A smart power utilization safety management method and system

Abstract

The application relates to the technical field of power management, and particularly discloses a smart power safety management method and system, which comprises the following steps: receiving a user-input monitoring area, and acquiring enterprise record information of each enterprise in the area; determining standard parameters of each power supply node in the enterprise in real time according to the enterprise record information; collecting current data of each power supply node of the enterprise according to a preset collection device, comparing the current data with corresponding standard parameters, and determining a power risk rate of the enterprise; when the power risk rate reaches a preset risk rate threshold, acquiring image information of a target area; and determining warning information according to the image information and the power risk rate. According to the enterprise record information, the application can formulate power standards that are more suitable for the enterprise in real time, and when the user starts to use power, the power use condition can be collected in real time, the power use condition can be analyzed based on the power standards, and then safety management can be performed; the fitting degree and flexibility are very high.

Description

Technical Field

[0001] This invention relates to the field of electricity management technology, specifically a smart electricity safety management method and system. Background Technology

[0002] Electricity is an energy source that uses electrical energy as its power source. Discovered in the 1870s, the discovery and application of electricity sparked the Second Industrial Revolution. It became one of the three technological revolutions that have occurred in the world since the 18th century, fundamentally changing people's lives. The large-scale power systems that emerged in the 20th century are among the most important achievements in the history of human engineering science.

[0003] The application of electricity has greatly saved human physical and mental labor and brought great convenience to our lives. However, the application of electricity has also brought many risks, most of which are quite serious. Therefore, electricity safety management is a very important part of the process of electricity application.

[0004] Existing electricity usage processes all rely on a reference standard, which restricts businesses based on that standard. However, these standards are mostly updated quarterly, with some updated monthly. In reality, even if updated daily, it remains a static electricity management system because it cannot be adjusted in real time according to the user's specific circumstances. Therefore, designing an electricity management system that better suits users is the technical problem that this invention aims to solve. Summary of the Invention

[0005] The purpose of this invention is to provide a smart electricity safety management method and system to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A smart electricity safety management method, the method comprising:

[0008] The system receives the monitoring area input by the user and obtains the enterprise registration information of each enterprise within that area based on a preset information template. The enterprise registration information includes the electricity user unit number, the electricity user unit type, and the power supply node.

[0009] The standard parameters of each power supply node in the enterprise are determined in real time based on the enterprise's registration information.

[0010] The current data of each power supply node of the enterprise is collected by the preset acquisition equipment, and the current data is compared with the corresponding standard parameters to determine the power consumption risk rate of the enterprise.

[0011] When the electricity risk rate reaches a preset risk rate threshold, the target area is determined based on the power supply node, and image information of the target area is acquired.

[0012] Warning information is determined based on the image information and the electricity risk rate.

[0013] As a further aspect of the present invention: the step of determining the standard parameters of each power supply node in the enterprise in real time based on the enterprise registration information includes:

[0014] Classify the types of electricity users according to their unit numbers, and calculate the number of each type of electricity user.

[0015] Obtain the energy consumption parameters for each type of electricity-consuming unit, and determine the corresponding energy consumption parameters for each type of electricity-consuming unit based on the energy consumption parameters and the quantity.

[0016] Receive the working time input by the user, and calculate the predicted power consumption based on the working time and the energy consumption parameters corresponding to each type of power consumption unit;

[0017] The enterprise's reference power consumption is determined based on the predicted power consumption, and standard parameters are determined based on the reference power consumption.

[0018] As a further aspect of the present invention: the step of determining the enterprise's reference power consumption based on the predicted power consumption, and determining the standard parameters based on the reference power consumption, includes:

[0019] Obtain holiday information, determine the center time based on the holiday length in the holiday information, and calculate the positional proportion of the center time within a year;

[0020] Obtain the company's product sales information, determine peak and off-peak season information based on the product sales information, and determine the impact radius of each holiday based on the peak and off-peak season information;

[0021] The holiday schedule is determined based on the location ratio and the radius of influence, and the correction rate is determined based on the holiday schedule.

