A digital power grid intelligent operation and maintenance system and method based on natural disaster risks

Abstract

The present invention discloses a digital power grid intelligent operation and maintenance system and method based on natural disaster risks. The present invention relates to the field of digital power grid operation and maintenance technology, and solves the problem that when the risk of natural disasters increases, especially in a cold environment, manual inspections are difficult to ensure the safety of transmission lines, and the transmission lines are often covered with ice. When the tensioner tightens the transmission lines, there is a lack of corresponding adjustment, which easily causes the transmission lines to fall off, causing danger. The present invention monitors the temperature and humidity of environmental data in real time, and the system can promptly discover abnormal conditions that may cause damage to power grid facilities. Under low temperature and high humidity conditions, by acquiring and processing key information in real time, the system can promptly adjust the tension of the transmission lines to prevent the transmission lines from falling off due to ice coverage, thereby improving the operational stability and safety of the power grid.

Description

Technical Field

[0001] The present invention relates to the technical field of digital power grid operation and maintenance, and in particular to a digital power grid intelligent operation and maintenance system and method based on natural disaster risks. Background Art

[0002] In modern society, the power system, as an important infrastructure supporting the national economic operation, bears important responsibilities such as power supply guarantee and economic development. At present, the operation of the power system is affected by various factors, such as natural disasters. Traditional transmission line operation and maintenance mainly rely on manual inspection and monitoring equipment. Manual inspection is currently the most commonly used operation and maintenance method. Inspection personnel regularly inspect the transmission line, find fault hazards and deal with them in time.

[0003] However, natural disasters have brought severe challenges to the power grid, especially in cold climates. Traditional power grid operation and maintenance methods mainly rely on manual inspections, which have defects such as low efficiency, limited coverage, and inability to monitor in real time. With the increased risk of natural disasters, especially in cold environments, manual inspections can hardly ensure the safety of transmission lines. Transmission lines are often covered with ice, and the tensioner lacks corresponding adjustments when tightening the transmission lines, which can easily cause the transmission lines to fall off and cause danger. At present, in response to this problem, there is still a lack of a digital power grid intelligent operation and maintenance system and method based on natural disaster risks to effectively monitor the status of transmission lines, detect problems in a timely manner and take measures to ensure the safe operation of the power grid.

[0004] Therefore, in order to solve the above problems, there is an urgent need for a digital power grid intelligent operation and maintenance system and method based on natural disaster risks. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a digital power grid intelligent operation and maintenance system and method based on natural disaster risks, which solves the problems in the background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A digital power grid intelligent operation and maintenance system based on natural disaster risks, comprising:

[0007] The data acquisition module is used to collect environmental data in real time. The environmental data includes temperature information and humidity information. The temperature information and humidity information are obtained by installing temperature sensors and humidity sensors in each grid node and sending the collected environmental data to the data identification module.

[0008] The data recognition module is used to receive the environmental data sent by the data acquisition module and determine whether the environmental data exceeds the threshold. When the threshold is exceeded, a collection signal is generated and the collection signal is sent to the subsequent data acquisition module;

[0009] A data acquisition module, which, at the moment of receiving the acquisition signal, acquires key information in the power grid and sends the key information to the subsequent data processing module. The key information includes: the angle between the insulator string and the transmission wire in the horizontal direction, the angle between the insulator string and the direction perpendicular to the ground, the weight of the electrical hardware, the comprehensive tensile force value of the transmission wire, the vertical distance between the electric poles at both ends of the transmission wire, and the conductor split factor;

[0010] A data processing module, which is used to receive the key information sent by the data acquisition module, determines the deflection angle of the insulator string by extracting the angle between the insulator string and the transmission wire in the horizontal direction and the angle between the insulator string and the direction perpendicular to the ground. Then, it determines the weight of the transmission wire covered with ice by extracting the weight of the electrical hardware and the tensile force value of the transmission wire in the key information. Subsequently, it determines the unit weight of the transmission wire covered with ice by extracting the vertical distance between the electric poles at both ends of the transmission wire and the conductor split factor in the key information. Finally, it calculates the specific ice thickness covered by using a preset formula;

[0011] An adjustment module, which takes the tensile force value of the transmission wire without ice coverage as the basic tensile force value of the transmission wire, acquires the ice thickness covered, establishes a relationship function between the ice thickness covered and the basic tensile force adjustment value, determines the basic tensile force adjustment value, and adjusts the tensile force value of the tensioner to tighten the transmission wire. Then, it judges the tensile force adjusted by the tensioner and decides whether to generate an early warning signal according to the judgment result. When an early warning signal is generated, it sends the early warning signal to the subsequent early warning module.

