Power performance detection method and device based on Internet of Things, and storage medium

Abstract

The invention discloses a power performance detection method and device based on the Internet of Things, and a storage medium. The method comprises the following steps: acquiring power consumption data of a power internet of things communication channel between power equipment related to the internet of things, and determining an actual power quality early warning index and a voltage frequency regulation control index of the power equipment according to the power consumption data; and determining an actual voltage frequency change correlation detection coefficient according to the actual power quality early warning index and the voltage frequency adjustment control index, and determining a power performance detection result according to the actual voltage frequency change correlation detection coefficient and a preset voltage frequency change correlation detection coefficient. The problems of incomplete information and response lag in power performance detection in related technologies are solved, the stability and reliability of a power system are improved, data support is provided for preventive maintenance of power equipment, and the fault occurrence rate is reduced and the energy utilization efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of power detection technology, and in particular to a power performance detection method, device and storage medium based on the Internet of Things. Background Art

[0002] With the development of Internet of Things technology, more and more power equipment are connected to the network, forming a complex power Internet of Things system. The communication between these devices not only involves data transmission, but also includes energy management and optimization.

[0003] In the related art, the power detection system often relies on sensors at fixed locations and regular data collection. Due to the complexity and dynamics of the power system, the power detection methods in the related art are difficult to meet the requirements of real-time and accuracy, especially when facing power quality problems such as voltage fluctuations and frequency changes. Summary of the invention

[0004] The present invention provides an Internet of Things-based power performance detection method, device and storage medium to solve the problems of incomplete information and delayed response in power performance detection in related technologies.

[0005] According to one aspect of the present invention, there is provided a method for detecting power performance based on the Internet of Things, comprising:

[0006] By collecting power consumption data of the power Internet of Things communication channel between power devices related to the Internet of Things, an actual power quality early warning index and a voltage and frequency regulation control index of the power devices are determined according to the power consumption data;

[0007] An actual voltage-frequency change correlation detection coefficient is determined according to the actual power quality warning index and the voltage-frequency regulation control index, and a power performance detection result is determined according to the actual voltage-frequency change correlation detection coefficient and a preset voltage-frequency change correlation detection coefficient.

[0008] According to another aspect of the present invention, there is provided an Internet of Things-based power performance detection device, comprising:

[0009] A voltage and frequency regulation control index determination module is used to determine an actual power quality warning index and a voltage and frequency regulation control index of the power equipment according to the power consumption data by collecting power consumption data of the power Internet of Things communication channel between power equipment related to the Internet of Things;

[0010] The power performance detection result determination module is used to determine the actual voltage-frequency change correlation detection coefficient according to the actual power quality warning index and the voltage-frequency regulation control index, and determine the power performance detection result according to the actual voltage-frequency change correlation detection coefficient and the preset voltage-frequency change correlation detection coefficient.

[0011] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0012] at least one processor; and

[0013] a memory communicatively connected to the at least one processor; wherein,

[0014] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the power performance detection method based on the Internet of Things described in any embodiment of the present invention.

[0015] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the power performance detection method based on the Internet of Things described in any embodiment of the present invention when executed.

[0016] According to another aspect of the present invention, the embodiments of the present disclosure further provide a computer program product, including a computer program, which, when executed by a processor, implements the power performance detection method based on the Internet of Things as described in any one of the embodiments of the present disclosure.

[0017] The technical solution of the embodiment of the present invention, first, by collecting power consumption data of the power Internet of Things communication channel between power equipment related to the Internet of Things, the actual power quality warning index and the voltage and frequency regulation control index of the power equipment are determined according to the power consumption data, so that the actual operating status of the power equipment can be determined in real time; then, the actual voltage-frequency change correlation detection coefficient is determined according to the actual power quality warning index and the voltage-frequency regulation control index, and the power performance detection result is determined according to the actual voltage-frequency change correlation detection coefficient and the preset voltage-frequency change correlation detection coefficient, so that the change of power system performance can be discovered in time, which solves the problems of incomplete information and delayed response in power performance detection in related technologies, not only improves the stability and reliability of the power system, but also provides data support for preventive maintenance of power equipment, which helps to reduce the occurrence of failures and improve energy utilization efficiency.

