the contributions of different dimensions; represents the non-linear risk amplification term used to capture the interaction effect between abnormal features and environmental parameters; cos(ωt + φ) represents the periodic fluctuation adjustment term; represents the absolute value of the temperature change rate of the i-th key part at time t; α represents the weight of the periodic fluctuation feature; sin(2πft) represents the periodic fluctuation function, where f is the frequency; β represents the weight of the temperature deviation feature; ΔT(i,t) 2 represents the deviation between the temperature of the i-th key part at time t and the dynamic baseline; γ represents the weight of the environmental change feature; E(t) represents the change rate of the environmental parameter at time t; δ represents the weight of the time logarithm feature; T base (i,t) represents the dynamic temperature baseline of the i-th key part at time t; T(i,j,t) represents the temperature value of the i-th key part at time t in the j-th historical data; N represents the total number of historical data; σ T(i,j,t) represents the temperature standard deviation of the i-th key part at time t in the j-th historical data; w1, w2 represent weight coefficients used to adjust the contribution ratio of the mean and standard deviation; κ represents the weight of the environmental factor used to introduce the influence of the external environmental variable E(t); η represents the periodic fluctuation adjustment coefficient; ω represents the angular frequency of the periodic fluctuation; φ represents the phase shift used to adjust the initial state of the periodic fluctuation; W(i,t) represents the warning level of the i-th key part at time t; R(i,t) represents the risk assessment value of the i-th key part at time t; θ1, θ2 represent warning thresholds used to distinguish risks of different levels. The above formulas achieve comprehensive monitoring and warning of potential equipment risks through the construction of dynamic temperature baselines, extraction of abnormal features, multi-dimensional risk assessment, and hierarchical warning. Each formula combines key factors in the actual application scenario to ensure the accuracy and practicality of the model.

[0068] The working principle and beneficial effects of the above technical solution are as follows: The data acquisition and fusion module of the present invention forms a multi-dimensional dynamic data set from the temperature data of key parts inside the high- and low-voltage switchgear and the external environment change information; based on the temperature historical data, a dynamic temperature baseline is constructed for each key part to identify the normal temperature fluctuation range of the equipment at key parts under different working conditions; the abnormal feature extraction module extracts features from the data of the multi-dimensional dynamic data set, paying attention to the temperature change rate, periodic fluctuation, and the correlation with environmental parameters. At the same time, combined with the temperature historical data, abnormal features deviating from the dynamic baseline are identified; the risk assessment module performs correlation analysis on the extracted abnormal features, environmental data, and equipment load information to form a multi-dimensional risk assessment model; according to the risk assessment results, potential risks are classified and warned, and the warning levels are divided into observation level, prevention level, and emergency level from low to high. Through the data acquisition and fusion module in the above solution, the system combines the internal temperature data with the external environment information to construct a multi-dimensional dynamic data set, which can real-time sense the operation state of the equipment and environmental changes, providing a comprehensive and accurate data basis; the construction of the dynamic temperature baseline ensures the accurate identification of the normal temperature range of the equipment under different working conditions. The abnormal feature extraction module, through in-depth analysis of multi-dimensional data, pays attention to the temperature change rate, periodic fluctuation, and the correlation with environmental parameters, and can quickly identify abnormal features deviating from the dynamic baseline; the intelligent abnormal identification method breaks through the limitations of traditional single-threshold monitoring, significantly improving the ability to discover potential risks. The risk assessment module combines abnormal features with environmental data and equipment load information to form a multi-dimensional risk assessment model, which not only considers the temperature itself, but also takes environmental factors and equipment operation status into account, making the risk judgment more comprehensive and scientific; the classification warning mechanism provides warnings at different levels according to the severity of the risk, avoiding over-reaction and ensuring the timely handling of emergencies.

[0069] In summary, this embodiment realizes the real-time monitoring, abnormal identification, and risk assessment of the operation state of the high- and low-voltage switchgear, providing a set of efficient and accurate warning mechanisms for users; through the collaborative work of multiple modules, it can detect and warn in advance when the risk is still in its infancy, effectively avoiding the occurrence of equipment failures or safety accidents. At the same time, the classification warning mechanism ensures the efficient allocation of resources, reducing both operating costs and improving the reliability and safety of equipment operation.

