Intelligent power management device

Abstract

The invention provides an intelligent power supply management device which comprises a power supply monitoring module used for monitoring the state of a mains supply input power supply, a battery module used for providing standby power supply capacity, and a power supply conversion module used for providing power supply conversion capacity. The switch module is used for switching power supply modes; the control module is electrically connected with the power supply monitoring module, the battery module, the power supply conversion module and the switch module, and is used for monitoring the state of a mains supply input power supply through the power supply monitoring module; and predicting and evaluating the occurrence probability of the abnormal condition of the commercial power input power supply state, and controlling the battery module, the power supply conversion module and the switch module to switch among a commercial power supply mode, a battery inversion power supply mode and a hybrid power supply mode according to an evaluation result. Stability of an input end power supply of the electronic equipment can be effectively guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of power management, and particularly relates to an intelligent power management device. Background Art

[0002] During the operation of electronic devices, the stability of the input power supply is crucial. For electronic devices directly powered by the mains, there are many situations that affect the voltage stability. For example, grid faults, lightning strikes, the startup or disconnection of large-capacity devices such as large motors or large transformers, the access of a large number of impact loads or non-linear loads, etc. will all cause problems such as voltage sags, voltage unbalances, voltage fluctuations, and excessive harmonic voltages in the mains power supply, thus seriously affecting the normal operation of electronic devices. Summary of the Invention

[0003] Based on the above problems, the present invention proposes an intelligent power management device that can effectively ensure the stability of the input power supply of electronic devices.

[0004] In view of this, the present invention proposes an intelligent power management device, including a power monitoring module for monitoring the state of the mains input power supply, a battery module for providing backup power supply capabilities, a power conversion module for providing power conversion capabilities, a switch module for switching the power supply mode, and a control module electrically connected to the power monitoring module, the battery module, the power conversion module, and the switch module. The control module is used to monitor the state of the mains input power supply through the power monitoring module, predict and evaluate the probability of abnormal situations in the state of the mains input power supply, and control the battery module, the power conversion module, and the switch module to switch between the mains power supply mode, the battery inverter power supply mode, and the hybrid power supply mode according to the evaluation results.

[0005] Further, the battery module includes a battery pack and a charging circuit. The input end of the charging circuit is connected to the mains input power supply, and the output end is connected to the battery pack, and is used to charge the battery pack through the mains input power supply in the mains power supply mode; The switch module includes a first switching switch with one end connected to the mains input power supply and the other end connected to the output end of the intelligent power management device, and a second switching switch with one end connected to the power conversion module and the other end connected to the output end of the intelligent power management device; The output end of the battery module is connected to the input end of the power conversion module, and is used to supply power to the load after boosting and inverting the battery voltage through the power conversion module; The power conversion module includes a boost circuit connected to the battery module and an inverter circuit connected to the second switching switch. When the second switching switch is turned on, the boost circuit boosts the battery voltage of the battery module and provides it to the subsequent inverter circuit. The inverter circuit converts the boosted voltage into a stable inverter voltage for output.

[0006] Further, the input end of the power monitoring module is connected to the mains input power supply for monitoring the power state of the mains input power supply, and the output end of the power monitoring module is connected to the control module for providing monitoring data to the control module, and the control module is configured as follows: Obtain power status data of the mains input power supply; Inputting the power state data into a pre-trained power state prediction model to predict the power state data within a future period of time; Use the predicted power status data to assess whether the AC input power supply is about to enter an abnormal power status; An operating mode decision is executed based on an evaluation result of whether the AC input power supply is about to enter an abnormal power supply state, so as to control the battery module, the power conversion module and the switch module to switch between the AC power supply mode, the battery inverter power supply mode and the hybrid power supply mode according to the operating mode decision.

[0007] Furthermore, in the step of evaluating whether the AC input power supply is about to enter an abnormal power supply state according to the predicted power supply state data, the control module is configured to: Based on the predicted power status data for a period of time in the future, the input variable set corresponding to each power abnormality state is extracted or calculated: , in is the voltage sag depth, is the duration of voltage sag, is the voltage unbalance, is the voltage fluctuation amplitude, is the total harmonic voltage distortion rate; The fuzzy variable set corresponding to the input variable set is determined based on the membership function of each input variable: , The fuzzy variable set is used to aggregate the fuzzy rules in the fuzzy rule base to obtain the output fuzzy set: , in is the number of output variables in the output fuzzy set; Get the basic score corresponding to each output element in the output fuzzy set ; Calculate the comprehensive prediction score of abnormal power supply status in the future: , in 1 to A positive integer between ; Based on the comprehensive prediction score of power supply abnormality in the future Determine whether the AC input power is about to enter an abnormal power state.

[0008] Furthermore, in the step of determining the fuzzy variable set corresponding to the input variable set based on the membership function of each input variable, the control module is configured as follows: Configure a calculation variable with a value range of 1 to 5 for traversing the input variable set ; Traverse each input variable of the input variable set to calculate the input variable value as follows: Determine the currently traversed input variable as the target input variable; Configure the target input variable corresponding to Membership threshold ,in satisfy: ; use represents the fuzzy state number in the fuzzy set of the target input variable. A fuzzy state whose fuzzy variables satisfy: when hour: ; when hour: ; when hour: .

[0009] Furthermore, in the step of using the fuzzy variable set to aggregate the fuzzy rules in the fuzzy rule base to obtain an output fuzzy set, the control module is configured as follows: The fuzzy rules in the fuzzy rule base are divided into corresponding A subset of rules, of which The rule subset contains Fuzzy rules; Configure the counting variable used to traverse each fuzzy rule in each rule subset , for the A subset of rules, 1 to A positive integer between ; The rule strength of each fuzzy rule in each rule subset is calculated based on the fuzzy variable set. ; Rule strength based on fuzzy rules in each rule subset Calculate each output variable of the output fuzzy set: .

