A method and system for dynamic analysis of power consumption based on energy efficiency optimization control

Abstract

The present invention discloses a method and system for dynamic analysis of power consumption based on energy efficiency optimization control, which relates to the field of energy management technology, including: forming an energy consumption set; forming an energy consumption topology architecture of an energy consumption mode; forming an energy consumption mode identification mechanism to obtain a target energy consumption mode for power operation; calculating the actual power distribution of the energy consumption topology architecture of the target energy consumption mode; analyzing the load distribution of the energy consumption topology architecture of the target energy consumption mode; based on the actual power distribution and load distribution, identifying ineffective power consumption and obtaining an energy consumption optimization point. By forming an energy consumption set, forming an energy consumption mode identification mechanism, obtaining the actual power distribution and load distribution, and obtaining an energy consumption optimization point, the effective conversion power and the required conversion power are estimated, and by comparing the two, the path where there is a problem with energy consumption conversion can be found.

Description

Technical Field

[0001] The present invention relates to the technical field of energy management, and in particular to a method and system for dynamically analyzing power consumption based on energy efficiency optimization control. Background Art

[0002] Dynamic power consumption analysis refers to the process of real-time monitoring, recording, and analyzing the power consumption of electronic devices or systems under different operating conditions. This analysis is crucial for optimizing energy efficiency, extending battery life, and reducing operating costs.

[0003] When optimizing energy efficiency, it is very important to accurately analyze the energy consumption in the power supply. The power supply operates in different modes in different situations, which will interfere with the analysis. However, there are many electronic components in the power supply design, and the connection relationship between the electronic components is complex. The conversion of electrical energy in the electronic components is difficult to determine. As a result, it is difficult to determine the location where there is room for optimization, and it is difficult to perform targeted energy efficiency optimization based on the results of energy consumption analysis. Summary of the Invention

[0004] In order to solve the above technical problems, a method and system for dynamic analysis of power consumption based on energy efficiency optimization control are provided. This technical solution solves the problems raised in the above background technology.

[0005] In order to achieve the above objects, the technical solution adopted by the present invention is:

[0006] A method for dynamic analysis of power consumption based on energy efficiency optimization control, comprising:

[0007] Obtain at least one energy consumption mode of power supply energy consumption, and obtain at least one energy consumption location of power supply energy consumption;

[0008] Summarize the energy consumption locations involved in the energy consumption pattern to form an energy consumption set;

[0009] Based on the energy consumption set, an energy consumption topology architecture of the energy consumption pattern is formed;

[0010] Form an energy consumption pattern recognition mechanism, obtain real-time data of power supply operation, use the energy consumption pattern recognition mechanism to identify the real-time data, and obtain the target energy consumption pattern of power supply operation;

[0011] Calculate the actual power distribution of the energy consumption topology architecture under the target energy consumption mode;

[0012] Analyze and obtain the load distribution of the energy consumption topology architecture of the target energy consumption mode;

[0013] Based on the actual power distribution and load distribution, invalid power consumption is identified and the energy consumption optimization point is obtained.

[0014] Preferably, the step of aggregating the energy consumption locations involved in the energy consumption pattern to form an energy consumption set includes the following steps:

[0015] The energy consumption location is the location of the filter, varistor, rectifier circuit, switch topology, power device, PWM controller, feedback loop, auxiliary power supply, output filter device and voltage regulator protection device in the power supply;

[0016] When the operation mode of the power supply is the energy consumption mode, the voltage difference at both ends of the energy consumption location is measured, and the energy consumption locations where the voltage difference at both ends is not 0 are summarized as the energy consumption locations involved in the energy consumption mode.

[0017] Preferably, forming an energy consumption topology architecture of an energy consumption pattern based on an energy consumption set comprises the following steps:

[0018] The topology formation mechanism is: when two energy consumption locations are directly connected by a wire in the power supply, the line segments are connected at the two energy consumption locations; otherwise, no processing is performed;

[0019] According to the topology formation mechanism, the energy consumption locations in the energy consumption set are connected by line segments. According to the operation of the current under the energy consumption mode corresponding to the energy consumption set, the time it takes for the current to reach the energy consumption location is obtained as the characteristic time.