[0070] Embodiment 3: As Figure 4 shown, on the basis of Embodiment 1, the temperature control and adjustment component provided by the embodiment of the present invention includes:

[0071] The initial strategy setting module is responsible for selecting an appropriate cooling strategy from passive cooling, air cooling, liquid cooling, and semiconductor cooling as the initial cooling strategy according to the temperature data of the key parts at the initial stage of the use of the high- and low-voltage switchgear, the external environment change data, and the equipment load; at the same time, setting the upper and lower limits of the temperature data at which each cooling strategy is started according to the external environment change data and the equipment load.

[0072] The cooling demand generation module is responsible for obtaining the temperature data of the key parts, the external environment change data, and the equipment load collected at the first time point, the second time point, and the third time point to form three sets of state parameter sets of the key parts; analyzing the three sets of state parameter sets to obtain the target cooling demand.

[0073] The demand relationship judgment module is responsible for generating a cooling strategy switching instruction according to the target cooling demand when the initial cooling strategy cannot meet the target cooling demand, and replacing the initial cooling strategy with a new cooling strategy; when reaching the next time point, continue to judge the relationship between the current cooling strategy and the current cooling demand.

[0074] The working principle and beneficial effects of the above technical solution are as follows: The initial strategy setting module of this embodiment selects a suitable heat dissipation strategy from passive heat dissipation, air-cooled heat dissipation, liquid-cooled heat dissipation, and semiconductor cooling as the initial heat dissipation strategy according to the temperature data of the initial key parts, the external environment change data, and the equipment load during the use of the high-voltage and low-voltage cabinets; at the same time, it sets the upper and lower limits of the temperature data at which each heat dissipation strategy is started according to the external environment change data and the equipment load; the heat dissipation demand generation module obtains the temperature data of the key parts, the external environment change data, and the equipment load collected at the first time point, the second time point, and the third time point, and forms three sets of state parameter sets of the key parts; analyzes the three sets of state parameter sets to obtain the target heat dissipation demand; when the initial heat dissipation strategy cannot meet the target heat dissipation demand, the demand relationship judgment module generates a heat dissipation strategy switching instruction, and replaces the initial heat dissipation strategy with a new heat dissipation strategy; when the next time point is reached, it continues to judge the relationship between the current heat dissipation strategy and the current heat dissipation demand. The initial strategy setting module of the above solution selects the most suitable initial heat dissipation strategy by analyzing the temperature data of the key parts, the external environment change data, and the equipment load, and sets the upper and lower temperature limits at which each strategy is started, providing a basic framework for temperature control to ensure that the device can dissipate heat in the optimal way when starting. The heat dissipation demand generation module collects the temperature data of the key parts, the external environment change data, and the equipment load at the first time point and the second time point, forms three sets of state parameter sets, and analyzes to obtain the target heat dissipation demand; it monitors the operation state of the device in real time to provide data support for the adjustment of the heat dissipation strategy. When the initial heat dissipation strategy cannot meet the target heat dissipation demand, the demand relationship judgment module generates a heat dissipation strategy switching instruction, replaces the initial strategy with a new heat dissipation strategy, and continues to judge the relationship between the current strategy and the demand at the next time point; dynamically adjusts the heat dissipation strategy to ensure that the device is always in the best heat dissipation state under different operating conditions.

[0075] In summary, this embodiment can intelligently select and dynamically adjust the heat dissipation strategy according to the device operation state and environmental changes, thereby effectively avoiding problems such as overheating or insufficient heat dissipation of the device, improving the stability and safety of device operation, optimizing the heat dissipation efficiency, and reducing energy consumption.

[0076] Embodiment 4: On the basis of Embodiment 3, the heat dissipation demand generation module provided by the embodiment of the present invention includes:

[0077] The trend judgment sub-module is responsible for obtaining the temperature data of the key parts from the three sets of state parameter sets, analyzing the temperature data at the three time points to obtain the temperature data trend at the next time point, judging whether the temperature data trend is increasing or decreasing, if it is decreasing, stop analyzing the temperature data, continue to wait for the next time point, and judge the temperature data trend.

[0078] The load demand sub-module is responsible for obtaining the trend of external environmental change data when the temperature data trend increases, and obtaining the device load based on the temperature data trend and the trend of external environmental change data.

[0079] The relationship judgment sub-module is responsible for taking the current temperature data as the target heat dissipation demand and judging the relationship between the target heat dissipation demand and the initial heat dissipation strategy when the temperature data exceeds the upper limit of the current heat dissipation strategy.

