Operation Analysis Method of Distribution Internet of Things Gateway in Weak Network Environment Based on Cloud-Edge Collaboration

Abstract

The present invention discloses an operation analysis method for a distribution Internet of Things gateway in a weak network environment based on cloud-edge collaboration, which relates to the technical field of distribution analysis and includes: obtaining the power demand of a distribution node corresponding to the current gateway based on a cloud-edge collaboration system; matching a suitable superior distribution node; analyzing the power supply influence index of the superior distribution node on the current distribution node; evaluating the distribution influence index of the current distribution node itself; analyzing the power transmission influence index of the subordinate distribution node on the current distribution node; comprehensively analyzing the risk rate existing in the current distribution node; setting a risk threshold, and judging whether the risk rate existing in the current distribution node exceeds the threshold. The advantages of the present invention are as follows: comprehensive analysis and management of all power supply nodes in the power supply network at three levels of up and down are carried out, realizing refined analysis and management of the distribution network.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution analysis, and specifically relates to a method for analyzing the operation of a distribution Internet of Things gateway in a weak network environment based on cloud-edge collaboration. Background Technique

[0002] The distribution network refers to the power grid that receives electric energy from the transmission network or regional power plant and distributes it locally through distribution facilities or step by step according to voltage levels to various users. It is composed of overhead lines, cables, poles, distribution transformers, disconnect switches, reactive power compensators, and some ancillary facilities, etc., and plays an important role in distributing electric energy in the power grid.

[0003] In the management of the distribution network, since the distribution nodes are not only affected by their own factors but also by the upper and lower distribution nodes, their own operating states fluctuate, which leads to difficulties in the power supply and distribution management of the distribution nodes. Therefore, how to comprehensively analyze and manage all the power supply nodes in the power supply network is a technical problem that urgently needs to be solved in this field. Based on this, this solution proposes a method for analyzing the operation of a distribution Internet of Things gateway in a weak network environment based on cloud-edge collaboration. Summary of the Invention

[0004] To solve the above technical problems, a method for analyzing the operation of a distribution Internet of Things gateway in a weak network environment based on cloud-edge collaboration is provided. This technical solution solves the problem that due to the fact that the distribution nodes are not only affected by their own factors but also by the upper and lower distribution nodes, their own operating states fluctuate, which leads to difficulties in the power supply and distribution management of the distribution nodes.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A method for analyzing the operation of a distribution Internet of Things gateway in a weak network environment based on cloud-edge collaboration, including:

[0007] Obtaining the power demand of the distribution node corresponding to the current gateway based on the cloud-edge collaboration system;

[0008] Transmitting the power demand of the distribution node to the cloud-edge collaborative power management system to match a suitable upper-level distribution node;

[0009] Extracting the characteristics of the upper-level distribution node affecting the current distribution node based on the Internet of Things gateway of the upper-level distribution node, and analyzing the power supply influence index of the upper-level distribution node on the current distribution node;

[0010] Evaluating the power distribution influence index of the current distribution node itself based on the power distribution capacity and power distribution load rate of the current distribution node;

[0011] The Internet of Things gateway of the lower-level distribution node based on the current distribution node extracts the characteristics of the lower-level distribution node that affect the current distribution node, and analyzes the power transmission impact index of the lower-level distribution node on the current distribution node;

[0012] Based on the power supply impact index of the upper-level distribution node on the current distribution node, the power distribution impact index of the current distribution node itself, and the power transmission impact index of the lower-level distribution node on the current distribution node, comprehensively analyze the risk rate of the current distribution node;

[0013] Set a risk threshold to determine whether the risk rate of the current distribution node exceeds the threshold. If not, monitor the status of the distribution node in real time based on the cloud-edge collaborative power management system. If so, conduct a risk investigation on the distribution node.

