Active power distribution network fault risk assessment system and method

Abstract

The invention discloses an active power distribution network fault risk assessment system and method, and relates to the technical field of power distribution network operation risk assessment, and the system comprises a natural environment data collection module, an environment risk assessment model construction module, and an environment risk assessment module. On the basis of historical data analysis and trend prediction functions, by analyzing historical meteorological data, geological disaster record data and historical fault records of the power distribution network, the current fault risk of the power distribution network can be accurately evaluated, and by predicting the change of environmental factors in a period of time in the future, the power distribution network fault risk can be accurately evaluated. And the prediction data are substituted into the risk calculation model to assess the possible fault risk of the power distribution network in the future according to the change trends of the rainfall, the wind speed, the temperature, the humidity and the water level. Therefore, the timeliness and accuracy of risk assessment are ensured, and more time is provided for the operation of the power grid to take preventive measures.

Description

Technical Field

[0001] The present invention relates to the field of distribution network operation risk assessment, and in particular to an active distribution network fault risk assessment system and method. Background Art

[0002] Under the background of energy transformation, active distribution network is becoming an important part of modern power system. It not only carries the task of transmitting traditional electricity, but also undertakes the task of absorbing distributed renewable energy. With the intensification of global climate change trend, the frequency and intensity of extreme weather events are increasing, which poses a severe challenge to the operational reliability and stability of active distribution network. Various power facilities in active distribution network, such as substations, distribution lines and equipment, distributed power sources, energy storage facilities, etc., are often located outdoors, directly exposed to various natural environments, and are more susceptible to severe weather conditions; the drastic changes in the natural environment are increasingly threatening the stable operation of active distribution network.

[0003] Conventional distribution network fault warning systems provide early warnings for various potential faults of distribution equipment by monitoring various operating parameters of distribution equipment, such as voltage, current, SF6 gas density and other indicators. However, these systems often ignore the direct impact of external environmental factors on the safety of distribution networks. This limitation leads to incomplete risk assessment models and insufficient assessments. Especially in the face of sudden natural disasters, the risk level cannot be assessed in a timely manner, which greatly reduces the effectiveness of the warning. Moreover, due to the lack of in-depth understanding of environmental factors and dynamic prediction capabilities, traditional assessment methods are difficult to make accurate fault predictions before extreme weather arrives, which not only limits the ability of power grid operators to take preventive measures, but also greatly increases the cost and time of fault repair.

[0004] In summary, the traditional distribution network fault risk warning system seems to be powerless in the face of complex and changeable natural environments and cannot effectively cope with the challenges brought by extreme weather and natural disasters. Therefore, it is particularly important to develop an active distribution network fault risk assessment system and method that can comprehensively consider environmental factors, achieve timely warning and rapid response. Summary of the invention

[0005] The present invention provides an active distribution network fault risk assessment system and method to solve the problem of poor effectiveness of assessment results in the prior art distribution network fault early warning system that implements risk assessment based on distribution network operating parameters.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] An active distribution network fault risk assessment system includes a natural environment data acquisition module, an environmental risk assessment model construction module, and an environmental risk assessment module, wherein:

[0008] The natural environment data acquisition module collects historical meteorological data, historical geological disaster record data, and active power distribution network fault data corresponding to the historical time period, and sends them to the environmental risk assessment model construction module;

[0009] The environmental risk assessment model building module extracts key features of environmental factors from the received historical meteorological data and historical geological disaster record data, and combines the active distribution network failure data of the corresponding historical time period to determine the degree of influence of the extracted key features of environmental factors on the active distribution network failure risk, thereby assigning corresponding weight values ​​to each key feature of environmental factors, and establishing a risk assessment model in combination with the key features of environmental factors and the corresponding weight values;

[0010] The environmental risk assessment module obtains current meteorological data and geological disaster record data, extracts key features of environmental factors from them, substitutes them into the risk assessment model, calculates the current fault risk value through the risk assessment model, and completes the risk assessment.

[0011] Furthermore, the key features of the environmental factors include data such as rainfall, wind speed, temperature and humidity extracted from meteorological data, and flood and mudslide data extracted from geological disaster record data.

