Power distribution system toughness evaluation method and system based on toughness power supply resource unified modeling

Abstract

The invention provides a power distribution system toughness evaluation method and system based on toughness power supply resource unified modeling. The method comprises the steps of obtaining node survival expectation, node load loss expectation and toughness resources in a power distribution network; based on the node survival expectation and the node load loss expectation, calculating the toughness resource supporting capability through a toughness resource unified model, wherein the toughness resource unified model is constructed based on the toughness resources and preset related constraints thereof; and calculating a power distribution system toughness index based on the toughness resource supporting capability, and completing power distribution system toughness evaluation. According to the invention, the problems of high complexity and difficulty of toughness evaluation of the existing power distribution system are solved.

Description

Technical Field

[0001] The present invention relates to the field of power grid control technology, and in particular to a distribution system resilience assessment method and system based on unified modeling of resilient power supply resources. Background Art

[0002] In the process of low-carbon transformation of distribution systems, distributed power sources and energy storage technologies have become important means to improve the resilience of distribution systems. Emerging energy forms such as electric vehicles (V2G) may also become potential resilience resources. However, as the types of resilience resources continue to increase, the complexity of resilience resource modeling has posed a challenge to further expand resilience-related research models. How to mathematically model various resilience resources while considering universality is a difficult problem in the field of resilience research.

[0003] For different forms of resilient resources, existing studies have modeled resilient resources from different aspects such as resource support capacity and dispatchability to improve the resilience of distribution systems. However, existing studies often model and analyze specific resilient resources, lacking analysis and summary of the common characteristics of different resilient resources. Due to the lack of common modeling, the role of different resilient resources in improving system resilience is difficult to quantify and compare. In addition, the complexity of modeling various types of resilient resources also increases the difficulty of system resilience assessment and reduces the computational efficiency of system optimization. In order to better evaluate the value of low-carbon resources in improving resilience and speed up the efficiency of resilience assessment, it is necessary to unify the modeling of different forms of resilient resources. Summary of the invention

[0004] The present invention provides a distribution system resilience assessment method and system based on unified modeling of resilient power supply resources, so as to solve the problem of high complexity and difficulty in existing distribution system resilience assessment.

[0005] The present invention provides a distribution system resilience assessment method based on unified modeling of resilient power supply resources, comprising: Obtain node survival expectation, node load loss expectation and resilience resources in the distribution network; Calculating the resilience resource support capability through a unified resilience resource model based on the node survival expectation and the node load loss expectation, wherein the unified resilience resource model is constructed based on the resilience resource and its preset related constraints; The resilience index of the power distribution system is calculated based on the supporting capacity of the resilience resources, and the resilience assessment of the power distribution system is completed.

[0006] According to a distribution system resilience assessment method based on unified modeling of resilient power supply resources provided by the present invention, the unified model of resilient resources is constructed based on the resilient resources and their preset related constraints, including: Obtaining upper and lower limits of energy and power of the toughness resource; Based on the upper and lower limits of energy and power of resilient resources, a unified model of resilient resources is constructed according to the preset timing constraints.

[0007] According to a distribution system resilience assessment method based on unified modeling of resilient power supply resources provided by the present invention, the resilient resource unified model is constructed based on the upper and lower limits of energy and power of resilient resources according to preset timing constraints, including: Obtaining the movable resource position of the emergency power supply vehicle and the energy boundary of the electrified transportation resource in the resilient resources, and determining the timing constraint relationship; Based on the energy and power limits of emergency power supply vehicles and electrified transportation resources, the energy range and power range resources are unified according to the timing constraints, and a unified model of resilience resources is constructed.

[0008] According to a distribution system resilience assessment method based on unified modeling of resilient power supply resources provided by the present invention, the method of obtaining the movable resource position of the emergency power supply vehicle and the energy boundary of the electrified transportation resources in the resilient resources and determining the timing constraint relationship includes: The movable resource position of the emergency power supply vehicle in the resilient resource is determined by deploying the movable resource to the node with the maximum expected load loss, performing support capacity calculation, and completing the correction and update of the expected load loss until the movable resource is deployed; The energy boundary of the electrified transportation resources is determined by taking daily commuting routes as units, inputting the behavior pattern statistics of the electrified transportation resources, respectively calculating the energy boundary of the electrified transportation resources of each behavior pattern, calculating the proportion of electric vehicles in each behavior pattern, aggregating the energy boundary of the electrified transportation resource cluster on the commuting route, and attributing its energy boundary to the energy boundary of the charging station according to the location of the electrified transportation resource; The movable resource position of the emergency power supply vehicle in the resilient resources and the energy boundary of the electrified transportation resources are combined as energy constraint conditions to determine the timing constraint relationship.

