Emergency power supply box and power supply method thereof

Abstract

The present application relates to the technical field of power supply for emergency power supply boxes, and specifically to an emergency power supply box and a power supply method thereof, the method comprising: collecting historical and real-time power consumption data of different power consumption terminals connected to the emergency power supply box; segmenting the historical data of different power consumption terminals by date and dividing them into power consumption level characteristic intervals; analyzing the power demand characteristics of different power consumption level characteristic intervals within different date segments; matching the endpoints of all power consumption level characteristic intervals within any two date segments to analyze the regular characteristics of power demand at different power consumption terminals; and adjusting the power distribution of the emergency power supply box at different power consumption terminals in real time by combining the power demand characteristics, the regular characteristics of power demand, and the voltage and power data collected in real time from different power consumption terminals. The present application aims to adjust the power distribution of the emergency power supply box at different power consumption terminals in real time, and to improve the rationality of the power distribution of the emergency power supply box in actual applications.

Description

Technical Field

[0001] The present application relates to the technical field of power supply of emergency power supply boxes, and in particular to an emergency power supply box and a power supply method thereof. Background Art

[0002] An emergency power supply box is an integrated device designed for rapid access to emergency power. It is typically pre-installed in locations such as substations and key power user sites. It allows for rapid access to emergency power, shortens cable connection time, and improves emergency power supply efficiency. Its core functions include rapid access, intelligent control, electrical protection, and status display.

[0003] However, traditional emergency power supply boxes often lack dynamic priority control in actual applications. When facing power users with different power demands, they often implement a pre-power supply mode. For some power users with critical loads or sudden load fluctuations, it is difficult to adapt to complex and changeable power supply scenarios. In extreme cases, there is even a risk of critical load interruption due to unreasonable power distribution. Summary of the Invention

[0004] In order to solve the above technical problems, the present application provides an emergency power supply box and a power supply method thereof. The technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present application provides a method for powering an emergency power supply box, the method comprising the following steps:

[0006] S1, collects historical and real-time voltage and power data of different power consumption terminals connected to the emergency power supply box;

[0007] S2: Divide the historical data of different electricity users into date segments by day. Use the inflection points after curve fitting of the power data to divide multiple power consumption level characteristic intervals within different date segments. Use the average level of power data and the fluctuation characteristics of voltage data to analyze the power demand characteristics of different power consumption level characteristic intervals within different date segments.

[0008] S3: The endpoints of all power consumption level characteristic intervals within each date segment are combined into an endpoint sequence; the endpoint sequences of any two date segments are matched and the DTW matching distance is calculated, and the power deviation and voltage deviation differences between each date segment and all other date segments in the intervals where the corresponding endpoints match are forward-fused to analyze the power demand regularity characteristics of different power consumption terminals; wherein, the power deviation or voltage deviation is obtained by curve fitting all the power data or voltage data within the power consumption level characteristic interval, and the mean of the absolute difference between all the power data or voltage data within the power consumption level characteristic interval and the corresponding fitting curve is calculated, and the mean of the absolute difference is used as the power deviation or voltage deviation respectively;

[0009] S4, combining the electricity demand characteristics, electricity demand regularity characteristics, and voltage and power data collected in real time from different electricity consumption ends, adjusts the power distribution of the emergency power supply box at different electricity consumption ends in real time.

[0010] Preferably, the voltage or power data collected each time is the average value of all voltage or power data in a collection time interval before the corresponding collection moment.

[0011] Preferably, the electricity demand characteristics of different electricity level characteristic intervals in different date segments are obtained by forward fusion of the average level of power data and the fluctuation characteristics of voltage data in the application electricity level characteristic interval.

[0012] Preferably, the regular characteristic of the current electricity demand of the electricity user is recorded as R, and the calculation expression is:

[0013]

[0014] Where, Indicates the number of date segments of the current electricity user. Indicates the The average of the DTW matching distances between a date segment and all other date segments, Indicates the The number of intervals in a date segment that match the DTW of all other date segments, Indicates the The mean of the absolute difference in power deviation between the jth power consumption level characteristic interval in the date segment and the DTW-matched power consumption level characteristic intervals in all other date segments, Indicates the The mean of the absolute differences in voltage deviations between the jth power consumption level characteristic interval in the date segment and the power consumption level characteristic intervals matched by DTW in all other date segments.