[0012] Furthermore, the environmental risk assessment module sets a plurality of risk value intervals corresponding to different risk levels, and matches the calculated current fault risk value with each risk value interval, thereby determining the current risk level.

[0013] Furthermore, the environmental risk assessment module also combines the key characteristics of environmental factors extracted from historical meteorological data and the key characteristics of environmental factors extracted from current meteorological data to predict the key characteristics of environmental factors in the future; then the environmental risk assessment module substitutes the key characteristics of future environmental factors into the risk assessment model to predict future failure risk values.

[0014] An active distribution network fault risk assessment method based on the above active distribution network fault risk assessment system comprises the following steps:

[0015] Step S100, obtaining historical meteorological data, historical geological disaster record data, and active distribution network fault data corresponding to the historical time period;

[0016] Step S200, extracting key features of environmental factors from historical meteorological data and historical geological disaster record data, and combining them with active distribution network failure data of the corresponding historical time period, determining the degree of influence of the extracted key features of environmental factors on the failure risk of the active distribution network, thereby assigning corresponding weight values ​​to each key feature of environmental factors, and establishing a risk assessment model in combination with the key features of environmental factors and the corresponding weight values;

[0017] Step S300, obtain current meteorological data and geological disaster record data, extract key characteristics of environmental factors from the current meteorological data and geological disaster record data, and then input them into the risk assessment model, and calculate the current fault risk value of the active distribution network through the risk assessment model, thereby completing the risk assessment.

[0018] The present invention can monitor the environmental factors of extreme weather and geological disasters in real time, comprehensively consider their impact on the operational stability of the active distribution network, and use the constructed environmentally sensitive risk assessment model to accurately calculate the fault risk value of the active distribution network, thereby significantly improving the comprehensiveness and accuracy of risk assessment.

[0019] Compared with the prior art, the active distribution network fault risk assessment system and method have the following beneficial effects:

[0020] Based on the historical data analysis and trend prediction function, the present invention can accurately assess the failure risk faced by the current distribution network by analyzing historical meteorological data, geological disaster record data and active distribution network failure history records, and can also predict the changes in environmental factors in the future, that is, the changing trends of rainfall, wind speed, temperature and humidity, and substitute the predicted data into the risk calculation model to assess the failure risk that the active distribution network will face in the future. This provides more time for the power grid operation unit to take preventive measures and ensures the timeliness and accuracy of risk assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a diagram of the working principle of the system in an embodiment of the present invention.

[0022] Figure 2 It is a flowchart of the method in an embodiment of the present invention. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. 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.

[0024] like Figure 1As shown, this embodiment discloses an active distribution network fault risk assessment system, including a natural environment data acquisition module, an environmental risk assessment model construction module, and an environmental risk assessment module. Among them:

[0025] In the active distribution network fault risk assessment system of this embodiment, the natural environment data acquisition module collects historical meteorological data, historical geological disaster record data, and distribution network fault data corresponding to the historical time period, and sends them to the environmental risk assessment model construction module.

[0026] Specifically, the historical meteorological data collected by natural environment data include historical rainfall, lightning activity frequency, wind speed, temperature and humidity data, etc. The historical geological disaster record data collected by natural environment data include historical flood and mudslide data, etc. The distribution network fault data collected by natural environment data for the corresponding historical time period include conductor dancing, conductor icing, conductor breakage, pole tower collapse, short circuit tripping, single-phase grounding, etc.

[0027] In the active distribution network fault risk assessment system of this embodiment, the environmental risk assessment model construction module first cleans and organizes the received historical meteorological data, historical geological disaster record data, and historical distribution network fault data to remove abnormal data and noise.

[0028] Then, the environmental risk assessment model building module extracts key features of environmental factors from the cleaned and sorted historical meteorological data and historical geological disaster record data. Among them, the key features of environmental factors extracted from historical meteorological data include historical rainfall, wind speed, temperature and humidity data, and the key features of environmental factors extracted from historical geological disaster record data include flood, mudslide and other data.