[0010] Further, the rule strength of each fuzzy rule in each rule subset is calculated based on the fuzzy variable set. In the step, the control module is configured to: Traverse each fuzzy rule in each rule subset; The first The first The fuzzy rules are determined as target rules; Determine the associated input variables of the target rule , association membership and the associated fuzzy state, the associated membership Enter the variable for the association The fuzzy variable value corresponding to the associated fuzzy state in the fuzzy variable set of 1 to A positive integer between the number of associated input variables in the target rule; Calculate the rule strength of the target rule: .

[0011] Further, in the step of executing the working mode decision according to the evaluation result of whether the mains input power supply is about to enter an abnormal power supply state, the control module is configured as follows: Get the pre-configured comprehensive score The score range corresponding to each working mode; Determine the comprehensive score The working mode corresponding to the score interval that falls into; When the comprehensive score When the score range corresponding to the mains power supply mode is fallen, the first switch is controlled to enter the on state, and the second switch is controlled to enter the off state so that the intelligent power management device supplies power to the load through the mains input power supply.

[0012] Furthermore, in determining the comprehensive score After the step of determining the working mode corresponding to the score interval, the control module is configured to: When the comprehensive score When the score range corresponding to the battery inverter power supply mode is fallen into, the first switch is controlled to enter the disconnected state, and the second switch is controlled to enter the connected state so that the intelligent power management device supplies power to the load through the battery module.

[0013] Furthermore, in determining the comprehensive score After the step of determining the working mode corresponding to the score interval, the control module is configured to: When the comprehensive score When falling into the score interval corresponding to the hybrid power supply mode, the first switching switch and the second switching switch are controlled to enter the on state, and the output voltage of the battery module is adjusted by the power conversion module to compensate for the supply voltage of the AC input power supply.

[0014] The present invention proposes an intelligent power management device, comprising a power monitoring module for monitoring the state of a mains input power supply, a battery module for providing backup power supply capability, a power conversion module for providing power conversion capability, a switch module for switching power supply modes, and a control module electrically connected to the power monitoring module, the battery module, the power conversion module, and the switch module. The control module is used to monitor the state of the mains input power supply through the power monitoring module, predict and evaluate the probability of abnormal conditions in the state of the mains input power supply, and control the battery module, the power conversion module, and the switch module to switch between a mains power supply mode, a battery inverter power supply mode, and a hybrid power supply mode according to the evaluation results, thereby effectively ensuring the stability of the power supply at the input end of the electronic device. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a schematic diagram of an intelligent power management device provided by an embodiment of the present invention; Figure 2 is a schematic diagram of an intelligent power management device provided by another embodiment of the present invention; Figure 3 It is a flow chart of a control method of an intelligent power management device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0016] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0017] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, the present invention may be practiced in other ways than those specifically described herein, and thus, the scope of protection of the present invention is not limited by the specific embodiments disclosed below.

[0018] In the description of the present invention, the term "plurality" refers to two or more, unless otherwise clearly defined. The orientation or positional relationship indicated by terms such as "upper", "lower", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as a limitation on the present invention. Terms such as "connection", "installation", "fixation", etc. should all be understood in a broad sense. For example, "connection" may be a fixed connection, a detachable connection, or an integral connection; it may be directly connected or indirectly connected through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances. In addition, terms such as "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, features defined with "first", "second", etc. may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise specified, the meaning of "plurality" is two or more.

[0019] In the description of this specification, the descriptions of terms such as "one embodiment", "some embodiments", "specific embodiments", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or instance. Moreover, the specific features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples.

[0020] The following describes an intelligent power management device according to some embodiments of the present invention with reference to the drawings.

[0021] As Figure 1As shown, the first aspect of the present invention proposes an intelligent power management device, including a power monitoring module for monitoring the state of the AC input power supply, a battery module for providing backup power supply capability, a power conversion module for providing power conversion capability, a switch module for switching the power supply mode, and a control module electrically connected to the power monitoring module, the battery module, the power conversion module, and the switch module, the control module being used to monitor the state of the AC input power supply through the power monitoring module, predict and evaluate the probability of abnormal conditions of the AC input power supply state, and control the battery module, the power conversion module, and the switch module to switch between the AC power supply mode, the battery inverter power supply mode, and the hybrid power supply mode according to the evaluation results.

[0022] Further, such as Figure 2 As shown, the battery module includes a battery pack and a charging circuit, the input end of the charging circuit is connected to the mains input power supply, and the output end is connected to the battery pack, and is used to charge the battery pack through the mains input power supply in the mains power supply mode; The switch module includes a first switch having one end connected to the mains input power supply and the other end connected to the output end of the intelligent power management device, and a second switch having one end connected to the power conversion module and the other end connected to the output end of the intelligent power management device; The output end of the battery module is connected to the input end of the power conversion module, and is used to supply power to the load after the battery voltage is boosted and inverted by the power conversion module; The power conversion module includes a boost circuit connected to the battery module and an inverter circuit connected to the second switching switch. When the second switching switch is turned on, the boost circuit boosts the battery voltage of the battery module and provides it to the subsequent inverter circuit. The inverter circuit converts the boosted voltage into a stable inverter voltage for output.

[0023] Specifically, the input end of the intelligent power management device is connected to the mains input power supply, and is used to directly supply power to the load through the mains in the mains power supply mode, and when the battery pack in the battery module needs to be charged, the battery pack is charged through the mains input power supply. The input end of the intelligent power management device is connected to the load, and is used to output the power supply voltage to the load through the mains input power supply or the battery pack in different power supply modes.