[0080] The working principle and beneficial effects of the above technical solution are as follows: The trend judgment sub-module of this embodiment obtains the temperature data of the key part from the three groups of state parameter sets, analyzes the temperature data at three time points, obtains the temperature data trend at the next time point, and judges whether the temperature data trend increases or decreases. If it decreases, stop the temperature data analysis and continue to wait for the next time point to judge the temperature data trend; when the temperature data trend increases, the load demand sub-module obtains the trend of external environmental change data again, and obtains the device load according to the temperature data trend and the trend of external environmental change data; when the temperature data exceeds the upper limit of the current heat dissipation strategy, the relationship judgment sub-module takes the current temperature data as the target heat dissipation demand and judges the relationship between the target heat dissipation demand and the initial heat dissipation strategy. The trend judgment sub-module of the above solution analyzes the temperature data at three time points to predict the temperature change trend at the next time point; if it is found that the temperature trend is decreasing, the module will temporarily stop the analysis and wait for the data update at the next time point, which can avoid unnecessary resource consumption and ensure real-time monitoring of temperature changes. When the trend judgment sub-module detects a temperature rise, the load demand sub-module starts to act. Combining the change trend of the external environment, comprehensively analyzing the device load demand; flexibly adjusting the working state of the device according to the changes of internal and external factors to ensure that the temperature will not get out of control. If the relationship judgment sub-module finds that the temperature data exceeds the upper limit of the current heat dissipation strategy, the relationship judgment sub-module will take the current temperature data as the target heat dissipation demand and compare and analyze it with the initial heat dissipation strategy.

[0081] In summary, this embodiment constructs a dynamic heat dissipation demand generation system; it can not only monitor the temperature change of the device in real time, but also intelligently adjust the device load and heat dissipation strategy according to the trend and the change of the external environment. It not only ensures the efficient operation of the device, but also effectively avoids the performance degradation or device damage caused by overheating, providing a strong guarantee for the stability and service life of the device.

[0082] Embodiment 5: On the basis of Embodiment 4, the load demand sub-module provided by the embodiment of the present invention includes:

[0083] A weight allocation unit, responsible for obtaining the temperature data trend and the external environment change data trend, and allocating dynamic weights to the variables of each external environment change data according to the different degrees of influence of the external environment change data on the temperature data;

[0084] An influence quantification unit, responsible for constructing a heat flow balance model of the device based on the first law of thermodynamics to describe the dynamic relationship in the processes of heat generation, transfer, and dissipation inside the device; introducing external environment variables into the heat flow balance model to quantify the influence on heat transfer;

[0085] Expression of the heat flow balance model: Internal heat accumulation = Heat generated by the device heat source - Heat dissipated through the heat dissipation mechanism;

[0086] A dynamic superposition unit, responsible for predicting the heat distribution and transfer path inside the device through finite element analysis; dynamically superposing the internal temperature data change trend and the external environment change data trend through the heat flow balance model and the weight allocation; calculating the device load threshold according to the current heat accumulation speed and distribution of the device after dynamic superposition.

[0087] The working principle and beneficial effects of the above technical solution are as follows: The weight distribution unit in this embodiment is responsible for obtaining the temperature data trend and the external environment change data trend, and allocating dynamic weights to the variables of each external environment change data according to the different degrees of influence of the external environment change data on the temperature data; The influence quantification unit constructs a heat flow balance model of the device based on the first law of thermodynamics to describe the dynamic relationship in the process of heat generation, transfer, and dissipation inside the device; The external environment variables are introduced into the heat flow balance model to quantify the influence on heat transfer; The expression of the heat flow balance model: Internal heat accumulation = Heat generated by the device heat source - Heat dissipated through the heat dissipation mechanism; The dynamic superposition unit predicts the heat distribution and transfer path inside the device through finite element analysis; Through the heat flow balance model and weight allocation, the internal temperature data change trend and the external environment change data trend are dynamically superimposed; According to the current heat accumulation speed and distribution of the device after dynamic superposition, the device load threshold is calculated. In the above solution, the weight distribution unit dynamically allocates weights according to the degree of influence of the external environment change data on the temperature data, flexibly adjusts the analysis model according to the importance of different variables, and improves the adaptability to complex environmental changes. The influence quantification unit constructs a heat flow balance model based on the first law of thermodynamics, introduces external environment variables into the model and quantifies their influence, ensuring an accurate description of the heat transfer process; The quantitative analysis provides a scientific basis for subsequent temperature prediction and load calculation. The dynamic superposition unit predicts the heat distribution and transfer path through finite element analysis, and combines the heat flow balance model and dynamic weight allocation to dynamically superimpose the internal temperature change trend and the external environment change trend, which can more accurately reflect the current heat state of the device; According to the heat accumulation speed and distribution after dynamic superposition, the system can calculate the device load threshold in real time, providing a scientific load adjustment basis for the thermal management of the device, thereby preventing the device from overheating or overloading and ensuring its operation within a safe range.

