An intelligent electrical cabinet with stable heat dissipation function and heat dissipation control method thereof

Abstract

The present invention relates to the field of heat dissipation control technology for electrical cabinets, and specifically to an intelligent electrical cabinet with stable heat dissipation function and a heat dissipation control method thereof. The present invention first obtains load power data, temperature data and heat dissipation power; further predicts the power change trend parameters in the future according to the change characteristics of the historical load power data; further obtains the heat dissipation effect parameters according to the fluctuation characteristics of the historical temperature data; further obtains the predicted heat dissipation power according to the power change trend parameters and heat dissipation effect parameters at the current moment, combined with the heat dissipation power at the current moment; finally, based on the predicted heat dissipation power, controls the heat dissipation of the intelligent electrical cabinet. The present invention predicts the change trend of the load power that the electrical cabinet may bear, and evaluates the heat dissipation effect of the current electrical cabinet, thereby obtaining the predicted heat dissipation power, controlling the heat dissipation of the intelligent electrical cabinet, so that the heat dissipation power is adjusted in time, the heat dissipation stability is improved, and the electrical cabinet is guaranteed to operate smoothly and safely.

Description

Technical Field

[0001] The present invention relates to the technical field of heat dissipation control of electrical cabinets, and in particular to an intelligent electrical cabinet with a stable heat dissipation function and a heat dissipation control method thereof. Background Art

[0002] An intelligent electrical cabinet is an electrical cabinet that integrates an intelligent control system and is used to manage and control electrical equipment. It is widely used in industrial automation, communications, energy and other fields, and realizes centralized control, monitoring and management of electrical equipment through intelligent means.

[0003] When the existing intelligent electrical cabinets are dissipating heat, generally the heat dissipation system starts to work and dissipate heat when the temperature sensed by the temperature sensor inside the electrical cabinet reaches the heat dissipation threshold or interval set by the heat dissipation system. However, this heat dissipation method may be relatively passive, and the heat dissipation considerations are single, which may lead to poor heat dissipation stability of the electrical cabinet in some cases, affecting the efficiency of the electrical cabinet, and may also increase the probability of failure of the electrical cabinet, and to a certain extent reduce the service life of the components inside the electrical cabinet. Summary of the invention

[0004] In order to solve the technical problem of poor heat dissipation stability of electrical cabinets, the purpose of the present invention is to provide an intelligent electrical cabinet with stable heat dissipation function and a heat dissipation control method thereof. The technical solutions adopted are as follows:

[0005] A heat dissipation control method for an intelligent electrical cabinet, the method comprising:

[0006] Obtain the load power data of the intelligent electrical cabinet, the temperature data inside the intelligent electrical cabinet, and the heat dissipation power;

[0007] According to the change characteristics of the historical load power data at the current moment, predict the power change trend parameters of the intelligent electrical cabinet in the future; according to the fluctuation characteristics of the historical temperature data at the current moment, obtain the heat dissipation effect parameters of the intelligent electrical cabinet at the current moment; according to the power change trend parameters and the heat dissipation effect parameters at the current moment, obtain the heat dissipation power adjustment parameters; according to the heat dissipation power at the current moment and the heat dissipation power adjustment parameters, obtain the predicted heat dissipation power;

[0008] Based on the heat dissipation power at the current moment and the predicted heat dissipation power, the heat dissipation of the intelligent electrical cabinet is controlled.

[0009] Furthermore, the method for acquiring the power change trend parameter includes:

[0010] Taking the current moment as the end point and the first preset historical length as the time length, intercept a section of historical load power data; dividing the historical load power data by preset time intervals to obtain segmented historical data; obtaining the overall power parameter of each preset time interval according to the concentrated features of the load power data in the segmented historical data of the same preset time interval; taking the sampling moment of the first data point of the preset time interval as the mark moment, and sorting the overall power parameters according to the mark moment to obtain an average power sequence;

[0011] The overall power parameter corresponding to the current moment in the average power sequence is used as the real-time load power, and the next adjacent overall power parameter is used as the predicted load power, and the power change trend parameter at the current moment is obtained according to the change characteristics of the real-time load power and the predicted load power;

[0012] The length of the preset time interval is shorter than the first preset history length.

[0013] Furthermore, the calculation method of the power change trend parameter includes:

[0014] The ratio of the difference between the predicted load power and the real-time load power to the difference between the corresponding mark moments is used as a power change trend parameter.