[0020] Aggregating at least one node of the energy consumption location to form a node set, where the node is the energy consumption location connected to the energy consumption location by a line segment, and the energy consumption location corresponds to the node set formed by the node set;

[0021] When the characteristic time consumption of a node is greater than the characteristic time consumption of the energy consumption location, the node will be deleted from the node set;

[0022] After the deletion is completed, the energy consumption locations and their corresponding node sets are summarized into the energy consumption topology architecture of the energy consumption pattern.

[0023] Preferably, the energy consumption pattern recognition mechanism comprises the following steps:

[0024] Acquire at least one sample operation data of the power supply in the energy consumption mode, and extract a sample value of the energy consumption position from the sample operation data;

[0025] Obtain at least one mapping function from a function database, wherein an independent variable of the mapping function is composed of all energy consumption locations;

[0026] Divide the (0, 1) interval into equal intervals to obtain at least one identification point;

[0027] forming at least one mapping weight group, the mapping weight group consisting of at least one mapping weight, the mapping weight being a random one among the identification points, and the number of mapping weights in the mapping weight group being the same as the number of mapping functions;

[0028] Multiply the mapping function with the mapping weight in the mapping weight group in sequence to obtain a mapping combination function;

[0029] Substitute the sample value of the energy consumption position in the energy consumption set under the energy consumption mode in the single sample operation data into the mapping combination function and set the remaining independent variables of the mapping combination function to 0 to obtain the result value;

[0030] Using the maximum and minimum values ​​of at least one result value in the energy consumption mode to form a judgment interval of the energy consumption mode;

[0031] The mapping combination function whose judgment intervals do not overlap with each other is used as the target mapping combination function.

[0032] Preferably, identifying the real-time data to obtain the target energy consumption mode of the power supply operation includes the following steps:

[0033] Identify from real-time data and obtain the actual value of energy consumption location;

[0034] Substitute the actual value of the energy consumption position in the energy consumption set into the target mapping combination function and set the remaining independent variables of the target mapping combination function to 0 to obtain the basic value;

[0035] The energy consumption pattern whose judgment interval includes the basic value is used as the target energy consumption pattern.

[0036] Preferably, the calculation of the actual power distribution of the energy consumption topology of the target energy consumption mode includes the following steps:

[0037] The energy consumption position in the energy consumption set corresponding to the target energy consumption pattern is used as the target energy consumption position, and the node set corresponding to the target energy consumption position is used as the target node set;

[0038] Counting at least one instantaneous power value of a target energy consumption location under the target energy consumption mode, fitting the instantaneous power value with respect to time to obtain a power fitting function, wherein the domain of the power fitting function is a preset time period, and the preset time period is any time range of the power supply operation under the target energy consumption mode;

[0039] Derivative the power fitting function to obtain the power derivative function;

[0040] A target coefficient group of the target node set is calculated, the target coefficient group is composed of at least one target coefficient, and the result of sequentially multiplying the power derivative function corresponding to the nodes in the target node set by the target coefficient in the target coefficient group is consistent with the power derivative function of the target energy consumption position corresponding to the target node set, and the nodes in the target node set are arranged in an arbitrary fixed order;

[0041] The nodes in the target node set are paired with the target energy consumption positions corresponding to the target node set to obtain a target energy consumption position group. The target energy consumption position group is arranged according to the arrangement order of the nodes in the target node set. The target coefficients of the target coefficient group are sequentially allocated to the target energy consumption position group to obtain the actual power distribution situation.

[0042] Preferably, the analyzing and obtaining the load distribution of the energy consumption topology of the target energy consumption mode comprises the following steps:

[0043] The reciprocal of the resistance values ​​of the target energy consumption positions corresponding to all target node sets including the node is accumulated to obtain the reciprocal of the comprehensive resistance value of the node;

[0044] The load factor is obtained by dividing the inverse of the resistance of the target energy consumption position in the target energy consumption position group by the inverse of the comprehensive resistance of the nodes in the target energy consumption position group. The load factor is paired with the target energy consumption position group to obtain the load distribution situation.

[0045] Preferably, the identification of ineffective power consumption and obtaining the energy consumption optimization point includes the following steps:

[0046] Multiplying the instantaneous power value of the node in the target energy consumption position group by the target coefficient corresponding to the target energy consumption position group to obtain the effective conversion power of the target energy consumption position group;

[0047] The instantaneous power value of the node in the target energy consumption position group is multiplied by the load factor corresponding to the target energy consumption position group to obtain the required conversion power of the target energy consumption position group;

[0048] The ineffective power consumption is obtained by subtracting the effective power consumption from the power consumption to be converted.