[0088] In summary, this embodiment can achieve a complete closed-loop from data collection to trend analysis and then to load threshold calculation, significantly improving the thermal management efficiency of the device and the reliability of the overall operation. The combined use of each unit realizes precise monitoring, dynamic analysis, and scientific management of the heat state of the device, providing guarantee for the safe and stable operation of the device under different environmental conditions.

[0089] Embodiment 6: On the basis of Embodiment 5, the dynamic superposition unit provided by the embodiment of the present invention includes:

[0090] The heat analysis subunit is responsible for dynamically superimposing the internal temperature data change trend and the external environment change data trend to form a comprehensive heat state description; Analyze the heat accumulation speed and its distribution inside the device;

[0091] The adjustment calculation subunit is responsible for obtaining the dynamic transfer characteristics of the internal heat of the device, combining the potential impact of external environmental changes on the thermal state of the device, and adjusting the calculation model of the load threshold;

[0092] The threshold determination subunit is responsible for establishing a heat accumulation model based on the structural materials and thermal characteristics of the device, calculating the maximum temperature reached by the device under specific working conditions; evaluating the heat dissipation capacity of the device under different environmental conditions; and determining the maximum load threshold within the safe operating range of the device based on the heat accumulation model and the heat dissipation capacity evaluation.

[0093] Among them,

[0094] In the formula, Q 综合 (t) represents the comprehensive heat state at time t; T 内部 (s) represents the internal temperature data at time s; E 外部 (s) represents the external environmental data at time s (such as air temperature, humidity, etc.); α1 represents the weight coefficient of the internal temperature, reflecting its contribution to the comprehensive heat; α2 represents the weight coefficient of the external environment, reflecting its contribution to the comprehensive heat; β represents the dynamic superposition adjustment coefficient, used to enhance the interaction effect between internal and external changes; t0 represents the initial time point; s represents the time variable, representing the time point in the integration process.

[0095] The working principle and beneficial effects of the above technical solution are as follows: The heat analysis sub-unit in this embodiment dynamically superimposes the internal temperature data change trend and the external environment change data trend to form a comprehensive heat state description; analyzes the heat accumulation speed and its distribution inside the device; adjusts the calculation sub-unit to obtain the dynamic heat transfer characteristics inside the device, and combines the potential impact of external environment changes on the thermal state of the device to adjust the calculation model of the load threshold; the threshold determination sub-unit establishes a heat accumulation model based on the structural materials and thermal characteristics of the device, calculates the maximum temperature reached by the device under specific working conditions; evaluates the heat dissipation capacity of the device under different environmental conditions; and determines the highest load threshold within the safe operating range of the device based on the heat accumulation model and the heat dissipation capacity evaluation. Through the heat analysis sub-unit, the above solution can dynamically superimpose the internal temperature change trend of the device and the external environment change trend to form a comprehensive heat state description; the heat analysis sub-unit can analyze in detail the heat accumulation speed and its distribution inside the device, reveal the aggregation characteristics and transfer paths of heat in the device, and help identify potential hot spots. The adjustment calculation sub-unit adjusts the calculation model of the load threshold by obtaining the dynamic heat transfer characteristics inside the device and combining the potential impact of external environment changes on the thermal state, making the model closer to the actual situation and improving the accuracy of the calculation results. The threshold determination sub-unit comprehensively analyzes the temperature limit and heat dissipation efficiency of the device under specific working conditions by establishing a heat accumulation model and evaluating the heat dissipation capacity, providing a scientific basis for determining the safe load range. Based on the above analysis, the threshold determination sub-unit can accurately calculate the highest load threshold within the safe operating range of the device and perform dynamic optimization in combination with real-time data to ensure that the device operates within a safe and efficient range. It realizes multi-dimensional monitoring, analysis, and optimization of the thermal state of the device, providing reliable technical support for the stable operation, extended service life, and improved energy efficiency of the device.