[0014] Preferably, the Internet of Things gateway based on the upper-level distribution node extracts the characteristics of the upper-level distribution node that affect the current distribution node, and the specific analysis of the power supply impact index of the upper-level distribution node on the current distribution node includes:

[0015] Obtain the output power deviation of the upper-level distribution node and analyze the power supply stability index of the upper-level distribution node;

[0016] Based on several characteristic detections of the output power of the upper-level distribution node, obtain the power quality index of the upper-level distribution node;

[0017] According to the operation data of the Internet of Things gateway of the upper-level distribution node, comprehensively analyze the power supply performance of the upper-level distribution node, and score the power supply stability index and power quality index of the upper-level distribution node;

[0018] According to the ratio of the score of each index to the total score, determine the weight of each index;

[0019] Based on the power supply stability index and power quality index of the upper-level distribution node, calculate and analyze the power supply impact index of the upper-level distribution node on the current distribution node.

[0020] Preferably, the calculation expression of the power supply impact index of the upper-level distribution node on the current distribution node is:

[0021] H = A1×W1 + A2×W2

[0022] In the formula, H is the power supply impact index of the upper-level distribution node on the current distribution node, A1 is the power supply stability index of the upper-level distribution node, A2 is the power quality index of the upper-level distribution node, W1 is the weight of the power supply stability index, and W2 is the weight of the power quality index.

[0023] Preferably, the evaluation of the power distribution impact index of the current distribution node itself based on the power distribution capacity and power distribution load rate of the current distribution node specifically includes:

[0024] Set a fixed period, obtain the maximum power distribution of the current power distribution node itself within this period, and record it as the power distribution capacity;

[0025] Obtain the actual power distribution of the current power distribution node according to the current power distribution node supply chain system;

[0026] Calculate the power distribution load rate of the current power distribution node based on the shipping capacity and actual power distribution of the current power distribution node;

[0027] Record several consecutive fixed periods as the sample period, and determine the redundant power of the current power distribution node and the power supply supplement of the current power distribution node within the sample period;

[0028] Calculate the power distribution impact index of the current power distribution node itself through the risk rate calculation formula of the current power distribution node itself.

[0029] Preferably, the power distribution load rate calculation formula is:

[0030]

[0031] In the formula, D is the power distribution load rate, Q 出 is the maximum power distribution of the current power distribution node within the period, Q 实 is the actual power distribution of the current power distribution node;

[0032] Among them, the risk rate calculation formula of the current power distribution node itself is:

[0033]

[0034] In the formula, P is the power distribution impact index of the current power distribution node itself, n is the total number of sample periods, T 流 is the redundant power of the power distribution node, T 入 is the power supply supplement of the power distribution node.

[0035] Preferably, extracting the characteristics of the lower-level power distribution nodes that affect the current power distribution node based on the Internet of Things gateway of the lower-level power distribution nodes of the current power distribution node, and analyzing the power transmission impact index of the lower-level power distribution nodes on the current power distribution node specifically includes:

[0036] Obtain the power distribution of each fixed period of the lower-level power distribution nodes;

[0037] Analyze the power distribution turnover rate and redundant power of the lower-level power distribution nodes according to the power distribution information of the lower-level power distribution nodes;

[0038] Based on the operating status of the lower-level power distribution nodes, judge the failure probability of the lower-level power distribution nodes;

[0039] Based on the power distribution turnover rate, redundant power, and failure probability of each fixed cycle of the lower-level power distribution nodes, analyze and calculate the influence index of the lower-level power distribution nodes on the current power distribution node.

[0040] Preferably, the calculation expression of the influence index of the lower-level power distribution node on the current power distribution node is:

[0041]

[0042] In the formula, U is the power transmission influence index of the lower-level power distribution node on the current power distribution node, O j is the power distribution volume of the jth lower-level power distribution node in each fixed cycle, B j is the failure probability of the jth lower-level power distribution node, K j is the redundant power of the jth lower-level power distribution node, C j is the power distribution turnover rate of the jth lower-level power distribution node, and m is the total number of lower-level power distribution nodes.