[0022] The enterprise's reference electricity consumption is determined based on the correction rate and the predicted electricity consumption.

[0023] The standard parameters are determined based on the reference power level.

[0024] As a further aspect of the present invention: the step of determining the standard parameters based on the reference power includes:

[0025] Obtain the user unit number corresponding to each power supply node, and query the power consumption unit type corresponding to the user unit number in the enterprise registration information;

[0026] Read the energy consumption parameters corresponding to the user unit number according to the type of electricity user unit;

[0027] By statistically analyzing the energy consumption parameters corresponding to the unit numbers of each user, the energy consumption parameters of that power supply node can be obtained.

[0028] The allocation ratio is determined based on the energy consumption parameters of different power supply nodes;

[0029] The allocated power of each power supply node is calculated based on the allocation ratio and the reference power, and the standard parameters of the power supply node are determined based on the allocated power.

[0030] As a further aspect of the present invention: the step of collecting current data from each power supply node of the enterprise using a preset acquisition device, comparing the current data with corresponding standard parameters, and determining the enterprise's electricity risk rate includes:

[0031] Generate a current queue of preset length; wherein the current queue is mapped to each acquisition device;

[0032] Send a preset acquisition frequency to each acquisition device to obtain current data at each power supply node, and insert the acquired current data into the current queue;

[0033] The current data in the current queue is read sequentially, and the current data is compared with the standard parameters at the power supply node to obtain the offset rate;

[0034] An offset curve is generated based on the offset rate, and the electricity risk rate is determined based on the offset curve; wherein, the independent variable of the offset curve is time.

[0035] As a further aspect of the present invention: the step of determining the target area based on the power supply node and acquiring image information of the target area when the electricity risk rate reaches a preset risk rate threshold includes:

[0036] When the electricity risk rate reaches the preset risk rate threshold, the electricity user number corresponding to the power supply node is read from the enterprise registration information.

[0037] Obtain the location information of the electricity user unit based on the electricity user unit number, and determine the target area based on the location information;

[0038] Locate the image acquisition device in the target area, and acquire image information based on the image acquisition device.

[0039] As a further aspect of the present invention: the step of determining the warning information based on the image information and the electricity risk rate includes:

[0040] The image information is sorted according to the acquisition time to obtain the image library to be inspected;

[0041] Traverse the image library to be inspected and extract the feature values ​​of each image to be inspected in the image library in turn to obtain a feature array;

[0042] The mean of the feature array is calculated in real time, and the difference between each feature value and the mean is calculated. When the difference reaches a preset difference threshold, the corresponding feature value is marked.

[0043] Read the acquisition time of the image information corresponding to the feature value, query the electricity risk rate in the offset curve, and determine the warning information based on the user risk rate.

[0044] The present invention also provides a smart electricity safety management system, the system comprising:

[0045] The registration information acquisition module is used to receive the monitoring area input by the user and obtain the enterprise registration information of each enterprise in the area according to the preset information template; the enterprise registration information includes the electricity user unit number, the electricity user unit type, and the power supply node.

[0046] The standard parameter determination module is used to determine the standard parameters of each power supply node in a company in real time based on the company's registration information.

[0047] The risk rate determination module is used to collect current data of each power supply node of the enterprise according to the preset acquisition equipment, compare the current data with the corresponding standard parameters, and determine the power consumption risk rate of the enterprise.

[0048] The image information acquisition module is used to determine the target area based on the power supply node and acquire the image information of the target area when the power consumption risk rate reaches a preset risk rate threshold.

[0049] The warning information determination module is used to determine the warning information based on the image information and the electricity risk rate.

[0050] As a further aspect of the present invention: the standard parameter determination module includes:

[0051] The classification calculation unit is used to classify the types of electricity users according to their unit numbers and to calculate the quantity of each type of electricity user.

[0052] The parameter classification unit is used to obtain the energy consumption parameters of each type of electricity consumption unit, and determine the corresponding energy consumption parameters of each type of electricity consumption unit based on the energy consumption parameters and the quantity.