[0024] Preferably, in the switch module, the first switch and the second switch are both SCR (Silicon Controlled Rectifier) ​​switches or IGBT (Insulated Gate Bipolar Transistor) switches.

[0025] The boost circuit in the power conversion module is a DC / DC (Direct Current / Direct Current) boost circuit, and the output end of the boost circuit is connected to the input end of the inverter circuit, and is used to boost the DC power provided by the battery pack and output it to the inverter circuit in the form of DC power. The inverter circuit in the power conversion module is a DC / AC (Direct Current / Alternating Current) inverter circuit, which is used to convert the DC power output by the boost circuit into AC power and output it to the load for power supply.

[0026] Further, such as Figure 3 As shown, the input end of the power monitoring module is connected to the mains input power supply for monitoring the power state of the mains input power supply, and the output end of the power monitoring module is connected to the control module for providing monitoring data to the control module. The control module is configured as follows: Obtain power status data of the mains input power supply; Inputting the power state data into a pre-trained power state prediction model to predict the power state data within a future period of time; Use the predicted power status data to assess whether the AC input power supply is about to enter an abnormal power status; An operating mode decision is executed based on an evaluation result of whether the AC input power supply is about to enter an abnormal power supply state, so as to control the battery module, the power conversion module and the switch module to switch between the AC power supply mode, the battery inverter power supply mode and the hybrid power supply mode according to the operating mode decision.

[0027] Preferably, the power supply monitoring module includes a high-precision voltage sensor for real-time acquisition of the voltage signal of the AC input power supply, and a high-precision current sensor for real-time acquisition of the current signal of the AC input power supply. The power supply status data collected by the power supply monitoring module includes but is not limited to amplitude data, phase data, frequency data, etc. of the voltage and current of the AC input power supply, so that the control module can fully grasp the operating status of the AC input power supply.

[0028] The power status prediction model is a power status prediction model obtained by training with machine learning algorithms such as neural networks and support vector machines using the historical power status data of the AC input power at the input end of the intelligent power management device monitored by the power monitoring module as sample data.

[0029] Preferably, the power state prediction model is a data sequence prediction model, that is, the power state prediction model is supervisedly trained by dividing a continuous section of the historical power state data into input sample data and output sample data, so that after the training of the power state prediction model is completed, a section of power state data with the same length as the input sample data monitored by the power monitoring module can be used as input data to predict the power state data of the AC input power supply in a future period of time. The data length of the input sample data and the output sample data can be configured according to actual implementation needs. Correspondingly, the collection time of the input data of the power state prediction model and the predicted duration of the "future period of time" are determined according to the configured data length of the input sample data and the output sample data.

[0030] The abnormal power supply state refers to a power supply abnormality state such as voltage sag, voltage imbalance, voltage fluctuation, and excessive harmonic voltage in the mains input power supply.

[0031] Voltage sag refers to the phenomenon that the effective value of the power supply voltage of the AC input power supply suddenly drops in a short period of time and returns to normal levels after a short period of time. It is mainly caused by short-circuit faults in the power system, startup of large-capacity equipment, lightning strikes and other reasons.

[0032] Voltage unbalance refers to the situation where the amplitudes of the three-phase voltages in the AC input power supply are not equal, which is usually caused by uneven distribution of the three-phase load.

[0033] Voltage fluctuation refers to the rapid, periodic or non-periodic change of the supply voltage of the AC input power supply over a period of time, and the amplitude variation range usually exceeds ±10% of the rated voltage. It is usually caused by the start or stop of large loads in the power grid, resulting in instantaneous changes in the load of the power grid, or the fluctuation of the supply voltage caused by large current fluctuations during the operation of impact loads.

[0034] When there are nonlinear loads in the power grid, the voltage waveform will be distorted, thereby generating harmonic voltage. When the harmonic voltage exceeds the standard, it will increase the loss of electrical equipment, increase the heating of the equipment, and shorten the service life of the equipment.

[0035] Furthermore, in the step of evaluating whether the AC input power supply is about to enter an abnormal power supply state according to the predicted power supply state data, the control module is configured to: Based on the predicted power status data for a period of time in the future, the input variable set corresponding to each power abnormality state is extracted or calculated: , in is the voltage sag depth, is the duration of voltage sag, is the voltage unbalance, is the voltage fluctuation amplitude, is the total harmonic voltage distortion rate; The fuzzy variable set corresponding to the input variable set is determined based on the membership function of each input variable: , The fuzzy variable set is used to aggregate the fuzzy rules in the fuzzy rule base to obtain the output fuzzy set: , in is the number of output variables in the output fuzzy set; Get the basic score corresponding to each output element in the output fuzzy set ; Calculate the comprehensive prediction score of abnormal power supply status in the future: , in 1 to A positive integer between ; Based on the comprehensive prediction score of power supply abnormality in the future Determine whether the AC input power is about to enter an abnormal power state.

[0036] In the technical solution of the above implementation mode, the input variable set is constructed by taking abnormal power supply conditions such as voltage sag, voltage imbalance, voltage fluctuation and excessive harmonic voltage as examples.

[0037] The voltage sag depth of the input variable set The difference between the voltage value measured in real time and the rated voltage is expressed as a percentage of the rated voltage, and its value range is between 0% and 100%. is the number of fuzzy states of voltage sag depth, are the fuzzy variable values ​​under each fuzzy state corresponding to the voltage sag depth.

[0038] The input variable is the voltage sag duration The duration of the voltage sag is usually in seconds, and its value range is configured according to empirical data, for example, it can be configured to 0-10 seconds. is the number of fuzzy states of voltage sag duration, are the fuzzy variable values ​​under each fuzzy state corresponding to the duration of voltage sag.