[0018] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 is a flow chart of a power performance detection method based on the Internet of Things provided according to Embodiment 1 of the present invention;

[0021] Figure 2 is a flow chart of a power performance detection method based on the Internet of Things provided according to Embodiment 2 of the present invention;

[0022] Figure 3 is a flow chart of a power performance detection method based on the Internet of Things provided according to Embodiment 3 of the present invention;

[0023] Figure 4 1 is a schematic diagram of the structure of an Internet of Things-based power performance detection device provided according to Embodiment 4 of the present invention;

[0024] Figure 5 It is a structural schematic diagram of an electronic device that implements the power performance detection method based on the Internet of Things according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0027] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0028] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0029] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0030] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0031] As an optional but non-limiting implementation, in response to receiving an active request from the user, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0032] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet the relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0033] It is understandable that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and relevant provisions.

[0034] Embodiment 1

[0035] Figure 1 A flowchart of an Internet of Things-based power performance detection method is provided for Embodiment 1 of the present invention. This embodiment is applicable to real-time detection and optimal management of power equipment in a smart grid. The method can be performed by an Internet of Things-based power performance detection device, which can be implemented in the form of hardware and / or software. Optionally, it can be implemented by an electronic device, which can be a mobile terminal, a PC or a server, etc.

[0036] like Figure 1 As shown, the method may specifically include:

[0037] S110, by collecting power consumption data of the power Internet of Things communication channel between power devices related to the Internet of Things, determining the actual power quality warning index and voltage and frequency regulation control index of the power equipment according to the power consumption data.

[0038] Among them, the power Internet of Things communication channel can be understood as a communication line or network used to connect different power devices, so that the power devices can exchange data through the Internet protocol. The power consumption data can be understood as information collected from power equipment about but not limited to the consumption of electrical energy, including but not limited to at least one of instantaneous power and accumulated power, which can be used to evaluate the working status of the equipment and efficiency and other influences. The actual power quality warning index can be understood as an indicator to measure the quality of power supply, which is used to reflect factors such as voltage stability and waveform distortion. The voltage frequency regulation control index can be understood as the ability of the power equipment to keep the voltage frequency within the specified range, which can ensure the safe and stable operation of the power equipment and avoid equipment damage and performance degradation caused by excessive or low voltage and frequency fluctuations.

[0039] On the basis of the above scheme, optionally, the collection of power consumption data of the power Internet of Things communication channel between power devices related to the Internet of Things may include: collecting power consumption data by acquiring an electric meter or power sensor installed on the target power device; or deploying a network proxy service at a target node in the power device, and collecting power consumption data at preset time intervals through the network proxy service; or, pulling power consumption data from network devices and servers through a network management protocol; or, acquiring power consumption data by calling a preset data acquisition interface, etc.

[0040] S120. Determine an actual voltage-frequency change correlation detection coefficient according to the actual power quality warning index and the voltage-frequency regulation control index, and determine a power performance detection result according to the actual voltage-frequency change correlation detection coefficient and a preset voltage-frequency change correlation detection coefficient.

[0041] Among them, the actual voltage-frequency change correlation detection coefficient can be understood as a parameter used to quantify the relationship between voltage changes and frequency changes, and can be used to determine the interaction relationship between the actual power quality warning index and the voltage-frequency regulation control index. The preset voltage-frequency change correlation detection coefficient can be understood as a standard value set according to historical data or theoretical models, which is used to compare the actual voltage-frequency change correlation detection coefficient to determine whether the current operating status of the power system deviates from the expected standard. The power performance test result can be understood as an evaluation result obtained based on the actual voltage-frequency change correlation detection coefficient and the preset voltage-frequency change correlation detection coefficient, which is used to evaluate the health status and service level of power equipment.