[0012] Preferably, in the data identification module, determining the generation of the acquisition signal includes the following steps:

[0013] P1: Extract the temperature information in the environmental data, mark it as Wn, judge the temperature information Wn. When Wn < Wt, generate an over-temperature signal, where Wt is a preset threshold;

[0014] P2: Extract the humidity information in the environmental data, mark it as Mn, judge the humidity information Mn. When Mn > Mt, generate a humidity-reached signal, where Mt is a preset threshold.

[0015] Preferably, after step P2, it further includes:

[0016] P3: Real-time acquire the over-temperature signal and the humidity-reached signal. When both the over-temperature signal and the humidity-reached signal are acquired simultaneously, the data identification module generates an acquisition signal and sends it to the subsequent data acquisition module, and does not perform any processing in other cases.

[0017] Preferably, in the data acquisition module, the angle between the insulator string and the transmission line in the horizontal direction and the angle between the insulator string and the vertical ground direction are obtained by sensors installed on the electric poles. The weight of the power fittings is stored in the database in advance before installation. The comprehensive tension value of the transmission line is obtained in real time by measuring with a tension sensor. The vertical distance between the electric poles at both ends of the transmission line is stored in the database in advance based on actual measurements. The conductor splitting coefficient is a preset value and is stored in the database in advance.

[0018] Preferably, in the data processing module, determining the thickness of the ice layer includes the following steps:

[0019] S1: Extract the angle between the insulator string and the horizontal direction of the transmission line and the angle between the insulator string and the vertical direction of the ground from the key information, and record them as θ1 and θ2 respectively. The deflection angle of the insulator string is obtained by the following formula:

[0020]

[0021] Where, θ represents the deflection angle of the insulator string;

[0022] S2: Then extract the weight of the power fittings and the comprehensive tensile force of the transmission line from the key information and record them as R and H respectively. The weight of the transmission line covered with ice is obtained by the following formula:

[0023]

[0024] Where G represents the weight of the transmission line covered with ice;

[0025] S3: Extract the vertical distance between the poles at both ends of the transmission line and the wire splitting coefficient from the key information, and record them as L and x respectively. The unit weight of the transmission line covered with ice is obtained by the following formula:

[0026] K=G÷L÷x

[0027] Wherein, K represents the unit weight of the transmission line covered with ice.

[0028] Preferably, after step S3, the method further includes:

[0029] S4: Then calculate the specific thickness of the ice layer using the following formula:

[0030]

[0031] Wherein, D represents the thickness of the covering ice layer, r represents the radius of the transmission line in the original state, ρ represents the density in the covering ice layer, which is 900 in this embodiment, and Ks represents the unit weight of the transmission line in the original state.

[0032] Preferably, in the adjustment module, generating the warning signal comprises the following steps:

[0033] AS1: Set the transmission line tension value when there is no ice cover as the transmission line basic tension value, marked as F;

[0034] AS2: Then, a functional relationship is established based on the relationship between the thickness of the covering ice layer and the basic tension adjustment value: ΔF=f(D), where ΔF is the basic tension adjustment value;

[0035] AS3: Then, according to the result of Fz=F+ΔF, the tensioner is adjusted to the tension value Fz;

[0036] AS4: And judge the size of Fz and the preset value Fy. When Fz>Fy, generate an early warning signal and send it to the subsequent early warning module. No processing is performed in other cases.

[0037] Preferably, it also includes:

[0038] The early warning module is used to receive early warning signals. After receiving the early warning signals, it will issue an alarm to inform the staff that the overall weight of the ice-covered power transmission wire exceeds the maximum adjustable tension range of the tensioner, and dispatch team members to perform on-site maintenance.

[0039] Preferably, a method for intelligent operation and maintenance of a digital power grid based on natural disaster risks is characterized in that the method is implemented by a digital power grid intelligent operation and maintenance system based on natural disaster risks as described in any one of claims 1-8.

[0040] The present invention provides a digital power grid intelligent operation and maintenance system and method based on natural disaster risks. Compared with the prior art, it has the following beneficial effects:

[0041] (1) The present invention monitors the temperature and humidity of environmental data in real time. The system can promptly detect abnormal conditions that may cause damage to power grid facilities. Under low temperature and high humidity conditions, ice may form on the transmission lines, which will increase the weight of the transmission lines and may also cause the transmission lines to break, thereby causing power supply interruption. By acquiring and processing these key information in real time, the system can promptly adjust the tension of the transmission lines to prevent the transmission lines from falling off due to ice, thereby improving the operational stability and safety of the power grid.