[0015] Preferably, the power distribution of the emergency power supply box at different power consumption ends is adjusted in real time based on the power consumption demand characteristics, the power consumption demand regularity characteristics, and the voltage and power data collected in real time from different power consumption ends, including the following steps:

[0016] Combined with the current power demand characteristics and power demand regularity characteristics of the power consumption end, the power allocation weight of the current power consumption end is calculated, and the initial power allocation is performed on the current power consumption end based on this;

[0017] Analyze the access index of key equipment at the current power consumption end using the voltage and power data collected in real time at the current power consumption end;

[0018] The power distribution of the emergency power supply box at different power consumption ends is adjusted by using the key equipment access index and the allocated initial power at the current power consumption end.

[0019] Preferably, the analysis method of calculating the power allocation weight of the current power user terminal based on the power demand characteristics and power demand regularity characteristics of the current power user terminal and performing initial power allocation on the current power user terminal includes:

[0020] Calculate the mean value of the electricity demand characteristics in each date segment of the current electricity user; construct the electricity demand characteristic change curve of all date segments of the current electricity user, where the vertical axis is the mean value of the electricity demand characteristics and the horizontal axis is the date segment time series;

[0021] Calculate the derivative mean of all points on the current electricity demand characteristic change curve of the electricity consumption end, take its absolute value and normalize it, which is recorded as ;

[0022] The current electricity consumption characteristic weight factor The characteristics of electricity demand at the current electricity consumption end The result of the multiplication is normalized and used as the power allocation weight of the current power consumption end, which is recorded as ; Calculate the initial allocated power of the current power consumption end , ,in Indicates the maximum distributable power currently preset by the emergency power supply box.

[0023] Preferably, the method of analyzing the key device access index of the current power consumption end by using the voltage and power data collected in real time from the current power consumption end includes:

[0024] Calculate the derivatives of the current voltage and power data at each acquisition moment on their fitting curves;

[0025] Sort all the derivatives on the voltage fitting curve in ascending order, then calculate the difference between adjacent elements in the sequence, select the extreme value among all the differences in the sequence, and for each extreme value, select the minimum value of the voltage derivative between the two adjacent elements corresponding to the extreme value and the decreasing interval on the voltage signal fitting curve; calculate the voltage range of each decreasing interval on the voltage fitting curve, which is recorded as ;

[0026] Calculate the mean of the power fitting curve; select each power data that is less than the mean in the power data, and calculate the variance of the absolute difference between these power data and the mean, which is recorded as ;

[0027] The key equipment access index at the current electricity consumption end is recorded as , the calculation expression is:

[0028]

[0029] In the formula, norm represents the normalization function, Indicates the number of subtraction intervals selected on the voltage fitting curve, Indicates the The time series length of the decreasing interval, Indicates the voltage range of the xth decreasing interval.

[0030] Preferably, the method for adjusting the power distribution of the emergency power supply box at different power consumption ends by using the key equipment access index and the allocated initial power at the current power consumption end is:

[0031] If the difference between the key device access index at the power consumption end at the current moment and the key device access index at the previous moment is less than or equal to the preset dynamic adjustment judgment threshold, the power supply box will not be adjusted;

[0032] Otherwise, the power of the power box is readjusted by calculating the product of the key equipment access index of the current power consumption end and the initial power allocated to the current power consumption end as the power allocated to the current power consumption end.

[0033] In the second aspect, an embodiment of the present application also provides an emergency power supply box, the system including a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, it implements a power supply method for an emergency power supply box as described above.

[0034] This application has at least the following beneficial effects:

[0035] This application performs feature analysis on the power consumption data of different power consumption ends of the emergency power supply box, thereby extracting the power demand characteristics of different power consumption level characteristic intervals in different date segments, as well as the regular characteristics of power demand at the current power consumption end, and jointly calculates the initial power distribution of the current power consumption end. Combined with the real-time voltage and power data collected by the current power consumption end, the power distribution of the emergency power supply box at different power consumption ends is adjusted in real time, thereby improving the rationality of power distribution of the emergency power supply box in actual applications, adapting to complex and changeable power supply scenarios, and reducing the probability that key equipment may be damaged during the power distribution process. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0037] Figure 1 A flowchart of the steps of a power supply method for an emergency power supply box provided in one embodiment of the present application. DETAILED DESCRIPTION

[0038] To further illustrate the technical means and effectiveness employed by this application to achieve the intended invention objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail an emergency power supply box and its power supply method, including its specific implementation, structure, features, and effectiveness. In the following description, references to different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0039] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0040] The following describes in detail an emergency power supply box and a specific power supply method provided by the present application with reference to the accompanying drawings.