[0009] According to a distribution system resilience assessment method based on unified modeling of resilient power supply resources provided by the present invention, the resilient resource support capability is calculated through a unified model of resilient resources based on the node survival expectation and the node load loss expectation, including: Setting a support range of resilience resources for a unified resilience resource model based on the node survival expectation and the node load loss expectation; Update the upper limit of the support capacity of the resilient resource based on the set support range, and calculate the support capacity of the resilient resource for the node where it is located; Update the node load loss expectation, the remaining support capacity of the resilient resources, and the remaining energy based on the support capacity of the resilient resources to the node. According to the updated node load loss expectation, the remaining support capacity of the resilience resource and the remaining energy, it is judged that the power of the resilience resource is not greater than zero and the remaining energy of the resilience resource is not greater than the lower limit of the resource energy, which means that all the resilience resources are consumed and the resilience resource support capacity is obtained.

[0010] According to a distribution system resilience assessment method based on unified modeling of resilient power supply resources provided by the present invention, a distribution system resilience index is calculated based on the resilient resource support capability to complete the distribution system resilience assessment, including: Deploy resilience resources at each node of the power grid in sequence according to their support capabilities; The distribution system resilience index is calculated based on the power support situation fed back by each node in real time, and the distribution system resilience assessment is completed based on the distribution system resilience index.

[0011] The present invention also provides a distribution system resilience assessment system based on unified modeling of resilient power supply resources, the system comprising: Resource acquisition module, used to obtain node survival expectation, node load loss expectation and resilience resources in the distribution network; A support capacity calculation module, used to calculate the resilience resource support capacity through a resilience resource unified model based on the node survival expectation and the node load loss expectation, wherein the resilience resource unified model is constructed based on the resilience resource and its preset related constraints; A resilience assessment module is used to calculate the resilience index of the distribution system based on the resilience resource support capability to complete the resilience assessment of the distribution system. The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, a distribution system resilience assessment method based on unified modeling of resilient power supply resources as described in any of the above is implemented.

[0012] The present invention also provides a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, it implements the distribution system resilience assessment method based on unified modeling of resilient power supply resources as described in any of the above.

[0013] The present invention also provides a computer program product, including a computer program, which, when executed by a processor, implements any of the above-mentioned methods for evaluating the resilience of a distribution system based on unified modeling of resilient power supply resources.

[0014] The present invention provides a distribution system resilience assessment method and system based on unified modeling of resilient power supply resources. By analyzing the common characteristics of resilient power supply resources, the resilient power supply resources are modeled as a generalized energy storage resource, and their key parameter attributes are given; a method for converting commonly used resilient power supply resources into a unified modeling model is proposed, and the resilient resource support capacity is calculated through a unified model of resilient resources based on node survival expectations and node load loss expectations. The distribution system resilience index is calculated according to the resilient resource support capacity, the distribution system resilience assessment is completed, and the complexity of the distribution system resilience assessment is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0016] Figure 1 It is a flow chart of the distribution system resilience assessment method based on unified modeling of resilient power supply resources provided by the present invention.

[0017] Figure 2 It is a schematic diagram of the support range of the resilient power supply resources provided by the present invention.

[0018] Figure 3 It is a module connection diagram of the distribution system resilience assessment system based on unified modeling of resilient power supply resources provided by the present invention.

[0019] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention.

[0020] Reference numerals: 110: resource acquisition module; 120: support capability calculation module; 130: resilience assessment module; 410: processor; 420: communication interface; 430: memory; 440: communication bus. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] The existing resilience resource assessment system only considers the impact of the system topology and power nodes in the system on the system resilience level, but does not consider other resilience resources in the distribution system. When other resilience resources are comprehensively considered, the revised node load expected level calculation method can be obtained: (1)

[0023] in, Representation Node i exist t The period is subject to resilience resources to support power expectations.

[0024] Combined with formula (1), it can be found that improving the resilience level of the system can be achieved by improving It can also be achieved by improving Implementation. For the former, it mainly includes resilience enhancement means / resilience resources acting on the system topology level, including but not limited to: adding transfer lines, adding maintenance resources, line reinforcement, adding power supply nodes, etc. For the latter, the present invention will be able to provide emergency support for the load, but it cannot be used as a power supply resource for the system power supply node, which is defined as a resilient power supply resource.