[0096] Embodiment 7: On the basis of Embodiment 3, the demand relationship judgment module provided by the embodiment of the present invention includes:

[0097] An instruction generation sub-module, which is responsible for matching the heat dissipation strategy according to the target heat dissipation demand and dynamically selecting a new heat dissipation strategy; when the new heat dissipation strategy is selected, it generates a corresponding heat dissipation strategy switching instruction, and the instruction includes the specific implementation method of the new heat dissipation strategy, the switching time node, the adjustment of the temperature threshold, and the adaptive adjustment to external environment changes;

[0098] A strategy switching sub-module, which is responsible for asking the initial heat dissipation strategy whether it agrees to be replaced when receiving the heat dissipation strategy switching instruction, and when the initial heat dissipation strategy agrees to switch, it switches the initial heat dissipation strategy to the new heat dissipation strategy as the switching input terminal;

[0099] The closed-loop feedback sub-module is responsible for monitoring the temperature changes of key parts, the fluctuations of the external environment, and the status of device load in real time after the heat dissipation strategy switching instruction is executed; at the same time, it continues to enter the demand judgment and strategy matching stage of the next time point, forming a closed-loop feedback mechanism.

[0100] The working principle and beneficial effects of the above technical solution are as follows: The instruction generation sub-module of this embodiment matches the heat dissipation strategy according to the target heat dissipation demand and dynamically selects a new heat dissipation strategy; when the new heat dissipation strategy is selected, a corresponding heat dissipation strategy switching instruction is generated, and the instruction includes the specific implementation method of the new heat dissipation strategy, the switching time node, the adjustment of the temperature threshold, and the adaptive adjustment to the external environment change; when the strategy switching sub-module receives the heat dissipation strategy switching instruction, it asks the initial heat dissipation strategy whether it agrees to switch as the switching input terminal. When the initial heat dissipation strategy agrees to switch, it switches the initial heat dissipation strategy to the new heat dissipation strategy as the switching input terminal; after the heat dissipation strategy switching instruction is executed, the closed-loop feedback sub-module monitors the temperature changes of key parts, the fluctuations of the external environment, and the status of device load in real time; at the same time, it continues to enter the demand judgment and strategy matching stage of the next time point, forming a closed-loop feedback mechanism. The instruction generation sub-module of the above solution dynamically selects the most suitable heat dissipation strategy according to the target heat dissipation demand and generates a detailed switching instruction; ensuring that the heat dissipation strategy can accurately match the specific operating state of the device and the external environment change, and avoiding the low heat dissipation efficiency or energy waste caused by the strategy mismatch. At the same time, the switching time node, temperature threshold adjustment, and adaptive adjustment mechanism included in the instruction further improve the flexibility and adaptability of the strategy switching. After receiving the switching instruction, the strategy switching sub-module ensures the stability and safety of the switching process through the interaction with the initial heat dissipation strategy; it not only reflects the respect for the initial strategy but also avoids the system fluctuations that may be caused by the sudden strategy switching. At the same time, as the switching input terminal of this sub-module, it simplifies and standardizes the execution process of the strategy switching. After the strategy switching is completed, the closed-loop feedback sub-module monitors the temperature of key parts, the external environment fluctuations, and the device load in real time and feeds them back to the demand judgment and strategy matching stage of the system; the closed-loop mechanism enables the system to continuously optimize the heat dissipation strategy according to the actual operation data, ensuring that the device is always in the best heat dissipation state. At the same time, this feedback mechanism also improves the response ability to dynamic changes, enabling it to quickly adapt to the new operating conditions.

[0101] In summary, through the collaborative work of its internal sub-modules, the demand relationship judgment module of this embodiment realizes the accurate matching, safe switching, and continuous optimization of the heat dissipation strategy. It not only improves the heat dissipation efficiency and operation stability of the device but also reduces the energy consumption and operation risk, providing a strong guarantee for the efficient operation of the device in a complex and changeable environment.

