Evaluation method and system for reliability of extreme meteorological new energy high-permeability power system

Abstract

The invention belongs to the technical field of power systems, and relates to a reliability evaluation method and system for an extreme meteorological new energy high-permeability power system. The method comprises the following steps: judging extreme meteorology, and constructing a new energy output and meteorological factor coupling model under the extreme meteorology; establishing a system operation model considering extreme meteorology, and obtaining system operation state parameters and power distribution parameters; calculating a short-time index reliability score and an ultra-short-time index reliability score of the system under each extreme weather and different time length scales; and fusing the reliability scores to obtain a comprehensive reliability score. The method can accurately describe the instantaneous impact and short-term influence of the extreme weather on the operation of the new energy high-permeability power system, and realizes the quantitative analysis of the reliability of the system; the reliability indexes of the system are divided into a short-time type and an ultra-short-time type, the power shortage risks under different time scales can be captured respectively, and more refined and dynamic reliability evaluation is provided for system operation under extreme weather.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of power systems, and in particular, relates to an extreme weather new energy high-penetration power system reliability evaluation method and system. BACKGROUND

[0002] With large-scale grid connection of renewable energy such as wind power and photovoltaic power, the power system in China has gradually evolved from a regulation-type power grid dominated by conventional generating units to a new type of power system dominated by new energy. However, renewable energy has significant intermittency, randomness and volatility, and its output characteristics are highly sensitive to weather conditions. In extreme weather conditions, the supply of wind and light resources will change dramatically, further exacerbating the operational risk and reliability challenges of the power system.

[0003] Traditional power system reliability evaluation indicators, such as system loss of load probability (LOLP) and expected energy not supplied (EENS), mainly reflect the power supply reliability and service continuity on an annual time scale. Such annual and statistical average indicators lack the ability to describe short-term strong impacts, regional synchronous mutations and tail risks, and cannot accurately reflect the spatiotemporal correlation reliability problems caused by the coupling of power supply side output drop, grid constraints and load side fluctuations under extreme weather conditions. Simply relying on the traditional power system stability evaluation index system cannot support operational decision-making and emergency configuration under extreme weather scenarios.

[0004] Therefore, there is an urgent need for a reliability evaluation method that considers the output variation of new energy and the multi-time scale operation characteristics of the power system under extreme weather conditions, to realize risk identification, probability modeling and operational reliability evaluation of the power system under extreme weather scenarios, and to provide a scientific basis for power grid safety dispatching and emergency protection. SUMMARY

[0005] To solve the above technical problems, the application provides an extreme weather new energy high-penetration power system reliability evaluation method and system.

[0006] In a first aspect, the application provides an extreme weather new energy high-penetration power system reliability evaluation method, comprising: determining extreme weather, and constructing a new energy output and weather factor coupling model under extreme weather; the new energy output and weather factor coupling model is used to represent the influence of different extreme weather conditions on new energy output and power grid parameters; the extreme weather includes ice disaster weather, sandstorm weather and little wind and light weather; establishing a system operation model considering extreme weather, and obtaining system operation state parameters using the system operation model; The reliability index is divided into a short-time index and an ultra-short-time index, and the system running state parameters are simulated under extreme weather conditions to make the system running state parameters not meet the running state, so as to calculate the short-time index reliability score and the ultra-short-time index reliability score of the system under each extreme weather condition and different time scales; The reliability scores under each extreme weather condition are fused by using a fusion weight method to obtain a comprehensive reliability score as the system comprehensive reliability evaluation result.

[0007] In a second aspect, the present application provides an extreme weather new energy high-penetration power system reliability evaluation system, which comprises a coupling model construction unit, a system running model construction unit, an index reliability division and score calculation unit, and a reliability score fusion unit. The coupling model construction unit is used for determining extreme weather and constructing a new energy output and weather factor coupling model under extreme weather conditions. The system running model construction unit is used for establishing a system running model considering extreme weather, and obtaining system running state parameters by using the system running model. The index reliability division and score calculation unit is used for dividing the reliability index into a short-time index and an ultra-short-time index, and calculating the short-time index reliability score and the ultra-short-time index reliability score of the system under each extreme weather condition and different time scales by simulating extreme weather conditions based on the system running state parameters. The reliability score fusion unit is used for fusing the reliability scores under each extreme weather condition by using a fusion weight method to obtain a comprehensive reliability score as the system comprehensive reliability evaluation result.