[0015] Furthermore, the method for obtaining the heat dissipation effect parameter includes:

[0016] Taking the current moment as the end point and the second preset historical length as the time length, intercepting a section of historical temperature data; obtaining a first heat dissipation parameter according to the relative size of each temperature data in the historical temperature data and the temperature data at the current moment;

[0017] Obtaining a second heat dissipation parameter according to a relative size between the preset maximum temperature data and the temperature data at the current moment;

[0018] According to the first heat dissipation parameter and the second heat dissipation parameter, a heat dissipation effect parameter of the intelligent electrical cabinet at the current moment is obtained; the first heat dissipation parameter and the second heat dissipation parameter are both positively correlated with the heat dissipation effect parameter.

[0019] Furthermore, the method for obtaining the heat dissipation power adjustment parameter includes:

[0020] When the power change trend parameter is greater than or equal to zero, a heat dissipation power adjustment parameter is obtained according to the power change trend parameter and the heat dissipation effect parameter; the power change trend parameter is positively correlated with the heat dissipation power adjustment parameter; the heat dissipation effect parameter is negatively correlated with the heat dissipation power adjustment parameter;

[0021] When the power change trend parameter is less than zero, the heat dissipation power adjustment parameter is obtained according to the power change trend parameter and the heat dissipation effect parameter; the power change trend parameter is positively correlated with the heat dissipation power adjustment parameter; the heat dissipation effect parameter is positively correlated with the heat dissipation power adjustment parameter.

[0022] Furthermore, the method for obtaining the predicted heat dissipation power includes:

[0023] The heat dissipation power adjustment parameter is mapped to a preset symmetric interval, and a power adjustment coefficient is obtained according to the mapping value and the preset power adjustment amplitude parameter; the mapping value of the heat dissipation power adjustment parameter and the preset power adjustment amplitude parameter are both positively correlated with the power adjustment coefficient;

[0024] The predicted heat dissipation power is acquired according to the power adjustment coefficient and the heat dissipation power at the current moment; the power adjustment coefficient and the heat dissipation power at the current moment are both positively correlated with the predicted heat dissipation power.

[0025] Furthermore, the calculation method for predicting heat dissipation power includes:

[0026] The product of the power regulation coefficient and the heat dissipation power at the current moment is used as the predicted heat dissipation power to control the heat dissipation of the intelligent electrical cabinet.

[0027] Furthermore, the method for controlling the heat dissipation of the intelligent electrical cabinet based on the heat dissipation power at the current moment and the predicted heat dissipation power includes:

[0028] According to the heat dissipation power at the current moment and the predicted heat dissipation power, the heat dissipation of the intelligent electrical cabinet is controlled by a PID control method.

[0029] Furthermore, the preset symmetry interval is symmetric about the origin.

[0030] The present invention also proposes an intelligent electrical cabinet with a stable heat dissipation function, the intelligent electrical cabinet comprising:

[0031] A data acquisition module is used to obtain the load power data of the intelligent electrical cabinet, the temperature data inside the intelligent electrical cabinet, and the heat dissipation power;

[0032] The heat dissipation analysis module is used to predict the power change trend parameters of the intelligent electrical cabinet in the future according to the change characteristics of the historical load power data at the current moment; obtain the heat dissipation effect parameters of the intelligent electrical cabinet at the current moment according to the fluctuation characteristics of the historical temperature data at the current moment; obtain the heat dissipation power adjustment parameters according to the power change trend parameters and the heat dissipation effect parameters at the current moment; obtain the predicted heat dissipation power according to the heat dissipation power at the current moment and the heat dissipation power adjustment parameters;

[0033] The heat dissipation control module controls the heat dissipation of the intelligent electrical cabinet based on the heat dissipation power at a current moment and the predicted heat dissipation power.

[0034] The present invention has the following beneficial effects:

[0035] The present invention first obtains the load power data of the intelligent electrical cabinet, the temperature data inside the intelligent electrical cabinet and the heat dissipation power, so as to provide a basis for subsequent analysis; further, according to the change characteristics of the historical load power data at the current moment, the power change trend parameters of the intelligent electrical cabinet in the future are predicted, so as to provide a basis for eliminating the lag and instability of the heat dissipation control of the traditional electrical cabinet and regulating the heat dissipation power; further, according to the fluctuation characteristics of the historical temperature data at the current moment, the heat dissipation effect parameters of the intelligent electrical cabinet at the current moment are obtained, so as to characterize the heat dissipation capacity of the current electrical cabinet, so as to accurately adjust the heat dissipation plan in the subsequent process; further, the power change trend parameters and the heat dissipation effect parameters at the current moment are integrated, and the heat dissipation power adjustment parameters are obtained according to the current situation, so as to facilitate subsequent adaptive adjustment; further, according to the heat dissipation power at the current moment and the heat dissipation power adjustment parameters, the predicted heat dissipation power is obtained as the target working power of the heat dissipation module, and the heat dissipation of the electrical cabinet is controlled in advance, so as to better adapt to the heat dissipation requirements of the electrical cabinet and increase the stability of the operation of the electrical cabinet; finally, based on the heat dissipation power at the current moment and the predicted heat dissipation power, the heat dissipation of the intelligent electrical cabinet is controlled. The present invention predicts the changing trend of the load power that the electrical cabinet may bear and evaluates the heat dissipation effect of the current electrical cabinet, thereby obtaining the predicted heat dissipation power and controlling the heat dissipation of the intelligent electrical cabinet, so that the heat dissipation power can be adjusted in time, the heat dissipation stability is improved, and the smooth and safe operation of the electrical cabinet is guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0037] Figure 1 A flow chart of a heat dissipation control method for an intelligent electrical cabinet provided by an embodiment of the present invention;