[0025] Combine the following Figure 1 A method for evaluating the resilience of a power distribution system based on unified modeling of resilient power supply resources according to the present invention is described, comprising: Step 100: Obtain node survival expectation, node load loss expectation and resilience resources in the distribution network; In the present invention, in order to uniformly model resilient power supply resources, it is first necessary to analyze the similarities and differences in the properties and application modes of commonly used resilient resources to provide a basis for establishing a unified model. An introduction is given to the commonly used forms of resilient resources in distribution systems. Common resilient resources mainly include: distributed power sources (gas turbines / diesel generators / renewable energy), energy storage, emergency power supply vehicles (power generation / energy storage), electrified transportation resources (electric buses / electric taxis / private electric vehicles), etc. The above resources have many differences in total energy, output power, mobility, dispatchability, etc., and the specific differences are shown in Table 1.

[0026] Table 1

[0027] The main grid power supply is usually not considered as a resilient resource, but as the main power supply source of the distribution system, its role in the distribution system cannot be ignored and is listed in the table for comparison with resilient resources; the standard for "Is the energy limited" in the table header is whether the corresponding resource will exhaust its energy during the resilient recovery process, so renewable energy is "×" in this item, and some gas turbines that use gas grid gas supply can be "×" in this item under the premise of the gas grid reliability; the standard for "Is the power limited" in the table header is whether the corresponding resource can support the entire distribution system. In the distribution system, the main grid power supply can usually be considered to have unlimited power. In some cases (such as overall power shortage in the upper power system), the main grid power can also be considered to have limited power. As shown in Table 1, most resilient power supply resources have limited energy and power during the resilient recovery process. Different resilient resources have large differences in mobility, which can be divided into movable resources and immovable resources. Among the movable resources, the location dispatchability of different resources is different.

[0028] Step 200: Calculate the resilience resource support capability through a resilience resource unified model based on the node survival expectation and the node load loss expectation, wherein the resilience resource unified model is constructed based on the resilience resource and its preset related constraints; Specifically, the unified resilience resource model is constructed based on the resilience resources and their preset related constraints, including: Obtaining upper and lower limits of energy and power of the toughness resource; Based on the upper and lower limits of energy and power of resilient resources, a unified model of resilient resources is constructed according to the preset timing constraints.

[0029] From the perspective of the energy of resilient resources, the energy of most resources during the resilience recovery process is limited. Therefore, in the unified model of resilient resources, there should be upper and lower limits on the total energy of resources. For resources such as renewable energy, their output depends on the natural environment rather than their own stored energy; for gas turbines supplied by the gas grid, their power output depends on the gas grid; and the main grid power supply energy depends on the main grid. The total energy of these types of resources can be considered to be (or no total amount of energy), that is, energy will not be exhausted (or there is no concept of total amount of energy).

[0030] Secondly, from the perspective of the power of resilient resources, the output power of resilient resources is usually unable to support the entire distribution system. Therefore, in the unified model of resilient resources, there should be upper and lower limits on the power output of resources. For resources that cannot adjust their output power (such as some renewable energy sources), their upper and lower limits of output power can be considered equal. The main grid power supply can be based on the output power upper limit. modeling in this way.

[0031] Finally, from the perspective of the mobility of resilient resources, except for the emergency power supply vehicles directly dispatched by the power grid company, the dispatching capabilities of other electrified vehicles are weak or cannot be dispatched. For this type of mobile resilient resources, when conducting resilience assessment, it is not necessary to pay attention to which specific electric car or electric bus provides the resources. It is only necessary to pay attention to the dispatching boundaries of the mobile resilient resources contained in each node of the power grid at different time periods. And this boundary can be modeled from the above-mentioned energy and power perspectives. In the present invention, resilient resources can be regarded as a special "energy storage" resource, and a unified model of resilient power supply resources for the distribution system is established.

[0032] In the analysis of commonly used resilient power supply resources, the criterion of "whether the power is limited" actually measures the support range of the resources. In the resilience assessment based on node survival, the support capacity of power supply resources for the system can be reflected in two ways: improving the expectation of node survival; reducing the expected loss of system load. The former corresponds to the power supply nodes in the system, and the latter corresponds to the resilient power supply resources.