[0053] The predicted power consumption calculation unit is used to receive the working time input by the user and calculate the predicted power consumption based on the working time and the energy consumption parameters corresponding to each type of power consumption unit.

[0054] The standard parameter calculation unit is used to determine the enterprise's reference power based on the predicted power, and to determine the standard parameters based on the reference power.

[0055] As a further aspect of the present invention: the standard parameter calculation unit includes:

[0056] The proportion determination subunit is used to obtain holiday information, determine the center time based on the holiday length in the holiday information, and calculate the position proportion of the center time within a year;

[0057] The radius determines the sub-unit, obtains the company's product sales information, determines peak and off-peak season information based on the product sales information, and determines the impact radius of each holiday based on the peak and off-peak season information.

[0058] The correction rate determination subunit is used to determine the holiday table based on the location ratio and the radius of influence, and to determine the correction rate based on the holiday table.

[0059] A reference determination unit is used to determine the reference power of the enterprise based on the correction rate and the predicted power;

[0060] An execution subunit is used to determine standard parameters based on the reference power level.

[0061] Compared with the prior art, the beneficial effects of the present invention are: the present invention formulates electricity consumption standards that are more in line with the enterprise's registration information in real time, and collects electricity consumption data in real time when the user starts to use electricity, analyzes the electricity consumption data based on the electricity consumption standards, and then conducts safety management; the degree of fit and flexibility is extremely high. Attached Figure Description

[0062] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention.

[0063] Figure 1 A flowchart for intelligent electricity safety management methods.

[0064] Figure 2 This is the first sub-flowchart of the intelligent electricity safety management method.

[0065] Figure 3 This is the second sub-flowchart of the intelligent electricity safety management method.

[0066] Figure 4 This is the third sub-process flowchart of the intelligent electricity safety management method.

[0067] Figure 5 This is the fourth sub-process flowchart of the intelligent electricity safety management method.

[0068] Figure 6 This is a block diagram showing the components of a smart electricity safety management system.

[0069] Figure 7This is a block diagram showing the composition of the standard parameter determination module in a smart electricity safety management system. Detailed Implementation

[0070] To make the technical problems to be solved, the technical solutions, and the beneficial effects 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 merely illustrative of the present invention and are not intended to limit the present invention.

[0071] Example 1

[0072] Figure 1 This is a flowchart of a smart electricity safety management method. In this embodiment of the invention, a smart electricity safety management method includes steps S100 to S500:

[0073] Step S100: Receive the monitoring area input by the user, and obtain the enterprise registration information of each enterprise in the area according to the preset information template; the enterprise registration information includes the electricity user unit number, the electricity user unit type, and the power supply node.

[0074] For the process of electricity monitoring, the monitoring always occurs within a certain area, such as an office building, a residential community, or a park. The area is input by the user. Once the monitoring area is determined, the registration information of each enterprise in the area is obtained according to the information template. When the monitoring area is a small area, each "enterprise" can be understood as each unit or each floor. Of course, in the technical solution of this invention, the scenario of the monitoring area being a residential community is almost non-existent, because now each household has an independent electricity meter, and the power management process is very simple.

[0075] Step S200: Determine the standard parameters of each power supply node in the enterprise in real time based on the enterprise's registration information;

[0076] Power supply nodes are the management target. If the safety of the power supply nodes is high enough, then the electricity use process is safe. Even if some accidents occur, it will not be an electricity safety issue. The standard parameters of each power supply node are determined based on the enterprise's filing information. The standard parameters are a reference, and the obtained power supply node data is compared with the standard parameters.

[0077] Step S300: Collect current data of each power supply node of the enterprise according to the preset acquisition device, compare the current data with the corresponding standard parameters, and determine the power consumption risk rate of the enterprise.

[0078] Step S300 is the specific monitoring step, which involves acquiring data from each power supply node and then comparing the data with the standard parameters to determine an electricity risk rate.