[0049] The nodes in the target energy consumption location group with invalid power consumption greater than 0 and the connection paths of the target energy consumption location are regarded as energy consumption optimizable points.

[0050] A power supply energy consumption dynamic analysis system based on energy efficiency optimization control, used to implement the above-mentioned power supply energy consumption dynamic analysis method based on energy efficiency optimization control, comprising:

[0051] a data acquisition module, wherein the data acquisition module acquires at least one energy consumption mode of power supply energy consumption and acquires at least one energy consumption location of power supply energy consumption, wherein the energy consumption mode is a standby power consumption mode, a light-load operation power consumption mode, or a full-load operation power consumption mode;

[0052] a data matching module that aggregates energy consumption locations involved in the energy consumption pattern to form an energy consumption set;

[0053] An architecture generation module, wherein the architecture generation module forms an energy consumption topology architecture of the energy consumption pattern based on the energy consumption set;

[0054] A pattern recognition module, wherein the pattern recognition module forms an energy consumption pattern recognition mechanism, obtains real-time data of power supply operation, uses the energy consumption pattern recognition mechanism to recognize the real-time data, and obtains a target energy consumption pattern of the power supply operation;

[0055] an efficiency calculation module, wherein the efficiency calculation module calculates the actual power distribution of the energy consumption topology architecture of the target energy consumption mode;

[0056] A load analysis module, wherein the load analysis module analyzes and obtains the load distribution of the energy consumption topology architecture of the target energy consumption mode;

[0057] The optimization identification module identifies ineffective power consumption based on actual power distribution and load distribution, and obtains energy consumption optimization points.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] By forming an energy consumption set, forming an energy consumption pattern identification mechanism, obtaining the actual power supply distribution and load distribution, and obtaining the energy consumption optimization point, the energy consumption pattern of the power supply operation can be identified, and then, in different situations, subsequent energy consumption analysis can be carried out according to the energy consumption pattern of the power supply operation, thereby improving the accuracy of the analysis. In addition, the step-by-step distribution of energy at the energy consumption location is estimated, and its effective conversion power and the power to be converted are estimated. By comparing the two, the path where there are problems in energy consumption conversion can be discovered, thereby ensuring the accuracy of the analysis results, and then subsequent optimization operations can be carried out according to the energy consumption optimization points obtained from the analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 Schematic diagram of the flow of the power supply energy consumption dynamic analysis method based on energy efficiency optimization control of the present invention;

[0061] Figure 2 A schematic diagram of a process for aggregating energy consumption locations involved in energy consumption patterns to form an energy consumption set according to the present invention;

[0062] Figure 3 A schematic diagram of a process for forming an energy consumption topology architecture of an energy consumption pattern based on an energy consumption set according to the present invention;

[0063] Figure 4 A schematic diagram of a flow chart of an energy consumption pattern recognition mechanism according to the present invention;

[0064] Figure 5 A schematic diagram of a process for identifying real-time data and obtaining a target energy consumption mode for power supply operation according to the present invention;

[0065] Figure 6 A schematic diagram of a flow chart of the actual power distribution of the energy consumption topology architecture for calculating the target energy consumption mode of the present invention;

[0066] Figure 7 A schematic diagram of a flow chart of load distribution of an energy consumption topology architecture of a target energy consumption mode obtained by analyzing the present invention;

[0067] Figure 8 The present invention is a flow chart of identifying ineffective power consumption and obtaining energy consumption optimization points. DETAILED DESCRIPTION

[0068] The following description is intended to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are merely examples, and those skilled in the art may conceive of other obvious variations.

[0069] Reference Figure 1 As shown, a power supply energy consumption dynamic analysis method based on energy efficiency optimization control includes:

[0070] Obtain at least one energy consumption mode of power supply energy consumption, and obtain at least one energy consumption location of power supply energy consumption;

[0071] Summarize the energy consumption locations involved in the energy consumption pattern to form an energy consumption set;

[0072] Based on the energy consumption set, an energy consumption topology architecture of the energy consumption pattern is formed;

[0073] Form an energy consumption pattern recognition mechanism, obtain real-time data of power supply operation, use the energy consumption pattern recognition mechanism to identify the real-time data, and obtain the target energy consumption pattern of power supply operation;

[0074] Calculate the actual power distribution of the energy consumption topology architecture under the target energy consumption mode;

[0075] Analyze and obtain the load distribution of the energy consumption topology architecture of the target energy consumption mode;

[0076] Based on the actual power distribution and load distribution, invalid power consumption is identified and the energy consumption optimization point is obtained.