[0033] In the process of calculating the survival expectation of nodes, it is necessary to set power supply nodes in the probability graph. This type of power supply node can be considered to be able to support the entire system, and its support capacity is reflected in reducing the probability of power failure of nodes in the entire network, thereby improving the resilience level of the system. This type of power supply is not modeled as a resilient power supply resource. For the main grid power supply, its active and reactive support capabilities are strong and can support the entire distribution system. In this study, it is set as a power supply node. For some distributed power sources with strong active and reactive support capabilities, they have the ability to serve as the core power supply of the isolated power grid during the topological reconstruction of the distribution system. Such resources can also be set as power supply nodes in the probability graph. Although this type of power supply cannot support the entire system when it is powered alone, in the resilience scenario, its ability to support the isolated power grid can be approximately considered to support the entire system: when the disaster is relatively minor, the probability of each load node being connected to the main grid power supply is relatively high, and the expected loss is relatively small. At this time, this type of power supply is used as a supplement to the main grid power supply and does not need to support the ability of the entire system; when the disaster is relatively serious, the probability of line outage is relatively high, and the probability of reliable power supply path from the power supply node to other load nodes decays rapidly with distance, so the actual support range does not need to and cannot reach the range of the complete system.

[0034] When calculating node load loss, the impact of resilient power supply resources on load loss needs to be considered. Resilient power supply resources with a small support range should not be set as power supply nodes in the probability graph. Their support capacity can be reflected in the expected load loss of the node when calculating load loss. The correction of The relationship between the node expected load loss and the node expected load is as follows:

[0035] in, Resilience Resources k A collection of Resilience Resources k For nodes support capabilities. Resilience Resources k For nodes The expected support capacity is calculated as follows:

[0036] in, Resilience resources k The node set of the support range, express t Time period resources k Node j To Node i The reliability probability of the power supply path is shown in the schematic diagram Figure 2 shown.

[0037] In the present invention, it is considered is the node where resource k is located and its adjacent nodes. The resilient resources classified in this category usually have weak support capabilities and mainly meet the load requirements of the nodes where they are located. If their support capabilities are greater than the requirements of the nodes where they are located, their support range is also small. They usually have no ability to support nodes that are far away, so it is considered The simplified assumptions for the node where resource k is located and its adjacent nodes are more reasonable. It can also be adjusted according to actual needs.

[0038] In the unified model of resilient power supply resources, the variables involved in expressing each resource and their meanings are specifically shown in Table 2.

[0039] Table 2

[0040] Different from the modeling form of ordinary energy storage, in order to be compatible with different types of resilient resources, resources k In the period t The energy upper / lower limits and power upper / lower limits are defined in a time-varying form.

[0041] In order to use the unified model of resilience resources in the resilience recovery scenario, the variables involved in the resources need to meet the following constraints:

[0042] Among them, formula (5) and (6) represent resources k The power and energy upper and lower limits of the resource are constrained. k The timing constraints of the energy are Indicates the duration of each period. Formula (8) indicates the resource k Energy ratio calculation method.

[0043] In equation (7), considering the scarcity of energy resources in the resilience recovery scenario, the behavior of charging resource k is simplified. If the impact of energy storage charging and discharging needs to be considered, the charging power can be added to the model and equation (7) can be modified accordingly. In addition, considering the existence of resources with time-varying energy upper and lower limits (such as aggregated electric vehicles), And use Ways to express t -1 period of energy.

[0044] In the present invention, a unified model of resilient resources is constructed based on the energy upper and lower limits and power upper and lower limits of resilient resources according to preset timing constraints, including: Obtaining the movable resource position of the emergency power supply vehicle and the energy boundary of the electrified transportation resource in the resilient resources, and determining the timing constraint relationship; Based on the energy and power limits of emergency power supply vehicles and electrified transportation resources, the energy range and power range resources are unified according to the timing constraints, and a unified model of resilience resources is constructed.

[0045] Specifically, different types of resilience resources are expressed differently in the unified resilience resource model.

[0046] Distributed power sources can be divided into two categories: unlimited energy and limited power, and limited energy and limited power.

[0047] For distributed power sources with unlimited energy and limited power (such as gas turbines supplied by the gas grid and renewable energy), their energy cap can be set to for , and the remaining attributes are set according to the actual attributes. For example, the upper and lower limits of the power of renewable energy should usually satisfy the following formula:

[0048] For distributed power sources with limited energy and power (such as diesel generators), their upper and lower limits of energy and power can be considered as constants, and the time series relationship of their residual energy can be simplified as follows:

[0049] Energy storage module, energy storage is a resilient resource with limited energy and power during resilience recovery, so it has the same expression as the distributed power source that relies on stored fuel, that is, the upper and lower limits of energy and power are constants. Without considering charging the energy storage during resilience recovery, the time series relationship of its remaining energy can also be simplified to the form of formula (10).