[0038] Figure 2 A schematic diagram of an intelligent electrical cabinet provided by an embodiment of the present invention;

[0039] Figure 3 A module block diagram of an intelligent electrical cabinet with stable heat dissipation function provided by an embodiment of the present invention.

[0040] The numbers in the figure are: 1. the electrical cabinet as a whole; 2. the heat dissipation device; 103. the heat dissipation control module; 4. the electric induction module; 5. the wire output terminal; 6. the temperature sensing module; 7. the air inlet; 8. the wire input terminal. DETAILED DESCRIPTION

[0041] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation, structure, features and effects of an intelligent electrical cabinet with stable heat dissipation function and its heat dissipation control method proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0042] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0043] The specific scheme of an intelligent electrical cabinet with stable heat dissipation function and a heat dissipation control method thereof provided by the present invention is described in detail below with reference to the accompanying drawings.

[0044] See also Figure 1 , which shows a flow chart of a heat dissipation control method of an intelligent electrical cabinet provided by an embodiment of the present invention, specifically comprising:

[0045] Step S1: Obtaining the load power data of the intelligent electrical cabinet, the temperature data inside the intelligent electrical cabinet, and the heat dissipation power.

[0046] See also Figure 2 , which shows a schematic diagram of an intelligent electrical cabinet provided by an embodiment of the present invention; the figure includes: an electrical cabinet as a whole 1, a heat dissipation device 2, a heat dissipation control module 103, an electric induction module 4, a wire output terminal 5, a temperature sensing module 6, an air inlet 7 and a wire input terminal 8; wherein the electric induction module 4 is located at the wire input terminal 8, the wire enters the electrical cabinet from the wire input terminal 8, and leaves the electrical cabinet from the wire output terminal 5, and the temperature sensing module 6 and the air inlet 7 are both symmetrically designed; the heat dissipation device 2, the electric induction module 4, the temperature sensing module 6 and the temperature sensing module 8 are all connected to the heat dissipation control module 103.

[0047] In the embodiment of the present invention, it is taken into account that the traditional electrical cabinet performs temperature feedback regulation through a temperature sensing device or module, which may cause lag and unstable heat dissipation of the electrical cabinet, and the heat of the electrical cabinet is mainly due to the thermal effect of the current when the circuit components and wires inside the electrical cabinet are powered on, which causes a certain amount of heat to be generated inside the cabinet, and the user's behavior habits and power usage patterns are different at different times. Therefore, the load power data is collected by the electric induction module 4 and the temperature data inside the electrical cabinet is collected by the temperature sensing module 6, which are transmitted to the heat dissipation control module 103 for analysis, and a control signal is output to adjust the heat dissipation power of the heat dissipation device 2, so as to adapt to the heat dissipation inside the electrical cabinet at different times and ensure the smooth and safe operation of the electrical cabinet.

[0048] It should be noted that, since there are multiple temperature sensing modules 6, in one embodiment of the present invention, the temperature data with the maximum temperature value in each collected data is selected for analysis; the collection frequency of each type of data is once every 10 seconds.

[0049] Step S2: According to the change characteristics of the historical load power data at the current moment, predict the power change trend parameters of the intelligent electrical cabinet in the future; according to the fluctuation characteristics of the historical temperature data at the current moment, obtain the heat dissipation effect parameters of the intelligent electrical cabinet at the current moment; according to the power change trend parameters and heat dissipation effect parameters at the current moment, obtain the heat dissipation power adjustment parameters; according to the heat dissipation power at the current moment and the heat dissipation power adjustment parameters, obtain the predicted heat dissipation power.

