CN109409661A - Electronic device, the building Electrical Safety recognition methods based on cusum algorithm and storage medium - Google Patents

Abstract

The invention provides a method for identifying the safety of building electricity consumption based on the cusum algorithm, which includes: obtaining a predetermined current load curve of a building within a predefined time period; and performing a current mutation point analysis on the obtained current load curve according to the cusum algorithm , to analyze the point where the current load value suddenly changes; if the point where the current load value suddenly changes is a working day, then compare the current load value at this point with the preset first warning threshold, and if it is greater than or equal to the first warning threshold When the first warning threshold is used, the safety warning information is sent to the predetermined terminal; if it is analyzed that the point at which the current load value suddenly changes is a rest day, the current load value at the point is compared with the preset second warning threshold, and When it is greater than or equal to the preset second warning threshold, the security warning information is sent to the predetermined terminal. It can improve the maintenance efficiency of electricity failure and reduce the hidden danger of electricity safety.

Description

Electronic device, building electricity safety identification method and storage based on cusum algorithm medium

technical field

The invention relates to the field of power data processing, in particular to an electronic device, a building power safety identification method based on a cusum algorithm, and a storage medium.

Background technique

With the continuous development of smart grid and the increase of electricity products year by year, how to quickly and effectively control the electricity load of different buildings within a safe range has become a problem that must be solved in the construction of smart grid.

At present, the power safety diagnosis method for different buildings mainly sets the safety constraint range for each node voltage, line current and power flow. . This safety diagnosis method often has a great impact on the operation of the entire power system, and once a circuit break occurs, a relay protection engineer is required to conduct fault inquiry and line maintenance on site, which consumes a lot of manpower time and affects users. user experience.

SUMMARY OF THE INVENTION

In view of this, the present invention proposes an electronic device, a building electricity safety identification method based on a cusum algorithm, and a storage medium, which can improve the maintenance efficiency of electricity failure and reduce the hidden danger of electricity safety.

First of all, in order to achieve the above object, the present invention provides an electronic device, the electronic device includes a memory and a processor connected to the memory, the processor is used for executing the building based on the cusum algorithm stored on the memory A power consumption safety identification program, when the building power consumption safety identification program based on the cusum algorithm is executed by the processor, the following steps are implemented:

A1. Obtain the current load curve of each type of day of the pre-determined building in the pre-defined time period;

A2. Perform current mutation point analysis on the acquired current load curve according to the predetermined cusum algorithm, so as to analyze the time interval corresponding to the point where the current load value changes abruptly;

A3. If it is analyzed that the time interval in which the current load value changes abruptly is a working day, the current load value in the time interval is compared with the preset first warning threshold. If the current load value in the time interval is greater than or equal to the pre-warning threshold If the first warning threshold is set, the security warning information is sent to the predetermined terminal;

A4. If it is analyzed that the time interval in which the current load value suddenly changes is a rest day, the current load value in this time interval is compared with the preset second warning threshold. If the current load value in this time interval is greater than or equal to the pre-warning threshold If the second pre-warning threshold is set, the security pre-warning information is sent to the predetermined terminal.

Preferably, the step A2 includes the following steps:

Obtain the current load values at each time point in the power load curve to form a data set sequence {y _i } of the current load values;

The data sequence of the current load value is analyzed according to the predetermined cusum algorithm to detect the time point corresponding to the sudden change of the current load value.

Preferably, the step of analyzing the data sequence of the current load value according to the predetermined cusum algorithm to detect the data point corresponding to the sudden change of the current load value includes:

Assuming that {y _i } is an independent identically distributed random sequence, the probability density function of each time point on the current load curve before the current load value abruptly changes is The probability density function at each time point of the current load curve after the sudden change of the current load value is: Assuming that θ ₀ and θ ₁ follow a normal distribution, then

Among them, μ is the mean value of the abrupt current load value {y _i }, and σ ² is the variance of the sudden change current load value {y _i };

The predefined time interval length for identifying the current load value is N, and the threshold value for the sudden change of the current load value is h;

Calculate the variance σ ₀ ² and the mean μ ₀ of the current load value {y _i } with sudden change in the previous time interval, as well as the variance σ ₁ ² and the mean value μ ₁ of the current load value {y _i } with sudden change in this time interval. ;

According to the calculation results, calculate the log-likelihood ratio s(y _i ) before and after the sudden change of the current load value at point y _i in this time interval:

in,

Calculate the cumulative sum of the log-likelihood ratios of the sudden change in the current load value in this time interval in,

Set up a hypothesis test based on the mean μ of the abrupt current load values {yi}, assuming

H ₀ : μ=μ ₀ , H ₁ : μ=μ ₁ ;

The test criteria are:

like Then d=0, if then d=1;

If d=0, it is determined that the current load value has not changed abruptly in this time interval, which is denoted as H ₀ ; if d=1, it is determined that the current load value has a sudden change in this time interval, which is denoted as H ₁ , where h is the current Threshold for load mutation.