[0102] Embodiment 8: Based on Embodiment 7, the instruction generation sub-module provided by the embodiment of the present invention includes:

[0103] A node selection unit, which is responsible for designing the functional deployment of the heat dissipation device and the limitation of operating parameters after a new heat dissipation strategy is determined; selecting a switching time node according to the temperature rise rate of key parts and the dynamic changes of the external environment based on the target heat dissipation demand and the real-time state of device operation;

[0104] A continuous monitoring unit, which is responsible for dynamically adjusting the temperature threshold according to the temperature data of key parts and the device load, and resetting the upper and lower limits of the temperature of key parts; continuously monitoring the changes in the external environment, and dynamically optimizing the new heat dissipation strategy;

[0105] A content embedding unit, which is responsible for embedding the specific implementation method, switching time node, temperature threshold adjustment, and external environment adaptive adjustment into the heat dissipation strategy switching instruction to generate a complete heat dissipation strategy switching instruction.

[0106] The working principle and beneficial effects of the above technical solutions are as follows: After a new heat dissipation strategy is determined, the node selection unit in this embodiment designs the functional deployment of the heat dissipation device and the limitation of operating parameters; selects a switching time node according to the temperature rise rate of key parts and the dynamic changes of the external environment based on the target heat dissipation demand and the real-time state of device operation; the continuous monitoring unit dynamically adjusts the temperature threshold according to the temperature data of key parts and the device load, and resets the upper and lower limits of the temperature of key parts; continuously monitors the changes in the external environment, and dynamically optimizes the new heat dissipation strategy; the content embedding unit embeds the specific implementation method, switching time node, temperature threshold adjustment, and external environment adaptive adjustment into the heat dissipation strategy switching instruction to generate a complete and executable instruction. The node selection unit of the above solution can trigger the strategy switch at the most appropriate time by combining the target heat dissipation demand, device operation state, temperature rise rate of key parts, and dynamic changes of the external environment, avoiding insufficient heat dissipation or resource waste caused by too early or too late switching. The continuous monitoring unit can timely adjust the temperature threshold, reset the upper and lower limits of the temperature of key parts, and optimize the heat dissipation strategy according to the environmental changes by continuously monitoring the temperature data of key parts, device load, and external environment changes. The content embedding unit embeds key information such as specific implementation methods, switching time nodes, temperature threshold adjustments, and external environment adaptive adjustments into the heat dissipation strategy switching instruction to generate a complete and executable instruction.

[0107] Embodiment 9: As Figure 5 shown, based on Embodiment 1, the energy recovery component provided by the embodiment of the present invention includes:

[0108] The heat guiding module is responsible for capturing the heat released by the heat dissipation device through a heat energy collection device during the operation of the heat dissipation device; guiding it to a heat exchange unit;

[0109] The heat energy conversion module is responsible for converting the heat energy of the heat exchange unit into secondary energy, generating electric energy by using thermoelectric power generation; at the same time, the heat energy enters the heat energy storage device;

[0110] The heat energy distribution module is responsible for configuring a multi-level heat energy distribution network; when heating or providing hot water is required, the heat energy is distributed to the heat utilization unit through intelligent regulation. The heat utilization unit adopts a zoning design and precisely controls the heat energy output according to different requirements.

[0111] The working principle and beneficial effects of the above technical solution are as follows: In the heat guiding module of this embodiment, during the operation of the heat dissipation device, the heat released by the heat dissipation device is captured through the heat energy collection device and guided to a heat exchange unit; the heat energy conversion module converts the heat energy of the heat exchange unit into secondary energy, generates electric energy by using thermoelectric power generation, and at the same time, the heat energy enters the heat energy storage device; the heat energy distribution module configures a multi-level heat energy distribution network; when heating or providing hot water is required, the heat energy is distributed to the heat utilization unit through intelligent regulation. The heat utilization unit adopts a zoning design and precisely controls the heat energy output according to different requirements. The heat guiding module of the above solution ensures the efficient capture and transmission of heat energy by precisely capturing and guiding the heat released by the heat dissipation device; the heat energy conversion module converts the collected heat energy into secondary energy, generates electric energy by using thermoelectric power generation, and stores the excess heat energy in the heat energy storage device at the same time, realizing the multi-level utilization of energy and improving the energy utilization rate. The heat energy distribution module precisely distributes the heat energy to heat utilization units such as heating and hot water through a multi-level heat energy distribution network and an intelligent regulation system, meeting the heat energy requirements in different scenarios and further expanding the application scope of heat energy. It not only effectively improves the energy utilization efficiency of the new energy storage system, but also realizes the recycling and optimal allocation of energy through the multi-functional conversion and distribution of heat energy, providing strong support for the sustainable operation of the system. While ensuring the efficient recovery of energy, it also provides users with a flexible and intelligent energy management experience, with significant practical value and environmental protection significance.