[0079] Step S400: When the electricity risk rate reaches a preset risk rate threshold, determine the target area based on the power supply node and acquire image information of the target area;

[0080] Step S500: Determine warning information based on the image information and the electricity risk rate;

[0081] If the risk rate of electricity use is high, it is necessary to further monitor the electrical equipment corresponding to the power supply node. The further monitoring method is to obtain image information and determine warning information based on the image information.

[0082] Figure 2 This is the first sub-process flowchart of the intelligent electricity safety management method. The step of determining the standard parameters of each power supply node in the enterprise in real time based on the enterprise's registration information includes steps S201 to S204:

[0083] Step S201: Classify the types of electricity users according to their unit numbers and calculate the quantity of each type of electricity user.

[0084] Step S202: Obtain the energy consumption parameters of each type of electricity consumption unit, and determine the corresponding energy consumption parameters of each type of electricity consumption unit based on the energy consumption parameters and the quantity.

[0085] Step S203: Receive the working time input by the user, and calculate the predicted power consumption based on the working time and the energy consumption parameters corresponding to each type of power consumption unit;

[0086] Step S204: Determine the enterprise's reference power consumption based on the predicted power consumption, and determine the standard parameters based on the reference power consumption.

[0087] Steps S201 to S204 specifically define the process for determining the standard parameters. First, the enterprise registration information includes electrical equipment items (number items), and each electrical equipment has its own power consumption type and power supply node. Multiple electrical equipment may be of the same type; for example, in a company, office computers may be of the same type. Multiple electrical equipment may also share the same power supply node; for example, in a company, a row of office computers may share a single power strip. Then, to facilitate calculation, the enterprise registration information is converted into type-indexed information to determine the total number of electrical equipment of each type. The energy consumption parameters (power consumption information, data from the factory label) corresponding to each type are read, and then, through simple multiplication, the total energy consumption parameters for each type can be determined. Finally, the user inputs the working time, and based on the working time and energy consumption parameters, the predicted power consumption for each type can be obtained, thus providing the company's reference power consumption. The standard parameters are then determined from the reference power consumption.

[0088] Furthermore, the step of determining the enterprise's reference electricity volume based on the predicted electricity volume, and determining the standard parameters based on the reference electricity volume, includes:

[0089] Obtain holiday information, determine the center time based on the holiday length in the holiday information, and calculate the positional proportion of the center time within a year;

[0090] Obtain the company's product sales information, determine peak and off-peak season information based on the product sales information, and determine the impact radius of each holiday based on the peak and off-peak season information;

[0091] The holiday schedule is determined based on the location ratio and the radius of influence, and the correction rate is determined based on the holiday schedule.

[0092] The enterprise's reference electricity consumption is determined based on the correction rate and the predicted electricity consumption.

[0093] The standard parameters are determined based on the reference power level.

[0094] The holidays mentioned don't necessarily have to be public holidays; weekends also count. Since the dates of public holidays vary each year, they need to be reordered based on their "center point." During peak seasons, there's more overtime work, while during off-seasons, not only are weekends off guaranteed, but some employees also extend their weekends into "mini-vacations" for travel. Therefore, based on this reordering of holidays and considering peak and off-season information, the "length" of each holiday can be redefined to determine a more accurate holiday schedule. This schedule can then be used to adjust predicted electricity consumption, determining the company's reference electricity consumption. The adjustment method involves setting a correction rate. For example, during holidays, the correction rate could be 20%, meaning the company's energy consumption would be 20% of normal levels. On weekdays, the correction rate could be 100% or even higher. Based on this percentage and predicted electricity consumption, the company's reference electricity consumption can be calculated.

[0095] Specifically, the step of determining the standard parameters based on the reference power quantity includes:

[0096] Obtain the user unit number corresponding to each power supply node, and query the power consumption unit type corresponding to the user unit number in the enterprise registration information;

[0097] Read the energy consumption parameters corresponding to the user unit number according to the type of electricity user unit;

[0098] By statistically analyzing the energy consumption parameters corresponding to the unit numbers of each user, the energy consumption parameters of that power supply node can be obtained.