[0029] Then, the environmental risk assessment model construction module combines the key features of environmental factors extracted from historical data to analyze the active distribution network fault data of the corresponding historical time period, determines the degree of influence of the extracted key features of environmental factors on the active distribution network failure risk, and assigns corresponding weight values ​​to each key feature of environmental factors according to the analysis results.

[0030] Among them, the impact of key characteristics of environmental factors extracted from historical meteorological data on the risk of active distribution network failure includes but is not limited to: in windy weather, overhead lines at local wind outlets may shake violently, causing line fatigue damage or even line breakage; in hot and dry weather, electric arcs generated by grounding faults in distribution networks can easily cause forest and grassland fires, causing huge personal and property losses; in low temperature and high humidity weather, humid water vapor can easily cover the surface of conductors and equipment with ice, leading to large-scale pole fall and line break accidents; in typhoon weather, wind speeds exceeding the design upper limit can easily blow down iron lattices and poles.

[0031] The impact of key features of environmental factors extracted from historical geological disaster record data on the risk of distribution network failure includes but is not limited to: in flood disasters, accumulated water seeps into underground distribution station buildings, causing equipment to be flooded and tripped, and the poles of overhead lines are very likely to tilt and fall over after being soaked in water for a long time; in heavy rainfall weather, mudslides are prone to occur in mountainous areas with severe soil erosion, which will cause large-scale damage to power facilities within the affected area.

[0032] Specifically, meteorological data refers to data collected and recorded from various meteorological elements in the atmosphere, which are usually collected and recorded by meteorological observation points; geological data refers to data recording the surface and underground characteristics of the earth, such as geological structure, rock distribution, seismic activity, etc., which are usually obtained from geological surveys and explorations; by analyzing historical meteorological data, geological disaster record data and distribution network failure history records, a risk assessment model is constructed for the risk assessment of power grid failures, so as to accurately assess the failure risk of the current active distribution network.

[0033] Finally, the environmental risk assessment model construction module combines the key characteristics of environmental factors and the corresponding weight values ​​to establish an environmentally sensitive risk assessment model. The risk assessment model formula is shown in formula (1):

[0034] R=w1x jyl +w2x fs +w3x wd +w4x sd (1)

[0035] Where: R is the failure risk value; x jyl 、x fs 、x wd 、x sd are the normalized values ​​of rainfall, wind speed, temperature and humidity among the key characteristics of environmental factors; w1, w2, w3 and w4 are the weights of rainfall, wind speed, temperature and humidity respectively.

[0036] In the active distribution network fault risk assessment system of this embodiment, the environmental risk assessment module obtains the current meteorological data and geological disaster record data, and cleans and organizes the current meteorological data and geological disaster record data to remove abnormal data and noise. Then, the rainfall, wind speed, temperature and humidity data in the key characteristics of the current environmental factors are extracted in advance from the cleaned and organized current meteorological data, and substituted into the risk assessment model shown in formula (1). The current fault risk value R is calculated by the risk assessment model, thereby completing the risk assessment.

[0037] During specific risk assessment, the environmental risk assessment module sets multiple risk value intervals corresponding to different risk levels, and matches the calculated current fault risk value R with each risk value interval to determine the risk value interval in which the current fault risk value R is located. The risk level corresponding to the risk value interval is the current risk level.

[0038] In the active distribution network fault risk assessment system of the present embodiment, the environmental risk assessment module also combines the key characteristics of environmental factors extracted from historical meteorological data and the key characteristics of environmental factors extracted from current meteorological data to predict the key characteristics of future environmental factors; then the environmental risk assessment module substitutes the key characteristics of future environmental factors into the risk assessment model to predict the future fault risk value.

[0039] Specifically, the calculation formula for rainfall in the key characteristics of future environmental factors is shown in formula (2):

[0040] x jyl (t+Δt)=x jyl (t)+gΔt+hsin(2πt / F) (2)

[0041] In formula (2): x jyl (t) is the normalized value of rainfall at the current moment, x jyl (t+Δt) is the normalized value of the predicted rainfall at a future time, Δt is the time interval, and g, h, and F are parameters fitted based on historical rainfall data.

