Power distribution network bearing capacity analysis method based on environmental parameters

Abstract

The invention provides a power distribution network bearing capacity analysis method based on environmental parameters. The method comprises the following steps: acquiring real-time environmental parameters such as environmental humidity information, environmental temperature information and environmental air pressure information; obtaining insulation performance information of the power distribution network equipment according to the environment humidity information, the environment temperature information and the equipment electric field intensity information; acquiring parameter information of the power distribution network equipment, and acquiring heat dissipation performance information of the power distribution network equipment according to the parameter information of the power distribution network equipment, the environment humidity information and the environment temperature information; acquiring air conductivity information according to the environmental parameters; and according to the insulation performance information, the heat dissipation performance information and the air conductivity information, carrying capacity information of the power distribution network is analyzed and obtained. According to the method, environmental parameters such as humidity, temperature and atmospheric pressure are monitored in real time, indexes such as equipment insulation resistance and heat dissipation capacity are combined, the influence of various factors on the bearing capacity of the power distribution network is comprehensively considered, and therefore the bearing capacity of the power distribution network is obtained more accurately and comprehensively.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power distribution networks, and particularly relates to a power distribution network carrying capacity analysis method based on environmental parameters. BACKGROUND

[0002] The prior art usually only relies on simple single factors (such as temperature, current, etc.) to evaluate the carrying capacity of power distribution network equipment. For example, the prior art mostly only calculates the working state of the equipment through the changes of the ambient temperature and the current, ignoring the influence of humidity on the equipment. While humidity, as an important environmental variable, can significantly change the insulation resistance, heat dissipation capacity and conductivity of the power distribution network equipment, especially in a high humidity environment, the change of humidity will cause nonlinear changes in the performance of the equipment. The influence of humidity on the insulation resistance, heat dissipation efficiency and conductivity of electrical equipment is not linear, especially in extreme humidity conditions, the traditional empirical formula may not be able to effectively cope with the sudden changes and large fluctuations in the performance of the equipment, resulting in that its prediction of the carrying capacity of the equipment cannot adapt to complex and variable climate conditions. SUMMARY

[0003] In order to solve the problems existing in the background art, the present application proposes a power distribution network carrying capacity analysis method based on environmental parameters.

[0004] A power distribution network carrying capacity analysis method based on environmental parameters, comprising the steps of:

[0005] S100, obtaining real-time environmental humidity information, environmental temperature information and environmental pressure information;

[0006] S200, obtaining electric field intensity information of the power distribution network equipment, and obtaining insulation performance information of the power distribution network equipment according to the environmental humidity information, the environmental temperature information and the electric field intensity information of the equipment;

[0007] S300, obtaining parameter information of the power distribution network equipment, and obtaining heat dissipation performance information of the power distribution network equipment according to the parameter information of the power distribution network equipment and the environmental humidity information and the environmental temperature information;

[0008] S400, obtaining air conductivity information according to the environmental humidity information, the environmental temperature information and the environmental pressure information;

[0009] S500, obtaining carrying capacity information of the power distribution network according to the obtained insulation performance information of the power distribution network equipment, the heat dissipation performance information of the power distribution network equipment and the air conductivity information.

[0010] Based on the above, in step S200, the insulation performance information is the insulation resistance value, and the insulation resistance R ins is:

[0011] R ins(H, T, E) = R0·exp(-a1H - a2T + a3E 2 )

[0012] wherein R0 is the insulation resistance under standard dry conditions; H is the relative humidity of the environment; T is the temperature of the environment; E is the electric field strength; a1, a2, a3 are experimental fitting coefficients, respectively representing the influence of humidity, temperature and electric field strength on the insulation resistance.

[0013] Based on the above, in step S300, the heat dissipation performance information of the power distribution network equipment is the heat dissipation power, and the heat dissipation power Q is:

[0014]

[0015] wherein h(H) is the heat convection heat transfer coefficient under the influence of humidity; A is the surface area of the equipment; AT is the temperature difference between the equipment and the environment; is the surface emissivity of the equipment; is the Stefan-Boltzmann constant; T s is the surface temperature of the equipment; T ∞ is the temperature of the environment.