[0077] Typically, the energy consumption modes are standby mode, light-load mode, or full-load mode, but more intermediate modes may be added depending on power usage requirements.

[0078] Each energy consumption location is connected to multiple energy consumption locations. The electric energy of the energy consumption location is transmitted from multiple energy consumption locations at the previous level. At the same time, the energy consumption location at the previous level may transmit electric energy to multiple energy consumption locations. During measurement, only the instantaneous power value at the energy consumption location can be measured. However, the instantaneous power value includes the comprehensive transmission status of multiple energy consumption locations at the previous level. Therefore, the instantaneous power value can only be used to determine whether there is an abnormality in the overall energy consumption, but it cannot be accurately determined between energy consumption locations. This leads to insufficient pertinence of optimization based on the analysis results. Therefore, a series of steps are set up in the subsequent step to determine the target energy consumption location group.

[0079] In fact, according to the distribution of resistance, the target energy consumption position group's conversion power can be determined. However, since the target energy consumption position group may be aged, the actual effective conversion power will deviate. Once a deviation occurs, it will cause problems with the energy consumption of the entire power supply. Therefore, it is necessary to optimize the target energy consumption position group with deviations. Since the target energy consumption position group only involves nodes and target energy consumption positions, and the node itself is also a target energy consumption position, the names are distinguished only to prevent confusion. Therefore, the location of the problem can be accurately determined.

[0080] Reference Figure 2 As shown, aggregating the energy consumption locations involved in the energy consumption pattern to form an energy consumption set includes the following steps:

[0081] The energy consumption location is the location of the filter, varistor, rectifier circuit, switch topology, power device, PWM controller, feedback loop, auxiliary power supply, output filter device and voltage regulator protection device in the power supply;

[0082] When the operation mode of the power supply is the energy consumption mode, the voltage difference at both ends of the energy consumption location is measured, and the energy consumption locations where the voltage difference at both ends is not 0 are summarized as the energy consumption locations involved in the energy consumption mode.

[0083] Reference Figure 3 As shown, based on the energy consumption set, forming an energy consumption topology architecture of the energy consumption pattern includes the following steps:

[0084] The topology formation mechanism is: when two energy consumption locations are directly connected by a wire in the power supply, the line segments are connected at the two energy consumption locations; otherwise, no processing is performed;

[0085] According to the topology formation mechanism, the energy consumption locations in the energy consumption set are connected by line segments. According to the operation of the current under the energy consumption mode corresponding to the energy consumption set, the time it takes for the current to reach the energy consumption location is obtained as the characteristic time.

[0086] Aggregating at least one node of the energy consumption location to form a node set, where the node is the energy consumption location connected to the energy consumption location by a line segment, and the energy consumption location corresponds to the node set formed by the node set;

[0087] When the characteristic time consumption of a node is greater than the characteristic time consumption of the energy consumption location, the node will be deleted from the node set;

[0088] After the deletion is completed, the energy consumption locations and their corresponding node sets are summarized into the energy consumption topology architecture of the energy consumption pattern.

[0089] The node here is also an energy consumption location, but if the energy consumption location is used as the name, it is easy to cause confusion in the description. Therefore, it is used as a node. The nodes in the node set corresponding to the energy consumption location are actually the energy consumption locations of the upper level that directly transmit power to it. The reason is that the energy consumption locations directly connected to the energy consumption location either transmit power to it or receive power from it. If the energy consumption location receives power from it, the corresponding feature time consumption must be greater, and these nodes are deleted.