[0050] In order to eliminate the lag and instability of the heat dissipation control of traditional electrical cabinets, and because load power is the main source of heat inside the electrical cabinet, it is necessary to predict the change of load power; considering that the users or electrical appliances involved in the electrical cabinet have certain usage patterns when using electricity, the change characteristics of historical load power data can be used to predict the future power change trend parameters of the intelligent electrical cabinet, providing a basis for subsequent regulation of the heat dissipation power.

[0051] Preferably, in one embodiment of the present invention, a section of historical load power data is intercepted with the current moment as the end point and the first preset historical length as the time length; in order to more finely distinguish the load power modes at different times, thereby predicting a more accurate load power change trend, the historical load power data is divided according to the preset time interval to obtain segmented historical data; considering that the fluctuations of the load power data in the same time interval of different days in a short period are relatively consistent, in order to analyze the changing law of the load power change and thus make a prediction of the future load power change, the overall power parameters of each preset time interval are obtained according to the concentrated features of the load power data in the segmented historical data of the same preset time interval; the sampling moment of the first data point in the preset time interval is taken as the mark moment, and according to the mark moment, the overall power parameters are sorted to obtain the average power sequence, and the change law of the load power is characterized by the average power sequence;

[0052] The overall power parameter corresponding to the current moment in the average power sequence is used as the real-time load power, and the next adjacent overall power parameter is used as the predicted load power. According to the change characteristics of the real-time load power and the predicted load power, the power change trend parameter at the current moment is obtained;

[0053] The length of the preset time interval is less than the first preset history length.

[0054] As an example, a smart electrical cabinet works in a residential community. It is believed that the load power between the hours of the day is similar, and the load power in the same time interval on different days is similar. The first preset historical length is set to 7 natural days, that is, the current time is taken as the end point, and the historical load power data of the most recent week is selected; the length of the preset time interval is 1 hour, and the hours between the hours are regarded as a time interval, for example, 0 o'clock to 1 o'clock is regarded as a time interval, and 1 o'clock to 2 o'clock is regarded as a time interval. When the first collection time is the hour and the collection frequency is once every 10 seconds, 59 minutes and 50 seconds of each hour is the last data, so the time interval can also be 0 o'clock to 0 o'clock 59 minutes and 50 seconds, with a total of 24 time intervals; the average value of the load power data contained in the same time interval is used as the overall power parameter of each time interval, and an average power sequence of length 24 is obtained after sorting. The average power sequence is considered to be the change pattern of the load power of the electrical cabinet, and the real-time load power and predicted load power are selected from the average power sequence to calculate the power change trend parameter.

[0055] It should be noted that, considering that the current time may not be the hour, the historical load power data can be shifted and spliced. For example, if the current time is 15:12:20, the power data from 0:00 to 15:12:20 on the day and the power data from 15:12:30 to 23:59:50, the earliest in the historical load power data, can be spliced ​​into one day, thus obtaining load power data for seven full days.

[0056] Preferably, in one embodiment of the present invention, the ratio of the difference between the predicted load power and the real-time load power to the difference between the corresponding mark moments is used as a power change trend parameter by means of slope or rate of change. The power change trend parameter includes the direction and amplitude of the load power change that the electrical cabinet may withstand in the future.

[0057] As another example, the implementer may also obtain power change trend parameters by means of curve fitting, for example: performing curve fitting on historical load power data to obtain a curve function, using the curve function to predict load power data within a certain period of time in the future, such as 10 minutes, taking the average value of the historical load power data for 10 minutes with the current moment as the end point as the load power, taking the average value of the predicted 10-minute load power data as the predicted load power, and calculating the power change trend parameters.

[0058] In other embodiments of the present invention, the concentrated characteristics of the load power data can also be represented by the mode, median and mean of the data. For example, the mode, median and mean of the load power data in the segmented historical data are weighted and summed with weights of 0.3, 0.3 and 0.4, and the sum value represents the concentrated characteristics of the load power data.

[0059] Taking into account the different heat dissipation conditions at different times, the heat dissipation capacity of the electrical cabinet varies. For example, when the outside temperature is high, the electrical cabinet is more likely to accumulate heat and the heat dissipation effect is worse. Therefore, it is necessary to analyze the current heat dissipation capacity of the electrical cabinet. Therefore, according to the fluctuation characteristics of the historical temperature data at the current moment, the heat dissipation effect parameters of the intelligent electrical cabinet at the current moment are obtained.