[0042] The calculation formula for wind speed in the key characteristics of future environmental factors is shown in formula (3):

[0043] x fs (t+Δt)=x fs ( t ) +eΔt+fcos ( 2πt / E ) (3)

[0044] In formula (3): x fs( t0 is the normalized value of wind speed at the current moment, x fs (t+Δt) is the normalized value of the predicted wind speed at the future moment, and e, f, and E are parameters fitted based on the historical wind speed data.

[0045] The calculation formula for temperature in the key characteristics of future environmental factors is shown in formula (4):

[0046] x wd (t+Δt)=x wd ( t ) +aΔt+bsin( 2πt / C ) (4)

[0047] In formula (4): x wd( t ) is the normalized value of the temperature at the current moment, x wd (t+Δt) is the normalized value of the predicted temperature at the future moment, and a, b, and C are the parameters obtained by fitting the historical temperature data.

[0048] The calculation formula of humidity in the key characteristics of future environmental factors is shown in formula (5):

[0049] x sd (t+Δt)=x sd ( t ) +cΔt+dsin ( 2πt / D ) (5)

[0050] In formula (5): x sd( t ) is the normalized value of humidity at the current moment, x sd (t+Δt) is the normalized value of the predicted humidity at the future moment, and c, d, and D are the parameters fitted based on the historical humidity data.

[0051] Then, the environmental risk assessment module substitutes the key characteristics of future environmental factors (including the normalized values ​​of future rainfall, wind speed, temperature, and humidity) into the risk assessment model shown in formula (1), thereby predicting the future failure risk value.

[0052] As an improvement to the active distribution network fault risk assessment system of this embodiment, the active distribution network fault risk assessment system of this embodiment further includes an early warning trigger module and an emergency response module.

[0053] The early warning trigger module generates a fault risk early warning signal of the corresponding level based on the risk level obtained by the environmental risk assessment module. The early warning signal includes the sound and light alarm of the dispatching desk and the SMS notification of the operation and maintenance personnel, so that the relevant dispatching, operation and management personnel can obtain risk information in a timely manner.

[0054] The emergency response module receives the warning signal generated by the early warning trigger module and automatically initiates the emergency response plan, including measures such as adjusting the grid operation mode, strengthening equipment inspections, and preparing emergency repair teams to reduce the probability and impact of failures. In the specific emergency response module, the distribution automation system automatically generates a fault isolation plan to minimize the power outage area and restoration time while maintaining the stable operation of the grid; and, based on the importance level of the users involved in the fault and the geographical location of the available emergency repair resources, the emergency repair team is quickly dispatched; at the same time, the distributed power supply and energy storage system are dispatched as emergency backup power supplies to quickly restore the power supply of important loads; in addition, the emergency response module also works with the external emergency command center to coordinate public safety responses in large-scale fault scenarios.

[0055] For low-risk warning signals, emergency measures include increasing the frequency of remote video inspections of equipment in the area, adjusting the grid operation mode, appropriately transferring the load in the area, and sending text messages to notify operation and maintenance personnel to remind them to pay attention. For medium-risk warning signals, emergency measures include starting special equipment inspections, arranging professional personnel to conduct on-site inspections, and completing load transfers as soon as possible, while issuing internal alarms. For high-risk warning signals, emergency measures include immediately completing fault isolation and load transfers, dispatching repair teams to the fault site, and issuing power outage notices to affected power users, while carrying out emergency repairs in the affected areas.

[0056] In this embodiment, by implementing a fault prevention and rapid response strategy based on risk assessment, the operating stability and power supply security of the active distribution network can be significantly improved. Once it is detected that the risk exceeds the preset threshold, the emergency response module can be triggered to automatically start the emergency plan, adjust the grid operation mode, strengthen equipment inspections and prepare emergency repair teams, reduce the probability and impact of faults, protect grid assets from damage, and also reduce the risk of power supply interruption to users, ensuring the continuity and reliability of power supply.