[0043] Preferably, based on the power supply influence index of the upper-level power distribution node on the current power distribution node, the power distribution influence index of the current power distribution node itself, and the power transmission influence index of the lower-level power distribution node on the current power distribution node, the specific risks existing in the current power distribution node are comprehensively analyzed as follows:

[0044] Standardize the power supply influence index of the upper-level power distribution node on the current power distribution node, the power distribution influence index of the current power distribution node itself, and the power transmission influence index of the lower-level power distribution node on the current power distribution node to obtain the standardized power supply influence index of the upper-level power distribution node on the current power distribution node, the standardized power distribution influence index of the current power distribution node itself, and the standardized power transmission influence index of the lower-level power distribution node on the current power distribution node;

[0045] Based on each standardized influence index, construct a risk model to predict the risk rate existing in the current power distribution node;

[0046] Among them, the expression of the risk model is:

[0047]

[0048] In the formula, V is the risk rate existing in the current power distribution node, H' is the standardized power supply influence index of the upper-level power distribution node on the current power distribution node, P' is the standardized power distribution influence index of the current power distribution node itself, U' is the standardized power transmission influence index of the lower-level power distribution node on the current power distribution node, β, γ, and δ are model coefficients.

[0049] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0050] The present invention proposes an operation analysis scheme for a distribution IoT gateway in a weak network environment based on cloud-edge collaboration. By analyzing the indicators of the superior distribution nodes affecting the current distribution node and the superior distribution nodes, a risk model is constructed in combination with the current node's own state to predict the operation risks of each distribution node on the distribution network. A threshold is set to judge the predicted risk rate. If the risk threshold is exceeded, a risk investigation of the tertiary nodes is carried out, realizing the refined management of the distribution network. Description of the Drawings

[0051] Figure 1 It is a flowchart of the operation analysis method for a distribution IoT gateway in a weak network environment based on cloud-edge collaboration proposed by the present invention;

[0052] Figure 2 It is a flowchart of the method for analyzing the power supply influence indicators of the superior distribution node on the current distribution node in the present invention;

[0053] Figure 3 It is a flowchart of the method for evaluating the power distribution influence indicators of the current distribution node itself in the present invention;

[0054] Figure 4 It is a flowchart of the method for analyzing the power transmission influence indicators of the inferior distribution node on the current distribution node in the present invention;

[0055] Figure 5 It is a flowchart of the method for comprehensively analyzing the risk rate existing in the current distribution node in the present invention:

[0056] Figure 6 It is a schematic structural diagram of the electronic device of the present invention;

[0057] Figure 7 It is a schematic structural diagram of the computer-readable storage medium of the present invention. Detailed Embodiments

[0058] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments in the following description are only examples, and those skilled in the art can think of other obvious variations.

[0059] Referring to Figure 1 As shown, an operation analysis method for a distribution IoT gateway in a weak network environment based on cloud-edge collaboration includes:

[0060] Obtaining the power demand of the distribution node corresponding to the current gateway based on the cloud-edge collaboration system;

[0061] Transmitting the power demand of the distribution node to the cloud-edge collaborative power management system to match a suitable superior distribution node;

[0062] Based on the Internet of Things gateway of the superior power distribution node, extract the characteristics of the superior power distribution node that affect the current power distribution node, and analyze the power supply impact indicators of the superior power distribution node on the current power distribution node;

[0063] Based on the power distribution capacity and power distribution load rate of the current power distribution node, evaluate the power distribution impact indicators of the current power distribution node itself;

[0064] Based on the Internet of Things gateway of the subordinate power distribution node of the current power distribution node, extract the characteristics of the subordinate power distribution node that affect the current power distribution node, and analyze the power transmission impact indicators of the subordinate power distribution node on the current power distribution node;

[0065] Based on the power supply impact indicators of the superior power distribution node on the current power distribution node, the power distribution impact indicators of the current power distribution node itself, and the power transmission impact indicators of the subordinate power distribution node on the current power distribution node, comprehensively analyze the risk rate of the current power distribution node;

[0066] Set a risk threshold to determine whether the risk rate of the current power distribution node exceeds the threshold. If not, monitor the status of the power distribution node in real time based on the cloud-edge collaborative power management system. If so, conduct a risk investigation on the power distribution node.