[0060] Preferably, in one embodiment of the present invention, a section of historical temperature data is intercepted with the current moment as the end point and the second preset historical length as the time length;

[0061] Considering that the larger the historical temperature data is relative to the temperature data at the current moment, the better the heat dissipation effect of the electrical cabinet is, the first heat dissipation parameter is obtained according to the relative size of each temperature data in the historical temperature data and the temperature data at the current moment;

[0062] It is also considered that the greater the maximum operating temperature of the electrical cabinet is relative to the temperature data at the current moment, the lower the temperature at the current moment is, and the better the heat dissipation effect of the electrical cabinet is. Therefore, the second heat dissipation parameter is obtained according to the relative size of the preset maximum temperature data and the temperature data at the current moment;

[0063] According to the first heat dissipation parameter and the second heat dissipation parameter, a heat dissipation effect parameter of the intelligent electrical cabinet at the current moment is obtained; the first heat dissipation parameter and the second heat dissipation parameter are both positively correlated with the heat dissipation effect parameter.

[0064] As an example, the second preset history length is 10 minutes, and the calculation formula of the heat dissipation effect parameter includes:

[0065] ;in, Indicates the heat dissipation effect parameters at the current moment; represents the linear normalization function; Indicates the number of temperature data in the historical temperature data; Indicates the temperature data at the current moment; Indicates the historical temperature data Temperature data; Indicates the preset maximum temperature data. In this example .

[0066] In the formula, Indicates the first heat dissipation parameter. The larger the first heat dissipation parameter is, the larger the overall temperature data in the historical temperature data is compared to the current temperature data, which means that the heat dissipation effect of the electrical cabinet is better and the larger the heat dissipation effect parameter is; The larger the value is, the farther the current temperature is from the highest temperature data, the better the heat dissipation effect of the current electrical cabinet is, and the larger the heat dissipation effect parameter is, the positive correlation mapping is performed by multiplication, and the value range is adjusted with the help of linear normalization.

[0067] In other embodiments of the present invention, the implementer may also perform positive correlation mapping by adding or positive correlation mapping functions, for example: ;in It is an exponential function with the natural constant e as the base and a positive correlation mapping function, which can amplify the sensitivity of the second heat dissipation parameter.

[0068] The power change trend parameter represents the change trend of the load power of the electrical cabinet in the future, and the heat dissipation effect parameter represents the current heat dissipation capacity of the electrical cabinet. Therefore, the heat dissipation power adjustment parameter can be obtained according to the power change trend parameter and the heat dissipation effect parameter at the current moment.

[0069] Preferably, in one embodiment of the present invention, considering that when the load power shows an upward trend in the future, the heat dissipation power needs to be increased, and the better the current heat dissipation effect is, the smaller the amplitude of increasing the heat dissipation power needs to be, so when the power change trend parameter is greater than or equal to zero, the heat dissipation power adjustment parameter is obtained according to the power change trend parameter and the heat dissipation effect parameter; the power change trend parameter is positively correlated with the heat dissipation power adjustment parameter; the heat dissipation effect parameter is negatively correlated with the heat dissipation power adjustment parameter;

[0070] Considering that when the load power shows a downward trend in the future, the heat dissipation power needs to be reduced, and the better the current heat dissipation effect is, the greater the amplitude of the heat dissipation power reduction needs to be. Therefore, when the power change trend parameter is less than zero, the heat dissipation power adjustment parameter is obtained according to the power change trend parameter and the heat dissipation effect parameter; the power change trend parameter is positively correlated with the heat dissipation power adjustment parameter; the heat dissipation effect parameter is positively correlated with the heat dissipation power adjustment parameter.

[0071] As an example, the calculation formula of the heat dissipation power adjustment parameter includes:

[0072] ;

[0073] in, Indicates the heat dissipation power adjustment parameter at the current moment; Indicates the power change trend parameter at the current moment; The cooling effect parameters at the current moment; Indicates the division by zero parameter, and takes 0.01.

[0074] In the formula, When the load power of the electrical cabinet remains unchanged or increases in the future, The larger the value, the stronger the trend of load power increase, the more it is necessary to increase the heat dissipation power in advance, and the larger the heat dissipation power adjustment parameter, the The larger it is, the worse the heat dissipation effect of the electrical cabinet is. When faced with heat accumulation when the load power of the electrical cabinet remains unchanged or stronger heat generation when the load increases, the greater the increase in the heat dissipation power is, the larger the heat dissipation power adjustment parameter is. When the load power of the electrical cabinet is decreasing in the future, The smaller it is, the stronger the downward trend is, and the smaller the heat dissipation power adjustment parameter is. The larger it is, the stronger the heat dissipation capacity is and the greater the reduction in heat dissipation power is, thus avoiding waste of electricity due to excessive heat dissipation, improving the utilization rate of energy and extending the service life of the cooling system.

