A power distribution network resilience risk assessment method and system suitable for a high proportion of new energy access scenarios

Abstract

The present application relates to a kind of distribution network flexibility risk assessment method and system suitable for high proportion new energy access scene, method includes: obtaining the active power output data of new energy of distribution network;New energy active power is modeled as interval variable, obtain new energy active power interval;Interval power flow calculation method based on affine arithmetic is used, interval solution of the voltage amplitude of each node of distribution network and the active power of each branch of distribution network is solved;The interval value of each flexibility quantization index in the flexibility quantization index system of distribution network is calculated;Based on sensitivity analysis method, the influence factor of each node and each branch of distribution network to each flexibility quantization index is calculated, and the weak link of distribution network is identified;According to the interval value of each flexibility quantization index and the weak link of distribution network, the flexibility risk assessment result of distribution network is generated.Compared with prior art, the present application significantly improves the engineering practicability, accuracy and pertinence of distribution network flexibility risk assessment under high proportion new energy access.

Description

Technical Field

[0001] This invention relates to the field of power system operation and analysis technology, and in particular to a method and system for assessing the resilience risk of distribution networks applicable to scenarios with a high proportion of renewable energy integration. Background Technology

[0002] As the penetration rate of distributed photovoltaic and wind power in distribution networks continues to rise, the high proportion of new energy access, while promoting the low-carbon transformation of energy, also brings new challenges to the safe and stable operation of distribution networks. The output of new energy sources is characterized by randomness, volatility, and intermittency. Its uncertainty directly affects the power flow distribution, voltage level, and branch load status of the distribution network, thereby affecting the resilience of the distribution network in the face of extreme events.

[0003] Power grid resilience refers to the ability of a power system to quickly recover and continuously provide power services to users after being subjected to high-impact, low-probability events. Accurately assessing distribution network resilience is of significant theoretical and practical importance for power grid planning decisions, operational optimization, and emergency management. Traditional distribution network resilience assessment methods mostly employ deterministic analysis frameworks, treating renewable energy output as a fixed value or using limited typical scenarios for static analysis. However, this approach ignores the inherent uncertainty of renewable energy output, making it difficult for the assessment results to fully reflect the risk range that the distribution network may face in actual operation.

[0004] Existing methods for handling uncertainties in renewable energy sources mainly fall into two categories: probabilistic methods and interval methods. Probabilistic methods require prior knowledge of the precise probability distribution function of renewable energy output. However, in practice, renewable energy output is influenced by multiple factors, including irradiance, wind speed, temperature, and season, making accurate probability distribution difficult to determine. In contrast, interval methods only require knowledge of the upper and lower boundaries of renewable energy output, thus having lower requirements for probability distribution information and being more suitable for practical engineering applications. However, existing interval analysis methods still face the following technical bottlenecks when applied to distribution network resilience assessment: (1) Interval expansion problem: Traditional interval arithmetic produces overly conservative interval estimation results when performing nonlinear power flow calculations, resulting in overly broad evaluation conclusions and a lack of practical engineering value; (2) Incomplete resilience indicator system: Existing studies mostly focus on single-dimensional resilience assessment and lack a systematic multi-dimensional quantitative indicator system that covers resistance, adaptation and recovery capabilities; (3) Difficulty in locating weak links: Under the continuous influence of uncertainty in the output of new energy sources, it is difficult to accurately identify and locate the key weak nodes and branches that affect the overall resilience of the distribution network.

[0005] For example, patent application CN120725542A discloses a distribution network resilience assessment method based on a multi-dimensional resilience index system. This method uses Analytic Hierarchy Processing (AHP) to subjectively weight the system function, voltage deviation, and user power supply status into a one-dimensional composite curve. From this curve, three geometric features—missing area, extreme value drops, and recovery time—are derived. After normalization, these features are input into a three-dimensional coordinate system to calculate the Euclidean distance and obtain a resilience score. However, this method can only provide deterministic resilience values ​​at the system level and cannot handle the range-based uncertainty of renewable energy output, cannot construct a truly independent multi-dimensional index system, and completely lacks the ability to locate key weak nodes and branches.