Preferably, in the step of predefining the length of the time interval for identifying the current load value as N, and the threshold value for the sudden change of the current load value as h, the N is the value of the power system corresponding to the building within one power frequency cycle. The number of sampling time points of the current load curve, the minimum unit of the length of the time interval is day, and the value range of the threshold h for the sudden change of the current load is 0.025N-0.1N.

Preferably, various types of days in the predefined time period include working days and non-working days, and the non-working days include holidays and weekends.

In addition, in order to achieve the above purpose, the present invention also proposes a method for identifying electricity safety in buildings based on a cusum algorithm, the method comprising the following steps:

S1. Obtain the current load curves of each type of day of a predetermined building in a predetermined time period respectively;

S2. Perform current mutation point analysis on the acquired current load curve according to a predetermined cusum algorithm, so as to analyze the time interval corresponding to the point where the current load value changes abruptly;

S3. If it is analyzed that the time interval in which the current load value changes abruptly is a working day, compare the current load value in the time interval with the preset first warning threshold, and if the current load value in the time interval is greater than or equal to the pre-warning threshold If the first warning threshold is set, the security warning information is sent to the predetermined terminal;

S4. If the time interval in which the sudden change of the current load value is analyzed is a rest day, compare the current load value in the time interval with the preset second warning threshold, and if the current load value in the time interval is greater than or equal to the pre-warning threshold If the second pre-warning threshold is set, the security pre-warning information is sent to the predetermined terminal.

Preferably, the step S2 includes the following steps:

Obtain the current load values at each time point in the power load curve to form a data set sequence {y _i } of the current load values;

The data sequence of the current load value is analyzed according to the predetermined cusum algorithm to detect the time point corresponding to the sudden change of the current load value.

Preferably, the step of analyzing the data sequence of the current load value according to the predetermined cusum algorithm to detect the data point corresponding to the sudden change of the current load value includes:

Assuming that {y _i } is an independent identically distributed random sequence, the probability density function of each time point on the current load curve before the current load value abruptly changes is The probability density function at each time point of the current load curve after the sudden change of the current load value is: Assuming that θ ₀ and θ ₁ follow a normal distribution, then

Among them, μ is the mean value of the abrupt current load value {y _i }, and σ ² is the variance of the sudden change current load value {y _i };

The predefined time interval length for identifying the current load value is N, and the threshold value for the sudden change of the current load value is h;

Calculate the variance σ ₀ ² and the mean μ ₀ of the current load value {y _i } with sudden change in the previous time interval, as well as the variance σ ₁ ² and the mean value μ ₁ of the sudden current load value {y _i } in this time interval. ;

According to the calculation results, calculate the log-likelihood ratio s(y _i ) before and after the sudden change of the current load value at point y _i in this time interval:

in,

Calculate the cumulative sum of the log-likelihood ratios of the sudden change in the current load value in this time interval in,

Set up a hypothesis test based on the mean μ of the abrupt current load values {yi}, assuming

H ₀ : μ=μ ₀ , H ₁ : μ=μ ₁ ;

The test criteria are:

like Then d=0, if then d=1;

If d=0, it is determined that the current load value has not changed abruptly in this time interval, which is denoted as H ₀ ; if d=1, it is determined that the current load value has a sudden change in this time interval, which is denoted as H ₁ , where h is the current Threshold for load mutation.

Preferably, in the step of predefining the length of the time interval for identifying the current load value as N, and the threshold value for the sudden change of the current load value as h, the N is the value of the power system corresponding to the building within one power frequency cycle. The number of sampling time points of the current load curve, the minimum unit of the length of the time interval is day, and the value range of the threshold h for the sudden change of the current load is 0.025N-0.1N.