[0112] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of equivalent technologies of the present invention, the present invention also intends to include these changes and modifications.

Claims

1. An intelligent temperature-controlled high and low voltage cabinet for a new energy energy storage system, characterized in that, Comprising: A monitoring and early warning component, which is responsible for collecting temperature data of each key part inside the high and low voltage switchgear in real time through a distributed temperature sensor array, and perceiving the external environment changes of the high and low voltage switchgear in combination with multi-dimensional environmental sensors; at the same time, according to the temperature historical data and real-time dynamics, it conducts abnormal early warning and anticipates potential risks in advance; A temperature control and regulation component, which is responsible for automatically switching to a heat dissipation strategy according to the temperature data of key parts, external environment change data and equipment load. The heat dissipation strategies include passive heat dissipation, air-cooled heat dissipation, liquid-cooled heat dissipation and semiconductor cooling; An energy recovery component, which is responsible for dynamically adjusting the operating parameters of the heat dissipation equipment in the heat dissipation strategy; integrating modular waste heat recovery to convert the heat generated by the heat dissipation equipment during the heat dissipation process into heating, hot water or electric energy.

2. The intelligent temperature-controlled high and low voltage cabinet of the new energy energy storage system according to claim 1, characterized in that, The monitoring and early warning component includes: A data acquisition and fusion module, which is responsible for forming a multi-dimensional dynamic data set from the temperature data of key parts inside the high and low voltage switchgear and the external environment change information; based on the temperature historical data, it constructs a dynamic temperature baseline for each key part to identify the normal temperature fluctuation range of the equipment at key parts under different working conditions; An abnormal feature extraction module, which is responsible for extracting features from the data of the multi-dimensional dynamic data set, paying attention to the temperature change rate, periodic fluctuation and the correlation with environmental parameters; at the same time, in combination with the temperature historical data, it identifies abnormal features deviating from the dynamic baseline; A risk assessment module, which is responsible for conducting correlation analysis on the extracted abnormal features, environmental data and equipment load information to form a multi-dimensional risk assessment model; according to the risk assessment results, it conducts hierarchical early warning on potential risks, and the early warning levels are divided into observation level, prevention level and emergency level from low to high.

3. The intelligent temperature-controlled high and low voltage cabinet of the new energy energy storage system according to claim 1, characterized in that, The temperature control and regulation component includes: An initial strategy setting module, which is responsible for selecting an appropriate heat dissipation strategy from passive heat dissipation, air-cooled heat dissipation, liquid-cooled heat dissipation and semiconductor cooling as the initial heat dissipation strategy according to the temperature data of key parts, external environment change data and equipment load at the initial stage when the high and low voltage switchgear is in use; at the same time, it sets the upper and lower limits of the temperature data at which each heat dissipation strategy is started according to the external environment change data and equipment load; A heat dissipation demand generation module, which is responsible for obtaining the temperature data of key parts, external environment change data and equipment load collected at the first time point, the second time point and the third time point to form three groups of state parameter sets of key parts; analyzing the three groups of state parameter sets to obtain the target heat dissipation demand; A demand relationship judgment module, which is responsible for generating a heat dissipation strategy switching instruction according to the target heat dissipation demand when the initial heat dissipation strategy cannot meet the target heat dissipation demand, and replacing the initial heat dissipation strategy with a new heat dissipation strategy; when reaching the next time point, it continues to judge the relationship between the current heat dissipation strategy and the current heat dissipation demand.

4. The intelligent temperature-controlled high and low voltage cabinet of the new energy energy storage system according to claim 3, characterized in that, The heat dissipation demand generation module includes: A trend judgment sub-module, which is responsible for obtaining the temperature data of key parts from the three groups of state parameter sets, analyzing the temperature data at the three time points to obtain the temperature data trend at the next time point, judging whether the temperature data trend is increasing or decreasing, if it is decreasing, stop the temperature data analysis, continue to wait for the next time point, and judge the temperature data trend. The load demand sub-module is responsible for, when the temperature data trend increases, obtaining the external environmental change data trend, and obtaining the device load based on the temperature data trend and the external environmental change data trend. The relationship judgment sub-module is responsible for, when the temperature data exceeds the upper limit of the current heat dissipation strategy, taking the current temperature data as the target heat dissipation demand and judging the relationship between the target heat dissipation demand and the initial heat dissipation strategy.