[0090] Reference Figure 4 As shown, the recognition mechanism for forming energy consumption patterns includes the following steps:

[0091] Acquire at least one sample operation data of the power supply in the energy consumption mode, and extract a sample value of the energy consumption position from the sample operation data;

[0092] Obtain at least one mapping function from a function database, wherein an independent variable of the mapping function is composed of all energy consumption locations;

[0093] Divide the (0, 1) interval into equal intervals to obtain at least one identification point;

[0094] forming at least one mapping weight group, the mapping weight group consisting of at least one mapping weight, the mapping weight being a random one among the identification points, and the number of mapping weights in the mapping weight group being the same as the number of mapping functions;

[0095] Multiply the mapping function with the mapping weight in the mapping weight group in sequence to obtain a mapping combination function;

[0096] Substitute the sample value of the energy consumption position in the energy consumption set under the energy consumption mode in the single sample operation data into the mapping combination function and set the remaining independent variables of the mapping combination function to 0 to obtain the result value;

[0097] Using the maximum and minimum values ​​of at least one result value in the energy consumption mode to form a judgment interval of the energy consumption mode;

[0098] The mapping combination function whose judgment intervals do not overlap with each other is used as the target mapping combination function.

[0099] Here, after the sample values ​​under different energy consumption modes are input into the target mapping combination function, the value ranges generated by them do not overlap with each other. Therefore, the target mapping combination function can be used to identify the energy consumption mode. However, the difficulty here lies in forming the target mapping combination function. Through the function database, at least one mapping function can be obtained, but the output results of these mapping functions for the sample values ​​under different energy consumption modes may overlap. Therefore, the required target mapping combination function cannot be directly obtained from these mapping functions. Therefore, the mapping combination function is formed by combining different weights, and the required target mapping combination function is selected from the mapping combination functions.

[0100] It should also be noted that the independent variable of the mapping function is the data of all energy consumption locations, while in the energy consumption mode, only the values ​​of the energy consumption locations in the corresponding energy consumption set are used. The remaining energy consumption locations do not generate power transmission in the energy consumption mode, so they are set to 0.

[0101] Reference Figure 5 As shown, identifying real-time data and obtaining a target energy consumption mode for power supply operation includes the following steps:

[0102] Identify from real-time data and obtain the actual value of energy consumption location;

[0103] Substitute the actual value of the energy consumption position in the energy consumption set into the target mapping combination function and set the remaining independent variables of the target mapping combination function to 0 to obtain the basic value;

[0104] The energy consumption pattern whose judgment interval includes the basic value is used as the target energy consumption pattern.

[0105] Reference Figure 6 As shown, calculating the actual power distribution of the energy consumption topology architecture of the target energy consumption mode includes the following steps:

[0106] The energy consumption position in the energy consumption set corresponding to the target energy consumption pattern is used as the target energy consumption position, and the node set corresponding to the target energy consumption position is used as the target node set;

[0107] Counting at least one instantaneous power value of a target energy consumption location under the target energy consumption mode, fitting the instantaneous power value with respect to time to obtain a power fitting function, wherein the domain of the power fitting function is a preset time period, and the preset time period is any time range of the power supply operation under the target energy consumption mode;

[0108] Derivative the power fitting function to obtain the power derivative function;

[0109] A target coefficient group of the target node set is calculated, the target coefficient group is composed of at least one target coefficient, and the result of sequentially multiplying the power derivative function corresponding to the nodes in the target node set by the target coefficient in the target coefficient group is consistent with the power derivative function of the target energy consumption position corresponding to the target node set, and the nodes in the target node set are arranged in an arbitrary fixed order;

[0110] The nodes in the target node set are paired with the target energy consumption positions corresponding to the target node set to obtain a target energy consumption position group. The target energy consumption position group is arranged according to the arrangement order of the nodes in the target node set. The target coefficients of the target coefficient group are sequentially allocated to the target energy consumption position group to obtain the actual power distribution situation.

[0111] The electric energy of the nodes in the target node set is allocated to the corresponding target energy consumption position group in a fixed proportion. Because there will not be a big structural change in the circuit in a short time, the electric energy of the target energy consumption position group is the sum generated by the node allocation in the target node set. Therefore, the rate of change of the part of the electric energy of the target energy consumption position group allocated by the nodes in the target node set is consistent with the rate of change of the electric energy of the node. Therefore, it is necessary to find a target coefficient group. The target coefficient group satisfies that the result of multiplying the power derivative function corresponding to the node in the target node set with the target coefficient in the target coefficient group in sequence is consistent with the power derivative function of the target energy consumption position corresponding to the target node set. According to the conditions satisfied by the target coefficient group, the power derivative function can be taken at multiple times to obtain multiple equations. If the unknown number in the equation is the target coefficient, the target coefficient can be solved.