[0075] After obtaining the heat dissipation power adjustment parameters, the predicted heat dissipation power can be obtained based on the current heat dissipation power and the heat dissipation power adjustment parameters. This can be used as the target working power of the heat dissipation module to control the heat dissipation of the electrical cabinet in advance, better adapt to the heat dissipation needs of the electrical cabinet, and increase the stability of the electrical cabinet operation.

[0076] Preferably, in one embodiment of the present invention, in order to control the regulation range of the heat dissipation power, the heat dissipation power regulation parameter is mapped to a preset symmetric interval, and the power regulation coefficient is obtained according to the mapping value and the preset power regulation amplitude parameter; the mapping value of the heat dissipation power regulation parameter and the preset power regulation amplitude parameter are both positively correlated with the power regulation coefficient;

[0077] The predicted heat dissipation power is obtained according to the power regulation coefficient and the heat dissipation power at the current moment; the power regulation coefficient and the heat dissipation power at the current moment are both positively correlated with the predicted heat dissipation power.

[0078] Preferably, in one embodiment of the present invention, the product of the power regulation coefficient and the heat dissipation power at the current moment is used as the predicted heat dissipation power to control the heat dissipation of the intelligent electrical cabinet.

[0079] As an example, the heat dissipation power adjustment parameter is mapped to -1 to 1 through the sigmoid function, and the preset symmetric interval is -1 to 1; the preset power adjustment amplitude parameter is set to 0.8, and the sum of the mapping value of the heat dissipation power adjustment parameter and the product of the preset power adjustment amplitude parameter and the constant 1 is used as the power adjustment coefficient. At this time, the power adjustment coefficient is distributed in the range of 0.2 to 1.8, that is, the current heat dissipation power can be reduced to 0.2 times or enlarged to 1.8 times at most.

[0080] In other embodiments of the present invention, a tanh function or other mapping methods may be used to set other preset parameters, which are technical means well known to those skilled in the art and will not be described in detail here.

[0081] Step S3: Based on the heat dissipation power at the current moment and the predicted heat dissipation power, control the heat dissipation of the intelligent electrical cabinet.

[0082] After obtaining the predicted heat dissipation power, the heat dissipation mode can be adjusted based on the current heat dissipation power to control the heat dissipation of the intelligent electrical cabinet.

[0083] Preferably, in one embodiment of the present invention, considering that the PID control method is a commonly used control method and is overly stable, the current heat dissipation power is smoothly transitioned to the predicted heat dissipation power through the PID control method according to the heat dissipation power at the current moment and the predicted heat dissipation power, so as to control the heat dissipation of the intelligent electrical cabinet.

[0084] It should be noted that, in one embodiment of the present invention, the heat dissipation device 2 of the electrical cabinet is an air-cooled heat dissipation device. By controlling the voltage and current of the fan, the output power of the fan gradually approaches and reaches the predicted heat dissipation power. Through continuous circulation, the electrical cabinet can dissipate heat stably and effectively. The PID control method is a technical means well known to those skilled in the art and will not be repeated here.

[0085] It should be noted that, when the predicted heat dissipation power exceeds the maximum heat dissipation power of the electrical cabinet, the heat dissipation power of the heat dissipation device 2 is controlled to increase to the maximum heat dissipation power.

[0086] The present invention also includes an intelligent electrical cabinet with stable heat dissipation function, see Figure 3 , which shows a module block diagram of an intelligent electrical cabinet with stable heat dissipation function provided by an embodiment of the present invention, specifically comprising:

[0087] The data acquisition module 101 is used to obtain the load power data of the intelligent electrical cabinet, the temperature data inside the intelligent electrical cabinet, and the heat dissipation power;

[0088] The heat dissipation analysis module 102 is used to predict the power change trend parameters of the intelligent electrical cabinet in the future according to the change characteristics of the historical load power data at the current moment; obtain the heat dissipation effect parameters of the intelligent electrical cabinet at the current moment according to the fluctuation characteristics of the historical temperature data at the current moment; obtain the heat dissipation power adjustment parameters according to the power change trend parameters and the heat dissipation effect parameters at the current moment; obtain the predicted heat dissipation power according to the heat dissipation power and the heat dissipation power adjustment parameters at the current moment;

[0089] The heat dissipation control module 103 controls the heat dissipation of the intelligent electrical cabinet based on the current heat dissipation power and the predicted heat dissipation power.

[0090] The intelligent electrical cabinet also includes an early warning device. In one embodiment of the present invention, when the electrical cabinet continues to operate at the maximum heat dissipation power for a certain period of time, such as 1 minute, and the temperature inside the electrical cabinet is still in the early warning range, such as the temperature is greater than 85% of the maximum temperature, the early warning device is triggered to limit the power of the power supply circuit, and a warning light can be installed to light up a red light for warning.

