Emergency power protection power box and power supply method thereof

Abstract

The invention relates to the technical field of power supply of emergency power guarantee power boxes, in particular to an emergency power guarantee power box and a power supply method thereof, and the method comprises the steps: collecting historical and real-time power utilization data of different power utilization ends connected to the emergency power guarantee power box; performing date segmentation on historical data of different power consumption terminals and dividing power consumption level characteristic intervals; analyzing power consumption demand characteristics of different power consumption level characteristic intervals in different date segments; matching end points of all the power utilization level characteristic intervals in any two date segments to analyze power utilization demand rule characteristics of different power utilization ends; the power distribution conditions of the emergency power supply box at different power utilization ends are adjusted in real time by combining the power utilization demand characteristics, the power utilization demand rule characteristics and the voltage and power data collected by the different power utilization ends in real time. According to the invention, the power distribution conditions of the emergency power supply box at different power utilization ends are adjusted in real time, and the reasonability of power distribution of the emergency power supply box in practical application is improved.

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] The emergency power supply box is an integrated device designed for rapid access to emergency power supply. It is usually pre-installed in substations, important power user sites and other places. It is used to quickly access emergency power supply, shorten cable connection time, and improve 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 faced with 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, and the technical solutions adopted are as follows: In a first aspect, an embodiment of the present application provides a power supply method for an emergency power supply box, the method comprising 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 power consumption ends into date segments in units of days; use the inflection points after curve fitting of power data to divide multiple power consumption level characteristic intervals in 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 in different date segments; S3, the endpoints of all power consumption level characteristic intervals in 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 forwardly integrated to analyze the power demand regularity characteristics of different power consumption ends; wherein, the power deviation or voltage deviation is obtained by curve fitting all the power data or voltage data in the power consumption level characteristic interval, and the mean of the absolute difference between all the power data or voltage data in the power consumption level characteristic interval and the corresponding fitting curve is calculated, which is used as the power deviation or voltage deviation respectively; S4, combining the electricity demand characteristics, the regular characteristics of electricity demand, and the 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.

[0005] 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.

[0006] Preferably, the electricity demand characteristics of different electricity consumption 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 electricity level characteristic interval.

[0007] Preferably, the regular characteristic of the current power demand of the power consumption terminal is recorded as R, and the calculation expression is: In the formula, Indicates the number of date segments of the current electricity user. Indicates The average DTW matching distance between a date segment and all other date segments, Indicates The number of intervals in a date segment that match the DTW of all other date segments, Indicates The mean of the absolute differences in power deviation between the jth power consumption feature interval in the date segment and the DTW-matched power consumption feature intervals in all other date segments, Indicates The mean of the absolute differences in voltage deviation between the jth power consumption level characteristic interval in a date segment and the power consumption level characteristic intervals matched by DTW in all other date segments.

[0008] Preferably, the power distribution of the emergency power supply box at different power consumption ends is adjusted in real time by combining 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, and the steps include: Combined with the power demand characteristics and power demand law characteristics of the current power user, the power allocation weight of the current power user is calculated, and the initial power allocation is performed on the current power user based on this; Analyze the key equipment 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; The power distribution of the emergency power supply box at different power consumption ends is adjusted by using the key equipment access index at the current power consumption end and the allocated initial power.

[0009] Preferably, 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 includes: Calculate the mean value of the power demand characteristics in each date segment of the current power consumption end; construct a power demand characteristic change curve for all date segments of the current power consumption end, where the vertical axis is the mean value of the power demand characteristics and the horizontal axis is the date segment time series; Calculate the derivative mean of all points on the current power demand characteristic change curve of the power consumption end, take its absolute value and normalize it, which is recorded as ; The current power consumption characteristic weight factor The characteristics of the current electricity demand at the power 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 preset by the current emergency power supply box.