[0112] Reference Figure 7 As shown, analyzing the load distribution of the energy consumption topology architecture of the target energy consumption mode includes the following steps:

[0113] The reciprocal of the resistance values ​​of the target energy consumption positions corresponding to all target node sets including the node is accumulated to obtain the reciprocal of the comprehensive resistance value of the node;

[0114] The load factor is obtained by dividing the inverse of the resistance of the target energy consumption position in the target energy consumption position group by the inverse of the comprehensive resistance of the nodes in the target energy consumption position group. The load factor is paired with the target energy consumption position group to obtain the load distribution situation.

[0115] Since the electric energy of a node will be distributed to multiple target energy consumption locations directly connected to the next level, and the target energy consumption locations directly connected to the next level can be approximately regarded as parallel, and the power under the parallel condition is proportional to the inverse of the resistance value, therefore, the load coefficient is formed according to the inverse of the resistance value to determine the proportion of the electric energy of the node distributed to the target energy consumption location. Here, the target energy consumption location group includes the node and the target energy consumption location. Therefore, a load coefficient is matched for each target energy consumption location group.

[0116] Reference Figure 8 As shown, identifying ineffective power consumption and obtaining energy consumption optimization points include the following steps:

[0117] Multiplying the instantaneous power value of the node in the target energy consumption position group by the target coefficient corresponding to the target energy consumption position group to obtain the effective conversion power of the target energy consumption position group;

[0118] The instantaneous power value of the node in the target energy consumption position group is multiplied by the load factor corresponding to the target energy consumption position group to obtain the required conversion power of the target energy consumption position group;

[0119] The ineffective power consumption is obtained by subtracting the effective power consumption from the power consumption to be converted.

[0120] The nodes in the target energy consumption location group with invalid power consumption greater than 0 and the connection paths of the target energy consumption location are regarded as energy consumption optimizable points.

[0121] If the ineffective power consumption is greater than 0, it means that part of the power that should be converted has no effect due to problems in the link between the nodes in the target energy consumption location group and the target energy consumption location, and therefore needs to be optimized.

[0122] A power supply energy consumption dynamic analysis system based on energy efficiency optimization control, used to implement the above-mentioned power supply energy consumption dynamic analysis method based on energy efficiency optimization control, comprising:

[0123] a data acquisition module, wherein the data acquisition module acquires at least one energy consumption mode of power supply energy consumption and acquires at least one energy consumption location of power supply energy consumption, wherein the energy consumption mode is a standby power consumption mode, a light-load operation power consumption mode, or a full-load operation power consumption mode;

[0124] a data matching module that aggregates energy consumption locations involved in the energy consumption pattern to form an energy consumption set;

[0125] An architecture generation module, wherein the architecture generation module forms an energy consumption topology architecture of the energy consumption pattern based on the energy consumption set;

[0126] A pattern recognition module, wherein the pattern recognition module forms an energy consumption pattern recognition mechanism, obtains real-time data of power supply operation, uses the energy consumption pattern recognition mechanism to recognize the real-time data, and obtains a target energy consumption pattern of the power supply operation;

[0127] an efficiency calculation module, wherein the efficiency calculation module calculates the actual power distribution of the energy consumption topology architecture of the target energy consumption mode;

[0128] A load analysis module, wherein the load analysis module analyzes and obtains the load distribution of the energy consumption topology architecture of the target energy consumption mode;

[0129] The optimization identification module identifies ineffective power consumption based on actual power distribution and load distribution, and obtains energy consumption optimization points.

[0130] Furthermore, the present solution also proposes a storage medium on which a computer-readable program is stored. When the computer-readable program is called, the above-mentioned power consumption dynamic analysis method based on energy efficiency optimization control is executed.

[0131] It is understandable that the storage medium may be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; an optical medium, such as a DVD; or a semiconductor medium, such as a solid state disk (SSD).

[0132] To sum up, the advantages of the present invention are: by forming an energy consumption set, forming an energy consumption pattern identification mechanism, obtaining the actual power supply distribution and load distribution, and obtaining the energy consumption optimization point, the energy consumption pattern of the power supply operation can be identified, and thus in different situations, subsequent energy consumption analysis is performed according to the energy consumption pattern of the power supply operation, thereby improving the accuracy of the analysis. In addition, the step-by-step distribution of energy at the energy consumption position is estimated, and its effective conversion power and the power to be converted are estimated. By comparing the two, the path where there are problems with energy consumption conversion can be found, thereby ensuring the accuracy of the analysis results, and then subsequent optimization operations can be performed based on the energy consumption optimization points obtained by analysis.