[0099] The allocation ratio is determined based on the energy consumption parameters of different power supply nodes;

[0100] The allocated power of each power supply node is calculated based on the allocation ratio and the reference power, and the standard parameters of the power supply node are determined based on the allocated power.

[0101] The purpose of the above is to allocate reference power to each power supply node. The allocation ratio is determined by the electrical equipment corresponding to each power supply node. For example, if a node is connected to multiple high-power devices, its allocation ratio will be larger, and if a node is connected to only a regular computer, its allocation ratio will be smaller. Determining the parameters of the power supply nodes based on power consumption also requires adding some time information, but this process is not difficult for those skilled in the art and can be set using some basic electrical formulas.

[0102] Figure 3 The second sub-flow diagram of the intelligent electricity safety management method includes steps S301 to S304, which involves collecting current data from each power supply node of the enterprise using preset acquisition equipment, comparing the current data with corresponding standard parameters, and determining the enterprise's electricity risk rate.

[0103] Step S301: Generate a current queue of preset length; wherein the current queue is mapped to each acquisition device;

[0104] Step S302: Send a preset acquisition frequency to each acquisition device to obtain current data at each power supply node, and insert the acquired current data into the current queue;

[0105] Step S303: Read the current data in the current queue sequentially, compare the current data with the standard parameters at the power supply node, and obtain the offset rate;

[0106] Step S304: Generate an offset curve based on the offset rate, and determine the electricity risk rate based on the offset curve; wherein, the independent variable of the offset curve is time.

[0107] Steps S301 to S304 describe in detail the process of generating the electricity risk rate. First, some storage areas, namely the current queue mentioned above, are opened. Then, the current queue is used as a buffer to collect current data. The current data is compared with the standard parameters to obtain the amount of deviation. Finally, the electricity risk rate can be determined based on the degree of deviation.

[0108] Figure 4 The third sub-flow diagram of the intelligent electricity safety management method includes steps S401 to S403, whereby when the electricity risk rate reaches a preset risk rate threshold, the step of determining the target area based on the power supply node and acquiring image information of the target area.

[0109] Step S401: When the electricity risk rate reaches the preset risk rate threshold, read the electricity unit number corresponding to the power supply node from the enterprise registration information;

[0110] Step S402: Obtain the location information of the electricity user unit based on the electricity user unit number, and determine the target area based on the location information;

[0111] Step S403: Locate the image acquisition device in the target area and acquire image information based on the image acquisition device.

[0112] The process from steps S401 to S403 is relatively simple. It should be noted that the step of querying the location information of the electricity user unit according to the number requires a pre-set repository, which is already existing data in the databases of many enterprises. The operation that the computer needs to perform is only a simple read operation.

[0113] Figure 5 This is the fourth sub-flowchart of the intelligent electricity safety management method. The step of determining the warning information based on the image information and the electricity risk rate includes steps S501 to S504:

[0114] Step S501: Sort the image information according to the acquisition time of the image information to obtain the image library to be inspected;

[0115] Step S502: Traverse the image library to be inspected, and extract the feature values ​​of each image to be inspected in the image library in turn to obtain a feature array;

[0116] Step S503: Calculate the mean of the feature array in real time, calculate the difference between each feature value and the mean, and mark the corresponding feature value when the difference reaches a preset difference threshold;

[0117] Step S504: Read the acquisition time of the image information corresponding to the feature value, query the electricity risk rate in the offset curve, and determine the warning information based on the user risk rate.

[0118] The image information judgment process in steps S501 to S504 involves first sorting the image information and obtaining corresponding feature values. There are many ways to obtain feature values; by converting and statistically analyzing each pixel, a value corresponding to the image can be obtained. By statistically analyzing the values ​​corresponding to all images, an array can be obtained. Then, some mathematical operations are performed on this feature array to mark the more "prominent" values. Finally, the image information and its time information are located based on this value, and the corresponding power consumption risk rate is queried. If the power consumption risk rate of the located image information is also relatively high, then the possibility of a problem is relatively high, and a warning message needs to be generated and reported. It is worth mentioning that the warning message can include image information and current queue.