[0041] An embodiment of the present application provides an emergency power supply box and a power supply method thereof. For details, please refer to Figure 1 , the method comprises the following steps:

[0042] S1 collects historical and real-time voltage and power data of different power consumption terminals connected to the emergency power supply box.

[0043] To design a dynamic priority control method for the emergency power supply box, it is necessary to monitor the historical power consumption data of the power box at the power consumption end in real time, and analyze and evaluate the historical power consumption data of the power consumption end in combination with the historical power consumption data of the power consumption end, so as to adjust the power distribution of different power consumption ends in real time.

[0044] Accordingly, in this embodiment, a high-precision current transformer and voltage sensor are installed on the outgoing side of the emergency power supply box to obtain voltage and power data of each outgoing port of the emergency power supply box, with a sampling frequency of 50 Hz.

[0045] A smart meter is connected to the power-consuming end of the emergency power supply box to continuously collect power consumption data under normal power supply conditions. In this embodiment, when the power-consuming end is connected to the emergency power supply box, the historical power consumption data of each connected power-consuming end in the past year is obtained. The power consumption data includes voltage and power data. The collection frequency is once per hour, that is, data is collected once every hour. The voltage and power data collected each time are the average values ​​within one hour before the collection time.

[0046] The collected real-time electricity consumption data and historical electricity consumption data are transmitted to the data processing center for processing in the following steps.

[0047] S2: Divide the historical data of different electricity consumption terminals into date segments based on the number of days; use the inflection points after curve fitting of the power data to divide multiple electricity consumption level characteristic intervals within different date segments; use the average level of power data and the fluctuation characteristics of voltage data to analyze the electricity demand characteristics of different electricity consumption level characteristic intervals within different date segments.

[0048] To allocate power to each consumer connected to the emergency power supply box, it is necessary to analyze the historical power demand of each consumer. It is important to note that in most cases, power demand varies over time. Therefore, when analyzing the historical power consumption characteristics of each consumer, it is necessary to first segment the historical data.

[0049] Electricity demand is significantly correlated with the time period, manifesting itself in different electricity consumption patterns across different timescales. Since emergency power supply periods are typically relatively short, and daily electricity consumption characteristics vary across weather and seasons, it's necessary to segment historical data from different electricity users by date based on daily power consumption variations. This historical data is then divided into hourly intervals, whereby these historical power consumption characteristics can be captured through power data.

[0050] a. Divide the historical data of different electricity users into date segments based on the number of days.

[0051] As an implementation method, the Pearson correlation coefficient between the power sequence of each day of the historical data of the current electricity consumption end and the power sequence of the next day is calculated as the electricity consumption change parameter; for the last day of the historical data, it is grouped with the penultimate day; wherein, the power sequence is obtained by sorting the power data of each day in history in chronological order from the front to the back.

[0052] Arrange the daily electricity consumption change parameters into a sequence in ascending order, and calculate the difference between adjacent elements in the sequence; select all pairs of adjacent elements whose difference is an extreme value. For two adjacent elements with one difference being an extreme value, select the date corresponding to the element in front as the breakpoint. In this way, multiple breakpoints can be obtained. Use multiple breakpoints to divide the history of the current electricity consumption end into dates in units of days to obtain multiple date segments.

[0053] The correlation coefficient reflects the changes in daily electricity consumption characteristics. When a landmark electricity consumption event occurs, such as starting to use air conditioning or adjusting work and rest schedules on a certain day, the electricity consumption characteristics will change significantly compared with the previous day. At this time, the correlation coefficient of the electricity consumption data of the two days is small, and the difference between it and the correlation coefficient of the previous days is large.