[0039] The voltage imbalance It can be expressed as a percentage of the negative-sequence voltage component to the positive-sequence voltage component, and its value range is between 0%-10%, wherein the positive-sequence voltage component is a set of three-phase voltages of equal size, 120° phase difference and the same phase sequence as the normal three-phase system. When the three-phase system is completely symmetrical, there is only a positive-sequence voltage component in the system. The negative-sequence voltage component is also a set of three-phase voltages of equal size and 120° phase difference, but its phase sequence is opposite to the positive sequence. Under normal circumstances, the three-phase voltage of the power system is symmetrical, and the negative-sequence voltage component is theoretically zero. However, when a fault occurs in the system (such as a single-phase ground short circuit, a two-phase short circuit, etc.) or the three-phase load is seriously unbalanced, a negative-sequence voltage component will be generated. In the technical scheme of the above-mentioned implementation method, is the number of fuzzy states of voltage imbalance, are the fuzzy variable values ​​under each fuzzy state corresponding to the voltage imbalance degree.

[0040] The voltage fluctuation amplitude It represents the magnitude of the real-time voltage monitored, and its unit is volt, and its value range is determined according to the power supply environment of the actual application. In the technical solution of the above implementation mode, is the number of fuzzy states of voltage fluctuation amplitude, They are the fuzzy variable values ​​under each fuzzy state corresponding to the voltage fluctuation amplitude.

[0041] The total harmonic voltage distortion rate , is the ratio of the square root of the sum of the squares of the effective values ​​of the harmonic voltages in the voltage signal to the effective value of the fundamental voltage, and is used to measure the severity of the harmonic content in the voltage signal. It is usually expressed as a percentage, and its value range is generally between 0% and 20%. In the technical solution of the above implementation, is the number of fuzzy states of voltage fluctuation amplitude, They are the fuzzy variable values ​​under each fuzzy state corresponding to the voltage fluctuation amplitude.

[0042] In the technical solution of the above-mentioned implementation mode, 1 to A positive integer between .

[0043] Based on the comprehensive prediction score of the occurrence of a power supply abnormal state within a future period of time In the step of judging whether the mains input power supply is about to have a power supply abnormal state, by comparing the comprehensive prediction score with a pre-configured scoring threshold to judge whether the mains input power supply is about to have a power supply abnormal state. When the comprehensive prediction score is greater than the scoring threshold, it is determined that a power supply abnormal state will occur within the predicted future period of time.

[0044] Furthermore, in the step of determining the fuzzy variable set corresponding to the input variable set based on the membership function of each input variable, the control module is configured to: Configure a calculation variable with a value range from 1 to 5 for traversing the input variable set ; Traverse each input variable in the input variable set to calculate the input variable value as follows: Determine the currently traversed input variable as the target input variable; Configure the corresponding membership thresholds of the target input variable , where satisfies: ; Use to represent the fuzzy state numbers in the fuzzy set of the target input variable. For the th fuzzy state in the fuzzy set of the target input variable, its fuzzy variable satisfies: When : ; When : ; When : .

[0045] Specifically, each input variable corresponds to a fuzzy set, and the fuzzy set is composed of several fuzzy states used to describe the degree of the power supply abnormal state corresponding to the input variable.

[0046] For example, the fuzzy set of the voltage sag depth can be defined as: "slight" (VS), "moderate" (MS), "severe" (SS), and representing the number of its fuzzy states is ; Similarly, the fuzzy set of the voltage sag duration can be defined as: "short" (ST), "medium" (MT), "long" (LT), and The number of fuzzy states is ; The fuzzy set of voltage unbalance can be defined as: “low” (L), “medium” (M), “high” (H). The number of fuzzy states is ; The fuzzy set of voltage fluctuation amplitude can be defined as: “micro” (VM), “small” (SM), “large” (LM), “huge” (GM). The number of fuzzy states is ; The fuzzy set of harmonic voltage THD can be defined as: "good" (G), "average" (F), "poor" (P), and The number of fuzzy states is .

[0047] It should be noted that the fuzzy sets listed above are only examples, and the fuzzy states and the number of fuzzy states they contain do not constitute a limitation of the present invention. In actual implementation, they can be configured as fuzzy sets composed of other fuzzy states according to implementation needs.

[0048] Furthermore, in the step of using the fuzzy variable set to aggregate the fuzzy rules in the fuzzy rule base to obtain an output fuzzy set, the control module is configured as follows: The fuzzy rules in the fuzzy rule base are divided into corresponding A subset of rules, of which The rule subset contains Fuzzy rules; Configure the counting variable used to traverse each fuzzy rule in each rule subset , for the A subset of rules, 1 to A positive integer between ; The rule strength of each fuzzy rule in each rule subset is calculated based on the fuzzy variable set. ; Rule strength based on fuzzy rules in each rule subset Calculate each output variable of the output fuzzy set: .

[0049] Specifically, each rule subset is associated with an output variable. For example, the output fuzzy set can be defined as "mild" (SL), "moderate" (MOD), and "severe" (SEV), and the output variable set contains three output variables. In this embodiment, the fuzzy rules in the fuzzy rule base can be divided into three rule subsets. represents the number of fuzzy rules in the fuzzy rule base, then the number of fuzzy rules in the fuzzy rule base The number of fuzzy rules in each rule subset satisfy: .

[0050] Further, the rule strength of each fuzzy rule in each rule subset is calculated based on the fuzzy variable set. In the step, the control module is configured to: Traverse each fuzzy rule in each rule subset; The first The first The fuzzy rules are determined as target rules; Determine the associated input variables of the target rule , association membership and the associated fuzzy state, the associated membership Enter the variable for the association The fuzzy variable value corresponding to the associated fuzzy state in the fuzzy variable set of 1 to A positive integer between the number of associated input variables in the target rule; Calculate the rule strength of the target rule: .