[0119] Example 2

[0120] Figure 6 This is a block diagram of the composition structure of a smart electricity safety management system. In this embodiment of the invention, a smart electricity safety management system, system 10 includes:

[0121] The filing information acquisition module 11 is used to receive the monitoring area input by the user and obtain the enterprise filing information of each enterprise in the area according to the preset information template; the enterprise filing information includes the electricity user unit number, the electricity user unit type, and the power supply node.

[0122] Standard parameter determination module 12 is used to determine the standard parameters of each power supply node in the enterprise in real time based on the enterprise's filing information.

[0123] The risk rate determination module 13 is used to collect current data of each power supply node of the enterprise according to the preset acquisition device, compare the current data with the corresponding standard parameters, and determine the power consumption risk rate of the enterprise.

[0124] The image information acquisition module 14 is used to determine the target area based on the power supply node and acquire the image information of the target area when the power consumption risk rate reaches a preset risk rate threshold.

[0125] The warning information determination module 15 is used to determine the warning information based on the image information and the electricity risk rate.

[0126] Figure 7 This is a structural block diagram of the standard parameter determination module 12 in the intelligent electricity safety management system. The standard parameter determination module 12 includes:

[0127] The classification calculation unit 121 is used to classify the types of electricity users according to the electricity user unit number and calculate the quantity of each type of electricity user unit.

[0128] The parameter classification unit 122 is used to obtain the energy consumption parameters of each type of electricity consumption unit, and determine the energy consumption parameters corresponding to each type of electricity consumption unit based on the energy consumption parameters and the quantity.

[0129] The predicted power consumption calculation unit 123 is used to receive the working time input by the user and calculate the predicted power consumption based on the working time and the energy consumption parameters corresponding to each type of power consumption unit.

[0130] The standard parameter calculation unit 124 is used to determine the enterprise's reference power based on the predicted power, and to determine the standard parameters based on the reference power.

[0131] Furthermore, the standard parameter calculation unit 124 includes:

[0132] The proportion determination subunit is used to obtain holiday information, determine the center time based on the holiday length in the holiday information, and calculate the position proportion of the center time within a year;

[0133] The radius determines the sub-unit, obtains the company's product sales information, determines peak and off-peak season information based on the product sales information, and determines the impact radius of each holiday based on the peak and off-peak season information.

[0134] The correction rate determination subunit is used to determine the holiday table based on the location ratio and the radius of influence, and to determine the correction rate based on the holiday table.

[0135] A reference determination unit is used to determine the reference power of the enterprise based on the correction rate and the predicted power;

[0136] An execution subunit is used to determine standard parameters based on the reference power level.

[0137] All the functions of the intelligent electricity safety management method are performed by computer equipment, which includes one or more processors and one or more memories. The one or more memories store at least one piece of program code, which is loaded and executed by the one or more processors to realize the functions of the intelligent electricity safety management method.

[0138] The processor fetches instructions from memory one by one, analyzes the instructions, and then performs the corresponding operations according to the instructions, generating a series of control commands to enable the various parts of the computer to act automatically, continuously, and in a coordinated manner, forming an organic whole. This enables the input of programs and data, as well as the calculation and output of results. The arithmetic or logical operations generated in this process are all performed by the arithmetic unit. The memory includes a read-only memory (ROM), which is used to store computer programs. The memory is equipped with external protection devices.

[0139] For example, a computer program can be divided into one or more modules, one or more of which are stored in memory and executed by a processor to perform the present invention. The one or more modules can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in a terminal device.

[0140] Those skilled in the art will understand that the above description of the service equipment is merely an example and does not constitute a limitation on the terminal equipment. It may include more or fewer components than described above, or a combination of certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0141] The processor referred to can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. This processor is the control center of the terminal device, connecting various parts of the user terminal via various interfaces and lines.