[0042] On the basis of the above scheme, optionally, the actual voltage-frequency change correlation detection coefficient can be determined according to the actual power quality warning index and the voltage-frequency regulation control index by the following formula:

[0043]

[0044]

[0045] Among them, θ represents the actual voltage frequency change correlation detection coefficient, α i It is expressed as the actual power quality warning index of the i-th power equipment, β i It is represented by the power system voltage and frequency regulation control index of the i-th power equipment, Δα is represented by the mean value of the power quality warning index, Δβ is represented by the mean value of the power system voltage and frequency regulation control index, and n is represented by the number of power equipment.

[0046] The technical solution of the embodiment of the present invention, first, by collecting power consumption data of the power Internet of Things communication channel between power equipment related to the Internet of Things, the actual power quality warning index and the voltage and frequency regulation control index of the power equipment are determined according to the power consumption data, so that the actual operating status of the power equipment can be determined in real time; then, the actual voltage-frequency change correlation detection coefficient is determined according to the actual power quality warning index and the voltage-frequency regulation control index, and the power performance detection result is determined according to the actual voltage-frequency change correlation detection coefficient and the preset voltage-frequency change correlation detection coefficient, so that the change of power system performance can be discovered in time, which solves the problems of incomplete information and delayed response in power performance detection in related technologies, not only improves the stability and reliability of the power system, but also provides data support for preventive maintenance of power equipment, which helps to reduce the occurrence of failures and improve energy utilization efficiency.

[0047] Embodiment 2

[0048] Figure 2 A flow chart of an Internet of Things-based power performance detection method provided in Embodiment 2 of the present invention, this embodiment is based on the above embodiments, and further refines how to determine the actual power quality warning index of the power equipment according to the power consumption data. Optionally, the actual power quality warning index of the power equipment determined according to the power consumption data includes: determining the generator speed response deviation of the power Internet of Things communication channel according to the power consumption data, and determining the actual power quality warning index according to the generator speed response deviation. For specific implementation methods, please refer to the description of this embodiment. Among them, the technical features that are the same or similar to the above embodiments are not repeated here.

[0049] like Figure 2 As shown, the method may specifically include:

[0050] S210, by collecting power consumption data of the power Internet of Things communication channel between power equipment related to the Internet of Things, determining the generator speed response deviation of the power Internet of Things communication channel according to the power consumption data, determining the actual power quality warning index according to the generator speed response deviation, and determining the voltage and frequency regulation control index according to the power consumption data.

[0051] The generator speed response deviation can be understood as the difference between the actual generator speed and the expected or set generator speed. In this embodiment, the generator speed is one of the key factors affecting the power output frequency. When the load changes, the generator cannot quickly adjust its speed to maintain a constant output frequency, which will produce a generator speed response deviation. The generator speed response deviation can be used to evaluate the performance and stability of the generator.

[0052] On the basis of the above scheme, optionally, the power consumption data includes at least generator speed data, voltage data and current data; the generator speed response deviation of the power Internet of Things communication channel is determined according to the power consumption data by the following formula:

[0053]

[0054] in, It is expressed as the generator speed response deviation of the ith power equipment and the ith power IoT communication channel, It is represented by the generator speed of the jth power IoT communication channel of the i-th power device, HV i 阈 It is expressed as the threshold value of the generator speed of the i-th power equipment, It is represented as the voltage of the jth power IoT communication channel of the i-th power device, It is represented by the current of the jth power IoT communication channel of the i-th power device, HY i 阈 It is represented as the voltage threshold of the i-th power device, It is represented as the threshold value of the current of the i-th power device.

[0055] The generator speed threshold may be understood as a preset target speed value, and the generator speed should be kept close to the threshold as much as possible to ensure the stability and efficiency of the power equipment.