[0051] Further, in the step of executing the working mode decision according to the evaluation result of whether the mains input power supply is about to enter an abnormal power supply state, the control module is configured as follows: Get the pre-configured comprehensive score The score range corresponding to each working mode; Determine the comprehensive score The working mode corresponding to the score interval that falls into; When the comprehensive score When the score range corresponding to the mains power supply mode is fallen, the first switch is controlled to enter the on state, and the second switch is controlled to enter the off state so that the intelligent power management device supplies power to the load through the mains input power supply.

[0052] Specifically, in the mains power supply mode, the intelligent power management device supplies power to the load through the mains input power supply, and the power output end of the intelligent power management device outputs the mains AC power to the load. Further, in the mains power supply mode, the control module periodically obtains the remaining power of the battery pack, and when the remaining power of the battery pack is less than a threshold, charges the battery pack through the mains input power supply.

[0053] Furthermore, in determining the comprehensive score After the step of determining the working mode corresponding to the score interval, the control module is configured to: When the comprehensive score When the score range corresponding to the battery inverter power supply mode is fallen into, the first switch is controlled to enter the disconnected state, and the second switch is controlled to enter the connected state so that the intelligent power management device supplies power to the load through the battery module.

[0054] Specifically, when the comprehensive score When it falls into the score interval corresponding to the battery inverter power supply mode, the AC input power supply may have the following situations in the future, such as the voltage sag depth exceeds the set threshold, the voltage imbalance seriously exceeds the standard, the voltage fluctuation amplitude is too large, or the harmonic voltage exceeds a certain limit. At this time, the first switching switch is controlled to enter the disconnected state, and the second switching switch is controlled to enter the connected state to enable the intelligent power management device to enter the battery inverter power supply mode, and the output voltage of the battery module is boosted in turn by the boost circuit, and after the inverter circuit is inverted, stable AC power is provided to the load, thereby avoiding the unstable state of the AC input power supply affecting the normal operation of the load or causing damage to it.

[0055] Furthermore, in determining the comprehensive score After the step of determining the working mode corresponding to the score interval, the control module is configured to: When the comprehensive score When falling into the score interval corresponding to the hybrid power supply mode, the first switching switch and the second switching switch are controlled to enter the on state, and the output voltage of the battery module is adjusted by the power conversion module to compensate for the supply voltage of the AC input power supply.

[0056] Specifically, in the hybrid power supply mode, for some minor power supply abnormalities, such as slight voltage fluctuations or low harmonic content, the intelligent power management device continues to supply power to the load through the mains input power supply, and at the same time controls the power conversion module to appropriately compensate and adjust the output voltage according to the power supply status data predicted in the future. For example, the inverter circuit outputs a certain reverse harmonic current to offset the harmonic components in the mains input power supply, or the output voltage of the boost circuit is adjusted to compensate for the voltage fluctuation of the mains input power supply.

[0057] like Figure 3 As shown, the second aspect of the present invention provides a control method for an intelligent power management device, comprising: Obtain power status data of the mains input power supply; Inputting the power state data into a pre-trained power state prediction model to predict the power state data within a future period of time; Use the predicted power status data to assess whether the AC input power supply is about to enter an abnormal power status; An operating mode decision is executed based on an evaluation result of whether the AC input power supply is about to enter an abnormal power supply state, so as to control the battery module, the power conversion module and the switch module to switch between the AC power supply mode, the battery inverter power supply mode and the hybrid power supply mode according to the operating mode decision.

[0058] Preferably, the power supply monitoring module includes a high-precision voltage sensor for real-time acquisition of the voltage signal of the AC input power supply, and a high-precision current sensor for real-time acquisition of the current signal of the AC input power supply. The power supply status data collected by the power supply monitoring module includes but is not limited to amplitude data, phase data, frequency data, etc. of the voltage and current of the AC input power supply, so that the control module can fully grasp the operating status of the AC input power supply.

[0059] The power status prediction model is a power status prediction model obtained by training with machine learning algorithms such as neural networks and support vector machines using the historical power status data of the AC input power at the input end of the intelligent power management device monitored by the power monitoring module as sample data.

[0060] Preferably, the power state prediction model is a data sequence prediction model, that is, the power state prediction model is supervisedly trained by dividing a continuous section of the historical power state data into input sample data and output sample data, so that after the training of the power state prediction model is completed, a section of power state data with the same length as the input sample data monitored by the power monitoring module can be used as input data to predict the power state data of the AC input power supply in a future period of time. The data length of the input sample data and the output sample data can be configured according to actual implementation needs. Correspondingly, the collection time of the input data of the power state prediction model and the predicted duration of the "future period of time" are determined according to the configured data length of the input sample data and the output sample data.

[0061] The abnormal power supply state refers to a power supply abnormality state such as voltage sag, voltage imbalance, voltage fluctuation, and excessive harmonic voltage in the mains input power supply.

[0062] Voltage sag refers to the phenomenon that the effective value of the power supply voltage of the AC input power supply suddenly drops in a short period of time and returns to normal levels after a short period of time. It is mainly caused by short-circuit faults in the power system, startup of large-capacity equipment, lightning strikes and other reasons.

[0063] Voltage unbalance refers to the situation where the amplitudes of the three-phase voltages in the AC input power supply are not equal, which is usually caused by uneven distribution of the three-phase load.

[0064] Voltage fluctuation refers to the rapid, periodic or non-periodic change of the supply voltage of the AC input power supply over a period of time, and the amplitude variation range usually exceeds ±10% of the rated voltage. It is usually caused by the start or stop of large loads in the power grid, resulting in instantaneous changes in the load of the power grid, or the fluctuation of the supply voltage caused by large current fluctuations during the operation of impact loads.