[0133] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions merely illustrate the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for dynamic analysis of power consumption based on energy efficiency optimization control, characterized in that: include: Obtain at least one energy consumption mode of power supply energy consumption, and obtain at least one energy consumption location of power supply energy consumption; Summarize the energy consumption locations involved in the energy consumption pattern to form an energy consumption set; Based on the energy consumption set, an energy consumption topology architecture of the energy consumption pattern is formed; Form an energy consumption pattern recognition mechanism, obtain real-time data of power supply operation, use the energy consumption pattern recognition mechanism to identify the real-time data, and obtain the target energy consumption pattern of power supply operation; Calculate the actual power distribution of the energy consumption topology architecture under the target energy consumption mode; Analyze and obtain the load distribution of the energy consumption topology architecture of the target energy consumption mode; Based on the actual power distribution and load distribution, invalid power consumption is identified to obtain the energy consumption optimization point; The energy consumption topology architecture of forming the energy consumption pattern based on the energy consumption set includes the following steps: The topology formation mechanism is: when two energy consumption locations are directly connected by a wire in the power supply, the line segments are connected at the two energy consumption locations; otherwise, no processing is performed; According to the topology formation mechanism, the energy consumption locations in the energy consumption set are connected by line segments. According to the operation of the current under the energy consumption mode corresponding to the energy consumption set, the time it takes for the current to reach the energy consumption location is obtained as the characteristic time. Aggregating at least one node of the energy consumption location to form a node set, where the node is the energy consumption location connected to the energy consumption location by a line segment, and the energy consumption location corresponds to the node set formed by the node set; When the characteristic time consumption of a node is greater than the characteristic time consumption of the energy consumption location, the node will be deleted from the node set; After the deletion is completed, the energy consumption locations and their corresponding node sets are summarized into the energy consumption topology architecture of the energy consumption pattern.

2. The method for dynamic analysis of power consumption based on energy efficiency optimization control according to claim 1, characterized in that: Summarizing the energy consumption locations involved in the energy consumption pattern to form an energy consumption set includes the following steps: The energy consumption location is the location of the filter, varistor, rectifier circuit, switch topology, power device, PWM controller, feedback loop, auxiliary power supply, output filter device and voltage regulator protection device in the power supply; When the operation mode of the power supply is the energy consumption mode, the voltage difference at both ends of the energy consumption location is measured, and the energy consumption locations where the voltage difference at both ends is not 0 are summarized as the energy consumption locations involved in the energy consumption mode.

3. The method for dynamic analysis of power consumption based on energy efficiency optimization control according to claim 2, characterized in that: The energy consumption pattern recognition mechanism includes the following steps: Acquire at least one sample operation data of the power supply in the energy consumption mode, and extract a sample value of the energy consumption position from the sample operation data; Obtain at least one mapping function from a function database, wherein an independent variable of the mapping function is composed of all energy consumption locations; Divide the (0, 1) interval into equal intervals to obtain at least one identification point; forming at least one mapping weight group, the mapping weight group consisting of at least one mapping weight, the mapping weight being a random one among the identification points, and the number of mapping weights in the mapping weight group being the same as the number of mapping functions; Multiply the mapping function with the mapping weight in the mapping weight group in sequence to obtain a mapping combination function; Substitute the sample value of the energy consumption position in the energy consumption set under the energy consumption mode in the single sample operation data into the mapping combination function and set the remaining independent variables of the mapping combination function to 0 to obtain the result value; Using the maximum and minimum values ​​of at least one result value in the energy consumption mode to form a judgment interval of the energy consumption mode; The mapping combination function whose judgment intervals do not overlap with each other is used as the target mapping combination function.

4. The method for dynamic analysis of power consumption based on energy efficiency optimization control according to claim 3, characterized in that: The identifying of real-time data to obtain a target energy consumption mode of power supply operation includes the following steps: Identify from real-time data and obtain the actual value of energy consumption location; Substitute the actual value of the energy consumption position in the energy consumption set into the target mapping combination function and set the remaining independent variables of the target mapping combination function to 0 to obtain the basic value; The energy consumption pattern whose judgment interval includes the basic value is used as the target energy consumption pattern.