[0016] Based on the above, in step S400, the air conductivity s is:

[0017] s(H, T, P) = s0·exp(b1H - b2T + b3P)

[0018] wherein s0 is the air conductivity under dry conditions; H is the relative humidity; T is the temperature; P is the atmospheric pressure; b1, b2, b3 are experimental fitting coefficients, respectively representing the influence of humidity, temperature and atmospheric pressure on the air conductivity.

[0019] Based on the above, in step S500, the carrying capacity P max (H) of the power distribution network is:

[0020]

[0021] wherein P max0 is the maximum carrying capacity of the power distribution network under standard humidity conditions; l1, l2, l3, t1, p1 are fitting coefficients, respectively representing the influence of humidity, temperature, pressure on the carrying capacity; R ins (H, T, E) is the insulation resistance under the influence of humidity, temperature and electric field strength; Q(H, s) is the equipment heat dissipation power under the influence of humidity, wind speed and conductivity; Q0 is the heat dissipation power under standard humidity conditions; R0 is the insulation resistance under standard humidity conditions.

[0022] The present application has outstanding substantial features and significant progress compared with the prior art. Specifically, the present application can more accurately and comprehensively obtain the carrying capacity of the power distribution network by monitoring the environmental parameters such as humidity, temperature, and atmospheric pressure in real time, and combining with the equipment insulation resistance, heat dissipation capacity, and other indicators, and comprehensively considering the influence of various factors on the carrying capacity of the power distribution network; through real-time monitoring and dynamic evaluation mechanism of environmental parameters and equipment parameters, the influence on the equipment performance under different humidity, temperature, and pressure conditions can be evaluated in real time, and through this mechanism, the changes of the insulation performance and heat dissipation capacity of the equipment can be effectively predicted, so as to facilitate timely adjustment of the operation strategy, ensure the safe and stable operation of the power distribution network under extreme climate, thereby providing strong protection for the safe operation of the power distribution network, especially when the humidity and temperature change greatly, the potential risks can be identified in advance. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 is a flowchart diagram of the present application. DETAILED DESCRIPTION

[0024] The technical solutions in the embodiments of the present application will be described clearly and completely in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0025] As shown in Figure 1 A power distribution network carrying capacity analysis method based on environmental parameters, comprising the steps of: S100, obtaining real-time environmental humidity information, environmental temperature information, and environmental air pressure information and other environmental parameters. In reality, the environmental humidity information is the relative humidity of air, the environmental temperature information is the air temperature, and the environmental air pressure information is the atmospheric pressure; S200, obtaining the electric field strength information of the power distribution network equipment, and obtaining the insulation performance information of the power distribution network equipment according to the environmental humidity information, the environmental temperature information, and the equipment electric field strength information; S300, obtaining the parameter information of the power distribution network equipment, and obtaining the heat dissipation performance information of the power distribution network equipment according to the parameter information of the power distribution network equipment and the environmental humidity information and the environmental temperature information; S400, obtaining the air conductivity information according to the environmental humidity information, the environmental temperature information, and the environmental air pressure information; S500, analyzing and obtaining the carrying capacity information of the power distribution network according to the obtained insulation performance information of the power distribution network equipment, the heat dissipation performance information of the power distribution network equipment, and the air conductivity information.

[0026] In reality, with climate change and the frequent occurrence of extreme weather events, air humidity has become a key factor affecting the safe and stable operation of distribution networks. Humidity impacts distribution networks not only on the insulation performance and heat dissipation of electrical equipment, but also on their electrical conductivity and leakage current. Therefore, establishing a complex mathematical model based on the impact of humidity on the carrying capacity of distribution networks can provide a scientific basis for the dispatching, operation, and maintenance of distribution networks, ensuring their stability and safety under various weather conditions.

[0027] The maximum carrying capacity of the distribution network is affected by many external factors, among which air humidity is one of the factors that cannot be ignored. The impact of humidity on electrical equipment is mainly reflected in the following aspects:

[0028] Insulation performance: Increased humidity increases the moisture content in the air, which reduces the insulation resistance and may cause equipment failure.

[0029] Thermal conductivity: When humidity increases, the heat convection coefficient of the equipment decreases, affecting the heat dissipation of the equipment;

[0030] Conductivity: The effect of humidity on air conductivity may cause partial discharge or electrical short circuit in electrical equipment, thereby affecting the stability of the distribution network.