[0056] On the basis of the above solution, optionally, the power quality warning index is determined according to the generator speed response deviation by the following formula:

[0057]

[0058] Among them, α i It is represented as the power quality early warning index of the ith power equipment, It is expressed as the maximum value of the generator speed response deviation of the i-th power equipment, It is expressed as the minimum value of the generator speed response deviation of the i-th power equipment, The generator speed of the jth generator of the i-th power equipment, ΔPX i It is represented by the mean value of the generator speed response deviation, λ1 is represented by the influencing factor of the generator speed response deviation, m is represented by the number of power Internet of Things communication channels, n represents the number of electrical equipment.

[0059] The generator speed response deviation influencing factor can be understood as a factor for adjusting the influence of the generator speed response deviation on the power quality warning index. By setting different λ1, the influence of the generator speed response deviation on the power quality warning index can be emphasized or weakened according to the needs.

[0060] S220. Determine an actual voltage-frequency change correlation detection coefficient according to the actual power quality warning index and the voltage-frequency regulation control index, and determine a power performance detection result according to the actual voltage-frequency change correlation detection coefficient and a preset voltage-frequency change correlation detection coefficient.

[0061] The technical solution of the embodiment of the present invention collects detailed power consumption data (including generator speed, voltage, current, power loss and power factor), calculates the generator speed response deviation, and determines the power quality early warning index based on this, thereby realizing real-time detection of the operating status of power equipment, being able to give early warning of potential power quality problems, and ensuring the stability and reliability of the power system.

[0062] Embodiment 3

[0063] Figure 3 A flowchart of an Internet of Things-based power performance detection method is provided for the third embodiment of the present invention. This embodiment is based on the above embodiments and further refines how to determine the voltage and frequency regulation control index of the power equipment according to the power consumption data. Optionally, the voltage and frequency regulation control index of the power equipment is determined according to the power consumption data, including: determining the generator power utilization of the power Internet of Things communication channel according to the power consumption data, and determining the voltage and frequency regulation control index according to the generator power utilization. For specific implementation methods, please refer to the description of this embodiment. Among them, the technical features that are the same or similar to the above embodiments are not repeated here.

[0064] S310, by collecting power consumption data of the power Internet of Things communication channel between power equipment related to the Internet of Things, determining the actual power quality warning index of the power equipment according to the power consumption data, and determining the generator power utilization degree of the power Internet of Things communication channel according to the power consumption data, and determining the voltage and frequency regulation control index according to the generator power utilization degree.

[0065] The generator power utilization degree can be understood as indicating the effective utilization rate of the generator output power, reflecting the efficiency of the generator in converting mechanical energy into electrical energy, as well as the loss of the generated electrical energy during transmission and use.

[0066] On the basis of the above scheme, optionally, the power consumption data includes at least generator speed data, power loss data and power factor; the generator power utilization degree of the power Internet of Things communication channel is determined according to the power consumption data by the following formula:

[0067]

[0068] Among them, PD i j It is expressed as the utilization degree of generator power in the jth power IoT communication channel of the i-th power equipment, It is represented as the power loss of the jth power IoT communication channel of the i-th power device, It is expressed as the power factor of the jth power IoT communication channel of the i-th power device, It is expressed as the generator speed of the jth power IoT communication channel of the i-th power device.

[0069] The power factor can be understood as an indicator that measures the ratio of the effective power actually consumed in the power Internet of Things communication channel to the total reactive power. In this embodiment, the power factor ranges from 0 to 1. When the power factor is 1, all input electrical energy is effectively utilized; when the power factor is lower than 1, it indicates that there is reactive power, that is, electrical energy that is not effectively utilized, which increases the current demand and causes additional line losses.

[0070] Based on the above solution, optionally, the voltage-frequency regulation control index is determined according to the power utilization degree of the generator by the following formula:

[0071]

[0072] Among them, β i It is represented as the power system voltage and frequency regulation control index of the i-th power equipment, It is expressed as the minimum value of the generator power utilization of the i-th power equipment, It is expressed as the maximum value of the generator power utilization of the i-th power equipment, PD i 预 It represents the preset generator power utilization degree of the i-th power equipment, and λ2 represents the influencing factor of the generator power utilization degree.