[0050] The emergency power supply vehicle is a resilient resource with limited energy and power during the resilience recovery process, so its upper and lower limits of energy and power are constants. Without considering the energy replenishment to the emergency power supply vehicle during resilience recovery, the time series relationship of its remaining energy can also be simplified to the form of formula (10).

[0051] The main difference between emergency power supply vehicles and energy storage is their mobility. If their location can be determined, their role in the resilience recovery process is similar to that of distributed power sources / energy storage. In the resilience recovery process, the deployment location of the emergency power supply vehicle can be determined by mathematical programming methods. In this paper, in order to simplify the resilience recovery calculation process, a location determination method for emergency power supply vehicle resources is designed.

[0052] In the resilience assessment method based on scenario sampling, movable resilient resources are usually scheduled using mathematical programming to determine their specific locations at different times. In the resilience assessment process based on node probability, if the specific location of the movable resources is not determined, it is difficult to calculate the support capacity of the resilient power supply resources.

[0053] To this end, the present invention provides a simple method for determining the location of movable resources: Calculate the support capacity of immovable resources for the system and complete the system nodes Correction updates; Deploy movable resources to The largest node; Calculate the resilience resource support capacity and complete Correction update

[0054] If there are still movable resources, return to deploying movable resources to The largest node, otherwise end.

[0055] As for electrified transportation, there are significant differences between electrified transportation and other resilient resources. Although electrified transportation resources are a type of resilient resource with huge potential energy storage capacity, their temporal and spatial distribution is highly random, and the number and willingness of electrified transportation vehicles that can participate in resilient recovery also vary greatly. For decentralized resources such as electrified transportation, a common approach is to aggregate such decentralized resources and provide services in the form of aggregators. Charging stations can be regarded as aggregators / aggregation units, and charging stations can be regarded as a special type of static energy storage resource, assuming that they are within the controllable range of electrified transportation energy storage resources. In the resilient recovery scenario, the electrified transportation resilient resources are modeled.

[0056] As a special energy storage resource that aggregates electrified transportation, the energy storage capacity and output power range of the charging station are affected by the number of electric vehicles that can participate in V2G within its range. Its energy upper and lower limits and power upper limit can be expressed as follows:

[0057] Equations (11)-(13) represent the upper and lower limits of the output power and energy of electrified transportation resources, where Indicates charging station k The number of charging stations, Indicates the upper limit of the charging power of the charging pile; express t Always at a charging station k The number of electric vehicles Indicates the upper and lower limits of energy for a single electric vehicle, Represents the proportion of vehicles participating in resilience recovery or supporting V2G functions. If there are electric vehicles with different performance or different types of electrified transportation, equations (11)-(13) can also be expressed in the form of classification summation. For the sake of simplicity in expression and subsequent analysis, it can be considered that the current equations (11)-(13) have obtained the performance of typical / average electric vehicles based on statistical results.

[0058] For aggregated electrified transportation resources, the energy timing relationship should satisfy:

[0059] In formula (14), express t Always leave the charging station k of electric vehicle energy, express t Arrive at the charging station in no time k The energy of electric vehicles expresses the energy time series relationship of the aggregated electrified transportation resources. Equations (15) and (16) represent t Time to leave / arrive at charging station k The calculation method of electric vehicle energy is Represents the power consumption of electric vehicles. Represents the driving time of an electric vehicle. To simplify the calculation, it is assumed that the time of leaving / arriving at a charging station k The average energy of electric vehicles t -1 moment charging station k In the resilience recovery process, ignoring the charging of electric vehicles and the power consumption of electric vehicle driving, and substituting equations (15) and (16) into equation (14), we can get equations (7) and (8).