5. The method for dynamic analysis of power consumption based on energy efficiency optimization control according to claim 4, characterized in that: Calculating the actual power distribution of the energy consumption topology of the target energy consumption mode includes the following steps: The energy consumption position in the energy consumption set corresponding to the target energy consumption pattern is used as the target energy consumption position, and the node set corresponding to the target energy consumption position is used as the target node set; Counting at least one instantaneous power value of a target energy consumption location under the target energy consumption mode, fitting the instantaneous power value with respect to time to obtain a power fitting function, wherein the domain of the power fitting function is a preset time period, and the preset time period is any time range of the power supply operation under the target energy consumption mode; Derivative the power fitting function to obtain the power derivative function; A target coefficient group of the target node set is calculated, the target coefficient group is composed of at least one target coefficient, and the result of sequentially multiplying the power derivative function corresponding to the nodes in the target node set by the target coefficient in the target coefficient group is consistent with the power derivative function of the target energy consumption position corresponding to the target node set, and the nodes in the target node set are arranged in an arbitrary fixed order; The nodes in the target node set are paired with the target energy consumption positions corresponding to the target node set to obtain a target energy consumption position group. The target energy consumption position group is arranged according to the arrangement order of the nodes in the target node set. The target coefficients of the target coefficient group are sequentially allocated to the target energy consumption position group to obtain the actual power distribution situation.

6. The method for dynamic analysis of power consumption based on energy efficiency optimization control according to claim 5, characterized in that: The analysis to obtain the load distribution of the energy consumption topology of the target energy consumption mode includes the following steps: The reciprocal of the resistance values ​​of the target energy consumption positions corresponding to all target node sets including the node is accumulated to obtain the reciprocal of the comprehensive resistance value of the node; The load factor is obtained by dividing the inverse of the resistance of the target energy consumption position in the target energy consumption position group by the inverse of the comprehensive resistance of the nodes in the target energy consumption position group. The load factor is paired with the target energy consumption position group to obtain the load distribution situation.

7. The method for dynamic analysis of power consumption based on energy efficiency optimization control according to claim 6, characterized in that: The identification of ineffective power consumption and obtaining the energy consumption optimization point includes the following steps: Multiplying the instantaneous power value of the node in the target energy consumption position group by the target coefficient corresponding to the target energy consumption position group to obtain the effective conversion power of the target energy consumption position group; The instantaneous power value of the node in the target energy consumption position group is multiplied by the load factor corresponding to the target energy consumption position group to obtain the required conversion power of the target energy consumption position group; The ineffective power consumption is obtained by subtracting the effective power consumption from the power consumption to be converted. The nodes in the target energy consumption location group with invalid power consumption greater than 0 and the connection paths of the target energy consumption location are regarded as energy consumption optimizable points.

8. A power supply energy consumption dynamic analysis system based on energy efficiency optimization control, used to implement the power supply energy consumption dynamic analysis method based on energy efficiency optimization control according to any one of claims 1 to 7, characterized in that: include: a data acquisition module, wherein the data acquisition module acquires at least one energy consumption mode of power supply energy consumption and acquires at least one energy consumption location of power supply energy consumption, wherein the energy consumption mode is a standby power consumption mode, a light-load operation power consumption mode, or a full-load operation power consumption mode; a data matching module that aggregates energy consumption locations involved in the energy consumption pattern to form an energy consumption set; An architecture generation module, wherein the architecture generation module forms an energy consumption topology architecture of the energy consumption pattern based on the energy consumption set; A pattern recognition module, wherein the pattern recognition module forms an energy consumption pattern recognition mechanism, obtains real-time data of power supply operation, uses the energy consumption pattern recognition mechanism to recognize the real-time data, and obtains a target energy consumption pattern of the power supply operation; an efficiency calculation module, wherein the efficiency calculation module calculates the actual power distribution of the energy consumption topology architecture of the target energy consumption mode; A load analysis module, wherein the load analysis module analyzes and obtains the load distribution of the energy consumption topology architecture of the target energy consumption mode; The optimization identification module identifies ineffective power consumption based on actual power distribution and load distribution, and obtains energy consumption optimization points.

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