[0073] The influencing factor of the generator power utilization can be understood as the factor used to adjust the influence of the generator power utilization on the voltage-frequency regulation control index. By setting different λ2, the influence of the generator power utilization on the voltage-frequency regulation control index can be emphasized or weakened according to the needs.

[0074] S320. Determine an actual voltage-frequency change correlation detection coefficient according to the actual power quality warning index and the voltage-frequency regulation control index, and determine a power performance detection result according to the actual voltage-frequency change correlation detection coefficient and a preset voltage-frequency change correlation detection coefficient.

[0075] The technical solution of the embodiment of the present invention collects power consumption data, calculates the power utilization of the generator, and determines the voltage and frequency regulation control index accordingly, thereby realizing real-time detection and evaluation of the operating status of the power equipment and ensuring the efficient and stable operation of the power system.

[0076] Embodiment 4

[0077] Figure 4 This is a schematic diagram of the structure of a power performance detection device based on the Internet of Things provided by the fourth embodiment of the present invention. Figure 4 As shown, the device includes: a voltage and frequency regulation control index determination module 410 and a power performance detection result determination module 420. Among them,

[0078] The voltage-frequency regulation control index determination module 410 is used to determine the actual power quality warning index and the voltage-frequency regulation control index of the power equipment according to the power consumption data collected through the power Internet of Things communication channel between power equipment related to the Internet of Things; the power performance detection result determination module 420 is used to determine the actual voltage-frequency change correlation detection coefficient according to the actual power quality warning index and the voltage-frequency regulation control index, and determine the power performance detection result according to the actual voltage-frequency change correlation detection coefficient and the preset voltage-frequency change correlation detection coefficient.

[0079] The technical solution of the embodiment of the present invention is as follows: first, the power consumption data of the power Internet of Things communication channel between the power equipment related to the Internet of Things is collected through the voltage and frequency regulation control index determination module 410, and the actual power quality warning index and the voltage and frequency regulation control index of the power equipment are determined according to the power consumption data, so that the actual operation status of the power equipment can be determined in real time; then, the actual voltage-frequency change correlation detection coefficient is determined according to the actual power quality warning index and the voltage and frequency regulation control index through the power performance detection result determination module 420, and the power performance detection result is determined according to the actual voltage-frequency change correlation detection coefficient and the preset voltage-frequency change correlation detection coefficient, so that the change of the power system performance can be discovered in time, which solves the problems of incomplete information and delayed response in power performance detection in the related technology, and not only improves the stability and reliability of the power system, but also provides data support for the preventive maintenance of power equipment, which helps to reduce the occurrence rate of failures and improve energy utilization efficiency.

[0080] On the basis of the above scheme, optionally, the voltage and frequency regulation control index determination module includes: an actual power quality early warning index determination submodule. The actual power quality early warning index determination submodule is used to determine the generator speed response deviation of the power Internet of Things communication channel according to the power consumption data, and determine the actual power quality early warning index according to the generator speed response deviation.

[0081] On the basis of the above scheme, optionally, the power consumption data includes at least generator speed data, voltage data and current data; the generator speed response deviation of the power Internet of Things communication channel is determined according to the power consumption data by the following formula:

[0082]

[0083] in, It is expressed as the generator speed response deviation of the ith power equipment and the ith power IoT communication channel, It is represented by the generator speed of the jth power IoT communication channel of the i-th power device, HV i 阈 It is expressed as the threshold value of the generator speed of the i-th power equipment, It is represented as the voltage of the jth power IoT communication channel of the i-th power device, It is represented by the current of the jth power IoT communication channel of the i-th power device, HY i 阈 It is represented as the voltage threshold of the i-th power device, It is represented as the threshold value of the current of the i-th power device.