[0006] Therefore, there is an urgent need for an innovative method that can effectively address the uncertainty of new energy output, suppress regional expansion, accurately assess the multidimensional resilience of the distribution network, and precisely identify weak links. Summary of the Invention

[0007] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a method and system for assessing the resilience risk of distribution networks in scenarios with a high proportion of renewable energy access, which significantly improves the engineering practicality, accuracy and pertinence of the assessment of the resilience risk of distribution networks under the scenario of a high proportion of renewable energy access.

[0008] The objective of this invention can be achieved through the following technical solutions: A method for assessing the resilience risk of distribution networks applicable to scenarios with a high proportion of renewable energy integration includes the following steps: Obtain historical active power output data of new energy sources in the power distribution network; Based on the historical active power output data of the new energy sources, the active power output of the new energy sources is modeled as an interval variable to obtain the active power output interval of the new energy sources. Based on the active power output range of new energy sources, an interval power flow calculation method based on affine arithmetic is adopted to solve the interval solutions of voltage amplitude at each node of the distribution network and active power of each branch of the distribution network. Based on the interval solutions of the voltage amplitude of each node in the distribution network and the active power of each branch in the distribution network, calculate the interval values ​​of each resilience quantification index in the distribution network resilience quantification index system. Based on the sensitivity analysis method, the influence factors of each node and branch of the distribution network on each resilience quantitative index are calculated to identify the weak links of the distribution network. Based on the range values ​​of each resilience quantification indicator and the weak links in the distribution network, a distribution network resilience risk assessment result is generated.

[0009] Furthermore, the active power output of the new energy sources includes the active power output of distributed photovoltaic power and the active power output of wind power, and the range of the active power output of distributed photovoltaic power is expressed as follows: In the formula, For access nodes The active power output range of distributed photovoltaic power generation. For the lower limit of the contribution of distributed photovoltaic power, The upper limit of the contribution of distributed photovoltaic power. This represents the historical average active power output of distributed photovoltaic systems. , is the confidence coefficient The standard deviation of historical distributed photovoltaic power output. This refers to the rated capacity of distributed photovoltaic power. The range of active power output of the wind power generation is represented as follows: In the formula, For access nodes The active power output range of wind power generation, The lower boundary contributes to wind power generation. The upper limit of the contribution of wind power generation. This represents the historical average active power output of wind power generation. The standard deviation of historical wind power output. This refers to the rated capacity of wind power generation.

[0010] Furthermore, the specific steps for solving the interval solutions for the voltage magnitude at each node and the active power of each branch of the distribution network using an interval power flow calculation method based on affine arithmetic include: Convert the active power output range of new energy sources at each node of the distribution network into an affine form; Substituting the affine form of the active power output interval of new energy sources into the power flow equation of the distribution network, the affine form of each state variable is solved by using the affine arithmetic operation rules, and then transformed into the interval solution of the voltage amplitude of each node and the active power of each branch of the distribution network.

[0011] Furthermore, the calculation formula for converting the active power output range of new energy sources at each node of the distribution network into an affine form is as follows: In the formula, For nodes The active power output range of affine-shaped new energy sources This is the center value of the active power output range of new energy sources. The radius of the active power output range of new energy sources. For noise symbols, The lower bound of the range for new energy contribution. This is the upper limit of the range for active power output from new energy sources.

[0012] Furthermore, the power flow equations of the distribution network are: In the formula, branch road active power, For nodes Net active power load, branch road The resistance, branch road The square of the current amplitude, For nodes The set of downstream nodes, branch road active power, branch road reactive power, For nodes reactive load, branch road Reactance, branch road reactive power, For nodes voltage amplitude, For nodes The voltage amplitude.