[0065] When there are nonlinear loads in the power grid, the voltage waveform will be distorted, thereby generating harmonic voltage. When the harmonic voltage exceeds the standard, it will increase the loss of electrical equipment, increase the heating of the equipment, and shorten the service life of the equipment.

[0066] Further, the step of evaluating whether the AC input power supply is about to enter an abnormal power supply state according to the predicted power supply state data specifically includes: Based on the predicted power status data for a period of time in the future, the input variable set corresponding to each power abnormality state is extracted or calculated: , in is the voltage sag depth, is the duration of voltage sag, is the voltage unbalance, is the voltage fluctuation amplitude, is the total harmonic voltage distortion rate; The fuzzy variable set corresponding to the input variable set is determined based on the membership function of each input variable: , The fuzzy variable set is used to aggregate the fuzzy rules in the fuzzy rule base to obtain the output fuzzy set: , in is the number of output variables in the output fuzzy set; Get the basic score corresponding to each output element in the output fuzzy set ; Calculate the comprehensive prediction score of abnormal power supply status in the future: , in 1 to A positive integer between ; Based on the comprehensive prediction score of power supply abnormality in the future Determine whether the AC input power is about to enter an abnormal power state.

[0067] In the technical solution of the above implementation mode, the input variable set is constructed by taking abnormal power supply conditions such as voltage sag, voltage imbalance, voltage fluctuation and excessive harmonic voltage as examples.

[0068] The voltage sag depth of the input variable set The difference between the voltage value measured in real time and the rated voltage is expressed as a percentage of the rated voltage, and its value range is between 0% and 100%. is the number of fuzzy states of voltage sag depth, are the fuzzy variable values ​​under each fuzzy state corresponding to the voltage sag depth.

[0069] The input variable is the voltage sag duration The duration of the voltage sag is usually in seconds, and its value range is configured according to empirical data, for example, it can be configured to 0-10 seconds. is the number of fuzzy states of voltage sag duration, are the fuzzy variable values ​​under each fuzzy state corresponding to the duration of voltage sag.

[0070] The voltage imbalance It can be represented by the percentage of the negative-sequence voltage component to the positive-sequence voltage component, and its value range is between 0% and 10%. The positive-sequence voltage component is a set of three-phase voltages with equal magnitudes, 120° phase differences from each other, and the phase sequence is the same as that of the normal three-phase system. When the three-phase system is completely symmetrical, there is only the positive-sequence voltage component in the system. The negative-sequence voltage component is also a set of three-phase voltages with equal magnitudes and 120° phase differences from each other, but its phase sequence is opposite to that of the positive-sequence. Under normal circumstances, the three-phase voltages of the power system are symmetrical, and the negative-sequence voltage component is theoretically zero. However, when a fault occurs in the system (such as single-phase grounding short circuit, two-phase short circuit, etc.) or the three-phase load is seriously unbalanced, a negative-sequence voltage component will be generated. In the technical solution of the above embodiment, is the number of fuzzy states of the voltage unbalance degree, are the fuzzy variable values under each fuzzy state corresponding to the voltage unbalance degree respectively.

[0071] The voltage fluctuation amplitude represents the magnitude of the monitored real-time voltage, and its unit is volt. Its value range is determined according to the actual power supply environment of the application. In the technical solution of the above embodiment, is the number of fuzzy states of the voltage fluctuation amplitude, are the fuzzy variable values under each fuzzy state corresponding to the voltage fluctuation amplitude respectively.

[0072] The total harmonic distortion rate of the voltage , which is the square root of the sum of the squares of the effective values of each harmonic voltage in the voltage signal divided by the effective value of the fundamental voltage, is used to measure the severity of the harmonic content in the voltage signal. It is usually expressed as a percentage, and its value range is generally between 0% and 20%. In the technical solution of the above embodiment, is the number of fuzzy states of the voltage fluctuation amplitude, are the fuzzy variable values under each fuzzy state corresponding to the voltage fluctuation amplitude respectively.

[0073] In the technical solution of the above embodiment, is a positive integer between 1 and inclusive.

[0074] In the step of judging whether the mains input power supply is about to have a power abnormal state according to the comprehensive prediction score of the occurrence of a power abnormal state in a future period of time, it is judged whether the mains input power supply is about to have a power abnormal state by comparing the comprehensive prediction score with a pre-configured scoring threshold. When the comprehensive prediction score is greater than the scoring threshold, it is determined that a power abnormal state will occur in the predicted future period of time.

[0075] Furthermore, the step of determining the fuzzy variable set corresponding to the input variable set based on the membership function of each input variable specifically includes: Configure a calculation variable with a value range of 1 to 5 for traversing the input variable set ; Traverse each input variable of the input variable set to calculate the input variable value as follows: Determine the currently traversed input variable as the target input variable; Configure the target input variable corresponding to Membership threshold ,in satisfy: ; use represents the fuzzy state number in the fuzzy set of the target input variable. A fuzzy state whose fuzzy variables satisfy: when hour: ; when hour: ; when hour: .

[0076] Specifically, each input variable corresponds to a fuzzy set, and the fuzzy set is composed of a plurality of fuzzy states for describing the degree to which the abnormal power supply state corresponds to the input variable.

[0077] For example, the fuzzy set of voltage sag depth can be defined as: “mild” (VS), “moderate” (MS), “severe” (SS), etc. The number of fuzzy states is ; Similarly, the fuzzy set of voltage sag duration can be defined as: short-term (ST), medium (MT), long-term (LT). The number of fuzzy states is ; The fuzzy set of voltage unbalance can be defined as: “low” (L), “medium” (M), “high” (H). The number of fuzzy states is ; The fuzzy set of voltage fluctuation amplitude can be defined as: “micro” (VM), “small” (SM), “large” (LM), “huge” (GM). The number representing its fuzzy state is then ; The fuzzy sets of the harmonic voltage THD can be defined as: "Good" (G), "Fair" (F), "Poor" (P), and The number representing its fuzzy state is then .