[0084] On the basis of the above solution, optionally, the actual power quality warning index can be determined according to the generator speed response deviation by the following formula:

[0085]

[0086] Among them, α i It is expressed as the actual power quality warning index of the ith power equipment, PX i max It is expressed as the maximum value of the generator speed response deviation of the i-th power equipment, It is expressed as the minimum value of the generator speed response deviation of the i-th power equipment, The generator speed of the jth generator of the i-th power equipment, ΔPX i It is represented by the mean value of the generator speed response deviation, λ1 is represented by the influencing factor of the generator speed response deviation, m is represented by the number of power Internet of Things communication channels, n represents the number of electrical equipment.

[0087] On the basis of the above scheme, optionally, the voltage-frequency regulation control index determination module includes: a voltage-frequency regulation control index determination submodule. The voltage-frequency regulation control index submodule is used to determine the generator power utilization degree of the power Internet of Things communication channel according to the power power consumption data, and determine the voltage-frequency regulation control index according to the generator power utilization degree.

[0088] On the basis of the above scheme, optionally, the power consumption data includes at least generator speed data, power loss data and power factor; the generator power utilization degree of the power Internet of Things communication channel is determined according to the power consumption data by the following formula:

[0089]

[0090] in, It is expressed as the utilization degree of generator power in the jth power IoT communication channel of the i-th power equipment, It is represented as the power loss of the jth power IoT communication channel of the i-th power device, It is expressed as the power factor of the jth power IoT communication channel of the i-th power device, It is expressed as the generator speed of the jth power IoT communication channel of the i-th power device.

[0091] Based on the above solution, optionally, the voltage-frequency regulation control index can be determined according to the power utilization degree of the generator by the following formula:

[0092]

[0093] Among them, β i It is represented as the power system voltage and frequency regulation control index of the i-th power equipment, It is expressed as the minimum value of the generator power utilization of the i-th power equipment, It is expressed as the maximum value of the generator power utilization of the i-th power equipment, PD i 预 It represents the preset generator power utilization degree of the i-th power equipment, and λ2 represents the influencing factor of the generator power utilization degree.

[0094] On the basis of the above solution, optionally, the actual voltage-frequency change correlation detection coefficient is determined according to the actual power quality warning index and the voltage-frequency regulation control index by the following formula:

[0095]

[0096] Among them, θ represents the actual voltage frequency change correlation detection coefficient, αi It is expressed as the actual power quality warning index of the i-th power equipment, β i It is represented by the power system voltage and frequency regulation control index of the i-th power equipment, Δα is represented by the mean value of the power quality warning index, Δβ is represented by the mean value of the power system voltage and frequency regulation control index, and n is represented by the number of power equipment.

[0097] The Internet of Things-based power performance detection device provided in the embodiment of the present invention can execute the Internet of Things-based power performance detection method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0098] Embodiment 5

[0099] Figure 5 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0100] like Figure 5 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0101] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0102] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a power performance detection method based on the Internet of Things.

[0103] In some embodiments, a method for detecting power performance based on the Internet of Things may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method for detecting power performance based on the Internet of Things described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform a method for detecting power performance based on the Internet of Things in any other appropriate manner (e.g., by means of firmware).

[0104] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0105] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0106] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0107] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0108] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0109] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0110] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0111] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A power performance detection method based on the Internet of Things, characterized in that: include: By collecting power consumption data of the power Internet of Things communication channel between power devices related to the Internet of Things, an actual power quality early warning index and a voltage and frequency regulation control index of the power devices are determined according to the power consumption data; An actual voltage-frequency change correlation detection coefficient is determined according to the actual power quality warning index and the voltage-frequency regulation control index, and a power performance detection result is determined according to the actual voltage-frequency change correlation detection coefficient and a preset voltage-frequency change correlation detection coefficient.

2. The power performance detection method based on the Internet of Things according to claim 1 is characterized in that: Determining the actual power quality warning index of the power equipment according to the power consumption data includes: The generator speed response deviation of the power Internet of Things communication channel is determined according to the power power consumption data, and the actual power quality early warning index is determined according to the generator speed response deviation.