[0013] Furthermore, the specific steps for substituting the affine form of the new energy active power output interval into the power flow equation of the distribution network, solving for the affine form of each state variable through affine arithmetic rules, and then converting it into the interval solution of the voltage amplitude of each node and the active power of each branch of the distribution network include: Calculate the affine form of the power of each branch sequentially from the end node of the distribution network towards the root node; From the root node of the distribution network to the terminal node, update the affine form of the voltage of each node in sequence; Calculate the maximum change in the center value of the affine form of each node voltage. If it is less than the preset convergence threshold, convert the affine form of each branch power and each node voltage into an interval form output to obtain the interval solution of the voltage amplitude of each node and the active power of each branch of the distribution network. Otherwise, return to the above steps for iteration. When the active power output range of new energy sources is too large, causing the interval power flow calculation based on affine arithmetic to fail to converge, the interval bisection method is used to divide the original active power output range of new energy sources into two sub-intervals, and the interval power flow calculation based on affine arithmetic is performed separately. The union of the results of the two sub-intervals is taken as the final result.

[0014] Furthermore, the resilience quantification index system includes resilience indicators, adaptability indicators, and recovery capability indicators. The resilience index is used to characterize the ability of the distribution network to maintain normal operation under disturbances, and the calculation formula is as follows: In the formula, As a resilience indicator, For nodes The importance weight of the load, For nodes The range of load reduction caused by voltage exceeding limits or branch overload. For nodes The original load; The adaptability index is used to characterize the ability of a distribution network to adapt to disturbances through topology reconfiguration and resource scheduling, and the calculation formula is as follows: In the formula, As an indicator of adaptability, The number of feasible running points to satisfy the operational constraints. This represents the total number of running points sampled within the interval; The recovery capability index is used to characterize the ability of the distribution network to recover from a fault state to a normal state, and the calculation formula is as follows: In the formula, As an indicator of recovery capacity, For the available reserve capacity of the distribution network, This represents the maximum possible load loss of the distribution network.

[0015] Furthermore, based on sensitivity analysis, the specific steps for identifying weak links in the distribution network include calculating the influence factors of each node and branch on each resilience quantification index, and identifying these weak links based on the sensitivity analysis method: Calculate the voltage over-limit sensitivity factor for each node; Calculate the overload sensitivity factor for each branch; All nodes and branches are sorted according to the magnitude of the voltage over-limit sensitivity factor and the overload sensitivity factor to identify the weak links in the distribution network.

[0016] Furthermore, the voltage over-limit sensitivity factor is used to characterize the degree of influence of changes in the active power output of new energy sources on the range of node voltage fluctuations, and the calculation formula is as follows: In the formula, For nodes Voltage over-limit sensitivity factor, For nodes The upper limit of the voltage range, For nodes The lower bound of the voltage range. It is the sum of the radii of the active power output ranges of all new energy sources; The overload sensitivity factor is used to characterize the impact of changes in the active power output of new energy sources on the maximum power of the branch. The calculation formula is as follows: In the formula, branch road The overload sensitivity factor branch road The upper limit of the active power range.

[0017] According to another aspect of the present invention, a distribution network resilience risk assessment system suitable for scenarios with a high proportion of renewable energy access is provided, comprising: The historical active power output data acquisition module is used to acquire historical active power output data of new energy sources in the distribution network; The active power output range construction module is used to model the active power output of new energy sources as range variables based on the historical active power output data of the new energy sources, so as to obtain the active power output range of new energy sources. The interval solution module is used to solve the interval solutions of voltage amplitude at each node and active power of each branch of the distribution network based on the active power output interval of new energy sources and the interval power flow calculation method based on affine arithmetic. The resilience quantification index interval value calculation module is used to calculate the interval values ​​of each resilience quantification index in the distribution network resilience quantification index system based on the interval solutions of the voltage amplitude of each node in the distribution network and the active power of each branch in the distribution network. The weak link identification module is used to calculate the influence factors of each node and branch of the distribution network on each resilience quantitative index based on the sensitivity analysis method, and to identify the weak links of the distribution network. The resilience risk assessment module is used to generate distribution network resilience risk assessment results based on the range values ​​of various resilience quantification indicators and the weak links in the distribution network.