[0078] It should be noted that the fuzzy sets listed above are only examples, and the fuzzy states and the number of fuzzy states they contain do not constitute a limitation to the present invention. During actual implementation, they can be configured as fuzzy sets composed of other fuzzy states according to implementation needs.

[0079] Furthermore, the steps of aggregating and calculating the fuzzy rules in the fuzzy rule base using the fuzzy variable set to obtain the output fuzzy set specifically include: Dividing the fuzzy rules in the fuzzy rule base into corresponding rule subsets for each output variable, where the th rule subset contains fuzzy rules; Configuring a counting variable for traversing each fuzzy rule in each rule subset , for the th rule subset, is a positive integer between 1 and ; Calculating the rule strength of each fuzzy rule in each rule subset based on the fuzzy variable set ; Calculating each output variable of the output fuzzy set based on the rule strength of the fuzzy rules in each rule subset : .

[0080] Specifically, each rule subset is correspondingly associated with an output variable. For example, if the output fuzzy set can be defined as "Slight" (SL), "Moderate" (MOD), "Severe" (SEV), then the output variable set contains 3 output variables. In this embodiment, the fuzzy rules in the fuzzy rule base can be divided into three rule subsets, and using to represent the number of fuzzy rules in the fuzzy rule base, then the number of fuzzy rules in the fuzzy rule base and the number of fuzzy rules in each rule subset satisfy: .

[0081] Furthermore, calculating the rule strength of each fuzzy rule in each rule subset based on the fuzzy variable set The steps specifically include: Traverse each fuzzy rule in each rule subset; The first The first The fuzzy rules are determined as target rules; Determine the associated input variables of the target rule , association membership and the associated fuzzy state, the associated membership Enter the variable for the association The fuzzy variable value corresponding to the associated fuzzy state in the fuzzy variable set of 1 to A positive integer between the number of associated input variables in the target rule; Calculate the rule strength of the target rule: .

[0082] Furthermore, the step of executing the working mode decision according to the evaluation result of whether the AC input power supply is about to enter an abnormal power supply state specifically includes: Get the pre-configured comprehensive score The score range corresponding to each working mode; Determine the comprehensive score The working mode corresponding to the score interval that falls into; When the comprehensive score When the score range corresponding to the mains power supply mode is fallen, the first switch is controlled to enter the on state, and the second switch is controlled to enter the off state so that the intelligent power management device supplies power to the load through the mains input power supply.

[0083] Specifically, in the mains power supply mode, the intelligent power management device supplies power to the load through the mains input power supply, and the power output end of the intelligent power management device outputs the mains AC power to the load. Further, in the mains power supply mode, the control module periodically obtains the remaining power of the battery pack, and when the remaining power of the battery pack is less than a threshold, charges the battery pack through the mains input power supply.

[0084] Furthermore, in determining the comprehensive score After the step of determining the working mode corresponding to the score interval, the method further includes: When the comprehensive score When the score range corresponding to the battery inverter power supply mode is fallen into, the first switch is controlled to enter the disconnected state, and the second switch is controlled to enter the connected state so that the intelligent power management device supplies power to the load through the battery module.

[0085] Specifically, when the comprehensive score When it falls into the score interval corresponding to the battery inverter power supply mode, the AC input power supply may have the following situations in the future, such as the voltage sag depth exceeds the set threshold, the voltage imbalance seriously exceeds the standard, the voltage fluctuation amplitude is too large, or the harmonic voltage exceeds a certain limit. At this time, the first switching switch is controlled to enter the disconnected state, and the second switching switch is controlled to enter the connected state to enable the intelligent power management device to enter the battery inverter power supply mode, and the output voltage of the battery module is boosted in turn by the boost circuit, and after the inverter circuit is inverted, stable AC power is provided to the load, thereby avoiding the unstable state of the AC input power supply affecting the normal operation of the load or causing damage to it.

[0086] Furthermore, in determining the comprehensive score After the step of determining the working mode corresponding to the score interval, the method further includes: When the comprehensive score When falling into the score interval corresponding to the hybrid power supply mode, the first switching switch and the second switching switch are controlled to enter the on state, and the output voltage of the battery module is adjusted by the power conversion module to compensate for the supply voltage of the AC input power supply.

[0087] Specifically, in the hybrid power supply mode, for some minor power supply abnormalities, such as slight voltage fluctuations or low harmonic content, the intelligent power management device continues to supply power to the load through the mains input power supply, and at the same time controls the power conversion module to appropriately compensate and adjust the output voltage according to the power supply status data predicted in the future. For example, the inverter circuit outputs a certain reverse harmonic current to offset the harmonic components in the mains input power supply, or the output voltage of the boost circuit is adjusted to compensate for the voltage fluctuation of the mains input power supply.

[0088] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0089] According to the embodiments of the present invention as described above, these embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and changes can be made based on the above description. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can make good use of the present invention and the modified use based on the present invention. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. An intelligent power management device, characterized in that: It includes a power monitoring module for monitoring the state of the mains input power supply, a battery module for providing backup power supply capability, a power conversion module for providing power conversion capability, a switch module for switching the power supply mode, and a control module electrically connected to the power monitoring module, the battery module, the power conversion module, and the switch module. The control module is used to monitor the state of the mains input power supply through the power monitoring module, predict and evaluate the probability of abnormal conditions in the state of the mains input power supply, and control the battery module, the power conversion module, and the switch module to switch between a mains power supply mode, a battery inverter power supply mode, and a hybrid power supply mode according to the evaluation results.