[0060] However, if the spatiotemporal distribution and mobility information of a large number of electrified transportation resources are calculated during the resilience recovery process, the calculation and analysis process will be complicated and will not directly help the resilience recovery. To this end, before resilience recovery, the time-varying energy boundary and power boundary of the electrified transportation resources can be calculated based on the statistical laws of the spatiotemporal distribution and mobility information of the electrified transportation resources, and then used as known information and input into the calculation process of resilience recovery as a constraint condition. The present invention will introduce a method for calculating the time-varying energy boundary and power boundary of electrified transportation resources, and the specific process is as follows: Input the behavior pattern statistics of electric vehicles based on daily commuting routes; The energy boundary of electric vehicles for each behavior mode is calculated separately; Calculate the proportion of electric vehicles in each behavior mode and aggregate them to obtain the energy boundary of the electric vehicle cluster on the commuting route; According to the location of the electric vehicle, its energy boundary is included in the energy boundary of the charging station.

[0061] The energy boundaries of electric vehicle resources in different forms are obtained. According to the obtained time-varying energy boundaries, the resilience resources of electrified transportation can be utilized to participate in the resilience recovery process of the distribution system.

[0062] Step 300: Calculate the resilience index of the power distribution system based on the resilience resource support capability to complete the resilience assessment of the power distribution system.

[0063] In the present invention, in the distribution system resilience assessment method based on node survival expectation, since there is no specific system disaster scenario, it is no longer feasible to reconstruct the system topology and dispatch resilience resources through mathematical programming methods in the traditional scenario-based assessment method. At this time, it is uncertain whether each line is shut down, and it is impossible to build a reconstructed island. Therefore, the support range of each resilient power supply resource is uncertain, and the location of the mobile resilient resources (emergency power supply vehicle) after dispatch is also unclear.

[0064] Refer to Table 3 to determine the calculation process for the support capacity of a single resilience resource.

[0065] Table 3

[0066] In the process of Table 3, step 2 ensures that the setting t Time period resources k Output power limit When , the constraints of equations (5) to (8) are satisfied. The operations of steps 3 to 4 and steps 9 to 10 correspond to the updating process of equation (2). The entire calculation process realizes the calculation of equation (4).

[0067] The distribution system resilience index is calculated based on the resilience resource support capacity, and the distribution system resilience assessment is completed, including: Deploy resilience resources at each node of the power grid in sequence according to their support capabilities; The distribution system resilience index is calculated based on the power support situation fed back by each node in real time, and the distribution system resilience assessment is completed based on the distribution system resilience index.

[0068] Based on the distribution system resilience assessment method based on unified modeling of resilient power supply resources provided by the present invention, by analyzing the common characteristics of resilient power supply resources, the resilient power supply resources are modeled as a generalized energy storage resource, and their key parameter attributes are given; a method for converting commonly used resilient power supply resources into a unified modeling model is proposed, and the resilient resource supporting capacity is calculated through the resilient resource unified model based on the node survival expectation and the node load loss expectation, and the distribution system resilience index is calculated according to the resilient resource supporting capacity, so as to complete the distribution system resilience assessment and reduce the complexity of the distribution system resilience assessment.

[0069] refer to Figure 3 The present invention also discloses a distribution system resilience assessment system based on unified modeling of resilient power supply resources, the system comprising: A resource acquisition module 110 is used to obtain node survival expectations, node load loss expectations and resilience resources in the distribution network; A support capacity calculation module 120, configured to calculate the resilience resource support capacity through a resilience resource unified model based on the node survival expectation and the node load loss expectation, wherein the resilience resource unified model is constructed based on the resilience resource and its preset related constraints; The resilience assessment module 130 is used to calculate the resilience index of the distribution system based on the resilience resource support capability and complete the resilience assessment of the distribution system.

[0070] The unified resilience resource model is constructed based on the resilience resources and their preset related constraints, including: Obtaining upper and lower limits of energy and power of the toughness resource; Based on the upper and lower limits of energy and power of resilient resources, a unified model of resilient resources is constructed according to the preset timing constraints.

[0071] Based on the upper and lower limits of energy and power of resilient resources, a unified model of resilient resources is constructed according to the preset timing constraints, including: Obtaining the movable resource position of the emergency power supply vehicle and the energy boundary of the electrified transportation resource in the resilient resources, and determining the timing constraint relationship; Based on the energy and power limits of emergency power supply vehicles and electrified transportation resources, the energy range and power range resources are unified according to the timing constraints, and a unified model of resilience resources is constructed.