[0057] like Figure 2 As shown, based on the above-mentioned active distribution network fault risk assessment system, the active distribution network fault risk assessment method implemented in this embodiment includes the following steps:

[0058] Step S100: Acquire historical meteorological data, historical geological disaster record data, and active power distribution network fault data corresponding to the historical time period.

[0059] Step S200, extract key features of environmental factors from historical meteorological data and historical geological disaster record data, and combine them with the active distribution network failure data of the corresponding historical time period to determine the degree of influence of the extracted key features of environmental factors on the active distribution network failure risk, thereby assigning corresponding weight values ​​to each key feature of environmental factors, and establishing a risk assessment model in combination with the key features of environmental factors and the corresponding weight values.

[0060] Step S300, obtain current meteorological data and geological disaster record data, extract key characteristics of environmental factors from the current meteorological data and geological disaster record data, and then input them into the risk assessment model, and calculate the current fault risk value of the active distribution network through the risk assessment model, thereby completing the risk assessment.

[0061] Step S400: Based on the current risk level, generate a corresponding level of fault risk warning signal;

[0062] Step S500: Based on the current fault risk warning signal of the corresponding level, the emergency response plan is automatically initiated, including adjusting the grid operation mode, strengthening equipment inspection and carrying out emergency repairs, so as to reduce the time and scope of the fault impact.

[0063] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. An active distribution network fault risk assessment system, characterized in that: It includes natural environment data collection module, environmental risk assessment model construction module and environmental risk assessment module, among which: The natural environment data acquisition module collects historical meteorological data, historical geological disaster record data, and active power distribution network fault data corresponding to the historical time period, and sends them to the environmental risk assessment model construction module; The environmental risk assessment model building module extracts key features of environmental factors from the received historical meteorological data and historical geological disaster record data, and combines the active distribution network failure data of the corresponding historical time period to determine the degree of influence of the extracted key features of environmental factors on the active distribution network failure risk, thereby assigning corresponding weight values ​​to each key feature of environmental factors, and establishing a risk assessment model in combination with the key features of environmental factors and the corresponding weight values; The environmental risk assessment module obtains current meteorological data and geological disaster record data, extracts key features of environmental factors from the current meteorological data and geological disaster record data, substitutes them into the risk assessment model, and calculates the current fault risk value through the risk assessment model, thereby completing the risk assessment.

2. The active distribution network fault risk assessment system according to claim 1, characterized in that: The key features of environmental factors include rainfall, wind speed, temperature and humidity data extracted from meteorological data, and flood and mudslide data extracted from geological disaster record data.

3. The active distribution network fault risk assessment system according to claim 1, characterized in that: The environmental risk assessment module sets a plurality of risk value intervals corresponding to different risk levels, and matches the calculated current fault risk value with each risk value interval, thereby determining the current risk level.

4. The active distribution network fault risk assessment system according to claim 1, characterized in that: The environmental risk assessment module also combines the key features of environmental factors extracted from historical meteorological data and the key features of environmental factors extracted from current meteorological data to predict the key features of environmental factors in the future; The environmental risk assessment module then substitutes the key characteristics of future environmental factors into the risk assessment model to predict future failure risk values.

5. An active distribution network fault risk assessment method based on the active distribution network fault risk assessment system according to any one of claims 1 to 4, characterized in that: The following steps are involved: Step S100, obtaining historical meteorological data, historical geological disaster record data, and active distribution network fault data corresponding to the historical time period; Step S200, extracting key features of environmental factors from historical meteorological data and historical geological disaster record data, and combining them with active distribution network failure data of the corresponding historical time period, determining the degree of influence of the extracted key features of environmental factors on the failure risk of the active distribution network, thereby assigning corresponding weight values ​​to each key feature of environmental factors, and establishing a risk assessment model in combination with the key features of environmental factors and the corresponding weight values; Step S300, obtain current meteorological data and geological disaster record data, extract key characteristics of environmental factors from the current meteorological data and geological disaster record data, and then input them into the risk assessment model, and calculate the current fault risk value of the active distribution network through the risk assessment model, thereby completing the risk assessment.

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