[0054] In other embodiments, other methods may be used to segment the historical data in different power consumption terminals into days, for example, by calculating the average power data for each day and selecting the date corresponding to the maximum value as the breakpoint for date segmentation.

[0055] b. Use the inflection points of the power data after curve fitting to divide multiple power consumption level characteristic intervals within different date segments.

[0056] For all power data in the current date segment, the least square method is used to perform curve fitting to obtain the power fitting curve of the current date segment;

[0057] Obtain the inflection point of the power fitting curve and segment the curve according to the position of the inflection point to obtain several power consumption level characteristic intervals. Each power consumption level characteristic interval will have several consecutive hours. All power consumption data in the current date segment are distinguished by the power consumption level characteristic interval.

[0058] The purpose of using inflection points to segment electricity consumption data is to segment time by the change in the power consumption trend, so as to obtain the difference in electricity consumption trends every day and better reflect the characteristics of electricity consumption levels.

[0059] c. Using the average level of power data and the fluctuation characteristics of voltage data, analyze the electricity demand characteristics of different electricity consumption level characteristic intervals within different date segments.

[0060] The electricity demand level first needs to be analyzed through historical power data of different electricity consumption level characteristic intervals: the power data within the interval directly reflects the electricity consumption information during this period. The larger the power data, the higher the electricity consumption in the current time.

[0061] The fluctuation characteristics of voltage data can also reflect the compliance of the power consumption end in the current range: when the voltage curve is relatively smooth, it means that the power demand of the power consumption end is relatively stable and the load is relatively balanced; when the voltage fluctuates to a certain extent, it means that the load fluctuates greatly in the current period, there are large load changes in a short period of time, and the power demand is relatively higher.

[0062] In addition, electricity demand is an overall characteristic within a time period or interval, but the actual electricity consumption process at the end of the electricity consumption may have various special circumstances. In order to reduce the impact of such special circumstances on the overall characteristics, it is necessary to consider the deviation of electricity consumption data on different dates within the same date segment during the analysis process.

[0063] Accordingly, in this application, as a preferred embodiment, the electricity demand characteristics of any electricity level characteristic interval in any date segment are obtained by forward fusion of the average level of power data and the fluctuation characteristics of voltage data in the application electricity level characteristic interval.

[0064] It can be understood that fusion can be divided into forward fusion and reverse fusion. This embodiment adopts the forward fusion method. Forward fusion is a fusion method such as addition and multiplication between data. The specific forward fusion method is determined by the implementer according to the actual situation. The application does not impose any special restrictions.

[0065] In other implementations, it is also possible to calculate the power deviation and voltage deviation within the application power level characteristic interval and correct the average level of power data and the fluctuation characteristics of voltage data respectively.

[0066] In this embodiment, for the current date segment, the number of days j in the current date segment is calculated. The power mean of the characteristic interval of electricity consumption level is recorded as ; Calculate the current date segment, the jth day in the The variance of the voltage difference at all adjacent sampling moments within the power consumption level characteristic interval is recorded as ; Calculate the current date segment, the jth day in the The power deviation and voltage deviation of the power consumption level characteristic interval are respectively recorded as , .

[0067] in, , The calculation method of this embodiment is as follows: for all voltage data in the current date segment, the least square method is used to perform curve fitting to obtain the voltage fitting curve of the current segment; the voltage of the jth day in the current date segment is calculated. The voltage and power at each collection moment in the electricity consumption level characteristic interval are calculated with the corresponding position on the fitting curve; the ... The absolute differences of power and voltage calculated at all sampling moments within the power consumption level characteristic interval are normalized and averaged respectively, which are used as the average values ​​of the jth day in the current date segment. The power deviation and voltage deviation of each power consumption level characteristic interval.

[0068] Using the above analysis, calculate the first Electricity demand characteristics of electricity consumption level characteristic intervals :

[0069]

[0070] Where, Indicates the The number of dates in the electricity consumption level characteristic interval, Indicates that the jth day in the current date segment is in the The power mean of the characteristic interval of electricity consumption level, Indicates that the jth day in the current date segment is in the The variance of the voltage difference at all adjacent sampling moments within a power consumption level characteristic interval, 、 Respectively represent the jth day in the current date segment The power deviation and voltage deviation of each power consumption level characteristic interval.