[0008] On the basis of the above technical solutions, the present application can also be improved as follows.

[0009] Further, the ice disaster weather is determined, including: Let be an ice disaster weather occurrence judgment index, represent ice disaster weather occurrence, represent ice disaster weather non-occurrence, be a power line icing thickness, be a freezing rain hour number, be an ice density, be a freezing rain amount, be an ice rain density, be a wind speed, be an air liquid water content, then the air liquid water content is represented as: The ice thickness of the power line under the ice disaster weather is represented as: ; The ice thickness of the power line is used to determine whether the ice disaster occurs, and is represented as: .

[0010] Further, the sandstorm weather is determined, including: Let be a sandstorm weather occurrence determination index, represent the occurrence of a sandstorm, represent the non-occurrence of a sandstorm, be the visibility, be the PM10 index, which is used to represent the mass concentration of inhalable particles with a particle size less than or equal to 10 microns in the air, and the sandstorm weather determination formula is represented as: .

[0011] Further, the little wind and dim light weather is determined, including: Let be a little wind weather occurrence determination index, represent the occurrence of a little wind weather, be the non-occurrence of a little wind weather, be a dim light weather occurrence determination index, represent the occurrence of a dim light weather, represent the non-occurrence of a dim light weather, be the solar irradiance, be the number of days in a statistical period, be a day index, be a time step index, then: ; ; When and , the little wind and dim light weather occurs.

[0012] Further, a new energy output and weather factor coupling model under ice disaster weather is constructed, including: Let be the ice wind load, be the line failure probability, be the lower threshold of the ice wind load, be the upper threshold of the ice wind load, then the line failure probability is represented as: ; Let be the lower threshold of the ice wind load, be the upper threshold of the ice wind load, is the threshold lower limit of wind force when the wind speed is the design value, is the threshold upper limit of wind force when the wind speed is the design value, is the threshold lower limit of ice force when the ice thickness is the design value, is the threshold upper limit of ice force when the ice thickness is the design value, is the design value of wind speed that the line can withstand, is the design value of ice thickness that the line can withstand, is a constant, is the span / span distance factor, is the outer diameter of the conductor, then: ; ; ; Let be the line failure probability under ice and wind force weather, then the line failure model under ice and wind force weather is expressed as: .

[0013] Further, the new energy output and meteorological factor coupling model under sandstorm weather is constructed, including: Let be the total wind load, be the line failure probability under sandstorm weather, be the threshold lower limit, be the threshold upper limit, then the exponential failure model under sandstorm weather is expressed as: ; Let be the wind force threshold lower limit, be the wind force threshold upper limit, be the design value of wind speed that the line can withstand, the force of the wind load is in the plane perpendicular to the conductor, at this time the threshold of wind speed in the failure model is expressed as , Let be the line failure probability under ice and wind force weather, then the line failure model of wind force is expressed as: .

[0014] Further, the new energy output and meteorological factor coupling model under little wind and light weather is constructed, including: Let be the line failure rate, be the line failure probability in the time period, then the line failure rate is expressed as: .

[0015] Further, the reliability index is divided into short-time index and ultra-short-time index, the short-time index reliability score and the ultra-short-time index reliability score of the system under each extreme weather and different time scales are calculated by jointly simulating the extreme weather and the system operation parameters, including: The reliability index of the influence time length of extreme weather on new energy output in the first set time length range is taken as the short-time index, the reliability index of the influence time length of extreme weather on new energy output in the second set time length range is taken as the ultra-short-time index, the short-time reliability probability index is calculated as the reliability score corresponding to the short-time index, and the ultra-short-time reliability probability index is calculated as the reliability score corresponding to the short-time index; Let The coefficient of the short-time index representing the system power shortage probability, The coefficient of the short-time index representing the power shortage frequency, The coefficient of the short-time index representing the power shortage duration, The coefficient of the ultra-short-time index representing the power shortage duration, The coefficient of the ultra-short-time index representing the power shortage frequency, The coefficient of the ultra-short-time index representing the power shortage duration, the short-time reliability probability index is , and the ultra-short-time reliability probability index is , The short-time index is represented by The ultra-short-time index is represented by The power shortage frequency is represented by The power shortage frequency is represented by The power shortage duration is represented by ; .