In addition, in order to solve the above technical problems, the present invention also proposes a computer-readable storage medium, the computer-readable storage medium stores a building electricity safety identification program based on a cusum algorithm, and the building The electrical safety identification program may be executed by at least one processor, so that the at least one processor executes the steps of the cusum algorithm-based building electrical safety identification method as described above.

The electronic device, the building electricity safety identification method and the storage medium based on the cusum algorithm proposed by the present invention obtain the current load curves of the pre-determined buildings for each type of day in the pre-defined time period respectively; according to the pre-determined cusum The algorithm analyzes the current mutation point of the acquired current load curve to analyze the time interval corresponding to the point where the current load value changes abruptly; The load value is compared with the preset first warning threshold. If the current load value in the time interval is greater than or equal to the preset first warning threshold, the safety warning information is sent to the predetermined terminal; if the current load value is analyzed If the time interval in which the sudden change occurs is a rest day, the current load value in the time interval is compared with the preset second warning threshold, and if the current load value in the time interval is greater than or equal to the preset second warning threshold, then Send security warning information to predetermined terminals. It can improve the maintenance efficiency of electricity failure and reduce the hidden danger of electricity safety.

Description of drawings

1 is a schematic diagram of an optional hardware architecture of an electronic device proposed by the present invention;

2 is a schematic diagram of a program module of a building electricity safety identification program based on a cusum algorithm in an embodiment of the electronic device of the present invention;

FIG. 3 is an implementation flow chart of a preferred embodiment of the method for identifying electricity safety in buildings based on the cusum algorithm of the present invention.

The realization, functional characteristics and advantages of the present invention will be further described with reference to the accompanying drawings in conjunction with the embodiments.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

It should be noted that the descriptions involving "first", "second", etc. in the present invention are only for the purpose of description, and should not be construed as indicating or implying their relative importance or implying the number of indicated technical features . Thus, a feature delimited with "first", "second" may expressly or implicitly include at least one of that feature. In addition, the technical solutions between the various embodiments can be combined with each other, but must be based on the realization by those of ordinary skill in the art. When the combination of technical solutions is contradictory or cannot be realized, it should be considered that the combination of such technical solutions does not exist. , is not within the scope of protection required by the present invention.

Referring to FIG. 1 , it is a schematic diagram of an optional hardware structure of the electronic device proposed by the present invention. In this embodiment, the electronic device 10 may include, but is not limited to, the memory 11 , the processor 12 , and the network interface 13 that can be connected to each other through the communication bus 14 in communication. It should be noted that FIG. 1 only shows the electronic device 10 having components 11-14, but it should be understood that it is not required to implement all of the illustrated components, and more or less components may be implemented instead.

Wherein, the memory 11 includes at least one type of computer-readable storage medium, and the computer-readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static Random Access Memory (SRAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), Programmable Read Only Memory (PROM), Magnetic Memory, Magnetic Disk, Optical Disk, etc. In some embodiments, the memory 11 may be an internal storage unit of the electronic device 10 , such as a hard disk or a memory of the electronic device 10 . In other embodiments, the memory 11 may also be an outsourced storage device of the electronic device 10, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) equipped on the electronic device 10 card, flash card (Flash Card) and so on. Of course, the memory 11 may also include both an internal storage unit of the electronic device 10 and an external storage device thereof. In this embodiment, the memory 11 is generally used to store the operating system and various application software installed in the electronic device 10 , such as a building electricity safety identification program based on the cusum algorithm, and the like. In addition, the memory 11 can also be used to temporarily store various types of data that have been output or will be output.

In some embodiments, the processor 12 may be a central processing unit (Central Processing Unit, CPU), a controller, a microcontroller, a microprocessor, or other data processing chips. The processor 12 is generally used to control the overall operation of the electronic device 10 . In this embodiment, the processor 12 is configured to run the program code or process data stored in the memory 11 , for example, the running safety identification program for building electricity consumption based on the cusum algorithm.

The network interface 13 may include a wireless network interface or a wired network interface, and the network interface 13 is generally used to establish a communication connection between the electronic device 10 and other electronic devices.

The communication bus 14 is used to implement the communication connection between the components 11-13.

FIG. 1 only shows the electronic device 10 with components 11-14 and a building electricity safety identification program based on the cusum algorithm, but it should be understood that it is not required to implement all the shown components, and more can be implemented instead. or fewer components.