[0018] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention obtains historical active power output data of renewable energy sources in the distribution network, models the active power output of renewable energy sources as interval variables, and only requires knowing the upper and lower boundaries of the output to describe the uncertainty. It adopts an interval power flow calculation method based on affine arithmetic, which uses the affine form to preserve the mathematical correlation between variables, effectively suppressing the interval expansion problem caused by the nonlinear operation of traditional interval arithmetic. Thus, it obtains interval solutions for the voltage amplitude of each node and the active power of each branch of the distribution network that are closer to reality. Furthermore, it calculates the interval values ​​of each resilience quantification index in the distribution network resilience quantification index system, solving the problems of traditional methods relying on precise probability distributions, difficulty in calibration in actual engineering, and overly conservative interval analysis results. It significantly improves the engineering practicality and accuracy of distribution network resilience risk assessment under high proportion of renewable energy access.

[0019] 2. This invention combines sensitivity analysis to quantify the voltage over-limit sensitivity factor of each node and the overload sensitivity factor of each branch in the distribution network. Based on the magnitude of the voltage over-limit sensitivity factor and the overload sensitivity factor, all nodes and branches are sorted to accurately identify weak nodes and branches. This solves the problem that existing assessment methods are unable to locate key risk points in uncertain environments, providing a clear target for the precise reinforcement and operational risk prevention of the distribution network, and effectively improving the pertinence of distribution network resilience risk assessment under high-proportion renewable energy access. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating a distribution network resilience risk assessment method suitable for scenarios with a high proportion of renewable energy access, as proposed in this invention. Figure 2 This is a flowchart illustrating the interval power flow calculation based on affine arithmetic. Figure 3 This is a schematic diagram of the structure of a distribution network resilience risk assessment system suitable for scenarios with a high proportion of new energy access, as proposed in this invention. Detailed Implementation

[0021] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0022] Example 1 This embodiment provides a method for assessing the resilience risk of distribution networks applicable to scenarios with a high proportion of new energy access, such as... Figure 1 As shown, it includes the following steps: S1. Obtain historical active power output data of new energy sources in the distribution network.

[0023] The active power output of new energy sources includes the active power output of distributed photovoltaic power and the active power output of wind power generation.

[0024] This invention targets radial distribution networks containing a high proportion of distributed renewable energy sources. Let the set of nodes in the distribution network be... Node 1 is the root node (the substation outlet connected to the upstream power grid). The branch set is... branch road Indicates the connection node and nodes The route.

[0025] S2. Based on the historical active power output data of new energy sources, the active power output of new energy sources is modeled as an interval variable to obtain the active power output interval of new energy sources.

[0026] For access nodes The distributed photovoltaic system is analyzed statistically based on historical output data. Let the historical output sample within a certain evaluation period be... ,in Calculate the sample mean given the sample size. and standard deviation .

[0027] The range of active power output of distributed photovoltaic power is represented as follows: In the formula, For access nodes The active power output range of distributed photovoltaic power generation. For the lower limit of the contribution of distributed photovoltaic power, The upper limit of active power contribution for distributed photovoltaic power generation. This represents the historical average active power output of distributed photovoltaic systems. , is the confidence coefficient The standard deviation of historical distributed photovoltaic power output. This represents the rated capacity of distributed photovoltaic systems. The lower bound is set to the larger of 0 and the statistical lower limit to ensure physical meaning (non-negative output), while the upper bound is set to the smaller of the rated capacity and the statistical upper limit to avoid exceeding the equipment's capacity.

[0028] The range of active power output of wind power generation is represented as follows: In the formula, For access nodes The active power output range of wind power generation, The lower boundary of the contribution to wind power generation. The upper limit of the contribution of wind power generation. This represents the historical average active power output of wind power generation. The standard deviation of historical wind power output. This refers to the rated capacity of wind power generation.

[0029] S3. Based on the active power output range of new energy sources, the interval power flow calculation method based on affine arithmetic is adopted to solve the interval solutions of voltage amplitude of each node and active power of each branch of the distribution network.