[0042] (2) The present invention can determine the basic tension adjustment value by establishing a relationship function between the thickness of the covering ice layer and the basic tension adjustment value in areas prone to natural disasters. It can also prepare countermeasures in advance by adjusting the tension of the transmission line, thereby improving the disaster resistance of the power grid and ensuring appropriate tension to prevent the transmission line from falling off due to insufficient tension, thereby causing danger. In addition, when the system detects that the tension of the transmission line exceeds the preset value, it will automatically issue an early warning to inform the staff to perform on-site maintenance. This can not only prevent power supply interruptions caused by equipment overload, but also avoid high maintenance costs caused by equipment damage. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The present invention will be further described below in conjunction with the accompanying drawings.

[0044] Figure 1 This is a system framework diagram of a digital power grid intelligent operation and maintenance system based on natural disaster risks of the present invention;

[0045] Figure 2 The present invention provides a flow chart for generating early warning signals for a digital power grid intelligent operation and maintenance system based on natural disaster risks. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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 are within the scope of protection of the present invention.

[0047] Embodiment 1

[0048] See also Figure 1-Figure 2 ,The present invention provides a digital power grid intelligent operation and maintenance system based on natural disaster risks, including;

[0049] The data acquisition module is used to collect environmental data in real time. The environmental data includes temperature information and humidity information. The temperature information and humidity information are obtained by installing temperature sensors and humidity sensors in each grid node and sending the collected environmental data to the data identification module.

[0050] The data recognition module is used to receive the environmental data sent by the data acquisition module and determine whether the environmental data exceeds the threshold. When the threshold is exceeded, a collection signal is generated and the collection signal is sent to the subsequent data acquisition module;

[0051] Determining the generation of the acquisition signal includes the following steps:

[0052] P1: Extract the temperature information from the environmental data, label it as Wn, and judge the temperature information Wn. When Wn < Wt, generate an over-temperature signal, where Wt is a preset threshold, which is specifically set by the staff. In this implementation, Wt is 0°C;

[0053] P2: Extract the humidity information from the environmental data, label it as Mn, and judge the humidity information Mn. When Mn > Mt, generate a humidity-reached signal, where Mt is a preset threshold, which is specifically set by the staff. In this implementation, Mt is 78%;

[0054] P3: Obtain the over-temperature signal and the humidity-reached signal in real time. When both the over-temperature signal and the humidity-reached signal are obtained simultaneously, the data recognition module generates a collection signal and sends it to the subsequent data acquisition module. In other cases, no processing is performed;

[0055] Data acquisition module: At the moment of receiving the collection signal, obtain the key information in the power grid and send the key information to the subsequent data processing module, where the key information includes: the angle between the insulator string and the transmission line in the horizontal direction, the angle between the insulator string and the vertical ground direction, the weight of the electrical fittings, the comprehensive tensile force value of the transmission line, the vertical distance between the electric poles at both ends of the transmission line, and the conductor split factor;

[0056] It should be noted that the angle between the insulator string and the transmission line in the horizontal direction and the angle between the insulator string and the vertical ground direction are obtained by sensors installed on the electric poles. The weight of the electrical fittings is stored in the database in advance before installation and can be obtained by the data acquisition module at any time. The comprehensive tensile force value of the transmission line is obtained in real time by measuring with a tensile force sensor. The vertical distance between the electric poles at both ends of the transmission line is stored in the database in advance according to actual measurement. The conductor split factor is a preset value, which is set by the staff in advance and stored in the database in advance;

[0057] Data processing module: Used to receive the key information sent by the data acquisition module, determine the deflection angle of the insulator string by extracting the angle between the insulator string and the transmission line in the horizontal direction and the angle between the insulator string and the vertical ground direction. Then, determine the weight of the transmission line covered with ice by extracting the weight of the electrical fittings and the tensile force value of the transmission line in the key information. Subsequently, determine the unit weight of the transmission line covered with ice by extracting the vertical distance between the electric poles at both ends of the transmission line and the conductor split factor in the key information. Finally, calculate the specific ice thickness covered by the transmission line through a preset formula;

[0058] Determining the ice thickness covered by the transmission line includes the following steps:

[0059] S1: Extract the angle between the insulator string and the transmission line in the horizontal direction and the angle between the insulator string and the vertical ground direction in the key information, and record them as θ1 and θ2 respectively. Obtain the deflection angle of the insulator string through the following formula:

[0060]

[0061] Where, θ represents the deflection angle of the insulator string;

[0062] S2: Then extract the weight of the power fittings and the comprehensive tensile force of the transmission line from the key information and record them as R and H respectively. The weight of the transmission line covered with ice is obtained by the following formula:

[0063]