[0142] The aforementioned memory can be used to store computer programs and / or modules. The aforementioned processor implements various functions of the aforementioned terminal device by running or executing the computer programs and / or modules stored in the memory, and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as information collection template display function, product information publishing function, etc.); the data storage area may store data created based on the use of the berth status display system (such as product information collection templates corresponding to different product types, product information that different product providers need to publish, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0143] If the modules / units integrated into the terminal device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the modules / units in the systems of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the functions of the various system embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0144] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0145] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A smart power utilization safety management method, characterized in that, The method comprises: Receiving a monitoring area input by a user, and obtaining enterprise record information of each enterprise in the area according to a preset information template; the enterprise record information comprises a power consumption unit number item, a power consumption unit type item and a power supply node item; Real-time determining standard parameters of each power supply node in the enterprise according to the enterprise record information; Collecting current data of each power supply node of the enterprise according to a preset collection device, comparing the current data with corresponding standard parameters, and determining a power consumption risk rate of the enterprise; When the power consumption risk rate reaches a preset risk rate threshold, determining a target area according to the power supply node, and obtaining image information of the target area; Determining warning information according to the image information and the power consumption risk rate; The step of real-time determining standard parameters of each power supply node in the enterprise according to the enterprise record information comprises: Classifying power consumption unit types according to power consumption unit numbers, and calculating the number of each power consumption unit type; Obtaining energy consumption parameters of each power consumption unit type, and determining energy consumption parameters corresponding to each power consumption unit type according to the energy consumption parameters and the number; Receiving a working time input by a user, and calculating a predicted power consumption according to the working time and the energy consumption parameters corresponding to each power consumption unit type; Determining a reference power consumption of the enterprise according to the predicted power consumption, and determining standard parameters according to the reference power consumption; The step of determining a reference power consumption of the enterprise according to the predicted power consumption, and determining standard parameters according to the reference power consumption comprises: Obtaining holiday information, determining a central time according to the holiday length in the holiday information, and calculating the position proportion of the central time in one year; Obtaining product sales information of the enterprise, determining off-season and peak-season information according to the product sales information, and determining the influence radius of each holiday according to the off-season and peak-season information; Determining a holiday table according to the position proportion and the influence radius, and determining a correction rate according to the holiday table; Determining the reference power consumption of the enterprise according to the correction rate and the predicted power consumption; Determining standard parameters according to the reference power consumption; The step of determining standard parameters according to the reference power consumption comprises: Obtaining a user unit number corresponding to each power supply node, and querying the power consumption unit type corresponding to the user unit number in the enterprise record information; Reading the energy consumption parameters corresponding to the user unit number according to the power consumption unit type; Counting the energy consumption parameters corresponding to each user unit number to obtain the energy consumption parameters of the power supply node; Determining a distribution proportion according to the energy consumption parameters of different power supply nodes; Calculating the distribution power consumption of each power supply node according to the distribution proportion and the reference power consumption, and determining the standard parameters of the power supply node according to the distribution power consumption; The step of collecting current data of each power supply node of the enterprise according to a preset collection device, comparing the current data with corresponding standard parameters, and determining a power consumption risk rate of the enterprise comprises: Generating a current queue of a preset length; wherein the current queue is in a mapping relationship with each collection device; Sending a preset collection frequency to each collection device, obtaining current data at each power supply node, and inserting the obtained current data into the current queue; Reading the current data in the current queue in turn, comparing the current data with the standard parameters at the power supply node, and obtaining an offset rate; The offset curve is generated according to the offset rate, and the power consumption risk rate is determined according to the offset curve; wherein, the independent variable of the offset curve is time. 2.The smart power utilization safety management method of claim 1, wherein, When the power consumption risk rate reaches the preset risk rate threshold, the target area is determined according to the power supply node, and the image information of the target area is obtained. When the power consumption risk rate reaches the preset risk rate threshold, the power consumption unit number corresponding to the power supply node is read from the enterprise filing information; The location information of the power consumption unit is obtained according to the power consumption unit number, and the target area is determined according to the location information; The image acquisition device in the target area is located, and the image information is obtained based on the image acquisition device. 3.The smart power utilization safety management method of claim 2, wherein, The step of determining the warning information according to the image information and the power consumption risk rate includes: The image information is sorted according to the acquisition time of the image information to obtain a to-be-inspected image library; Each feature value of each to-be-inspected image in the to-be-inspected image library is extracted in turn to obtain a feature array; The mean value of the feature array is calculated in real time, the difference between each feature value and the mean value is calculated, and when the difference reaches a preset difference threshold, the corresponding feature value is marked; The acquisition time of the image information corresponding to the feature value is read, the power consumption risk rate is queried in the offset curve, and the warning information is determined according to the user risk rate.