[0091] In summary, in response to the technical problem of poor heat dissipation stability of electrical cabinets, the present invention provides an intelligent electrical cabinet with stable heat dissipation function and a heat dissipation control method thereof. The present invention first obtains load power data, temperature data and heat dissipation power; further predicts the power change trend parameters of the intelligent electrical cabinet in the future according to the change characteristics of historical load power data; further obtains the heat dissipation effect parameters of the intelligent electrical cabinet at the current moment according to the fluctuation characteristics of historical temperature data; further obtains the predicted heat dissipation power according to the power change trend parameters and heat dissipation effect parameters at the current moment, combined with the heat dissipation power at the current moment; finally, based on the heat dissipation power at the current moment and the predicted heat dissipation power, controls the heat dissipation of the intelligent electrical cabinet. The present invention predicts the change trend of the load power that the electrical cabinet may bear, and evaluates the heat dissipation effect of the current electrical cabinet, thereby obtaining the predicted heat dissipation power, controlling the heat dissipation of the intelligent electrical cabinet, so that the heat dissipation power is adjusted in time, the heat dissipation stability is improved, and the electrical cabinet is guaranteed to operate smoothly and safely.

[0092] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0093] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A heat dissipation control method for an intelligent electrical cabinet, characterized in that: The method comprises: Obtain the load power data of the intelligent electrical cabinet, the temperature data inside the intelligent electrical cabinet, and the heat dissipation power; According to the change characteristics of the historical load power data at the current moment, predict the power change trend parameters of the intelligent electrical cabinet in the future; according to the fluctuation characteristics of the historical temperature data at the current moment, obtain the heat dissipation effect parameters of the intelligent electrical cabinet at the current moment; according to the power change trend parameters and the heat dissipation effect parameters at the current moment, obtain the heat dissipation power adjustment parameters; according to the heat dissipation power at the current moment and the heat dissipation power adjustment parameters, obtain the predicted heat dissipation power; Based on the heat dissipation power at the current moment and the predicted heat dissipation power, controlling the heat dissipation of the intelligent electrical cabinet; The method for obtaining the power change trend parameter includes: Taking the current moment as the end point and the first preset historical length as the time length, intercept a section of historical load power data; dividing the historical load power data by preset time intervals to obtain segmented historical data; obtaining the overall power parameter of each preset time interval according to the concentrated features of the load power data in the segmented historical data of the same preset time interval; taking the sampling moment of the first data point of the preset time interval as the mark moment, and sorting the overall power parameters according to the mark moment to obtain an average power sequence; The overall power parameter corresponding to the current moment in the average power sequence is used as the real-time load power, and the next adjacent overall power parameter is used as the predicted load power, and the power change trend parameter at the current moment is obtained according to the change characteristics of the real-time load power and the predicted load power; The length of the preset time interval is less than the first preset history length; The calculation method of the power change trend parameter includes: The ratio of the difference between the predicted load power and the real-time load power to the difference between the corresponding mark moments is used as a power change trend parameter; The method for obtaining the heat dissipation effect parameter includes: Taking the current moment as the end point and the second preset historical length as the time length, intercepting a section of historical temperature data; obtaining a first heat dissipation parameter according to the relative size of each temperature data in the historical temperature data and the temperature data at the current moment; Obtaining a second heat dissipation parameter according to a relative size between the preset maximum temperature data and the temperature data at the current moment; According to the first heat dissipation parameter and the second heat dissipation parameter, a heat dissipation effect parameter of the intelligent electrical cabinet at the current moment is obtained; the first heat dissipation parameter and the second heat dissipation parameter are both positively correlated with the heat dissipation effect parameter; The calculation formulas for the heat dissipation effect parameters include: ;in, Indicates the heat dissipation effect parameters at the current moment; represents the linear normalization function; Indicates the number of temperature data in the historical temperature data; Indicates the temperature data at the current moment; Indicates the historical temperature data Temperature data; Indicates the preset maximum temperature data; represents a first heat dissipation parameter; represents the second heat dissipation parameter.

2. The heat dissipation control method of an intelligent electrical cabinet according to claim 1, characterized in that: The method for obtaining the heat dissipation power adjustment parameter includes: When the power change trend parameter is greater than or equal to zero, a heat dissipation power adjustment parameter is obtained according to the power change trend parameter and the heat dissipation effect parameter; the power change trend parameter is positively correlated with the heat dissipation power adjustment parameter; the heat dissipation effect parameter is negatively correlated with the heat dissipation power adjustment parameter; When the power change trend parameter is less than zero, the heat dissipation power adjustment parameter is obtained according to the power change trend parameter and the heat dissipation effect parameter; the power change trend parameter is positively correlated with the heat dissipation power adjustment parameter; the heat dissipation effect parameter is positively correlated with the heat dissipation power adjustment parameter.