[0016] Further, the reliability scores under each extreme weather are fused by using a fusion weight method to obtain a comprehensive reliability score as the system comprehensive reliability evaluation result, including: Let the short-time reliability probability index be , and the ultra-short-time reliability probability index be , The fusion weight corresponding to the short-time reliability probability index is The fusion weight corresponding to the ultra-short-time reliability probability index is , and the comprehensive reliability score is .

[0017] The beneficial effects of the present application are: (1) By constructing a coupling model between new energy output and meteorological factors, this invention can accurately describe the instantaneous impact and short-term influence of extreme weather such as ice storms, sandstorms, and strong winds on the operation of new energy high-penetration power systems, and realize the quantitative analysis of system reliability. (2) The present invention divides the system reliability index into two categories: short time and ultra-short time, which can capture the power shortage risk on time scales of minutes to hours and seconds to minutes respectively, providing a more refined and dynamic reliability assessment for system operation under extreme weather conditions; (3) Through the multi-scenario fusion weight method, the present invention can incorporate different extreme weather events into the evaluation, realize the calculation of the system's comprehensive reliability index, and provide a comprehensive and scientific reliability judgment result. Attached Figure Description

[0018] Figure 1 A schematic diagram of the reliability assessment method for high-penetration power systems with extreme weather conditions provided in Embodiment 1 of the present invention; Figure 2 Simulation graph showing short-term indicator results for an ice storm scenario; Figure 3 Simulation diagram of ultra-short-term indicator results for ice storm scenarios; Figure 4 The schematic diagram of the reliability assessment system for high-penetration power systems for extreme weather new energy sources provided in Embodiment 1 of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0020] Example 1 As an example, see the attached document. Figure 1 As shown, to solve the above-mentioned technical problems, this embodiment provides a reliability assessment method for high-penetration power systems with new energy sources in extreme weather conditions, including: Extreme weather conditions are assessed, and a coupled model of renewable energy output and meteorological factors under extreme weather conditions is constructed. This coupled model is used to characterize the impact of different extreme weather conditions on renewable energy output and grid parameters. Extreme weather conditions include ice storms, sandstorms, and low wind and low light conditions. Establish a system operation model that takes extreme weather into account, and use the system operation model to obtain system operation state parameters; The reliability index is divided into short-time index and ultra-short-time index, and based on the system operation state parameters, the system operation state parameters are made not to meet the operation state by joint simulation of extreme weather, and the short-time index reliability score and the ultra-short-time index reliability score of the system under each extreme weather and different time scales are calculated; The reliability scores under each extreme weather are fused by using a fusion weight method to obtain a comprehensive reliability score as the system comprehensive reliability evaluation result.

[0021] Optionally, the ice disaster weather is determined, including: Let be an ice disaster weather occurrence judgment index, represent that the ice disaster weather occurs, represent that the ice disaster weather does not occur, be a power line icing thickness, be a freezing rain hour number, be an ice density, be a freezing rain amount, be an ice rain density, be a wind speed, be a liquid water content in the air, then the liquid water content in the air is represented as: ; the power line icing thickness under the ice disaster weather is represented as: ; then the power line icing thickness is used to determine whether the ice disaster occurs, represented as: .

[0022] Optionally, the sandstorm weather is determined, including: Let be a sandstorm weather occurrence judgment index, represent that the sandstorm occurs, represent that the sandstorm does not occur, be a visibility, be a PM10 index, the PM10 index is used to represent the mass concentration of inhalable particles with a particle size less than or equal to 10 microns in the air, and a sandstorm weather determination formula is represented as: .

[0023] Optionally, the little wind and little light weather is determined, including: Let be a little wind weather occurrence judgment index, represent that the little wind weather occurs, represent that the little wind weather does not occur, be a little light weather occurrence judgment index, represent that the little light weather occurs, represent that the little light weather does not occur, is the solar irradiance, is the number of days in the statistical period, is the day index, is the time step index, then: ; ; When and , the little wind and low light weather occurs.