[0072] Obtain the movable resource position of the emergency power supply vehicle and the energy boundary of the electrified transportation resource in the resilient resource, and determine the timing constraint relationship, including: The movable resource position of the emergency power supply vehicle in the resilient resource is determined by deploying the movable resource to the node with the maximum expected load loss, performing support capacity calculation, and completing the correction and update of the expected load loss until the movable resource is deployed; The energy boundary of the electrified transportation resources is determined by taking daily commuting routes as units, inputting the behavior pattern statistics of the electrified transportation resources, respectively calculating the energy boundary of the electrified transportation resources of each behavior pattern, calculating the proportion of electric vehicles in each behavior pattern, aggregating the energy boundary of the electrified transportation resource cluster on the commuting route, and attributing its energy boundary to the energy boundary of the charging station according to the location of the electrified transportation resource; The movable resource position of the emergency power supply vehicle in the resilient resources and the energy boundary of the electrified transportation resources are combined as energy constraint conditions to determine the timing constraint relationship.

[0073] The resilient resource support capability is calculated based on the node survival expectation and the node load loss expectation through a resilient resource unified model, including: Setting a support range of resilience resources for a unified resilience resource model based on the node survival expectation and the node load loss expectation; Update the upper limit of the support capacity of the resilient resource based on the set support range, and calculate the support capacity of the resilient resource for the node where it is located; Update the node load loss expectation, the remaining support capacity of the resilient resources, and the remaining energy based on the support capacity of the resilient resources to the node. According to the updated node load loss expectation, the remaining support capacity of the resilience resource and the remaining energy, it is judged that the power of the resilience resource is not greater than zero and the remaining energy of the resilience resource is not greater than the lower limit of the resource energy, which means that all the resilience resources are consumed and the resilience resource support capacity is obtained.

[0074] The distribution system resilience index is calculated based on the resilience resource support capacity, and the distribution system resilience assessment is completed, including: Deploy resilience resources at each node of the power grid in sequence according to their support capabilities; The distribution system resilience index is calculated based on the power support situation fed back by each node in real time, and the distribution system resilience assessment is completed based on the distribution system resilience index.

[0075] Based on the distribution system resilience assessment system based on unified modeling of resilient power supply resources provided by the present invention, by analyzing the common characteristics of resilient power supply resources, the resilient power supply resources are modeled as a generalized energy storage resource, and their key parameter attributes are given; a method for converting commonly used resilient power supply resources into a unified modeling model is proposed, and the resilient resource supporting capacity is calculated through the resilient resource unified model based on the node survival expectation and the node load loss expectation, and the distribution system resilience index is calculated according to the resilient resource supporting capacity, so as to complete the distribution system resilience assessment and reduce the complexity of the distribution system resilience assessment.

[0076] Figure 4 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430 and a communication bus 440, wherein the processor 410, the communication interface 420 and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute a distribution system resilience assessment method based on unified modeling of resilient power supply resources, the method comprising: obtaining node survival expectations, node load loss expectations and resilient resources in the distribution network; calculating the resilient resource support capability through a resilient resource unified model based on the node survival expectations and node load loss expectations, wherein the resilient resource unified model is constructed based on the resilient resources and their preset related constraints; calculating the distribution system resilience index based on the resilient resource support capability to complete the distribution system resilience assessment.

[0077] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0078] On the other hand, the present invention also provides a computer program product, which includes a computer program, and the computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the distribution system resilience assessment method based on unified modeling of resilient power supply resources provided by the above-mentioned methods, and the method includes: obtaining node survival expectations, node load loss expectations and resilient resources in the distribution network; calculating the resilient resource support capability through a unified resilient resource model based on the node survival expectations and node load loss expectations, wherein the unified resilient resource model is constructed based on the resilient resources and their preset related constraints; calculating the distribution system resilience index based on the resilient resource support capability to complete the distribution system resilience assessment.

[0079] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, it is implemented to execute the distribution system resilience assessment method based on unified modeling of resilient power supply resources provided by the above-mentioned methods, the method comprising: obtaining node survival expectations, node load loss expectations and resilient resources in the distribution network; calculating the resilient resource support capability through a unified resilient resource model based on the node survival expectations and node load loss expectations, wherein the unified resilient resource model is constructed based on the resilient resources and their preset related constraints; calculating the distribution system resilience index based on the resilient resource support capability to complete the distribution system resilience assessment.

[0080] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0081] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A distribution system resilience assessment method based on unified modeling of resilient power supply resources, characterized in that: include: Obtain node survival expectation, node load loss expectation and resilience resources in the distribution network; Calculating the resilience resource support capability through a unified resilience resource model based on the node survival expectation and the node load loss expectation, wherein the unified resilience resource model is constructed based on the resilience resource and its preset related constraints; The resilience index of the power distribution system is calculated based on the supporting capacity of the resilience resources, and the resilience assessment of the power distribution system is completed.