3. The power performance detection method based on the Internet of Things according to claim 2 is characterized in that: The power consumption data at least includes generator speed data, voltage data and current data; the generator speed response deviation of the power Internet of Things communication channel is determined according to the power consumption data by the following formula: in, It is expressed as the generator speed response deviation of the ith power equipment and the ith power IoT communication channel, It is represented by the generator speed of the jth power IoT communication channel of the i-th power device, HV i 阈 It is expressed as the threshold value of the generator speed of the i-th power equipment, It is represented as the voltage of the jth power IoT communication channel of the i-th power device, It is represented by the current of the jth power IoT communication channel of the i-th power device, HY i 阈 It is represented as the voltage threshold of the i-th power device, It is represented as the threshold value of the current of the i-th power device.

4. The power performance detection method based on the Internet of Things according to claim 2 is characterized in that: The power quality warning index is determined according to the generator speed response deviation by the following formula: Among them, α i It is represented as the power quality early warning index of the ith power equipment, It is expressed as the maximum value of the generator speed response deviation of the i-th power equipment, It is expressed as the minimum value of the generator speed response deviation of the i-th power equipment, The generator speed of the jth generator of the i-th power equipment, ΔPX i It is represented by the mean value of the generator speed response deviation, λ1 is represented by the influencing factor of the generator speed response deviation, m is represented by the number of power Internet of Things communication channels, n represents the number of electrical equipment.

5. The power performance detection method based on the Internet of Things according to claim 1 is characterized in that: The step of determining the voltage and frequency regulation control index of the electric power equipment according to the power consumption data comprises: The generator power utilization degree of the power Internet of Things communication channel is determined according to the power power consumption data, and the voltage and frequency regulation control index is determined according to the generator power utilization degree.

6. The power performance detection system based on the Internet of Things according to claim 5 is characterized in that: The power consumption data at least includes generator speed data, power loss data and power factor; the generator power utilization of the power Internet of Things communication channel is determined according to the power consumption data by the following formula: in, It is expressed as the utilization degree of generator power in the jth power IoT communication channel of the i-th power equipment, It is represented as the power loss of the jth power IoT communication channel of the i-th power device, It is expressed as the power factor of the jth power IoT communication channel of the i-th power device, It is expressed as the generator speed of the jth power IoT communication channel of the i-th power device.

7. The power performance detection system based on the Internet of Things according to claim 6 is characterized in that: The voltage and frequency regulation control index is determined according to the power utilization degree of the generator by the following formula: Among them, β i It is represented as the power system voltage and frequency regulation control index of the i-th power equipment, It is expressed as the minimum value of the generator power utilization of the i-th power equipment, It is expressed as the maximum value of the generator power utilization of the i-th power equipment, It represents the preset generator power utilization degree of the i-th power equipment, and λ2 represents the influencing factor of the generator power utilization degree.

8. The power performance detection system based on the Internet of Things according to claim 1 is characterized in that: The actual voltage-frequency change correlation detection coefficient is determined according to the actual power quality warning index and the voltage-frequency regulation control index by the following formula: Among them, θ represents the actual voltage frequency change correlation detection coefficient, α i It is expressed as the actual power quality warning index of the i-th power equipment, β i It is represented by the power system voltage and frequency regulation control index of the i-th power equipment, Δα is represented by the mean value of the power quality warning index, Δβ is represented by the mean value of the power system voltage and frequency regulation control index, and n is represented by the number of power equipment.

9. An electric power performance detection device based on the Internet of Things, characterized in that: include: A voltage and frequency regulation control index determination module is used to determine an actual power quality warning index and a voltage and frequency regulation control index of the power equipment according to the power consumption data by collecting power consumption data of the power Internet of Things communication channel between power equipment related to the Internet of Things; The power performance detection result determination module determines the actual voltage-frequency change correlation detection coefficient according to the actual power quality warning index and the voltage-frequency regulation control index, and determines the power performance detection result according to the actual voltage-frequency change correlation detection coefficient and the preset voltage-frequency change correlation detection coefficient.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the power performance detection method based on the Internet of Things as described in any one of claims 1-8 when executed.

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