[0024] In the actual application process, for little wind and low light weather, the average wind speed less than 0.2 m / s in the statistical time is defined as little wind, and the average solar irradiance less than 15 is defined as low light.

[0025] Under the premise of considering the influence of icing, the calculation formula of unit span line wind load is derived to accurately evaluate the wind force borne by the line, let be the wind load, be a constant, be the span / span factor, be the gust speed, be the conductor outer diameter, be the ice thickness, then the wind load is: ; Let be the freezing rain hours, be the ice density, be usually 0.9 ( ), be the freezing rain density, usually 1 ( ), be the liquid water content in the air, be the freezing rain amount.

[0026] According to the relationship between the ice thickness of the power line and the freezing rain, the ice thickness calculation formula can be obtained. Given the ice thickness and the radius of the power transmission line, the ice force load under a span can be derived, let be the ice force load, then: ; The new ice and wind force load is obtained by the composition of the force under the action of ice and wind, let the composed ice and wind force load be , be the angle between the ice and wind force load vector and the vertical ground, then: ; ; The force generated by the line due to icing has a design limit. When it exceeds this limit, the bearing capacity decreases rapidly, and the line failure probability increases significantly.

[0027] Optionally, a new energy output and meteorological factor coupling model under ice disaster weather is constructed, comprising: Let be the ice wind load, be the line fault probability, be the threshold lower limit of the ice wind load, be the threshold upper limit of the ice wind load, then the line fault probability is represented as: ; Let be the threshold lower limit of the ice wind force, be the threshold upper limit of the ice wind force, be the threshold lower limit of the wind force when the wind speed is the design value, be the threshold upper limit of the wind force when the wind speed is the design value, be the threshold lower limit of the ice force when the ice thickness is the design value, be the threshold upper limit of the ice force when the ice thickness is the design value, be the wind speed design value that the line can withstand, be the ice thickness design value that the line can withstand, be a constant, be a span / span factor, be the outer diameter of the conductor, then: ; ; ; Let be the line fault probability under ice wind force weather, then the line fault model under ice wind force weather is represented as: .

[0028] In actual application process, the influence of sandstorm on system reliability is analyzed, and the calculation method of oblique parabola is used to calculate the related parameters. Let the wind speed be , the horizontal wind load perpendicular to the conductor direction be , be the uneven coefficient of conductor wind pressure, be the body shape coefficient of wind load, be the outer diameter of the conductor, be the wind speed value, be the angle between the wind direction and the conductor direction, under the action of wind speed , .

[0029] Optionally, a new energy output and meteorological factor coupling model under sandstorm weather is constructed, comprising: Let be the total wind load, is the line failure probability under sandstorm weather, is the threshold lower limit, is the threshold upper limit, then the exponential failure model under sandstorm weather is expressed as: ; Let be the wind force threshold lower limit, be the wind force threshold upper limit, be the wind speed design value that the line can withstand, the force of the wind load is in the plane perpendicular to the conductor, at this time the threshold of the wind speed in the failure model is expressed as , Let be the line failure probability under ice wind force weather, then the line failure model of wind force is expressed as: .

[0030] When the wind speed or rainfall exceeds a certain value, the line failure probability increases with the increase of the wind speed.

[0031] Optionally, a new energy output and meteorological factor coupling model under little wind and light weather is constructed, including: let be the line failure rate, be the line failure probability in the time period, then the line failure rate is expressed as: .

[0032] The present application can accurately describe the instantaneous impact and short-term influence of extreme weather such as ice disaster, sandstorm and strong wind on the operation of new energy high-penetration power system by constructing a new energy output and meteorological factor coupling model, and realizes the quantitative analysis of system reliability.