[0031] The insulation performance of electrical equipment is the basis for the stable operation of the distribution network. As the humidity increases, the conductivity of the air increases and the insulation resistance of the electrical equipment decreases. In this embodiment, the insulation resistance R ins The changes with humidity H, temperature T and electric field strength E are expressed by the following formula:

[0032] R ins (H,T,E)=R0·exp(-α1H-α2T+α3E 2 )

[0033] Where: R ins is the insulation resistance under humidity, temperature and electric field strength (unit: Ω); R0 is the insulation resistance under standard drying conditions (unit: Ω); H is the relative humidity (%); T is the temperature (unit: ℃); E is the electric field strength (unit: V / m); α1, α2, and α3 are experimental fitting coefficients, respectively representing the effects of humidity, temperature, and electric field strength on the insulation resistance.

[0034] As humidity increases, the insulation resistance R ins The formula provides a basis for quantifying the effect of humidity on insulation resistance.

[0035] Humidity also has a direct impact on the heat dissipation performance of power distribution network equipment, especially the combined effect of convective heat transfer and thermal radiation heat transfer. The heat dissipation power Q of the equipment is represented by the following formula:

[0036]

[0037] Where: Q is the heat dissipation power (unit: W); h(H) is the convective heat transfer coefficient under the influence of humidity, which usually decreases with increasing humidity. The equipment parameter information is: A is the equipment surface area (unit: m 2 ); ΔT is the temperature difference between the equipment and the environment (unit: K); ò is the equipment surface emissivity; σ is the Stefan-Boltzmann constant; T s is the equipment surface temperature (unit: K); T ∞ is the ambient temperature (unit: K).

[0038] The increase in humidity reduces the convective heat transfer coefficient h(H) of the equipment, resulting in a decrease in heat dissipation efficiency, thereby increasing the operating temperature of the equipment and affecting the carrying capacity of the power distribution network.

[0039] The increase in air humidity significantly increases the electrical conductivity of air, which may increase the leakage current of electrical equipment. The air conductivity σ can be described by the following formula:

[0040] σ(H, T, P) = σ0·exp(β1H - β2T + β3P)

[0041] Where: σ is the air conductivity under the conditions of humidity, temperature and pressure (unit: S / m); σ0 is the air conductivity under dry conditions; H is the relative humidity (%); T is the temperature (unit: °C); P is the atmospheric pressure (unit: Pa); β1, β2, β3 are experimental fitting coefficients representing the influence of humidity, temperature and pressure on air conductivity.

[0042] When humidity increases, the electrical conductivity of air increases, which may increase the leakage current of power distribution network equipment, thereby affecting its normal operation.

[0043] In this embodiment, based on the analysis of humidity, temperature, air conductivity and other factors, the maximum carrying capacity P max (H) of the power distribution network can be expressed by the following multi-dimensional model:

[0044]

[0045] Where: P max (H, T, P) is the maximum carrying capacity of the power distribution network under the conditions of humidity, temperature and pressure (unit: MW); P max0is the maximum carrying capacity of the distribution network under standard humidity conditions (unit: MW); λ1, λ2, λ3, τ1, ρ1 are fitting coefficients representing the influence of humidity, temperature, pressure, etc. on the carrying capacity; R ins (H, T, E) is the insulation resistance under the influence of humidity, temperature, and electric field strength; Q(H, σ) is the heat dissipation power of the equipment under the influence of humidity and conductivity; Q0 is the heat dissipation power under standard humidity conditions; R0 is the insulation resistance under standard humidity conditions.

[0046] This model comprehensively considers environmental factors such as humidity, temperature, and pressure, as well as the insulation performance and heat dissipation capacity of the equipment, and can more accurately assess the maximum carrying capacity of the distribution network under different weather conditions.

[0047] In reality, to verify the effectiveness and accuracy of the above model, the following work needs to be done: data collection: collect the operation data of the distribution network, the temperature, conductivity, heat dissipation power, and insulation resistance of electrical equipment under different humidity, temperature, pressure, and wind speed conditions; experimental verification: simulate the influence of different humidity environments on equipment performance through experiments, and measure the maximum carrying capacity of the distribution network under different humidity and temperature conditions; model optimization: use experimental data to optimize the fitting coefficients in the model to ensure that the model matches the actual data and improve the prediction accuracy of the model.