[0030] like Figure 2 As shown, the specific steps for solving the interval solutions for voltage amplitude at each node and active power in each branch of the distribution network using an interval power flow calculation method based on affine arithmetic include: The active power output range of new energy sources at each node of the distribution network is converted into an affine form, and the calculation formula is as follows: In the formula, For nodes The active power output range of affine-shaped new energy sources This is the center value of the active power output range of new energy sources. The radius of the active power output range of new energy sources. Different noise symbols are used for different new energy nodes to distinguish their respective sources of uncertainty. This represents the lower bound of the range for new energy contribution. This is the upper limit of the range for active power output from new energy sources.

[0031] Substituting the affine form of the active power output interval of new energy sources into the power flow equation of the distribution network, the affine form of each state variable is solved by using the affine arithmetic operation rules, and then transformed into the interval solution of the voltage amplitude of each node and the active power of each branch of the distribution network.

[0032] The power flow equations of the distribution network are: In the formula, branch road active power, For nodes Net active power load, branch road The resistance, branch road The square of the current amplitude, For nodes The set of downstream nodes, branch road active power, branch road reactive power, For nodes reactive load, branch road Reactance, branch road reactive power, For nodes voltage amplitude, For nodes The voltage amplitude.

[0033] The specific steps for substituting the affine form of the active power output interval of new energy sources into the power flow equations of the distribution network, solving for the affine form of each state variable through affine arithmetic rules, and then converting it into the interval solution of the voltage amplitude of each node and the active power of each branch of the distribution network include: Starting from the end node of the distribution network and moving towards the root node, calculate the affine form of the power of each branch sequentially. This step is a forward scan process; for each branch... According to the power flow equations of the distribution network, the recursive relationship between its active power and reactive power is as follows: All operations are performed in an affine manner, following the rules of addition, subtraction, and constant multiplication in affine arithmetic. The core of this step is to synthesize the affine expression of the upstream branch power level by level using the known affine form of the downstream branch power. After the scan is complete, the active power of all branches in the entire network is obtained. and reactive power Affine form.

[0034] The affine form of the voltage at each node is updated sequentially from the root node to the end node of the distribution network.

[0035] This step is a back-substitution scan process, based on the root node voltage. Starting with the initial value, the affine form of the voltage at each node is updated sequentially, progressing layer by layer along the branch towards the terminal node. For the branch... According to the power flow equations of the distribution network, the recursive relationship of the square of the node voltage is as follows: This step uses the affine form of the branch power obtained from the forward scan and the square of the upstream node voltage to update the affine form of the square of the downstream node voltage level by level.

[0036] Each round of forward and backward substitution constitutes one iteration. After each iteration, the center value of the affine form of the voltage at each node is extracted. (i.e., the constant term in the affine form), calculate its maximum change from the previous iteration's central value: In the formula, The maximum change in the center value. For the first The center value of the next iteration For the first The center value of the next iteration The preset convergence threshold (typically set to...) ).

[0037] Calculate the maximum change in the center value of the affine form of each node voltage. If it is less than the preset convergence threshold, convert the affine form of each branch power and each node voltage into an interval form output to obtain the interval solution of the voltage amplitude of each node and the active power of each branch of the distribution network. Otherwise, return to the above steps for iteration.

[0038] When the active power output range of new energy sources is too large, causing the interval power flow calculation based on affine arithmetic to fail to converge, the interval bisection method is used to divide the original active power output range of new energy sources into two sub-intervals, and the interval power flow calculation based on affine arithmetic is performed separately. The union of the results of the two sub-intervals is taken as the final result.

[0039] S4. Based on the interval solutions of the voltage amplitude of each node in the distribution network and the active power of each branch in the distribution network, calculate the interval values ​​of each resilience quantification index in the distribution network resilience quantification index system.

[0040] The resilience quantification index system includes resilience indicators, adaptability indicators, and recovery capability indicators.