[0071] Adjust the voltage and power characteristics in the historical data through power deviation and voltage deviation to reduce the impact of special cases on the The impact of the overall electricity demand characteristics of each electricity consumption level characteristic interval. Indicates the current date segment The electricity demand characteristics of the electricity consumption level characteristic interval.

[0072] S3: The endpoints of all electricity consumption level feature intervals within each date segment are combined into an endpoint sequence. The endpoint sequences of any two date segments are matched and the DTW matching distance is calculated. The power deviation and voltage deviation differences between each date segment and all other date segments in the corresponding endpoint matching intervals are forward fused to analyze the electricity demand characteristics of different electricity users.

[0073] Typically, historical electricity consumption data usually has obvious regularity, which is mainly reflected in the periodicity of the time dimension and the patterning of load characteristics. In this application, the time dimension of the electricity consumption cycle of historical electricity consumption data is mainly determined by date segments.

[0074] Date segments are divided based on the impact of wide-ranging factors like weather and season on electricity consumption data. Within each date segment, electricity consumption characteristic intervals are further differentiated based on the impact of daily hourly user electricity usage activity on electricity consumption data. Due to the uncontrollability of external factors, the primary purpose of evaluating electricity demand regularity should be to focus on electricity data that reflects user electricity usage activity. Therefore, the regularity of electricity demand can be assessed by comparing electricity consumption characteristics on different days within different date segments.

[0075] Accordingly, in this application, as a preferred implementation method, the endpoints of all electricity consumption level feature intervals in each date segment are obtained and formed into an endpoint sequence in order of size; the endpoint sequences of any two date segments are matched and the DTW matching distance is calculated, and the differences in power deviation and voltage deviation between each date segment and all other date segments in the corresponding endpoint matching intervals are forwardly fused to determine the regular characteristics of electricity demand at the current electricity consumption end.

[0076] In this embodiment, the endpoint sequences of the power consumption level characteristic intervals of two date segments are obtained respectively, which are recorded as A and B respectively; for example, the power consumption level characteristic interval of a certain date segment is , where each number represents the collection time in a day, in hours, then the endpoint sequence of the electricity consumption level characteristic interval of the date segment is .

[0077] Furthermore, the DTW matching distance is calculated for the endpoint sequences of the two date segments as the time series difference of the user's electricity usage activity. The DTW matching distance is calculated by applying the DTW algorithm to the two sequences. All power consumption feature intervals within the two date segments are matched to their endpoints using the DTW algorithm. All power consumption feature intervals between the date segments are then matched one-to-one, and the corresponding power consumption feature intervals are used as DTW matching intervals.

[0078] Furthermore, based on the above analysis, the current electricity demand characteristics of the electricity user are calculated. :

[0079]

[0080] Where, Indicates the number of date segments of the current electricity user. Indicates the The average of the DTW matching distances between a date segment and all other date segments, Indicates the The number of intervals in a date segment that match the DTW of all other date segments, Indicates the The mean of the absolute difference in power deviation between the jth power consumption level characteristic interval in the date segment and the DTW-matched power consumption level characteristic intervals in all other date segments, Indicates the The mean of the absolute differences in voltage deviations between the jth power consumption level characteristic interval in the date segment and the power consumption level characteristic intervals matched by DTW in all other date segments.

[0081] It should be noted that Can be used to characterize the The difference between the time concentration characteristics of user electricity consumption activities in the date segment and all other date segments within the date segment is The similarity of the overall characteristic deviation of the user's electricity consumption activities on a daily basis and in the date segment is further subdivided; Characterizes the regular characteristics of electricity demand at the current electricity consumption end. The larger the value, the more similar the characteristics of electricity consumption activities of users at the electricity consumption end are in time series, that is, the more obvious the regularity of electricity demand is.

[0082] S4, combining the electricity demand characteristics, electricity demand regularity characteristics, and voltage and power data collected in real time from different electricity consumption ends, adjusts the power distribution of the emergency power supply box at different electricity consumption ends in real time.

[0083] After obtaining the power demand characteristics and power demand pattern characteristics of different power users, initial power allocation can be performed on the power users connected to the emergency power supply box. In the initial power allocation, higher power is allocated to power users with higher power demand. The more obvious the power demand pattern is, the more accurate the initial power allocation based on the power demand characteristics will be. The less obvious the power demand pattern is, the less clear the initial power allocation will be based on the power demand characteristics, and further adjustments will be required based on actual power consumption. Therefore, initial power allocation should prioritize power users with obvious power demand patterns.