4. A smart power utilization safety management system, characterized in that, The system includes: The filing information acquisition module is used to receive the monitoring area input by the user, and obtain the enterprise filing information of each enterprise in the area according to a preset information template; the enterprise filing information includes a power consumption unit number item, a power consumption unit type item, and a power supply node item; The standard parameter determination module is used to determine the standard parameters of each power supply node in the enterprise in real time according to the enterprise filing information; The risk rate determination module is used to determine the power consumption risk rate of the enterprise by comparing the current data of each power supply node in the enterprise collected by the preset acquisition device with the corresponding standard parameters; The image information acquisition module is used to determine the target area according to the power supply node when the power consumption risk rate reaches the preset risk rate threshold, and obtain the image information of the target area; The warning information determination module is used to determine the warning information according to the image information and the power consumption risk rate; The standard parameter determination module includes: The classification calculation unit is used to classify the power consumption unit types according to the power consumption unit number, and calculate the number of each type of power consumption unit type; The parameter classification unit is used to obtain the energy consumption parameters of each power consumption unit type, and determine the energy consumption parameters corresponding to each power consumption unit type according to the energy consumption parameters and the number; The predicted power calculation unit is used to receive the working time input by the user, and calculate the predicted power according to the working time and the energy consumption parameters corresponding to each power consumption unit type; The standard parameter calculation unit is used to determine the reference power of the enterprise according to the predicted power, and determine the standard parameters according to the reference power; The standard parameter calculation unit includes: The proportion determination subunit is used to obtain holiday information, determine the center time according to the holiday length in the holiday information, and calculate the position proportion of the center time in one year. The radius determining sub-unit obtains product sales information of the enterprise, determines off-season and peak season information according to the product sales information, and determines an influence radius of each holiday according to the off-season and peak season information; The correction rate determining sub-unit is configured to determine a holiday table according to the location proportion and the influence radius, and determine a correction rate according to the holiday table; The reference determining unit is configured to determine a reference power of the enterprise according to the correction rate and the predicted power; The execution sub-unit is configured to determine a standard parameter according to the reference power; The determining of the standard parameter according to the reference power includes: obtaining a user unit number corresponding to each power supply node, and querying an electricity consumption unit type corresponding to the user unit number in enterprise filing information; reading an energy consumption parameter corresponding to the user unit number according to the electricity consumption unit type; counting the energy consumption parameter corresponding to each user unit number to obtain an energy consumption parameter of the power supply node; determining a distribution proportion according to the energy consumption parameters of different power supply nodes; calculating a distribution power of each power supply node according to the distribution proportion and the reference power, and determining a standard parameter of the power supply node according to the distribution power; The determining of the electricity consumption risk rate of the enterprise according to the current data collected by the preset collection device and the corresponding standard parameter includes: generating a current queue of a preset length; the current queue is in a mapping relationship with each collection device; sending a preset collection frequency to each collection device to obtain current data at each power supply node, and inserting the obtained current data into the current queue; reading the current data in the current queue in sequence, comparing the current data with the standard parameter at the power supply node, and obtaining a deviation rate; generating a deviation curve according to the deviation rate, and determining the electricity consumption risk rate according to the deviation curve; the independent variable of the deviation curve is time.

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