[0041] The resilience index is used to characterize the ability of a distribution network to maintain normal operation under disturbances. The calculation formula is as follows: In the formula, As a resilience indicator, For nodes The importance weight of the load, For nodes The range of load reduction caused by voltage exceeding limits or branch overload. For nodes The original load; The adaptability index is used to characterize the ability of a distribution network to adapt to disturbances through topology reconfiguration and resource scheduling. The calculation formula is as follows: In the formula, As an indicator of adaptability, The number of feasible running points to satisfy the operational constraints. This represents the total number of operating points sampled within the interval. An operating point refers to a complete operating state of the distribution network under a certain set of active power output from new energy sources.

[0042] The recovery capability index is used to characterize the ability of a distribution network to recover from a fault state to a normal state. The calculation formula is as follows: In the formula, As an indicator of recovery capacity, For the available reserve capacity of the distribution network, This represents the maximum possible load loss of the distribution network.

[0043] S5. Based on the sensitivity analysis method, calculate the influence factors of each node and branch of the distribution network on each resilience quantitative index, and identify the weak links of the distribution network.

[0044] Based on sensitivity analysis, the specific steps for identifying weak links in the distribution network, including calculating the influence factors of each node and branch on each resilience quantification index, are as follows: Calculate the voltage limit sensitivity factor for each node. The voltage limit sensitivity factor is used to characterize the impact of changes in active power output from new energy sources on the voltage fluctuation range of the nodes. The calculation formula is as follows: In the formula, For nodes Voltage over-limit sensitivity factor, For nodes The upper limit of the voltage range, For nodes The lower bound of the voltage range. It is the sum of the radii of the active power output ranges of all new energy sources.

[0045] Calculate the overload sensitivity factor for each branch. The overload sensitivity factor characterizes the impact of changes in the active power output of new energy sources on the maximum power of the branch. The calculation formula is as follows: In the formula, branch road The overload sensitivity factor branch road The upper limit of the active power range.

[0046] All nodes and branches are sorted according to the magnitude of the voltage over-limit sensitivity factor and the overload sensitivity factor to identify the weak links in the distribution network. All nodes are sorted from largest to smallest by their voltage over-limit sensitivity factor, and the top few are selected as weak nodes; all branches are sorted from largest to smallest by their overload sensitivity factor, and the top few are selected as weak branches.

[0047] S6. Based on the range values ​​of each resilience quantification indicator and the weak links in the distribution network, generate the distribution network resilience risk assessment results.

[0048] Based on the resilience index range and the identification results of weak links, a distribution network resilience risk assessment report is generated, which includes risk level classification and reinforcement recommendations.

[0049] Example 2 This embodiment provides a distribution network resilience risk assessment system suitable for scenarios with a high proportion of new energy access, such as... Figure 3 As shown, it includes: The historical active power output data acquisition module is used to acquire historical active power output data of new energy sources in the distribution network; The active power output range construction module is used to model the active power output of new energy sources as range variables based on the historical active power output data of new energy sources, so as to obtain the active power output range of new energy sources. The interval solution module is used to solve the interval solutions of voltage amplitude at each node and active power of each branch of the distribution network based on the active power output interval of new energy sources and the interval power flow calculation method based on affine arithmetic. The resilience quantification index interval value calculation module is used to calculate the interval values ​​of each resilience quantification index in the distribution network resilience quantification index system based on the interval solutions of the voltage amplitude of each node in the distribution network and the active power of each branch in the distribution network. The weak link identification module is used to calculate the influence factors of each node and branch of the distribution network on each resilience quantitative index based on the sensitivity analysis method, and to identify the weak links of the distribution network. The resilience risk assessment module is used to generate distribution network resilience risk assessment results based on the range values ​​of various resilience quantification indicators and the weak links in the distribution network.

[0050] The rest is the same as in Example 1.