2. The method for evaluating the resilience of a distribution system based on unified modeling of resilient power supply resources according to claim 1 is characterized in that: The unified resilience resource model is constructed based on the resilience resources and their preset related constraints, including: Obtaining upper and lower limits of energy and power of the toughness resource; Based on the upper and lower limits of energy and power of resilient resources, a unified model of resilient resources is constructed according to the preset timing constraints.

3. The method for evaluating the resilience of a distribution system based on unified modeling of resilient power supply resources according to claim 2 is characterized in that: The energy upper and lower limits and power upper and lower limits based on the resilient resources are used to construct a unified resilient resource model according to a preset timing constraint relationship, including: Obtaining the movable resource position of the emergency power supply vehicle and the energy boundary of the electrified transportation resource in the resilient resources, and determining the timing constraint relationship; Based on the energy and power limits of emergency power supply vehicles and electrified transportation resources, the energy range and power range resources are unified according to the timing constraints, and a unified model of resilience resources is constructed.

4. The method for evaluating the resilience of a distribution system based on unified modeling of resilient power supply resources according to claim 3 is characterized in that: The obtaining of the movable resource position of the emergency power supply vehicle in the resilient resources and the energy boundary of the electrified transportation resources and determining the timing constraint relationship includes: The movable resource position of the emergency power supply vehicle in the resilient resource is determined by deploying the movable resource to the node with the maximum expected load loss, performing support capacity calculation, and completing the correction and update of the expected load loss until the movable resource is deployed; The energy boundary of the electrified transportation resources is determined by taking daily commuting routes as units, inputting the behavior pattern statistics of the electrified transportation resources, respectively calculating the energy boundary of the electrified transportation resources of each behavior pattern, calculating the proportion of electric vehicles in each behavior pattern, aggregating the energy boundary of the electrified transportation resource cluster on the commuting route, and attributing its energy boundary to the energy boundary of the charging station according to the location of the electrified transportation resource; The movable resource position of the emergency power supply vehicle in the resilient resources and the energy boundary of the electrified transportation resources are combined as energy constraint conditions to determine the timing constraint relationship.

5. The method for evaluating the resilience of a distribution system based on unified modeling of resilient power supply resources according to claim 1, characterized in that: The calculating the resilience resource support capability through a resilience resource unified model based on the node survival expectation and the node load loss expectation includes: Setting a support range of resilience resources for a unified resilience resource model based on the node survival expectation and the node load loss expectation; Update the upper limit of the support capacity of the resilient resource based on the set support range, and calculate the support capacity of the resilient resource for the node where it is located; Update the node load loss expectation, the remaining support capacity of the resilient resources, and the remaining energy based on the support capacity of the resilient resources to the node. According to the updated node load loss expectation, the remaining support capacity of the resilience resource and the remaining energy, it is judged that the power of the resilience resource is not greater than zero and the remaining energy of the resilience resource is not greater than the lower limit of the resource energy, which means that all the resilience resources are consumed and the resilience resource support capacity is obtained.

6. The method for evaluating the resilience of a distribution system based on unified modeling of resilient power supply resources according to claim 1 is characterized in that: Based on the resilience resource support capability, the distribution system resilience index is calculated to complete the distribution system resilience assessment, including: Deploy resilience resources in sequence at each node of the power grid according to their support capabilities; The distribution system resilience index is calculated based on the power support situation fed back by each node in real time, and the distribution system resilience assessment is completed based on the distribution system resilience index.

7. A distribution system resilience assessment system based on unified modeling of resilient power supply resources, characterized in that: The system comprises: Resource acquisition module, used to obtain node survival expectation, node load loss expectation and resilience resources in the distribution network; A support capacity calculation module, used to calculate the resilience resource support capacity through a resilience resource unified model based on the node survival expectation and the node load loss expectation, wherein the resilience resource unified model is constructed based on the resilience resource and its preset related constraints; The resilience assessment module is used to calculate the resilience index of the distribution system based on the resilience resource support capacity and complete the resilience assessment of the distribution system.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, it implements the distribution system resilience assessment method based on unified modeling of resilient power supply resources as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the distribution system resilience assessment method based on unified modeling of resilient power supply resources as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, it implements the distribution system resilience assessment method based on unified modeling of resilient power supply resources as described in any one of claims 1 to 6.

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