[0067] This solution analyzes the superior power distribution node and the indicators of the superior power distribution node that affect the current power distribution node, constructs a risk model in combination with the current node's own status to predict the operation risks of each power distribution node on the power distribution network, sets a threshold to judge the predicted risk rate, and conducts a risk investigation on the tertiary nodes if the risk threshold is exceeded, realizing the refined management of the power distribution network.

[0068] Refer to Figure 2 As shown, the Internet of Things gateway based on the superior power distribution node extracts the characteristics of the superior power distribution node that affect the current power distribution node, and the specific analysis of the power supply impact indicators of the superior power distribution node on the current power distribution node includes:

[0069] Obtain the output power deviation of the superior power distribution node and analyze the power supply stability index of the superior power distribution node;

[0070] Based on several characteristic detections of the output power of the superior power distribution node, obtain the power quality index of the superior power distribution node;

[0071] According to the operation data of the Internet of Things gateway of the superior power distribution node, comprehensively analyze the power supply performance of the superior power distribution node, and score the power supply stability index and power quality index of the superior power distribution node;

[0072] According to the ratio of each index score to the total score, determine the weight of each index;

[0073] Based on the power supply stability index and power quality index of the upper-level distribution node, calculate and analyze the power supply influence index of the upper-level distribution node on the current distribution node.

[0074] The calculation expression of the power supply influence index of the upper-level distribution node on the current distribution node is:

[0075] H = A1 × W1 + A2 × W2

[0076] In the formula, H is the power supply influence index of the upper-level distribution node on the current distribution node, A1 is the power supply stability index of the upper-level distribution node, A2 is the power quality index of the upper-level distribution node, W1 is the weight of the power supply stability index, and W2 is the weight of the power quality index.

[0077] In this solution, by assigning corresponding weights to various power supply stability indexes and power quality indexes, the power distribution influence index of the upper-level node on the current node can be calculated, so as to comprehensively evaluate the upper-level node. This analysis method can comprehensively evaluate the comprehensive state of the upper-level node and provide an important basis for decision-making.

[0078] Refer to Figure 3 As shown, evaluating the power distribution influence index of the current distribution node itself based on the power distribution capacity and power distribution load rate of the current distribution node specifically includes:

[0079] Set a fixed period, and obtain the maximum power distribution amount of the current distribution node itself within this period, denoted as the power distribution capacity;

[0080] Obtain the actual power distribution amount of the current distribution node according to the current distribution node supply chain system;

[0081] Calculate the power distribution load rate of the current distribution node based on the shipping capacity and actual power distribution amount of the current distribution node;

[0082] Denote several consecutive fixed periods as the sample period, and determine the redundant power and power replenishment of the current distribution node within the sample period;

[0083] Calculate the power distribution influence index of the current distribution node itself through the risk rate calculation formula of the current distribution node itself.

[0084] The calculation formula of the power distribution load rate is:

[0085]

[0086] In the formula, D is the power distribution load rate, Q 出 is the maximum power distribution amount of the current distribution node within the period, Q 实 is the actual power distribution amount of the current distribution node;

[0087] Among them, the risk rate calculation formula of the current power distribution node itself is as follows:

[0088]

[0089] In the formula, P is the power distribution influence index of the current power distribution node itself, n is the total number of sample periods, T 流 is the redundant power of the power distribution node, T 入 is the power supply supplement of the power distribution node.