[0033] Optionally, the reliability index is divided into short-time index and ultra-short-time index, the short-time index reliability score and the ultra-short-time index reliability score of the system under each extreme weather and different time scales are calculated by jointly simulating the extreme weather and the system operation parameters, including: The reliability index whose influence time of extreme weather on new energy output is in the range of the first set time is taken as the short-time index, the reliability index whose influence time of extreme weather on new energy output is in the range of the second set time is taken as the ultra-short-time index, the short-time reliability probability index is calculated as the reliability score corresponding to the short-time index, and the ultra-short-time reliability probability index is calculated as the reliability score corresponding to the short-time index; in the embodiment of the present application, the short-time index is defined as the power system reliability index with a time span of 3 to 30 days; the ultra-short-time index is defined as the power system reliability index with a time span of less than 3 days; Let represent the coefficient of the short-time index of the system power shortage probability, a coefficient of a short-term index representing power shortage frequency, a coefficient of a short-term index representing power shortage duration, a coefficient of an ultra-short-term index representing power shortage duration, a coefficient of an ultra-short-term index representing power shortage frequency, a coefficient of an ultra-short-term index representing power shortage duration, the short-term reliability probability index is , the ultra-short-term reliability probability index is , representing a short-term index, representing an ultra-short-term index, representing power shortage frequency, representing power shortage frequency, representing power shortage duration, then: ; .

[0034] The present application divides the system reliability index into short-term and ultra-short-term two categories, which can capture the power shortage risk in the time scale of minutes to several hours and several seconds to several minutes respectively, and provide more refined and dynamic reliability evaluation for system operation under extreme weather.

[0035] Optionally, the reliability scores under each extreme weather are fused by using a fusion weight method to obtain a comprehensive reliability score as a system comprehensive reliability evaluation result, including: Let the short-term reliability probability index be , the ultra-short-term reliability probability index be , the fusion weight corresponding to the short-term reliability probability index, the fusion weight corresponding to the ultra-short-term reliability probability index, and the comprehensive reliability score be , then: .

[0036] In actual application process, and can be set according to the importance of the scene or experience, for example, set to be a set reliability threshold, which can be set according to standards or experience, when , the system is determined to be reliable.

[0037] The reliability evaluation method provided by the present application can provide decision basis for planning, design, dispatching and operation of new energy high-penetration power system under extreme weather conditions, improve the safety and stability of the system, and support long-term operation risk management.

[0038] A certain capacity of wind and solar power was added to the existing IEEE-118 system. The power output of the new energy units was obtained using the wind farm and solar power operation simulation method proposed earlier. The simulation assumes the system includes one diesel generator set, five hydroelectric generator sets, 29 wind turbine generator sets, 11 solar power units, and five energy storage batteries. To verify the effectiveness of the proposed multi-timescale reliability indices, the following simulation examples mainly focus on two aspects: short-term and ultra-short-term reliability indices under ice storm weather conditions. To verify the effectiveness of the proposed multi-timescale reliability indices, this embodiment designs simulation examples for ice storm weather conditions, mainly verifying short-term and ultra-short-term reliability indices. (See attached...) Figure 2 The short-term indicator results for the ice storm scenario are shown in the attached figure. Figure 3 The results of ultra-short-term reliability indicators for the ice storm scenario are shown below. The horizontal axis represents the number of days, and the vertical axis represents the system reliability probability index score. Short-term reliability indicators are used to assess the reliability fluctuations of the system over a continuous period during an ice storm, reflecting the power supply stability of lines, towers, and key nodes under continuous icing and wind effects. Ultra-short-term reliability indicators are used to quantify the impact of the instantaneous impact of extreme weather events on the local or global operating status of the system, and can identify the critical time points when reliability suddenly drops.

[0039] Example 2 Based on the same principle as the method shown in Embodiment 1 of the present invention, as illustrated in the appendix. Figure 4 As shown, the embodiments of the present invention also provide a reliability assessment system for high-penetration power systems with new energy sources in extreme weather, including a coupling model construction unit, a system operation model construction unit, an indicator reliability division and score calculation unit, and a reliability score fusion unit; The coupling model construction unit is used to determine extreme weather conditions and construct a coupling model between new energy output and meteorological factors under extreme weather conditions. The coupling model between new energy output and meteorological factors is used to characterize the impact of different extreme weather conditions on new energy output and grid parameters. Extreme weather conditions include ice storms, sandstorms, and low wind and low light conditions. The system operation model construction unit is used to establish a system operation model that takes extreme weather into account, and to obtain system operation state parameters using the system operation model. The reliability index classification and score calculation unit is used to classify reliability indexes into short-time indexes and ultra-short-time indexes. Based on the system operating state parameters, extreme weather is jointly simulated to make the system operating state parameters not meet the operating state, and the reliability scores of short-time indexes and ultra-short-time indexes are calculated under various extreme weather conditions and different time scales. The reliability score fusion unit is configured to fuse the reliability scores under each extreme weather condition using a fusion weight method to obtain a comprehensive reliability score as a system comprehensive reliability evaluation result.