[0010] Preferably, the method of analyzing the key equipment 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; All the derivatives on the voltage fitting curve are sorted in ascending order, and then the differences between adjacent elements in the sequence are calculated, and the extreme values ​​among all the differences in the sequence are selected. For each extreme value, the minimum value of the voltage derivative between the two adjacent elements corresponding to the extreme value is selected on the voltage signal fitting curve. The voltage range of each decreasing interval on the voltage fitting curve is calculated, which is recorded as ; 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, recorded as ; The key equipment access index of the current power consumption end is recorded as , the calculation expression is: In the formula, norm represents the normalization function, Indicates the number of reduction intervals selected on the voltage fitting curve, Indicates The time length of the reduction interval, Indicates the voltage range of the xth decreasing interval.

[0011] 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: When the difference between the key equipment access index at the power consumption end at the current moment and the key equipment access index at the previous moment is less than or equal to the preset dynamic adjustment judgment threshold, the power of the power supply box is not 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.

[0012] In the second aspect, an embodiment of the present application also provides an emergency power supply box, the system includes 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.

[0013] This application has at least the following beneficial effects: The present 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 allocation of the current power consumption end. Combined with the real-time voltage and power data collected at 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 allocation of the emergency power supply box in actual applications, so as to adapt to complex and changeable power supply scenarios and reduce the probability that key equipment may be damaged during the power distribution process. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0015] 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

[0016] In order to further explain the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following is a detailed description of an emergency power supply box and its power supply method proposed in accordance with the present application, its specific implementation method, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0017] 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.

[0018] The following is a detailed description of an emergency power supply box and a specific power supply method provided by the present application in conjunction with the accompanying drawings.

[0019] 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: S1, collects historical and real-time voltage and power data of different power consumption terminals connected to the emergency power supply box.

[0020] 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, so as to adjust the power distribution of different power consumption ends in real time.

[0021] Accordingly, in this embodiment, a high-precision current transformer and a voltage sensor are installed on the outgoing side of the emergency power supply box to obtain the voltage and power data of each outgoing port of the emergency power supply box, with a sampling frequency of 50 Hz.

[0022] A smart meter is connected to the power consumption end of the emergency power supply box to continuously collect power consumption data under normal power supply conditions. In this embodiment, when the power consumption end is connected to the emergency power supply box, the historical power consumption data of each connected power consumption 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 1 hour. The voltage and power data collected each time are the average values ​​within one hour before the collection time.

[0023] The collected real-time power consumption data and historical power consumption data are transmitted to the data processing center for processing in the following steps.

[0024] S2, divide the historical data of different electricity consumption ends into date segments in units of days; use the inflection points after curve fitting of power data to divide multiple electricity consumption level characteristic intervals in 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 in different date segments.

[0025] To allocate power to each power terminal connected to the emergency power supply box, it is necessary to analyze the historical power demand of each power terminal. It should be noted that in most cases, there are usually some differences in power demand in different periods, so when analyzing the historical power consumption characteristics of each power terminal, it is necessary to first segment the historical data.

[0026] There is a significant correlation between electricity demand and the time stage, which is manifested in the difference in electricity consumption patterns at different time scales. Since emergency power supply time is usually relatively short, and the daily electricity consumption characteristics vary under different weather and seasonal conditions, it is necessary to segment the historical data of different electricity users by date based on the daily electricity consumption level change characteristics, and then divide the historical electricity consumption data characteristics into electricity consumption level characteristic intervals in hours, where the historical electricity consumption level characteristics can be reflected through power data.

[0027] a. Divide the historical data of different electricity users into date segments based on days.

[0028] As an implementation method, the Pearson correlation coefficient between the power sequence of each day of the historical data of the current power consumption end and the power sequence of the next day is calculated as a power consumption change parameter; for the last day in the historical data, it is grouped together with the penultimate day; wherein the power sequence is obtained by sorting the power data of each day in history in chronological order from front to back.

[0029] 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, and for two adjacent elements whose difference is an extreme value, select the date corresponding to the element in front as the breakpoint, thereby obtaining multiple breakpoints, and use multiple breakpoints to divide the history of the current electricity consumption end into dates in units of days to obtain multiple date segments.

[0030] The correlation coefficient is used to reflect 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 for the two days is small, and the correlation coefficient between it and the previous days is quite different.