[0090] The actual power distribution amount of this solution can reflect the load status of the node itself, and the power distribution load rate can reflect the utilization degree of the node's own capabilities. Furthermore, the comprehensive operation status of the node itself can be understood, and the power data required from the upper-level node can be determined, avoiding excessive or insufficient energy storage in the node and reducing the power distribution risk of the node.

[0091] Refer to Figure 4 As shown, the IoT gateway of the lower-level power distribution node based on the current power distribution node extracts the characteristics of the lower-level power distribution node that affect the current power distribution node, and the analysis of the power transmission influence index of the lower-level power distribution node on the current power distribution node specifically includes:

[0092] Obtain the power distribution amount of each fixed period of the lower-level power distribution node;

[0093] According to the power distribution information of the lower-level power distribution node, analyze the power distribution turnover rate and redundant power of the lower-level power distribution node;

[0094] Based on the operation status of the lower-level power distribution node, judge the failure probability of the lower-level power distribution node;

[0095] Based on the power distribution turnover rate, redundant power and failure probability of each fixed period of the lower-level power distribution node, analyze and calculate the influence index of the lower-level power distribution node on the current power distribution node.

[0096] The calculation expression of the influence index of the lower-level power distribution node on the current power distribution node is:

[0097]

[0098] In the formula, U is the power transmission influence index of the lower-level power distribution node on the current power distribution node, O j is the power distribution amount of the jth lower-level power distribution node in each fixed period, B j is the failure probability of the jth lower-level power distribution node, K j is the redundant power of the jth lower-level power distribution node, C j is the power distribution turnover rate of the jth lower-level power distribution node, and m is the total number of lower-level power distribution nodes.

[0099] Refer to Figure 5As shown, the comprehensive analysis of the risk rate existing in the current distribution node based on the power supply influence index of the upper-level distribution node on the current distribution node, the distribution influence index of the current distribution node itself, and the power transmission influence index of the lower-level distribution node on the current distribution node specifically includes:

[0100] Standardize the power supply influence index of the upper-level distribution node on the current distribution node, the distribution influence index of the current distribution node itself, and the power transmission influence index of the lower-level distribution node on the current distribution node to obtain the standardized power supply influence index of the upper-level distribution node on the current distribution node, the standardized distribution influence index of the current distribution node itself, and the standardized power transmission influence index of the lower-level distribution node on the current distribution node;

[0101] Based on each standardized influence index, construct a risk model to predict the risk rate existing in the current distribution node;

[0102] Among them, the expression of the risk model is:

[0103]

[0104] In the formula, V is the risk rate existing in the current distribution node, H' is the standardized power supply influence index of the upper-level distribution node on the current distribution node, P' is the standardized distribution influence index of the current distribution node itself, U' is the standardized power transmission influence index of the lower-level distribution node on the current distribution node, β, γ and δ are model coefficients.

[0105] The risk model in this solution is a linear model, which reflects the linear relationship between three independent indicators. The change of each indicator affects the dependent variable in a linear form, and a complex phenomenon is modeled by linearly superimposing the influences of multiple independent variables, which can realize the rapid and accurate pre-identification of the risks of each distribution node in the distribution network.

[0106] Furthermore, the method according to the embodiment of the present application can also be implemented with the help of Figure 6 the architecture of the electronic device shown. As Figure 6 shown, the electronic device 500 may include a bus 501, one or more CPUs 502, a read-only memory (ROM) 503, a random access memory (RAM) 504, a communication port 505 connected to the network, an input / output component 506, a hard disk 507, etc. The storage device in the electronic device 500, such as the ROM 503 or the hard disk 507, may store a method for analyzing the operation of a distribution IoT gateway in a weak network environment based on cloud-edge collaboration provided by the present application. The electronic device 500 may also include a user interface 508. Of course, Figure 6 the architecture shown is only exemplary. When implementing different devices, according to actual needs, it can be omitted Figure 6One or more components in the illustrated electronic device.