[0051] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A method for assessing the resilience risk of distribution networks applicable to scenarios with a high proportion of renewable energy integration, characterized in that, Includes the following steps: Obtain historical active power output data of new energy sources in the power distribution network; Based on the historical active power output data of the new energy sources, the active power output of the new energy sources is modeled as an interval variable to obtain the active power output interval of the new energy sources. Based on the active power output range of new energy sources, an interval power flow calculation method based on affine arithmetic is used to solve the interval solutions of voltage amplitude at each node of the distribution network and active power of each branch of the distribution network; based on the interval solutions of voltage amplitude at each node of the distribution network and active power of each branch of the distribution network, the interval values ​​of each resilience quantification index in the distribution network resilience quantification index system are calculated. Based on the sensitivity analysis method, the influence factors of each node and branch of the distribution network on each resilience quantification index are calculated to identify the weak links in the distribution network; based on the interval values ​​of each resilience quantification index and the weak links in the distribution network, the distribution network resilience risk assessment results are generated.

2. The method for assessing the resilience risk of distribution networks applicable to scenarios with a high proportion of renewable energy access, as described in claim 1, is characterized in that... The active power output of the new energy sources includes the active power output of distributed photovoltaic power and the active power output of wind power. The range of the active power output of distributed photovoltaic power is represented as follows: In the formula, For access nodes The active power output range of distributed photovoltaic power generation. For the lower limit of the contribution of distributed photovoltaic power, The upper limit of the contribution of distributed photovoltaic power. This represents the historical average active power output of distributed photovoltaic systems. , is the confidence coefficient The standard deviation of historical distributed photovoltaic power output. This refers to the rated capacity of distributed photovoltaic power. The range of active power output of the wind power generation is represented as follows: In the formula, For access nodes The active power output range of wind power generation, The lower boundary contributes to wind power generation. The upper limit of the contribution of wind power generation. This represents the historical average active power output of wind power generation. The standard deviation of historical wind power output. This refers to the rated capacity of wind power generation.

3. The method for assessing the resilience risk of distribution networks applicable to scenarios with a high proportion of renewable energy access, as described in claim 1, is characterized in that... The specific steps for solving the interval solutions for voltage magnitude at each node and active power in each branch of the distribution network using an interval power flow calculation method based on affine arithmetic include: Convert the active power output range of new energy sources at each node of the distribution network into an affine form; Substituting the affine form of the active power output interval of new energy sources into the power flow equation of the distribution network, the affine form of each state variable is solved by using the affine arithmetic operation rules, and then transformed into the interval solution of the voltage amplitude of each node and the active power of each branch of the distribution network.

4. The method for assessing the resilience risk of distribution networks applicable to scenarios with a high proportion of renewable energy access, as described in claim 3, is characterized in that... The calculation formula for converting the active power output range of new energy sources at each node of the distribution network into affine form is as follows: In the formula, For nodes The active power output range of affine-shaped new energy sources This is the center value of the active power output range of new energy sources. The radius of the active power output range of new energy sources. For noise symbols, The lower bound of the range for new energy contribution. This is the upper limit of the range for active power output from new energy sources.

5. The method for assessing the resilience risk of distribution networks applicable to scenarios with a high proportion of renewable energy access, as described in claim 3, is characterized in that... The power flow equations of the distribution network are as follows: In the formula, branch road active power, For nodes Net active power load, branch road The resistance, branch road The square of the current amplitude, For nodes The set of downstream nodes, branch road active power, branch road reactive power, For nodes reactive load, branch road Reactance, branch road reactive power, For nodes voltage amplitude, For nodes The voltage amplitude.

6. The method for assessing the resilience risk of distribution networks applicable to scenarios with a high proportion of renewable energy access, as described in claim 3, is characterized in that... The specific steps for substituting the affine form of the active power output interval of new energy sources into the power flow equations of the distribution network, solving for the affine form of each state variable through affine arithmetic rules, and then converting it into the interval solution of the voltage amplitude of each node and the active power of each branch of the distribution network include: Calculate the affine form of the power of each branch sequentially from the end node of the distribution network towards the root node; From the root node of the distribution network to the terminal node, update the affine form of the voltage of each node in sequence; Calculate the maximum change in the center value of the affine form of each node voltage. If it is less than the preset convergence threshold, convert the affine form of each branch power and each node voltage into an interval form output to obtain the interval solution of the voltage amplitude of each node and the active power of each branch of the distribution network. Otherwise, return to the above steps for iteration. When the active power output range of new energy sources is too large, causing the interval power flow calculation based on affine arithmetic to fail to converge, the interval bisection method is used to divide the original active power output range of new energy sources into two sub-intervals, and the interval power flow calculation based on affine arithmetic is performed separately. The union of the results of the two sub-intervals is taken as the final result.