[0031] In other implementations, other methods may be used to segment the historical data in different power consumption terminals by days, for example, by calculating the average of the daily power data and selecting the date corresponding to the maximum value as the breakpoint for date segmentation.

[0032] b. Use the inflection points after curve fitting based on power data to divide multiple characteristic intervals of electricity consumption levels within different date segments.

[0033] 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; The inflection point of the power fitting curve is obtained, and the curve is segmented 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.

[0034] The purpose of using inflection points to segment electricity consumption data is to segment time according to the change in the trend of electricity power consumption, so as to obtain the difference in electricity consumption trends every day and better reflect the characteristics of electricity consumption levels.

[0035] c. Analyze the electricity demand characteristics of different electricity consumption level characteristic intervals in different date segments by using the average level of power data and the fluctuation characteristics of voltage data.

[0036] The electricity demand level first needs to be analyzed through historical power data in 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.

[0037] 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 stable, 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 is a large load change in a short period of time, and the power demand is relatively higher.

[0038] In addition, electricity demand is an overall characteristic within a time period or interval, but there may be various special circumstances in the actual electricity consumption process. 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 in the same date segment during the analysis process.

[0039] Accordingly, in the present application, as a preferred implementation, 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 within the application electricity level characteristic interval.

[0040] 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.

[0041] In other implementations, it is also possible to consider calculating the power deviation and voltage deviation within the application power level characteristic interval, and respectively correcting the average level of power data and the fluctuation characteristics of voltage data.

[0042] In this embodiment, for the current date segment, the number of days in the current date segment is calculated. The power mean of the characteristic interval of power consumption level is recorded as ; Calculate the current date segment, the jth day in the The variance of the voltage difference at all adjacent collection times 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 , .

[0043] in, , The calculation method of in 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 fitting curve of the jth day in the current date segment is calculated. The voltage and power at each collection moment in the power 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 collection times within the power consumption level characteristic interval are normalized and averaged respectively, and 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.

[0044] Using the above analysis, calculate the first Electricity demand characteristics of electricity consumption level characteristic intervals : In the formula, Indicates The number of dates in the electricity consumption level characteristic interval, Indicates that the jth day in the current date segment is in The power mean value of the characteristic interval of power consumption level, Indicates that the jth day in the current date segment is in The variance of the voltage difference at all adjacent collection times within the 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.

[0045] The voltage and power characteristics in the historical data are adjusted through power deviation and voltage deviation to reduce the impact of special circumstances on the The impact of the overall electricity demand characteristics in the electricity consumption level characteristic interval. Indicates the current date segment The electricity demand characteristics of the electricity consumption level characteristic interval.

[0046] S3, the endpoints of all power consumption level characteristic intervals in 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 corresponding endpoint matching intervals are forward fused to analyze the power demand regularity characteristics of different power consumption ends.

[0047] Generally, 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 the historical electricity consumption data is mainly determined by date segmentation.

[0048] Date segmentation is based on the impact of weather, seasons and other factors with a large span on electricity consumption data, while the electricity consumption level characteristic interval is a level of further distinction based on the impact of user electricity consumption activities on electricity consumption data in hours per day within each date segment. Among them, due to the uncontrollability of external factors, the main purpose of evaluating the regularity of electricity demand should focus on electricity data that can reflect user electricity consumption activities. Therefore, the regularity of electricity demand can be evaluated by comparing the electricity consumption characteristics of different dates between different date segments.

[0049] Accordingly, in the present application, as a preferred implementation, the endpoints of all power consumption level characteristic 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 power deviation and voltage deviation differences between each date segment and all other date segments in the corresponding endpoint matching intervals are forwardly fused to determine the regular characteristics of power demand at the current power consumption end.

[0050] 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 characteristic interval of the power consumption level of the date segment is .

[0051] 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. Among them, the DTW matching distance is calculated by using the DTW algorithm on the two sequences. All the power consumption level feature intervals in the two date segments are matched according to the endpoints after the DTW algorithm, and all the power consumption level feature intervals between the date segments are matched one by one, and the one-to-one corresponding power consumption level feature intervals are used as the DTW matching intervals.