[0048] After obtaining a stable and accurate mathematical model, the influence of changes in environmental parameters such as humidity on the carrying capacity of the distribution network can be dynamically predicted through the accurate mathematical model, potential risks can be identified in advance, and timely preventive measures can be taken, thereby effectively improving the safety and stability of the distribution network.

[0049] It is apparent to those skilled in the art that the present application is not limited to the details of the foregoing exemplary embodiments, but can be implemented in other concrete forms without departing from the spirit or essential characteristics of the present application. Therefore, the embodiments should be considered in all respects as illustrative and not restrictive, and the scope of the present application is defined by the appended claims rather than the foregoing description, and it is intended to encompass all changes falling within the meaning and scope of the equivalent elements of the claims. Any reference signs in the claims should not be considered as limiting the claims involved.

Claims

1. A method for analyzing the carrying capacity of a distribution network based on environmental parameters, characterized in that: Including steps: S100, obtaining real-time ambient humidity information, ambient temperature information, and ambient air pressure information; S200, obtaining electric field strength information of distribution network equipment, and obtaining insulation performance information of the distribution network equipment based on ambient humidity information, ambient temperature information, and equipment electric field strength information; S300, obtaining parameter information of the distribution network equipment, and obtaining heat dissipation performance information of the distribution network equipment based on the parameter information of the distribution network equipment, ambient humidity information, and ambient temperature information; S400, obtaining air conductivity information based on ambient humidity information, ambient temperature information, and ambient air pressure information; S500: Analyze and obtain the carrying capacity information of the distribution network based on the obtained insulation performance information, heat dissipation performance information, and air conductivity information of the distribution network equipment.

2. The method for analyzing the carrying capacity of a distribution network based on environmental parameters according to claim 1, characterized in that: In step S200, the insulation performance information is the insulation resistance value, the insulation resistance R ins for: R ins (H,T,E)=R0·exp(-α1H-α2T+α3E 2 ) Where R0 is the insulation resistance under standard dry conditions; H is the ambient relative humidity; T is the ambient temperature; E is the electric field strength; α1, α2, and α3 are experimental fitting coefficients, representing the effects of humidity, temperature, and electric field strength on the insulation resistance, respectively.

3. The method for analyzing the carrying capacity of a distribution network based on environmental parameters according to claim 1, characterized in that: In step S300, the heat dissipation performance information of the distribution network equipment is the heat dissipation power, and the heat dissipation power Q is: Where h(H) is the heat transfer coefficient under the influence of humidity; A is the surface area of ​​the device; ΔT is the temperature difference between the device and the environment; ò is the emissivity of the device surface; σ is the Stefan-Boltzmann constant; T s is the surface temperature of the equipment; T ∞ is the ambient temperature.

4. The method for analyzing the carrying capacity of a distribution network based on environmental parameters according to claim 1, characterized in that: In step S400, the air conductivity σ is: σ(H,T,P)=σ0·exp(β1H-β2T+β3P) Wherein, σ0 is the air conductivity under dry conditions; H is the relative humidity; T is the temperature; P is the atmospheric pressure; β1, β2, and β3 are experimental fitting coefficients, representing the effects of humidity, temperature, and atmospheric pressure on air conductivity, respectively.

5. The method for analyzing the carrying capacity of a distribution network based on environmental parameters according to claim 1, characterized in that: In step S500, the carrying capacity P of the distribution network max (H) is: Among them, P max0 is the maximum carrying capacity of the distribution network under standard humidity conditions; λ1, λ2, λ3, τ1, and ρ1 are fitting coefficients, representing the effects of humidity, temperature, and pressure on the carrying capacity; R ins (H, T, E) is the insulation resistance under the influence of humidity, temperature, and electric field strength; Q(H, σ) is the heat dissipation power of the equipment under the influence of humidity and conductivity; Q0 ​​is the heat dissipation power under standard humidity conditions; R0 is the insulation resistance under standard humidity conditions.

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