3. The heat dissipation control method of an intelligent electrical cabinet according to claim 1, characterized in that: The method for obtaining the predicted heat dissipation power includes: The heat dissipation power adjustment parameter is mapped to a preset symmetric interval, and a power adjustment coefficient is obtained according to the mapping value and the preset power adjustment amplitude parameter; the mapping value of the heat dissipation power adjustment parameter and the preset power adjustment amplitude parameter are both positively correlated with the power adjustment coefficient; The predicted heat dissipation power is acquired according to the power adjustment coefficient and the heat dissipation power at the current moment; the power adjustment coefficient and the heat dissipation power at the current moment are both positively correlated with the predicted heat dissipation power.

4. The heat dissipation control method of an intelligent electrical cabinet according to claim 3, characterized in that: The calculation method for predicting the heat dissipation power includes: The product of the power regulation coefficient and the heat dissipation power at the current moment is used as the predicted heat dissipation power to control the heat dissipation of the intelligent electrical cabinet.

5. The heat dissipation control method of an intelligent electrical cabinet according to claim 1, characterized in that: The method for controlling the heat dissipation of the intelligent electrical cabinet based on the heat dissipation power at the current moment and the predicted heat dissipation power includes: According to the heat dissipation power at the current moment and the predicted heat dissipation power, the heat dissipation of the intelligent electrical cabinet is controlled by a PID control method.

6. The heat dissipation control method of an intelligent electrical cabinet according to claim 3, characterized in that: The preset symmetry interval is symmetric about the origin.

7. An intelligent electrical cabinet with stable heat dissipation function, characterized in that: The intelligent electrical cabinet comprises: A data acquisition module is used to obtain the load power data of the intelligent electrical cabinet, the temperature data inside the intelligent electrical cabinet, and the heat dissipation power; The heat dissipation analysis module is used to predict the power change trend parameters of the intelligent electrical cabinet in the future according to the change characteristics of the historical load power data at the current moment; obtain the heat dissipation effect parameters of the intelligent electrical cabinet at the current moment according to the fluctuation characteristics of the historical temperature data at the current moment; obtain the heat dissipation power adjustment parameters according to the power change trend parameters and the heat dissipation effect parameters at the current moment; obtain the predicted heat dissipation power according to the heat dissipation power at the current moment and the heat dissipation power adjustment parameters; A heat dissipation control module, which controls the heat dissipation of the intelligent electrical cabinet based on the heat dissipation power at the current moment and the predicted heat dissipation power; The method for obtaining the power change trend parameter includes: Taking the current moment as the end point and the first preset historical length as the time length, intercept a section of historical load power data; dividing the historical load power data by preset time intervals to obtain segmented historical data; obtaining the overall power parameter of each preset time interval according to the concentrated features of the load power data in the segmented historical data of the same preset time interval; taking the sampling moment of the first data point of the preset time interval as the mark moment, and sorting the overall power parameters according to the mark moment to obtain an average power sequence; The overall power parameter corresponding to the current moment in the average power sequence is used as the real-time load power, and the next adjacent overall power parameter is used as the predicted load power, and the power change trend parameter at the current moment is obtained according to the change characteristics of the real-time load power and the predicted load power; The length of the preset time interval is less than the first preset history length; The calculation method of the power change trend parameter includes: The ratio of the difference between the predicted load power and the real-time load power to the difference between the corresponding mark moments is used as a power change trend parameter; The method for obtaining the heat dissipation effect parameter includes: Taking the current moment as the end point and the second preset historical length as the time length, intercepting a section of historical temperature data; obtaining a first heat dissipation parameter according to the relative size of each temperature data in the historical temperature data and the temperature data at the current moment; Obtaining a second heat dissipation parameter according to a relative size between the preset maximum temperature data and the temperature data at the current moment; According to the first heat dissipation parameter and the second heat dissipation parameter, a heat dissipation effect parameter of the intelligent electrical cabinet at the current moment is obtained; the first heat dissipation parameter and the second heat dissipation parameter are both positively correlated with the heat dissipation effect parameter; The calculation formulas for the heat dissipation effect parameters include: ;in, Indicates the heat dissipation effect parameters at the current moment; represents the linear normalization function; Indicates the number of temperature data in the historical temperature data; Indicates the temperature data at the current moment; Indicates the historical temperature data Temperature data; Indicates the preset maximum temperature data; represents a first heat dissipation parameter; represents the second heat dissipation parameter.

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