[0052] Furthermore, based on the above analysis, the current electricity demand characteristics of the electricity consumption end are calculated : In the formula, Indicates the number of date segments of the current electricity user. Indicates The average DTW matching distance between a date segment and all other date segments, Indicates The number of intervals in a date segment that match the DTW of all other date segments, Indicates The mean of the absolute differences in power deviation between the jth power consumption feature interval in the date segment and the DTW-matched power consumption feature intervals in all other date segments, Indicates The mean of the absolute differences in voltage deviation between the jth power consumption level characteristic interval in a date segment and the power consumption level characteristic intervals matched by DTW in all other date segments.

[0053] 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 the current electricity demand at the electricity consumption end. The larger the value, the more similar the characteristics of the electricity consumption activities of the users at the electricity consumption end are in time series, that is, the more obvious the regularity of electricity demand is.

[0054] S4, combining the electricity demand characteristics, the regular characteristics of electricity demand, and the 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.

[0055] After obtaining the power demand characteristics and power demand regularity characteristics of different power users, the initial power allocation can be performed on the power users connected to the emergency power supply box. In the initial power allocation, a larger power is allocated to the power users with higher power demand; the more obvious the power demand regularity is, the more accurate the initial power allocated through the power demand characteristics is; the worse the power demand regularity is, the less obvious the initial power allocation is through the power demand characteristics, and further adjustments are needed according to the actual power consumption situation. Therefore, the initial power allocation should give priority to the power users with obvious power demand regularity.

[0056] Based on this, the present application combines the power demand characteristics and power demand law 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 to the current power user.

[0057] This embodiment first calculates the mean value of the power demand characteristics in each date segment of the current power user; 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 value after taking the absolute value of the tanh function to set its value range The interval is denoted as , used to assess the development of historical electricity consumption levels at the current electricity consumption end.

[0058] 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 are to have the same sign, which means that there is a certain regularity in the change trend of all points on the current electricity demand characteristic change curve, indicating that the electricity demand at the current electricity consumer has a certain change and development trend. The reference value of the electricity demand characteristic reference segment to which the same historical date belongs to the power of the current electricity consumer is lower.

[0059] The current power consumption characteristic weight factor The characteristics of the current electricity demand at the power consumption end After multiplication, the product results of all power consumption ends are normalized using the range normalization method to represent 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 preset by the current emergency power supply box.

[0060] Furthermore, in the actual process of power distribution, it is also necessary to adjust the power distribution results by analyzing the key equipment that may appear in the power consumption end. Among them, high-power equipment consumes a lot of electricity and has a relatively high cost of use, that is, the value of this equipment is generally greater for users; in addition, in the case of emergency power supply, for users, key equipment includes not only high-power equipment, but also equipment that needs to operate stably and continuously.

[0061] High-power equipment usually requires a large starting current. When high-power equipment 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 an instantaneous voltage drop. When there are key equipment with stable and continuous operation 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.

[0062] Based on this, the present 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.

[0063] 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.

[0064] Sort all the derivatives on the voltage fitting curve from small to large, 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 on the voltage signal fitting curve. It should be noted that if the position of the voltage derivative does not belong to the fitting curve subtraction interval, the point will be discarded. Calculate the voltage range of each subtraction interval on the voltage fitting curve, recorded as .

[0065] 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, recorded as .

[0066] Based on this, calculate the key equipment access index at the current power consumption end : In the formula, norm represents the normalization function, Indicates the number of reduction intervals selected on the voltage fitting curve, Indicates The time length of the reduction interval, Indicates the voltage range of the xth decreasing interval.

[0067] It should be understood that By adjusting the time 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 degree in each reduction interval is used as an evaluation indicator for the connection of high-power electrical appliances at the power consumption end; It can be used to characterize the stability of lower power during the power supply of the emergency power supply box. The smaller the value, the better the stability of lower power during the power supply of the emergency power supply box. The probability of there being 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 the port is maintained at a certain level.