Optionally, the electronic device 10 may further include a user interface (not shown in FIG. 1 ), the user interface may include a display, an input unit such as a keyboard, and the user interface may further include a standard wired interface, a wireless interface, and the like.

Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED touch, and the like. Further, the display may also be referred to as a display screen or a display unit for displaying information processed in the electronic device 10 and for displaying a user interface for visualization.

Optionally, in some embodiments, the electronic device 10 may further include an audio unit (the audio unit is not shown in FIG. 1 ), and the audio unit may be in a call signal receiving mode, a talking mode, a recording mode, a voice recognition mode when the electronic device 10 is in a Mode, broadcast receiving mode, etc., convert the received or stored audio data into audio signals; further, the electronic device 10 may also include an audio output unit, and the audio output unit outputs the audio signal converted by the audio unit, and The audio output unit may also provide audio output related to a specific function performed by the electronic device 10 (eg, call signal reception sound, message reception sound, etc.), and the audio output unit may include a speaker, a buzzer, and the like.

Optionally, in some embodiments, the electronic device 10 may further include an alarm unit (not shown in the figure), and the alarm unit may provide an output that the occurrence of the event has been notified to the electronic device 10 . Typical events may include call reception, message reception, key signal input, touch input, and the like. In addition to audio or video output, the alarm unit can provide output in various ways to notify the occurrence of an event. For example, the alarm unit may provide an output in the form of vibrations, and the alarm unit may provide a haptic output (ie, vibration) to notify the user when a call, message, or some other event is received that may put the electronic device 10 into a communication mode.

In one embodiment, when the building electricity safety identification program based on the cusum algorithm stored in the memory 11 is executed by the processor 12, the following operations are implemented:

A1, respectively obtain the current load curve of the pre-determined building in the pre-defined time period on each day;

Specifically, the predetermined building may be an inpatient building of a hospital, an outpatient building, a school classroom, an administrative building of a government agency, various shopping malls, and the like. It can be understood that due to the laws of human social activities, such as working on weekdays, weekends, holidays, etc., the historical current load curves of the same building on different types of days (type days include working days, holidays, and weekends) are different. Moreover, the historical current load curve on the same type of day has periodic characteristics. Therefore, in the analysis and statistics of power system electricity consumption, it is necessary to identify the power consumption load of each type of day, so as to improve the data processing efficiency of the power system and promote urbanization. The development of smart grid.

A2, according to the pre-determined cusum algorithm, perform current mutation point analysis on the acquired current load curve, so as to analyze the time interval corresponding to the point where the current load value changes abruptly;

Specifically, the predetermined cusum algorithm is used to detect a data point that begins to turn in a relatively stable data sequence. The so-called turning point means that the mean and variance of the series before and after it begins to change, which in turn affects the stability of the entire set of data.

Cusum achieves the effect of amplification by accumulating small deviations between the actual value and the reference value, and improves the sensitivity of small deviations in the detection process. When the accumulated deviation exceeds the threshold to a certain extent, it is considered that a mutation point or abnormal value occurs. Therefore, the cusum algorithm is also known as the cumulative sum algorithm.

Specifically, in this embodiment, the step S2 includes the following steps:

Assuming that the current load data in the obtained power load curve constitute the data set {y _i }, let {y _i } be an independent and identically distributed random sequence, the probability density function of each point on the current load curve before the current load value changes abruptly for The probability density function of each point of the current load curve after the sudden change of the current load value is: Further in this implementation, assuming that θ ₀ and θ ₁ obey normal distribution, then

Among them, μ is the mean value of the abrupt current load data {y _i }, and σ ² is the variance of the abrupt current load data {y _i };

The length of the pre-defined time interval for identifying the current load data of the building is N (N generally takes the sampling time points of the current load curve of the power system corresponding to the building in one power frequency cycle. In this embodiment, the time interval is The minimum unit of length is day), and the threshold of current load mutation is h (the value range is 0.025N-0.1N);

Calculate the variance σ ₀ ² and the mean μ ₀ of the current load data {y _i } with sudden change in the previous time interval, as well as the variance σ ₁ ² and the mean μ ₁ of the current load data {y _i } with sudden change in this time interval ;

According to the above calculation results, calculate the log-likelihood ratio s(y _i ) before and after the sudden change of the current load data at point _yi in this time interval:

in,

Calculate the cumulative sum of the log-likelihood ratio of the current load data with sudden change in this time interval in,

Build a hypothesis test based on the mean μ of the abrupt current load data {yi}, specifically, assuming

H ₀ : μ=μ ₀ , H ₁ : μ=μ ₁ ;

The test criteria are:

like Then d=0, if then d=1;

If d=0, it is determined that the current load data has not changed abruptly in this time interval, and it is recorded as H ₀ ; if d=1, it is determined that the current load data has changed abruptly in this time interval, and it is recorded as H ₁ , where h is the current Threshold for load mutation.