[0064] Where G represents the weight of the transmission line covered with ice;

[0065] S3: Extract the vertical distance between the poles at both ends of the transmission line and the wire splitting coefficient from the key information, and record them as L and x respectively. The unit weight of the transmission line covered with ice is obtained by the following formula:

[0066] K=G÷L÷x

[0067] Where K represents the unit weight of the transmission line covered with ice;

[0068] S4: Then calculate the specific thickness of the ice layer using the following formula:

[0069]

[0070] Wherein, D represents the thickness of the covering ice layer, r represents the radius of the transmission line in the original state, ρ represents the density in the covering ice layer, which is taken as 900 in this embodiment, and Ks represents the unit weight of the transmission line in the original state;

[0071] An adjustment module is used to use the tension value of the transmission line when there is no ice cover as the basic tension value of the transmission line, obtain the thickness of the ice cover, establish a relationship function between the thickness of the ice cover and the basic tension adjustment value, determine the basic tension adjustment value, and adjust the tension value of the tensioner to tighten the transmission line, then judge the tension adjusted by the tensioner, and decide whether to generate an early warning signal according to the result of the judgment, and send the early warning signal when the early warning signal is generated;

[0072] The early warning module is used to receive the early warning signal. After receiving the early warning signal, it will issue an alarm to inform the staff that the weight of the ice-covered power transmission wire exceeds the maximum adjustable tension range of the tensioner, and dispatch team members to perform on-site maintenance;

[0073] Embodiment 2

[0074] In the specific implementation process, this embodiment is based on the first embodiment and is different from the first embodiment in that, in the adjustment module, generating the warning signal includes the following steps:

[0075] AS1: Set the transmission line tension value when there is no ice cover as the transmission line basic tension value, marked as F;

[0076] Specifically, the tension value of the transmission line is obtained by a tension sensor installed on the transmission line. Under normal circumstances, the tensioner tightens the transmission line according to the size of the basic tension value;

[0077] AS2: Then, a functional relationship is established based on the relationship between the thickness of the covering ice layer and the basic tension adjustment value: ΔF=f(D), where ΔF is the basic tension adjustment value;

[0078] The specific basic tension adjustment value refers to the additional tension value required when the transmission line is covered with ice;

[0079] AS3: Then, according to the result of Fz=F+ΔF, the tensioner is adjusted to the tension value Fz, so as to ensure the appropriate tension and prevent the transmission line from falling off due to insufficient tension of the tensioner, thus causing danger;

[0080] AS4: Determine the size of Fz and the preset value Fy. When Fz>Fy, generate an early warning signal and send it to the subsequent early warning module. In other cases, no processing is performed. The preset value Fy is set by professionals.

[0081] Embodiment 3

[0082] In the specific implementation process, this embodiment is based on the first and second embodiments, and the difference from the first and second embodiments is that:

[0083] The present invention also provides a technical solution: a digital power grid intelligent operation and maintenance method based on natural disaster risks. The method uses the above-mentioned digital power grid intelligent operation and maintenance system based on natural disaster risks to adjust the tension value of the tensioner of the ice-covered transmission line, so it will not be elaborated here.

[0084] Embodiment 4

[0085] The specific implementation process of this embodiment includes all the implementation processes of the above three groups of embodiments.