[0107] Figure 7 It is a schematic structural diagram of a computer-readable storage medium provided by an embodiment of the present application. As Figure 7 shown, it is a computer-readable storage medium 600 according to an embodiment of the present application. Computer-readable instructions are stored on the computer-readable storage medium 600. When the computer-readable instructions are run by a processor, a method for analyzing the operation of a power distribution IoT gateway in a weak network environment based on cloud-edge collaboration according to an embodiment of the present application described with reference to the above drawings can be executed. The storage medium 600 includes, but is not limited to, for example, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and cache memory, etc. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0108] In summary, the advantages of the present invention are as follows: comprehensive analysis and management of all power supply nodes in the power supply network at three levels up and down are carried out, realizing refined analysis and management of the distribution network.

[0109] The basic principles, main features and advantages of the present invention have been shown and described above. Those skilled in the art should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, various changes and improvements will occur to the present invention, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A distribution Internet of Things gateway operation analysis method in a weak network environment based on cloud-edge collaboration, characterized in that: include: Obtain the power demand of the power distribution node corresponding to the current gateway based on the cloud-edge collaborative system; Transmit the power demand of the distribution node to the cloud-edge collaborative power management system to match the appropriate upper-level distribution node; Based on the IoT gateway of the upper power distribution node, the characteristics of the upper power distribution node affecting the current power distribution node are extracted, and the power supply impact index of the upper power distribution node on the current power distribution node is analyzed; Based on the power distribution capacity and power distribution load rate of the current power distribution node, evaluate the power distribution impact index of the current power distribution node itself; Based on the IoT gateway of the lower-level distribution node of the current distribution node, the characteristics of the lower-level distribution node affecting the current distribution node are extracted, and the transmission impact index of the lower-level distribution node on the current distribution node is analyzed; Based on the power supply impact index of the upper distribution node on the current distribution node, the distribution impact index of the current distribution node itself, and the transmission impact index of the lower distribution node on the current distribution node, the risk rate of the current distribution node is comprehensively analyzed; Set a risk threshold to determine whether the risk rate of the current distribution node exceeds the threshold. If not, monitor the status of the distribution node in real time based on the cloud-edge collaborative power management system. If so, conduct risk investigation on the distribution node. The IoT gateway based on the upper power distribution node extracts the characteristics of the upper power distribution node affecting the current power distribution node, and analyzes the power supply impact index of the upper power distribution node on the current power distribution node, which specifically includes: Obtain the output power deviation of the upper-level distribution node and analyze the power supply stability index of the upper-level distribution node; Based on detecting several characteristics of the output power of the upper distribution node, obtaining the power quality index of the upper distribution node; According to the operation data of the IoT gateway of the upper-level distribution node, the power supply performance of the upper-level distribution node is comprehensively analyzed, and the power supply stability index and power quality index of the upper-level distribution node are scored; Determine the weight of each indicator based on the ratio of each indicator score to the total score; Based on the power supply stability index and power quality index of the upper-level distribution node, the power supply impact index of the upper-level distribution node on the current distribution node is calculated and analyzed; The IoT gateway based on the lower-level distribution node of the current distribution node extracts the characteristics of the lower-level distribution node affecting the current distribution node, and analyzes the transmission impact index of the lower-level distribution node on the current distribution node, specifically including: Obtain the power distribution of the lower-level power distribution node in each fixed period; Analyze the power distribution turnover rate and redundant power of the lower-level power distribution nodes according to the power distribution information of the lower-level power distribution nodes; Based on the operation status of the lower-level distribution nodes, determine the failure probability of the lower-level distribution nodes; Based on the distribution turnover rate, redundant power and failure probability of each fixed cycle of the lower-level distribution node, the transmission impact indicators of the lower-level distribution node on the current distribution node are analyzed and calculated.