A3, if it is determined that the time interval in which the current load value suddenly changes is a working day, the current load value in the time interval is compared with the preset first warning threshold. If the first warning threshold is set, the security warning information is sent to the predetermined terminal;

A4. If it is determined that the time interval in which the current load value suddenly changes is a rest day, the current load value in the time interval is compared with the preset second warning threshold. If the current load value in the time interval is greater than or equal to the pre-warning threshold If the second pre-warning threshold is set, the security pre-warning information is sent to the predetermined terminal.

It can be seen from the above-mentioned embodiments that the electronic device proposed by the present invention obtains the current load curves of each type of day in a predetermined time period of a pre-determined building respectively; Mutation point analysis, to analyze the time interval corresponding to the point where the current load value changes abruptly; if it is analyzed that the time interval where the current load value changes abruptly is a working day, the current load value in this time interval is compared with the preset first warning thresholds are compared, and if the current load value in this time interval is greater than or equal to the preset first warning threshold, the safety warning information is sent to the predetermined terminal; if it is analyzed that the time interval in which the current load value suddenly changes is a rest day, The current load value in the time interval is compared with the preset second warning threshold, and if the current load value in the time interval is greater than or equal to the preset second warning threshold, the safety warning information is sent to the predetermined terminal. . It can improve the maintenance efficiency of electricity failure and reduce the hidden danger of electricity safety.

In addition, the building electricity safety identification program based on the cusum algorithm of the present invention can be described by program modules with the same functions according to the different functions realized by its various parts. Please refer to FIG. 2 , which is a schematic diagram of a program module of a building electricity safety identification program based on the cusum algorithm in an embodiment of the electronic device of the present invention. In this embodiment, the building electricity safety identification program based on the cusum algorithm can be divided into an acquisition module 201 , an analysis module 202 , a first early warning prediction module 203 and a second early warning module according to the different functions implemented by its various parts. 204. It can be seen from the above description that the program module referred to in the present invention refers to a series of computer program instruction segments that can complete specific functions, and is more suitable than a program to describe the cusum algorithm-based building power safety identification program in the electronic device 10. Implementation process. The functions or operation steps implemented by the modules 201-204 are similar to the above, and will not be described in detail here, for example, in which:

The obtaining module 201 is used to obtain the current load curves of each type of day of the pre-determined building in the pre-defined time period respectively;

The analysis module 202 is configured to perform current mutation point analysis on the acquired current load curve according to a predetermined cusum algorithm, so as to analyze the time interval corresponding to the point where the current load value changes abruptly;

The first warning module 203 is configured to compare the current load value of the time interval with the preset first warning threshold if the time interval in which the sudden change of the current load value is analyzed is a working day, if the current load value of the time interval is If the value is greater than or equal to the preset first warning threshold, send security warning information to the predetermined terminal;

The second early warning module 204 is configured to compare the current load value in the time interval with the preset second warning threshold if the time interval in which the sudden change of the current load value is analyzed is a rest day, and if the current load value in the time interval is If the value is greater than or equal to the preset second pre-warning threshold, the security pre-warning information is sent to the pre-determined terminal.

In addition, the present invention also proposes a building electricity safety identification method based on the cusum algorithm, please refer to FIG. 3 , the building electricity safety identification method based on the cusum algorithm includes the following steps:

S301, respectively acquiring the current load curve of the predetermined building on each day in the predetermined time period;

Specifically, the predetermined building may be an inpatient building of a hospital, an outpatient building, a school classroom, an administrative building of a government agency, various shopping malls, and the like. It can be understood that due to the laws of human social activities, such as working on weekdays, weekends, holidays, etc., the historical current load curves of the same building on different types of days (type days include working days, holidays, and weekends) are different. Moreover, the historical current load curve on the same type of day has periodic characteristics. Therefore, in the analysis and statistics of power system electricity consumption, it is necessary to identify the power consumption load of each type of day, so as to improve the data processing efficiency of the power system and promote urbanization. The development of smart grid.