[0040] Optionally, the ice disaster weather is determined, including: Let be an ice disaster weather occurrence judgment index, represent that the ice disaster weather occurs, represent that the ice disaster weather does not occur, be a power line icing thickness, be a freezing rain hour number, be an ice density, be a freezing rain amount, be an ice rain density, be a wind speed, be a liquid water content in the air, then the liquid water content in the air is represented as: ; the power line icing thickness under the ice disaster weather is represented as: ; then the determination of whether the ice disaster occurs using the power line icing thickness is represented as: .

[0041] Optionally, the sandstorm weather is determined, including: Let be a sandstorm weather occurrence judgment index, represent that the sandstorm occurs, represent that the sandstorm does not occur, be a visibility, be a PM10 index, the PM10 index is used to represent the mass concentration of inhalable particles with a particle size less than or equal to 10 microns in the air, and a sandstorm weather determination formula is represented as: .

[0042] Optionally, the little-wind and low-light weather is determined, including: Let be a little-wind weather occurrence judgment index, represent that the little-wind weather occurs, represent that the little-wind weather does not occur, be a low-light weather occurrence judgment index, represent that the low-light weather occurs, represent that the low-light weather does not occur, be a solar irradiance, be a number of days in a statistical period, be a day index, be a time step index, then: ; ; When and , little wind and light meteorological conditions occur.

[0043] Optionally, a new energy output and meteorological factor coupling model under ice disaster weather is constructed, including: Let be the ice wind load, be the line fault probability, be the threshold lower limit of the ice wind load, be the threshold upper limit of the ice wind load, then the line fault probability is expressed as: ; Let be the threshold lower limit of the ice wind load, be the threshold upper limit of the ice wind load, be the threshold lower limit of the wind load when the wind speed is the design value, be the threshold upper limit of the wind load when the wind speed is the design value, be the threshold lower limit of the ice load when the ice thickness is the design value, be the threshold upper limit of the ice load when the ice thickness is the design value, be the wind speed design value that the line can withstand, be the ice thickness design value that the line can withstand, be a constant, be a span / span factor, be the outer diameter of the conductor, then: ; ; ; Let be the line fault probability under ice wind weather, then the line fault model under ice wind weather is expressed as: .

[0044] Optionally, a new energy output and meteorological factor coupling model under sandstorm weather is constructed, including: Let be the total wind load, be the line fault probability under sandstorm weather, be the threshold lower limit, be the threshold upper limit, then the exponential fault model under sandstorm weather is expressed as: ; Let be the threshold lower limit of the wind load, wind force threshold upper limit, wind force threshold upper limit, , , let be the line failure probability under ice wind force weather, then the line failure model of wind force is expressed as: .

[0045] Optionally, a new energy output and meteorological factor coupling model under a little wind and little light weather is constructed, including: let be the line failure rate, be the line failure probability in a time period, then the line failure rate is expressed as: .

[0046] Optionally, the reliability index is divided into a short-time index and an ultra-short-time index, the short-time index reliability score and the ultra-short-time index reliability score of the system under each extreme weather and different time scales are calculated by jointly simulating the extreme weather and the system operation parameters, including: the reliability index whose influence time of the extreme weather on the new energy output is in the range of the first set time length is taken as the short-time index, the reliability index whose influence time of the extreme weather on the new energy output is in the range of the second set time length is taken as the ultra-short-time index, the short-time reliability probability index is calculated as the reliability score corresponding to the short-time index, and the ultra-short-time reliability probability index is calculated as the reliability score corresponding to the short-time index; let represent the coefficient of the short-time index of the system power shortage probability, represent the coefficient of the short-time index of the power shortage frequency, represent the coefficient of the short-time index of the power shortage duration, represent the coefficient of the ultra-short-time index of the power shortage duration, represent the coefficient of the ultra-short-time index of the power shortage frequency, represent the coefficient of the ultra-short-time index of the power shortage duration, the short-time reliability probability index is , and the ultra-short-time reliability probability index is , represent the short-time index, represent the ultra-short-time index, represent the power shortage frequency, represent the power shortage frequency, represent the power shortage duration, then: ; .