[0084] Based on this, the present application combines the power demand characteristics and power demand regularity characteristics of the current power user to calculate the power allocation weight of the current power user, and uses this to perform initial power allocation on the current power user.

[0085] This embodiment first calculates the mean value of the power demand characteristics of the current power user in each date segment; constructs the power demand characteristic change curve of all date segments of the current power user, where the vertical axis is the mean value of the power demand characteristics and the horizontal axis is the date segment time series; calculates the derivative mean of all points on the power demand characteristic change curve of the current power user, and uses the tanh function to take the absolute value of the value to set its value range The interval is recorded as , used to assess the development of historical electricity consumption levels at the current electricity consumption end.

[0086] It should be understood that The larger it is, the larger the numerical value of the mean of its derivatives before using the tanh function, that is, the more likely the derivatives of all points on the current electricity demand characteristic change curve have the same sign, which means that the change trend of all points on the current electricity demand characteristic change curve has certain development regularity characteristics, indicating that the electricity demand at the current electricity consumption end has a certain change and development trend, and the reference value of the electricity demand characteristic reference segment to which the same historical date belongs to the current electricity consumption end power is lower.

[0087] The current electricity consumption characteristic weight factor The characteristics of electricity demand at the current electricity consumption end After multiplication, the product of all power consumption ends is normalized using the range normalization method to express the power allocation weight of each power consumption end, which is recorded as ; Calculate the initial allocated power of the current power consumption end , ,in Indicates the maximum distributable power currently preset by the emergency power supply box.

[0088] Furthermore, during the actual power allocation process, it is necessary to adjust the power allocation results by analyzing the key devices that may be present at the power consumption end. High-power devices consume a lot of electricity and are relatively expensive to use, meaning that they are generally more valuable to the user. Furthermore, in the case of emergency power supply, key devices for users include not only high-power devices but also devices that require stable and continuous operation.

[0089] High-power equipment usually requires a large starting current. When a high-power device is connected to the power consumption end, a large amount of current will be drawn from the power grid at the power consumption end in a short period of time, which can easily cause a momentary voltage drop. When there are key equipment that operates stably and continuously at the power consumption end, in order to ensure the stable operation of the key equipment, the power data will usually be relatively stable and not lower than the operating power of the key equipment to ensure the normal operation of the stable operating equipment.

[0090] Based on this, this application uses the voltage and power data collected in real time at the current power consumption end to analyze the key equipment access index at the current power consumption end.

[0091] In this embodiment, the least squares method is used to construct a fitting curve of the voltage and power data of the outlet port corresponding to the current power consumption end, where the horizontal axis represents time and the vertical axis represents voltage or power data; the derivative of the fitting curve of the current voltage and power data at each collection moment is calculated.

[0092] Sort all the derivatives on the voltage fitting curve in ascending order, then calculate the difference between adjacent elements in the sequence, select the extreme value among all the differences in the sequence, and for each extreme value, select the minimum value of the voltage derivative between the two adjacent elements corresponding to the extreme value in the calculated difference, and place it in the decreasing interval on the voltage signal fitting curve. It should be noted that if the position of the voltage derivative does not belong to the decreasing interval of the fitting curve, the point will be discarded. Calculate the voltage range of each decreasing interval on the voltage fitting curve, which is recorded as .

[0093] Calculate the mean of the power fitting curve; select each power data that is less than the mean in the power data, and calculate the variance of the absolute difference between these power data and the mean, which is recorded as .

[0094] Based on this, calculate the key equipment access index of the current electricity consumption end :

[0095]

[0096] In the formula, norm represents the normalization function, Indicates the number of subtraction intervals selected on the voltage fitting curve, Indicates the The time series length of the decreasing interval, Indicates the voltage range of the xth decreasing interval.