S302, perform current mutation point analysis on the acquired current load curve according to a predetermined cusum algorithm, so as to analyze the time interval corresponding to the point where the current load value changes abruptly;

Specifically, the predetermined cusum algorithm is used to detect a data point that begins to turn in a relatively stable data sequence. The so-called turning point means that the mean and variance of the series before and after it begins to change, which in turn affects the stability of the entire set of data.

Cusum achieves the effect of amplification by accumulating small deviations between the actual value and the reference value, and improves the sensitivity of small deviations in the detection process. When the accumulated deviation exceeds the threshold to a certain extent, it is considered that a mutation point or abnormal value occurs. Therefore, the cusum algorithm is also known as the cumulative sum algorithm.

Specifically, in this embodiment, the step S2 includes the following steps:

Assuming that the current load data in the obtained power load curve constitute the data set {y _i }, let {y _i } be an independent and identically distributed random sequence, the probability density function of each point on the current load curve before the current load value changes abruptly for The probability density function of each point of the current load curve after the sudden change of the current load value is: Further in this implementation, assuming that θ ₀ and θ ₁ obey normal distribution, then

Among them, μ is the mean value of the abrupt current load data {y _i }, and σ ² is the variance of the abrupt current load data {y _i };

The length of the pre-defined time interval for identifying the current load data of the building is N (N generally takes the sampling time points of the current load curve of the power system corresponding to the building in one power frequency cycle. In this embodiment, the time interval is The minimum unit of length is day), and the threshold of current load mutation is h (the value range is 0.025N-0.1N);

Calculate the variance σ ₀ ² and the mean μ ₀ of the current load data {y _i } with sudden change in the previous time interval, as well as the variance σ ₁ ² and the mean μ ₁ of the current load data {y _i } with sudden change in this time interval ;

According to the above calculation results, calculate the log-likelihood ratio s(y _i ) before and after the sudden change of the current load data at point _yi in this time interval:

in,

Calculate the cumulative sum of the log-likelihood ratio of the current load data with sudden change in this time interval in,

Build a hypothesis test based on the mean μ of the abrupt current load data {yi}, specifically, assuming

H ₀ : μ=μ ₀ , H ₁ : μ=μ ₁ ;

The test criteria are:

like Then d=0, if then d=1;

If d=0, it is determined that the current load data has not changed abruptly in this time interval, and it is recorded as H ₀ ; if d=1, it is determined that the current load data has changed abruptly in this time interval, and it is recorded as H ₁ , where h is the current Threshold for load mutation.

S303, if it is determined that the time interval in which the current load value changes abruptly is a working day, compare the current load value in the time interval with the preset first warning threshold, and if the current load value in the time interval is greater than or equal to the pre-warning threshold If the first warning threshold is set, the security warning information is sent to the predetermined terminal;

S304, if it is determined that the time interval in which the current load value suddenly changes is a rest day, compare the current load value in the time interval with the preset second warning threshold, and if the current load value in the time interval is greater than or equal to the pre-warning threshold If the second pre-warning threshold is set, the security pre-warning information is sent to the predetermined terminal.

It can be seen from the above-mentioned embodiments that the method for identifying the safety of building electricity consumption based on the cusum algorithm proposed by the present invention obtains the current load curves of the pre-determined buildings for each type of day in the pre-defined time period respectively; according to the pre-determined cusum The algorithm analyzes the current mutation point of the acquired current load curve to analyze the time interval corresponding to the point where the current load value changes abruptly; The load value is compared with the preset first warning threshold. If the current load value in the time interval is greater than or equal to the preset first warning threshold, the safety warning information is sent to the predetermined terminal; if the current load value is analyzed If the time interval in which the sudden change occurs is a rest day, the current load value in the time interval is compared with the preset second warning threshold, and if the current load value in the time interval is greater than or equal to the preset second warning threshold, then Send security warning information to predetermined terminals. It can improve the maintenance efficiency of electricity failure and reduce the hidden danger of electricity safety.