[0047] Optionally, the reliability scores under each extreme weather are fused by using a fusion weight method to obtain a comprehensive reliability score as a system comprehensive reliability evaluation result, including: Let the short-time reliability probability index be , the ultra-short-time reliability probability index be , , the fusion weight corresponding to the short-time reliability probability index be , the fusion weight corresponding to the ultra-short-time reliability probability index be, and the comprehensive reliability score be , then: .

[0048] The above only is the preferred embodiment of the present application and is not used to limit the present application. For those skilled in the art, the present application can have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A reliability assessment method for high-penetration power systems powered by new energy sources in extreme weather conditions, characterized in that, include: To determine extreme weather conditions, a coupled model of new energy output and meteorological factors under extreme weather conditions is constructed. A coupled model of renewable energy output and meteorological factors is used to characterize the impact of different extreme weather conditions on renewable energy output and grid parameters; extreme weather includes ice storms, sandstorms, and low wind and low light conditions. Establish a system operation model that takes extreme weather into account, and use the system operation model to obtain system operation state parameters; Reliability indicators are divided into short-time indicators and ultra-short-time indicators. Based on the system operating state parameters, extreme weather is jointly simulated to make the system operating state parameters not meet the operating state. The reliability scores of short-time indicators and ultra-short-time indicators are calculated under various extreme weather conditions and different time scales. The reliability scores under various extreme weather conditions are fused using a fusion weighting method to obtain a comprehensive reliability score as the overall reliability assessment result of the system.

2. The reliability assessment method for high-penetration power systems with extreme weather and new energy sources according to claim 1, characterized in that, The assessment of meteorological conditions for ice storms includes: set up As an indicator for judging the occurrence of ice storms, This indicates that an ice storm has occurred. This indicates that no ice storm occurred. For the thickness of ice accretion on power lines, This refers to the number of hours of freezing rain. The density of ice, This is the amount of freezing rain. For ice rain density, For wind speed, The liquid water content in the air is expressed as: The thickness of ice accumulation on power lines under ice storm conditions is expressed as follows: ； The determination of whether an ice storm has occurred is based on the thickness of ice accumulation on power lines, expressed as follows: 。 3. The reliability assessment method for high-penetration power systems with extreme weather and new energy sources according to claim 1, characterized in that, Determining the weather conditions of a sandstorm includes: set up It serves as an indicator for determining the occurrence of sandstorms. This indicates that a sandstorm has occurred. This indicates that no sandstorm occurred. For visibility, The PM10 index is used to characterize the mass concentration of inhalable particulate matter with a diameter of 10 micrometers or less in the air. The formula for determining dust storm weather is as follows: 。 4. The reliability assessment method for high-penetration power systems with extreme weather and new energy sources according to claim 1, characterized in that, Determining the weather conditions of low wind and dim light includes: set up As an indicator for determining the occurrence of low wind weather, This indicates that there is little wind. No windy weather occurred. As an indicator for determining the occurrence of low-light meteorological events, This indicates the occurrence of faint light weather. This indicates that no faint weather event occurred. Solar irradiance, For the number of days in the statistical period, Indexed by number of days, If the index is the time step, then: ； ； when and At that time, there was little wind and light.