[0097] It should be understood that By adjusting the time series length of the reduction interval After the logic relationship of the voltage instantaneous drop evaluation process, the actual reduction degree of the voltage in the reduction interval Combined, indicating The instantaneous voltage drop in each reduction interval is used as an evaluation indicator for the connection of high-power electrical appliances to the power consumption end; It can be used to characterize the stability of the lower power during the power supply period of the emergency power supply box. The smaller the value, the better the stability of the lower power during the power supply period of the emergency power supply box. The probability of the existence of key equipment with stable operation at the power consumption end is higher. During dynamic allocation, it is necessary to ensure that the power allocated to this port is maintained at a certain level.

[0098] Furthermore, in this application, the power distribution of the emergency power supply box at different power consumption ends is adjusted by using the key equipment access index and the allocated initial power at the current power consumption end. The specific method is as follows:

[0099] Preset a dynamically adjusted judgment threshold , this embodiment takes its value , starting from the second moment when the current power consumption terminal is connected to the power box, when the difference between the key equipment access index of the power consumption terminal at the current moment and the key equipment access index of the previous moment is less than or equal to the dynamic adjustment judgment threshold When the power consumption terminal is not affected by the existence of critical load or sudden load fluctuation, the power supply box will not be adjusted; on the contrary, when the difference between the key equipment access index of the power consumption terminal at the current moment and the key equipment access index of the previous moment is greater than the dynamic adjustment judgment threshold When the power supply is affected by the power consumption end with critical load or sudden load fluctuation, the power of the power box is readjusted. The readjustment method is: calculate the product of the key equipment access index of the current power consumption end and the initial power allocated to the current power consumption end, and use it as the power allocated to the current power consumption end.

[0100] Based on the same inventive concept as the above method, an embodiment of the present application also provides an emergency power supply box, the system including a memory, a processor, and a computer program stored in the memory and running on the processor, and when the processor executes the computer program, it implements any one of the above-mentioned power supply methods for the emergency power supply box.

[0101] The various embodiments in this application are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0102] It should be noted that, unless otherwise specified and limited, terms such as "include", "comprising" or any other variations thereof are intended to cover non-exclusive inclusion, so that a circuit structure, 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 article or device. In the absence of further restrictions, the phrase "including a ..." defines an element, does not exclude the presence of other identical elements in the article or device including the element. In addition, the term "and\or" used herein includes any and all combinations of one or more related listed items.

[0103] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention herein. This application is intended to cover any variations, uses, or adaptations of the present application that follow the general principles of the present application and include common knowledge or customary techniques in the art not invented herein.

[0104] It will be understood that the present application is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof.

Claims

1. A power supply method for an emergency power supply box, characterized in that: The method comprises the following steps: S1, collects historical and real-time voltage and power data of different power consumption terminals connected to the emergency power supply box; S2: Divide the historical data of different electricity users into date segments by day. Use the inflection points after curve fitting of the power data to divide multiple power consumption level characteristic intervals within different date segments. Use the average level of power data and the fluctuation characteristics of voltage data to analyze the power demand characteristics of different power consumption level characteristic intervals within different date segments. S3: The endpoints of all power consumption level characteristic intervals within each date segment are combined into an endpoint sequence; the endpoint sequences of any two date segments are matched and the DTW matching distance is calculated, and the power deviation and voltage deviation differences between each date segment and all other date segments in the intervals where the corresponding endpoints match are forward-fused to analyze the power demand regularity characteristics of different power consumption ends; wherein, the power deviation and voltage deviation are respectively obtained by curve fitting all the power data and voltage data within the power consumption level characteristic interval, and the mean of the absolute differences between all the power data and voltage data within the power consumption level characteristic interval and the corresponding fitting values ​​on the fitting curve of the corresponding types of data are calculated, and are used as the power deviation and voltage deviation respectively; S4, combining the electricity demand characteristics, electricity demand regularity characteristics, and voltage and power data collected in real time from different electricity consumption ends, adjusts the power distribution of the emergency power supply box at different electricity consumption ends in real time.

2. A power supply method for an emergency power supply box according to claim 1, characterized in that: The voltage or power data collected each time is the average value of all voltage or power data in a collection time interval before the corresponding collection moment.

3. The power supply method of the emergency power supply box according to claim 1, characterized in that: The electricity demand characteristics of different electricity level characteristic intervals in the different date segments are obtained by forward fusion of the average level of power data and the fluctuation characteristics of voltage data in the application level characteristic interval.