In addition, the present invention also provides a computer-readable storage medium, which stores a building electricity safety identification program based on the cusum algorithm, and the building electricity safety identification program based on the cusum algorithm is The processor executes the following operations:

Obtain the current load curve of each type of day of the pre-determined building in the pre-defined time period;

Perform current mutation point analysis on the acquired current load curve according to the predetermined cusum algorithm, so as to analyze the time interval corresponding to the point where the current load value changes abruptly;

If it is analyzed that the time interval in which the current load value suddenly changes is a working day, the current load value in the time interval is compared with the preset first warning threshold, and if the current load value in the time interval is greater than or equal to the preset value the first warning threshold, sending security warning information to a predetermined terminal;

If it is analyzed that the time interval in which the sudden change of the current load value is a rest day, the current load value of the time interval is compared with the preset second warning threshold, and if the current load value of the time interval is greater than or equal to the preset value The second warning threshold is to send security warning information to a predetermined terminal.

The specific implementation process of the computer-readable storage medium of the present invention is similar to that of the electronic device and the method for identifying electricity safety in buildings based on the cusum algorithm, and will not be repeated here.

From the description of the above embodiments, those skilled in the art can clearly understand that the method of the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is better implementation. Based on this understanding, the technical solutions of the present invention can be embodied in the form of software products in essence or the parts that make contributions to the prior art, and the computer software products are stored in a storage medium (such as ROM/RAM, magnetic disk, CD-ROM), including several instructions to make a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) execute the methods described in the various embodiments of the present invention. The above are only preferred embodiments of the present invention, and are not intended to limit the scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the description and drawings of the present invention, or directly or indirectly applied in other related technical fields , are similarly included in the scope of patent protection of the present invention.

Claims (10)