5. The reliability assessment method for high-penetration power systems with extreme weather and new energy sources according to claim 1, characterized in that, Constructing a coupling model between new energy output and meteorological factors under ice storm weather conditions, including: set up For ice wind load, This represents the probability of a line fault. This represents the lower threshold of the ice wind load. If the upper limit of the ice wind load threshold is given, then the line fault probability is expressed as: ； set up This is the lower limit of the threshold for ice wind force. This represents the upper limit of the threshold for ice wind force. This is the lower threshold of wind force when the wind speed is at the design value. This represents the upper limit of the wind force threshold when the wind speed is at the design value. This is the lower limit of the ice force threshold when the ice thickness is the design value. This represents the upper limit of the ice force threshold when the ice thickness is the design value. The design value for the wind speed that the line can withstand. The design value for the ice thickness that the line can withstand. It is a constant. For span / range factor, Let be the outer diameter of the conductor, then: ； ； ； set up Let be the line fault probability under icy wind conditions. Then, the line fault model under icy wind conditions is expressed as follows: 。 6. The reliability assessment method for high-penetration power systems with extreme weather and new energy sources according to claim 1, characterized in that, A coupled model of new energy output and meteorological factors under dust storm conditions was constructed, including: set up For total wind load, The probability of line failure under sandstorm weather conditions. The lower limit of the threshold. If the upper limit of the threshold is used, then the exponential fault model under dust storm weather is expressed as: ； set up This is the lower limit of the wind force threshold. This is the upper limit of the wind force threshold. Given the design wind speed that the line can withstand, and the wind load acting on a plane orthogonal to the conductor, the wind speed threshold in the fault model is expressed as: , ,set up Let be the probability of line faults under icy wind conditions. Then, the line fault model under wind conditions can be expressed as: 。 7. The reliability assessment method for high-penetration power systems with extreme weather renewable energy sources according to claim 1, characterized in that, Constructing a coupled model of new energy output and meteorological factors under low wind and low light conditions, including: setting For line failure rate, for The probability of line failure within a time period is expressed as: .

8. The reliability assessment method for high-penetration power systems with extreme weather conditions and new energy sources according to claim 1, characterized in that, Reliability indicators are divided into short-time indicators and ultra-short-time indicators. By jointly simulating extreme weather conditions and system operating parameters, the reliability scores of the short-time and ultra-short-time indicators are calculated under various extreme weather conditions and different time scales, including: The reliability index of the impact duration of extreme weather on new energy output within the first set duration range is used as the short-time index, and the reliability index of the impact duration of extreme weather on new energy output within the second set duration range is used as the ultra-short-time index. The short-time reliability probability index is calculated as the reliability score corresponding to the short-time index, and the ultra-short-time reliability probability index is calculated as the reliability score corresponding to the short-time index. set up A coefficient representing a short-term indicator of the probability of insufficient power in the system. A coefficient representing a short-term indicator of the frequency of power shortages. A coefficient representing a short-term indicator of the duration of power shortage. A coefficient representing the duration of power shortage as an ultra-short-term index. A coefficient representing the frequency of power shortages in ultra-short-time indices. The coefficient representing the duration of power shortage is the short-time reliability probability index. The ultra-short time reliability probability index is , Indicates short-term indicators, Indicates a very short-term indicator. Indicates the frequency of insufficient power. Indicates the frequency of insufficient power. If we represent the duration of power shortage, then: ； 。 9. The reliability assessment method for high-penetration power systems with extreme weather and new energy sources according to claim 1, characterized in that, A fusion weighting method is used to fuse the reliability scores under various extreme weather conditions, resulting in a comprehensive reliability score as the overall system reliability assessment result, including: Let the short-time reliability probability index be... The ultra-short time reliability probability index is , The fusion weights are the short-term reliability probability indicators. The fusion weights corresponding to the ultra-short-time reliability probability index are used to calculate the overall reliability score. ,but: 。 10. A reliability assessment system for high-penetration power systems in extreme weather conditions, characterized in that: It includes a coupling model construction unit, a system operation model construction unit, an indicator reliability division and score calculation unit, and a reliability score fusion unit; The coupling model construction unit is used to determine extreme weather conditions and construct a coupling model between new energy output and meteorological factors under extreme weather conditions. The coupling model between new energy output and meteorological factors is used to characterize the impact of different extreme weather conditions on new energy output and grid parameters. Extreme weather conditions include ice storms, sandstorms, and low wind and low light conditions. The system operation model construction unit is used to establish a system operation model that takes extreme weather into account, and to obtain system operation state parameters using the system operation model. The reliability index classification and score calculation unit is used to classify reliability indexes into short-time indexes and ultra-short-time indexes. Based on the system operating state parameters, extreme weather is jointly simulated to make the system operating state parameters not meet the operating state, and the reliability scores of short-time indexes and ultra-short-time indexes are calculated under various extreme weather conditions and different time scales. The reliability score fusion unit is used to fuse the reliability scores under various extreme weather conditions using a fusion weighting method to obtain a comprehensive reliability score as the overall system reliability assessment result.

Images