5. The intelligent temperature-controlled high and low voltage cabinet of the new energy energy storage system according to claim 4, characterized in that, The load demand sub-module includes: The weight allocation unit is responsible for obtaining the temperature data trend and the external environmental change data trend, and allocating dynamic weights to the variables of each external environmental change data according to the different degrees of influence of the external environmental change data on the temperature data. The influence quantification unit is responsible for, based on the first law of thermodynamics, constructing a heat flow balance model of the device to describe the dynamic relationship in the processes of heat generation, transfer, and dissipation inside the device; introducing external environmental variables into the heat flow balance model to quantify the influence on heat transfer. The dynamic superposition unit is responsible for, through finite element analysis, predicting the heat distribution and transfer path inside the device. Through the heat flow balance model and the allocation of weights, the internal temperature data change trend and the external environmental change data trend are dynamically superposed; according to the current heat accumulation speed and distribution of the device after dynamic superposition, the device load threshold is calculated.

6. The intelligent temperature-controlled high and low voltage cabinet of the new energy energy storage system according to claim 5, characterized in that, The expression of the heat flow balance model: Internal heat accumulation = Heat generated by the device heat source - Heat dissipated through the heat dissipation mechanism.

7. The intelligent temperature-controlled high and low voltage cabinet of the new energy energy storage system according to claim 5, characterized in that, The dynamic superposition unit includes: The heat analysis sub-unit is responsible for dynamically superposing the internal temperature data change trend and the external environmental change data trend to form a comprehensive heat state description; analyzing the heat accumulation speed and its distribution inside the device. The adjustment calculation sub-unit is responsible for obtaining the dynamic transfer characteristics of the heat inside the device, combining the potential influence of external environmental changes on the heat state of the device, and adjusting the calculation model of the load threshold. The threshold determination sub-unit is responsible for, according to the structural materials and thermal characteristics of the device, establishing a heat accumulation model, calculating the highest temperature reached by the device under specific working conditions; evaluating the heat dissipation capacity of the device under different environmental conditions; based on the heat accumulation model and the heat dissipation capacity evaluation, determining the highest load threshold within the safe operating range of the device.

8. The intelligent temperature-controlled high and low voltage cabinet of the new energy energy storage system according to claim 3, characterized in that, The demand relationship judgment module includes: The instruction generation sub-module is responsible for matching the heat dissipation strategy according to the target heat dissipation demand and dynamically selecting a new heat dissipation strategy; when the new heat dissipation strategy is selected, generating a corresponding heat dissipation strategy switching instruction. The strategy switching sub-module is responsible for, when receiving the heat dissipation strategy switching instruction, serving as the switching input terminal to ask whether the initial heat dissipation strategy agrees to be replaced, and when the initial heat dissipation strategy agrees to switch, serving as the switching input terminal to switch the initial heat dissipation strategy to the new heat dissipation strategy. The closed-loop feedback sub-module is responsible for, after the heat dissipation strategy switching instruction is executed, real-time monitoring the temperature changes at key parts, the fluctuations of the external environment, and the status of the device load; at the same time, continuing to enter the demand judgment and strategy matching stage at the next time point to form a closed-loop feedback mechanism.

9. The intelligent temperature-controlled high and low voltage cabinet of the new energy energy storage system according to claim 8, characterized in that, The instruction includes the specific implementation method of the new heat dissipation strategy, the switching time node, the adjustment of the temperature threshold, and the adaptive adjustment to external environmental changes.

10. The intelligent temperature-controlled high and low voltage cabinet of the new energy energy storage system according to claim 8, characterized in that, Instruction generation sub-module, including: Node selection unit, responsible for determining the function deployment of the heat dissipation device and the limitation of operating parameters after the new heat dissipation strategy is determined; selecting a switching time node according to the temperature rise rate of key parts and the dynamic changes of the external environment based on the target heat dissipation requirement and the real-time state of device operation; Continuous monitoring unit, responsible for dynamically adjusting the temperature threshold according to the temperature data of key parts and the device load, and resetting the upper and lower limits of the temperature of key parts; continuously monitoring the changes in the external environment and dynamically optimizing the new heat dissipation strategy; Content embedding unit, responsible for embedding the specific implementation method, switching time node, temperature threshold adjustment, and external environment adaptive adjustment into the heat dissipation strategy switching instruction to generate a complete heat dissipation strategy switching instruction.

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