1. An electronic device, characterized in that the electronic device comprises a memory and a processor connected to the memory, and the processor is used to execute a building electricity safety identification based on a cusum algorithm stored on the memory The program, when the building electricity safety identification program based on the cusum algorithm is executed by the processor, implements the following steps: A1. Obtain the current load curve of each type of day of the pre-determined building in the pre-defined time period; A2. Perform current mutation point analysis on the acquired current load curve according to the predetermined cusum algorithm, so as to analyze the time interval corresponding to the point where the current load value changes abruptly; A3. If it is analyzed that the time interval in which the current load value changes abruptly is a working day, the current load value in the time interval is compared with the preset first warning threshold. If the current load value in the time interval is greater than or equal to the pre-warning threshold If the first warning threshold is set, the security warning information is sent to the predetermined terminal; A4. If it is analyzed that the time interval in which the current load value suddenly changes is a rest day, the current load value in this time interval is compared with the preset second warning threshold. If the current load value in this time interval is greater than or equal to the pre-warning threshold If the second pre-warning threshold is set, the security pre-warning information is sent to the predetermined terminal. 2. The electronic device according to claim 1, wherein the step A2 comprises the following steps: Obtain the current load values at each time point in the power load curve to form a data set sequence {y _i } of the current load values; The data sequence of the current load value is analyzed according to the predetermined cusum algorithm to detect the time point corresponding to the sudden change of the current load value. 3 . The electronic device according to claim 2 , wherein the data sequence of the current load value is analyzed according to the predetermined cusum algorithm to detect the data point corresponding to the abrupt change of the current load value. 4 . steps, including: Assuming that {y _i } is an independent identically distributed random sequence, the probability density function of each time point on the current load curve before the current load value abruptly changes is The probability density function at each time point of the current load curve after the sudden change of the current load value is: Assuming that θ ₀ and θ ₁ follow a normal distribution, then Among them, μ is the mean value of the abrupt current load value {y _i }, and σ ² is the variance of the sudden change current load value {y _i }; The predefined time interval length for identifying the current load value is N, and the threshold value for the sudden change of the current load value is h; Calculate the variance σ ₀ ² and the mean μ ₀ of the current load value {y _i } with sudden change in the previous time interval, as well as the variance σ ₁ ² and the mean value μ ₁ of the sudden current load value {y _i } in this time interval. ; According to the calculation results, calculate the log-likelihood ratio s(y _i ) before and after the sudden change of the current load value at point y _i in this time interval: in, Calculate the cumulative sum of the log-likelihood ratios of the sudden change in the current load value in this time interval in, Establish a hypothesis test based on the mean μ of the abrupt current load values {yi}, assuming H ₀ : μ = μ ₀ , H ₁ : μ = μ ₁ ; The test criteria are: like Then d=0, if then d=1; If d=0, it is determined that the current load value has not changed abruptly in this time interval, which is denoted as H ₀ ; if d=1, it is determined that the current load value has a sudden change in this time interval, which is denoted as H ₁ , where h is the current Threshold for load mutation. 4 . The electronic device according to claim 3 , wherein, in the step of predefining the length of the time interval for identifying the current load value as N, and the threshold value of the sudden change of the current load value as h, the N is the The number of sampling time points of the current load curve of the power system corresponding to the building in one power frequency cycle, the minimum unit of the length of the time interval is day, and the value range of the threshold h of the current load mutation is 0.025N-0.1N . 5 . The electronic device according to claim 1 , wherein each type of days in the predefined time period includes working days and non-working days, and the non-working days include holidays and weekends. 6 . 6. a building electricity safety identification method based on cusum algorithm, is characterized in that, described method comprises the steps: S1. Obtain the current load curves of each type of day of a predetermined building in a predetermined time period respectively; S2. Perform current mutation point analysis on the acquired current load curve according to a predetermined cusum algorithm, so as to analyze the time interval corresponding to the point where the current load value changes abruptly; S3. If it is analyzed that the time interval in which the current load value changes abruptly is a working day, compare the current load value in the time interval with the preset first warning threshold, and if the current load value in the time interval is greater than or equal to the pre-warning threshold If the first warning threshold is set, the security warning information is sent to the predetermined terminal; S4. If the time interval in which the sudden change of the current load value is analyzed is a rest day, compare the current load value in the time interval with the preset second warning threshold, and if the current load value in the time interval is greater than or equal to the pre-warning threshold If the second pre-warning threshold is set, the security pre-warning information is sent to the predetermined terminal. 7. the building electricity safety identification method based on cusum algorithm as claimed in claim 6, is characterized in that, described step S2 comprises the steps: Obtain the current load values at each time point in the power load curve to form a data set sequence {y _i } of the current load values; The data sequence of the current load value is analyzed according to the predetermined cusum algorithm to detect the time point corresponding to the sudden change of the current load value. 8 . The method for identifying electricity safety in buildings based on the cusum algorithm according to claim 7 , wherein the data sequence of the current load value is analyzed according to the predetermined cusum algorithm to detect a sudden change. 9 . The steps of the data point corresponding to the current load value include: Assuming that {y _i } is an independent identically distributed random sequence, the probability density function of each time point on the current load curve before the current load value abruptly changes is The probability density function at each time point of the current load curve after the sudden change of the current load value is: Assuming that θ ₀ and θ ₁ follow a normal distribution, then Among them, μ is the mean value of the abrupt current load value {y _i }, and σ ² is the variance of the sudden change current load value {y _i }; The predefined time interval length for identifying the current load value is N, and the threshold value for the sudden change of the current load value is h; Calculate the variance σ ₀ ² and the mean μ ₀ of the current load value {y _i } with sudden change in the previous time interval, as well as the variance σ ₁ ² and the mean value μ ₁ of the current load value {y _i } with sudden change in this time interval. ; According to the calculation results, calculate the log-likelihood ratio s(y _i ) before and after the sudden change of the current load value at point y _i in this time interval: in, Calculate the cumulative sum of the log-likelihood ratios of the sudden change in the current load value in this time interval in, Establish a hypothesis test based on the mean μ of the abrupt current load values {yi}, assuming H ₀ : μ = μ ₀ , H ₁ : μ = μ ₁ ; The test criteria are: like Then d=0, if then d=1; If d=0, it is determined that the current load value has not changed abruptly in this time interval, which is denoted as H ₀ ; if d=1, it is determined that the current load value has a sudden change in this time interval, which is denoted as H ₁ , where h is the current Threshold for load mutation. 9 . The method for identifying electricity safety in buildings based on cusum algorithm according to claim 8 , wherein the length of the time interval for identifying the current load value in the predefined definition is N, and the threshold value of the sudden change of the current load value is h 9 . In the step of , the N is the number of sampling time points of the current load curve of the power system corresponding to the building in a power frequency cycle, the minimum unit of the length of the time interval is day, the threshold h of the current load mutation is The value range is 0.025N-0.1N. 10. A computer-readable storage medium storing a building electricity safety identification program based on a cusum algorithm, wherein the building electricity safety identification program based on the cusum algorithm can be used by at least one processor. Executing, so that the at least one processor executes the steps of the cusum algorithm-based safety identification method for building electricity consumption according to any one of claims 6-9.