2. The intelligent power management device according to claim 1, characterized in that: The battery module comprises a battery pack and a charging circuit, wherein the input end of the charging circuit is connected to a mains input power supply, and the output end is connected to the battery pack, and is used to charge the battery pack through the mains input power supply in a mains power supply mode; The switch module includes a first switch having one end connected to the mains input power supply and the other end connected to the output end of the intelligent power management device, and a second switch having one end connected to the power conversion module and the other end connected to the output end of the intelligent power management device; The output end of the battery module is connected to the input end of the power conversion module, and is used to supply power to the load after the battery voltage is boosted and inverted by the power conversion module; The power conversion module includes a boost circuit connected to the battery module and an inverter circuit connected to the second switching switch. When the second switching switch is turned on, the boost circuit boosts the battery voltage of the battery module and provides it to the subsequent inverter circuit. The inverter circuit converts the boosted voltage into a stable inverter voltage for output.

3. The intelligent power management device according to claim 1 or 2, characterized in that: The input end of the power monitoring module is connected to the mains input power supply, and is used to monitor the power state of the mains input power supply. The output end of the power monitoring module is connected to the control module, and is used to provide monitoring data to the control module. The control module is configured as follows: Obtain power status data of the mains input power supply; Inputting the power state data into a pre-trained power state prediction model to predict the power state data within a future period of time; Use the predicted power status data to assess whether the AC input power supply is about to enter an abnormal power status; An operating mode decision is executed based on an evaluation result of whether the AC input power supply is about to enter an abnormal power supply state, so as to control the battery module, the power conversion module and the switch module to switch between the AC power supply mode, the battery inverter power supply mode and the hybrid power supply mode according to the operating mode decision.

4. The intelligent power management device according to claim 3, characterized in that: In the step of evaluating whether the AC input power supply is about to enter an abnormal power supply state according to the predicted power supply state data, the control module is configured to: Based on the predicted power status data for a period of time in the future, the input variable set corresponding to each power abnormality state is extracted or calculated: ， in is the voltage sag depth, is the duration of voltage sag, is the voltage unbalance, is the voltage fluctuation amplitude, is the total harmonic voltage distortion rate; The fuzzy variable set corresponding to the input variable set is determined based on the membership function of each input variable: ， The fuzzy variable set is used to aggregate the fuzzy rules in the fuzzy rule base to obtain the output fuzzy set: ， in is the number of output variables in the output fuzzy set; Get the basic score corresponding to each output element in the output fuzzy set ; Calculate the comprehensive prediction score of abnormal power supply status in the future: ， in 1 to A positive integer between ; Based on the comprehensive prediction score of power supply abnormality in the future Determine whether the AC input power is about to enter an abnormal power state.

5. The intelligent power management device according to claim 4, characterized in that: In the step of determining the fuzzy variable set corresponding to the input variable set based on the membership function of each input variable, the control module is configured as follows: Configure a calculation variable with a value range of 1 to 5 for traversing the input variable set ; Traverse each input variable of the input variable set to calculate the input variable value as follows: Determine the currently traversed input variable as the target input variable; Configure the target input variable corresponding to Membership threshold ,in satisfy: ； use represents the fuzzy state number in the fuzzy set of the target input variable. A fuzzy state whose fuzzy variables satisfy: when hour: ; when hour: ； when hour: 。 6. The intelligent power management device according to claim 4, characterized in that: In the step of using the fuzzy variable set to aggregate and calculate the fuzzy rules in the fuzzy rule base to obtain an output fuzzy set, the control module is configured to: The fuzzy rules in the fuzzy rule base are divided into corresponding A subset of rules, of which The rule subset contains Fuzzy rules; Configure the counting variable used to traverse each fuzzy rule in each rule subset , for the A subset of rules, 1 to A positive integer between ; The rule strength of each fuzzy rule in each rule subset is calculated based on the fuzzy variable set. ; Rule strength based on fuzzy rules in each rule subset Calculate each output variable of the output fuzzy set: 。 7. The intelligent power management device according to claim 6, characterized in that: The rule strength of each fuzzy rule in each rule subset is calculated based on the fuzzy variable set. In the step, the control module is configured to: Traverse each fuzzy rule in each rule subset; The first The first The fuzzy rules are determined as target rules; Determine the associated input variables of the target rule , association membership and the associated fuzzy state, the associated membership Enter the variable for the association The fuzzy variable value corresponding to the associated fuzzy state in the fuzzy variable set of 1 to A positive integer between the number of associated input variables in the target rule; Calculate the rule strength of the target rule: 。 8. The intelligent power management device according to claim 4, characterized in that: In the step of executing the working mode decision according to the evaluation result of whether the mains input power supply is about to enter an abnormal power supply state, the control module is configured to: Get the pre-configured comprehensive score The score range corresponding to each working mode; Determine the comprehensive score The working mode corresponding to the score interval that falls into; When the comprehensive score When the score range corresponding to the mains power supply mode is fallen, the first switch is controlled to enter the on state, and the second switch is controlled to enter the off state so that the intelligent power management device supplies power to the load through the mains input power supply.

9. The intelligent power management device according to claim 8, characterized in that: In determining the composite score After the step of determining the working mode corresponding to the score interval, the control module is configured to: When the comprehensive score When the score range corresponding to the battery inverter power supply mode is fallen into, the first switch is controlled to enter the disconnected state, and the second switch is controlled to enter the connected state so that the intelligent power management device supplies power to the load through the battery module.

10. The intelligent power management device according to claim 8, characterized in that: In determining the composite score After the step of determining the working mode corresponding to the score interval, the control module is configured to: When the comprehensive score When falling into the score interval corresponding to the hybrid power supply mode, the first switching switch and the second switching switch are controlled to enter the on state, and the output voltage of the battery module is adjusted by the power conversion module to compensate for the supply voltage of the AC input power supply.

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