7. The method for assessing the resilience risk of distribution networks applicable to scenarios with a high proportion of renewable energy access, as described in claim 1, is characterized in that... The resilience quantification index system includes resilience indicators, adaptability indicators, and recovery capability indicators. The resilience index is used to characterize the ability of the distribution network to maintain normal operation under disturbances, and the calculation formula is as follows: In the formula, As a resilience indicator, For nodes The importance weight of the load, For nodes The range of load reduction caused by voltage exceeding limits or branch overload. For nodes The original load; The adaptability index is used to characterize the ability of a distribution network to adapt to disturbances through topology reconfiguration and resource scheduling, and the calculation formula is as follows: In the formula, As an indicator of adaptability, The number of feasible running points to satisfy the operational constraints. This represents the total number of running points sampled within the interval; The recovery capability index is used to characterize the ability of the distribution network to recover from a fault state to a normal state, and the calculation formula is as follows: In the formula, As an indicator of recovery capacity, For the available reserve capacity of the distribution network, This represents the maximum possible load loss of the distribution network.

8. The method for assessing the resilience risk of distribution networks applicable to scenarios with a high proportion of renewable energy access, as described in claim 1, is characterized in that... Based on sensitivity analysis, the specific steps for identifying weak links in the distribution network, including calculating the influence factors of each node and branch on each resilience quantification index, are as follows: Calculate the voltage over-limit sensitivity factor for each node; Calculate the overload sensitivity factor for each branch; All nodes and branches are sorted according to the magnitude of the voltage over-limit sensitivity factor and the overload sensitivity factor to identify the weak links in the distribution network.

9. The method for assessing the resilience risk of distribution networks applicable to scenarios with a high proportion of renewable energy access, as described in claim 8, is characterized in that... The voltage exceedance sensitivity factor is used to characterize the impact of changes in active power output from new energy sources on the range of node voltage fluctuations. The calculation formula is as follows: In the formula, For nodes Voltage over-limit sensitivity factor, For nodes The upper limit of the voltage range, For nodes The lower bound of the voltage range. It is the sum of the radii of the active power output ranges of all new energy sources; The overload sensitivity factor is used to characterize the impact of changes in the active power output of new energy sources on the maximum power of the branch. The calculation formula is as follows: In the formula, branch road The overload sensitivity factor branch road The upper limit of the active power range.

10. A distribution network resilience risk assessment system suitable for scenarios with a high proportion of renewable energy access, characterized in that, include: The historical active power output data acquisition module is used to acquire historical active power output data of new energy sources in the distribution network; The active power output range construction module is used to model the active power output of new energy sources as range variables based on the historical active power output data of the new energy sources, so as to obtain the active power output range of new energy sources. The interval solution module is used to solve the interval solutions of voltage amplitude at each node and active power of each branch of the distribution network based on the active power output interval of new energy sources and the interval power flow calculation method based on affine arithmetic. The resilience quantification index interval value calculation module is used to calculate the interval values ​​of each resilience quantification index in the distribution network resilience quantification index system based on the interval solutions of the voltage amplitude of each node in the distribution network and the active power of each branch in the distribution network. The weak link identification module is used to calculate the influence factors of each node and branch of the distribution network on each resilience quantitative index based on the sensitivity analysis method, and to identify the weak links of the distribution network. The resilience risk assessment module is used to generate distribution network resilience risk assessment results based on the range values ​​of various resilience quantification indicators and the weak links in the distribution network.

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