[0086] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0087] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A digital power grid intelligent operation and maintenance system based on natural disaster risks, characterized in that: Including: A data acquisition module, which is used to collect environmental data in real time. The environmental data includes temperature information and humidity information. The temperature information and humidity information are obtained by installing temperature sensors and humidity sensors in each power grid node, and the collected environmental data is sent to the data recognition module; A data recognition module, which is used to receive the environmental data sent by the data acquisition module, and determine whether the environmental data exceeds the threshold. When it exceeds the threshold, a collection signal is generated and sent to the subsequent data acquisition module; A data acquisition module, at the moment of receiving the collection signal, obtains the key information in the power grid and sends the key information to the subsequent data processing module. The key information includes: the included angle between the insulator string and the transmission wire in the horizontal direction, the included angle between the insulator string and the vertical ground direction, the weight of the electrical hardware, the comprehensive tensile force value of the transmission wire, the vertical distance between the wire poles at both ends of the transmission wire, and the conductor split coefficient; A data processing module, which is used to receive the key information sent by the data acquisition module, determines the deflection angle of the insulator string by extracting the included angle between the insulator string and the transmission wire in the horizontal direction and the included angle between the insulator string and the vertical ground direction. Then, it determines the weight of the transmission wire covered with ice by extracting the weight of the electrical hardware and the tensile force value of the transmission wire in the key information. Subsequently, it determines the unit weight of the transmission wire covered with ice by extracting the vertical distance between the wire poles at both ends of the transmission wire and the conductor split coefficient in the key information. Finally, the specific ice thickness is calculated through a preset formula; An adjustment module, which uses the tensile force value of the transmission wire without ice coverage as the basic tensile force value of the transmission wire, obtains the ice thickness, establishes a relationship function between the ice thickness and the basic tensile force adjustment value, determines the basic tensile force adjustment value, and adjusts the tensile force value of the tensioner to tighten the transmission wire. Then, it judges the tensile force adjusted by the tensioner and decides whether to generate a warning signal according to the judgment result. When a warning signal is generated, it sends the warning signal to the subsequent warning module; A warning module, which is used to receive the warning signal. After receiving the warning signal, it issues an alarm to inform the staff that the overall weight of the transmission wire covered with ice exceeds the maximum adjustable tensile force range of the tensioner, and dispatches team members for on-site maintenance; In the adjustment module, generating a warning signal includes the following steps: AS1: Set the tensile force value of the transmission wire without ice coverage as the basic tensile force value of the transmission wire, marked as F; AS2: Then, establish a functional relationship through the relationship between the ice thickness and the basic tensile force adjustment value as: ΔF = f(D), where ΔF is the basic tensile force adjustment value; AS3: Subsequently, according to the result of Fz = F + ΔF, adjust the tensioner to the tensile force value Fz; AS4: And judge the magnitude of Fz and the preset value Fy. When Fz > Fy, generate a warning signal and send the warning signal to the subsequent warning module. In other cases, no processing is performed.

2. According to claim 1, a digital power grid intelligent operation and maintenance system based on natural disaster risks is characterized in that: In the data recognition module, determining the generation of a collection signal includes the following steps: P1: Extract the temperature information in the environmental data, marked as Wn, and judge the temperature information Wn. When Wn < Wt, generate an over-temperature signal, where Wt is the preset threshold; P2: Extract humidity information from environmental data, mark it as Mn, judge the humidity information Mn, and generate a humidity signal when Mn>Mt, where Mt is a preset threshold.

3. A digital power grid intelligent operation and maintenance system based on natural disaster risks according to claim 2, characterized in that: After step P2, the following steps are also included: P3: Acquire over-temperature signal and humidity signal in real time. When both over-temperature signal and humidity signal are acquired at the same time, the data recognition module generates a collection signal and sends it to the subsequent data acquisition module. No processing is performed in other cases.

4. A digital power grid intelligent operation and maintenance system based on natural disaster risks according to claim 1, characterized in that: In the data acquisition module, the horizontal angle between the insulator string and the transmission line and the angle between the insulator string and the vertical ground are obtained through sensors installed on the power poles. The weight of the power fittings is stored in the database in advance before installation. The comprehensive tension value of the transmission line is obtained in real time by measuring with a tension sensor. The vertical distance between the power poles at both ends of the transmission line is stored in the database in advance based on actual measurements. The conductor splitting coefficient is a preset value and is stored in the database in advance.

5. A digital power grid intelligent operation and maintenance system based on natural disaster risks according to claim 1, characterized in that: In the data processing module, determining the thickness of the ice cover includes the following steps: S1: Extract the angle between the insulator string and the horizontal direction of the transmission line and the angle between the insulator string and the vertical direction of the ground from the key information, and record them as θ1 and θ2 respectively. The deflection angle of the insulator string is obtained by the following formula: Where, θ represents the deflection angle of the insulator string; S2: Then extract the weight of the power fittings and the comprehensive tensile force of the transmission line from the key information and record them as R and H respectively. The weight of the transmission line covered with ice is obtained by the following formula: Where G represents the weight of the transmission line covered with ice; S3: Extract the vertical distance between the poles at both ends of the transmission line and the conductor splitting coefficient from the key information, and record them as L and x respectively. The unit weight of the transmission line covered with ice is obtained by the following formula: K=G÷L÷x Where K represents the unit weight of the transmission line covered with ice.

6. A digital power grid intelligent operation and maintenance system based on natural disaster risks according to claim 5, characterized in that: After step S3, the method further includes: S4: Then calculate the specific thickness of the ice layer using the following formula: Where D represents the thickness of the covering ice layer, r represents the radius of the transmission line in the original state, ρ represents the density of the covering ice layer, which is 900, and Ks represents the unit weight of the transmission line in the original state.

7. A digital power grid intelligent operation and maintenance method based on natural disaster risks, characterized in that: The method is implemented by a digital power grid intelligent operation and maintenance system based on natural disaster risks as described in any one of claims 1-6.

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