2. According to the method of analyzing the operation of power distribution Internet of Things gateway in a weak network environment based on cloud-edge collaboration in claim 1, it is characterized in that: The calculation expression of the power supply impact index of the upper-level distribution node on the current distribution node is: H=A1×W1+A2×W2 Where H is the power supply impact index of the upper distribution node on the current distribution node, A1 is the power supply stability index of the upper distribution node, A2 is the power quality index of the upper distribution node, W1 is the power supply stability index weight, and W2 is the power quality index weight.

3. According to claim 2, a method for analyzing the operation of distribution Internet of Things gateways in a weak network environment based on cloud-edge collaboration is characterized in that: The power distribution impact index of the current power distribution node itself evaluated based on the power distribution capacity and power distribution load rate of the current power distribution node specifically includes: Set a fixed period, obtain the maximum power distribution of the current power distribution node itself within the period, and record it as the power distribution capacity; Obtain the actual power distribution of the current power distribution node according to the current power distribution node supply chain system; Calculate the distribution load rate of the current distribution node based on the delivery capacity and actual distribution capacity of the current distribution node; Record several consecutive fixed periods as sample periods, and determine the redundant power of the current distribution node and the power replenishment of the current distribution node within the sample period; The power distribution impact index of the current power distribution node itself is calculated through the risk rate calculation formula of the current power distribution node itself.

4. According to claim 3, a method for analyzing the operation of distribution Internet of Things gateways in a weak network environment based on cloud-edge collaboration is characterized in that: The distribution load rate calculation formula is: Where D is the distribution load rate, Q 出 is the maximum power distribution of the current power distribution node in the cycle, Q 实 The actual power distribution of the current power distribution node; The risk rate calculation formula of the current power distribution node itself is: Where P is the power distribution impact index of the current power distribution node itself, n is the total number of sample cycles, T 流 is the redundant power of the distribution node, T 入 Replenish the power of the power distribution nodes.

5. According to claim 4, a method for analyzing the operation of distribution Internet of Things gateways in a weak network environment based on cloud-edge collaboration is characterized in that: The calculation expression of the transmission impact index of the lower-level distribution node on the current distribution node is: Where U is the transmission impact index of the lower distribution node on the current distribution node, O j is the power distribution of the jth lower-level power distribution node in each fixed period, B j is the failure probability of the jth lower-level distribution node, K j is the redundant power of the jth lower-level distribution node, C j is the distribution turnover rate of the jth lower-level distribution node, and m is the total number of lower-level distribution nodes.

6. According to claim 5, a method for analyzing the operation of distribution Internet of Things gateways in a weak network environment based on cloud-edge collaboration is characterized in that: The comprehensive analysis of the risk rate of the current distribution node based on the power supply impact index of the upper distribution node on the current distribution node, the distribution impact index of the current distribution node itself, and the transmission impact index of the lower distribution node on the current distribution node specifically includes: The power supply impact index of the upper distribution node on the current distribution node, the distribution impact index of the current distribution node itself, and the transmission impact index of the lower distribution node on the current distribution node are standardized to obtain the standardized power supply impact index of the upper distribution node on the current distribution node, the standardized distribution impact index of the current distribution node itself, and the standardized transmission impact index of the lower distribution node on the current distribution node; Based on various standardized impact indicators, a risk model is constructed to predict the risk rate of the current distribution node; The risk model is expressed as: Where V is the risk rate of the current distribution node, H' is the standardized power supply impact index of the upper distribution node on the current distribution node, P' is the standardized power distribution impact index of the current distribution node itself, and U' is the standardized transmission impact index of the lower distribution node on the current distribution node. β, γ and δ are model coefficients.

7. An electronic device, characterized in that: include: at least one processor; and a memory communicatively connected to the at least one processor, wherein: The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a distribution Internet of Things gateway operation analysis method in a weak network environment based on cloud-edge collaboration as described in any one of claims 1-6.

8. A computer-readable storage medium storing a computer-readable program, characterized in that: When the computer-readable program is executed by the processor, it implements a distribution Internet of Things gateway operation analysis method in a weak network environment based on cloud-edge collaboration as described in any one of claims 1-6.

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