4. The power supply method of the emergency power supply box according to claim 1, characterized in that: The regular characteristics of the current electricity demand at the electricity consumption end are recorded as R, and the calculation expression is: Where, K represents the number of date segments of the current electricity user, D k represents the mean of the DTW matching distances between the kth date segment and all other date segments, U k Indicates the number of intervals in the kth date segment that match the DTW of all other date segments. represents the mean of the absolute differences in power deviations between the jth power consumption feature interval in the kth date segment and the DTW-matched power consumption feature intervals in all other date segments. It represents the mean of the absolute differences in voltage deviations between the jth power consumption feature interval in the kth date segment and the DTW-matched power consumption feature intervals in all other date segments.

5. The power supply method of the emergency power supply box according to claim 1, characterized in that: The power distribution of the emergency power supply box at different power consumption ends is adjusted in real time based on the power consumption demand characteristics, power consumption regularity characteristics, and voltage and power data collected in real time from different power consumption ends, including the following steps: Combined with the current power demand characteristics and power demand regularity characteristics of the power consumption end, the power allocation weight of the current power consumption end is calculated, and the initial power allocation is performed on the current power consumption end based on this; Analyze the access index of key equipment at the current power consumption end using the voltage and power data collected in real time at the current power consumption end; The power distribution of the emergency power supply box at different power consumption ends is adjusted by using the key equipment access index and the allocated initial power at the current power consumption end.

6. A power supply method for an emergency power supply box according to claim 5, characterized in that: The analysis method of calculating the power allocation weight of the current power user terminal by combining the power demand characteristics and the power demand regularity characteristics of the current power user terminal and performing initial power allocation on the current power user terminal based on the weight includes: Calculate the mean value of the electricity demand characteristics in each date segment of the current electricity user; construct the electricity demand characteristic change curve of all date segments of the current electricity user, where the vertical axis is the mean value of the electricity demand characteristics and the horizontal axis is the date segment time series; Calculate the derivative mean of all points on the current electricity demand characteristic change curve of the electricity consumption end, take its absolute value and normalize it, which is recorded as The current electricity consumption characteristic weight factor The result of multiplying the power demand regularity characteristic R of the current power consumption end is normalized and used as the power allocation weight of the current power consumption end, which is recorded as Calculate the initial allocated power of the current power consumption end Where W max Indicates the maximum distributable power currently preset by the emergency power supply box.

7. A power supply method for an emergency power supply box according to claim 5, characterized in that: The method for analyzing the key device access index of the current power consumption end by using the voltage and power data collected in real time at the current power consumption end includes: Calculate the derivatives of the current voltage and power data at each acquisition moment on their fitting curves; Sort all the derivatives on the voltage fitting curve in ascending order, then calculate the difference between adjacent elements in the sequence, select the extreme value among all the differences in the sequence, and for each extreme value, select the decreasing interval on the voltage signal fitting curve where the voltage derivative has the smallest value between the two adjacent elements corresponding to the extreme value. Calculate the voltage range of each decreasing interval on the voltage fitting curve, recorded as ΔU. Calculate the mean of all fitted values ​​corresponding to the power data on the power fitting curve; select each power data that is less than the mean in the power data, and calculate the variance of the absolute difference between these power data and the mean, which is recorded as The key equipment access index at the current power consumption end is recorded as A, and the calculation expression is: Where norm represents the normalization function, Y represents the number of reduction intervals selected on the voltage fitting curve, and t x Indicates the time series length of the xth decreasing interval, ΔU x Indicates the voltage range of the xth decreasing interval.

8. The power supply method for an emergency power supply box according to claim 5, characterized in that: The method for adjusting the power distribution of the emergency power supply box at different power consumption ends by using the key equipment access index and the allocated initial power at the current power consumption end is as follows: If the difference between the key device access index at the power consumption end at the current moment and the key device access index at the previous moment is less than or equal to the preset dynamic adjustment judgment threshold, the power supply box will not be adjusted; Otherwise, the power of the power box is readjusted by calculating the product of the key equipment access index of the current power consumption end and the initial power allocated to the current power consumption end as the power allocated to the current power consumption end.

9. An emergency power supply box, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the power supply method for the emergency power supply box according to any one of claims 1 to 8 is implemented.

Images