[0068] Furthermore, in this application, the key equipment access index and the allocated initial power of the current power consumption end are used to adjust the power distribution of the emergency power supply box at different power consumption ends. The specific method is as follows: 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 end 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 current moment and the previous moment of the power consumption end is greater than the dynamic adjustment judgment threshold When the power supply is at a certain time, that is, it may be affected by the power consumption end with critical load or sudden load fluctuation, the power of the power supply box is readjusted. The method of readjustment 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.

[0069] 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 includes 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 in any one of the above.

[0070] The various embodiments in the present application are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0071] It should be noted that, unless otherwise specified and limited, terms such as "include", "comprises" or any other variants 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, an element defined by the sentence "including one..." does not exclude the existence 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.

[0072] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not invented by the present application.

[0073] It should 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 power consumption ends into date segments in units of days; use the inflection points after curve fitting of power data to divide multiple power consumption level characteristic intervals in 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 in different date segments; S3, the endpoints of all power consumption level characteristic intervals in 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 forwardly integrated to analyze the power demand regularity characteristics of different power consumption ends; wherein, the power deviation or voltage deviation is obtained by curve fitting all the power data or voltage data in the power consumption level characteristic interval, and the mean of the absolute difference between all the power data or voltage data in the power consumption level characteristic interval and the corresponding fitting curve is calculated, which is used as the power deviation or voltage deviation respectively; S4, combining the electricity demand characteristics, the regular characteristics of electricity demand, and the 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 as claimed in 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 time.

3. A power supply method for an emergency power supply box as claimed in claim 1, characterized in that: The electricity demand characteristics of different electricity consumption 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 electricity level characteristic interval.

4. A power supply method for an emergency power supply box as claimed in claim 1, characterized in that: The current power demand characteristics of the power consumption end are recorded as R, and the calculation expression is: In the formula, Indicates the number of date segments of the current electricity user. Indicates The average DTW matching distance between a date segment and all other date segments, Indicates The number of intervals in a date segment that match the DTW of all other date segments, Indicates The mean of the absolute differences in power deviation between the jth power consumption feature interval in the date segment and the DTW-matched power consumption feature intervals in all other date segments, Indicates The mean of the absolute differences in voltage deviation between the jth power consumption level characteristic interval in a date segment and the power consumption level characteristic intervals matched by DTW in all other date segments.

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

6. A power supply method for an emergency power supply box as claimed in 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 by using the weight includes: Calculate the mean value of the power demand characteristics in each date segment of the current power consumption end; construct a power demand characteristic change curve for all date segments of the current power consumption end, where the vertical axis is the mean value of the power demand characteristics and the horizontal axis is the date segment time series; Calculate the derivative mean of all points on the current power demand characteristic change curve of the power consumption end, take its absolute value and normalize it, which is recorded as ; The current power consumption characteristic weight factor The characteristics of the current electricity demand at the power 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 preset by the current emergency power supply box.

7. A power supply method for an emergency power supply box as claimed in claim 5, characterized in that: The method of analyzing the key equipment 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; All the derivatives on the voltage fitting curve are sorted in ascending order, and then the differences between adjacent elements in the sequence are calculated, and the extreme values ​​among all the differences in the sequence are selected. For each extreme value, the minimum value of the voltage derivative between the two adjacent elements corresponding to the extreme value is selected on the voltage signal fitting curve. The voltage range of each decreasing interval on the voltage fitting curve is calculated, which is recorded as ; 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, recorded as ; The key equipment access index of the current power consumption end is recorded as , the calculation expression is: In the formula, norm represents the normalization function, Indicates the number of reduction intervals selected on the voltage fitting curve, Indicates The time length of the reduction interval, Indicates the voltage range of the xth decreasing interval.

8. A power supply method for an emergency power supply box as claimed in 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: When the difference between the key equipment access index at the power consumption end at the current moment and the key equipment access index at the previous moment is less than or equal to the preset dynamic adjustment judgment threshold, the power of the power supply box is not 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 as described in any one of claims 1-8 is implemented.

Images