Planning method of urban power distribution network and related device

Abstract

The invention provides a planning method of an urban power distribution network and a related device. The planning method comprises the following steps: according to historical operation data of an urban power distribution network, improving the urban power distribution network according to power supply and load balance constraints to obtain a first simulation power distribution network; a second simulation power distribution network is obtained by adjusting a network construction type energy storage device in the first simulation power distribution network; wherein the short-circuit ratio of power grid nodes in the second simulation power distribution network is higher than a specified threshold value; for a high-occurrence-probability fault determined according to the historical operation data, a fault coping scheme is formulated for the second simulation power distribution network, so that when the high-occurrence-probability fault occurs in the second simulation power distribution network, a specified transient stability constraint is met; wherein the transient stability constraint is used for representing a transient stability requirement when a fault occurs. According to the urban power distribution network planning method and the related device, the stability of the urban power distribution network can be improved to a certain extent.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of power electronics technology, and specifically to a planning method and related devices for an urban distribution network. Background Art

[0002] Urban distribution networks are the core infrastructure of modern urban power supply, and their operational reliability and stability are directly related to the normal operation of residents' lives and economic activities. However, with the increasing proportion of distributed energy (such as wind power and photovoltaics) access, the operational stability of urban distribution networks faces increasing risks. Summary of the invention

[0003] Multiple embodiments of the present application provide a planning method and related devices for an urban distribution network, which can improve the stability of the urban distribution network to a certain extent.

[0004] In a first aspect, an embodiment of the present application provides a planning method for an urban distribution network, comprising: based on historical operation data of the urban distribution network, improving the urban distribution network in accordance with power and load balance constraints to obtain a first simulated distribution network; obtaining a second simulated distribution network by adjusting a grid-forming energy storage device in the first simulated distribution network; wherein the short-circuit ratio of the grid nodes in the second simulated distribution network is higher than a specified threshold; for a high probability fault determined according to the historical operation data, formulating a fault response plan for the second simulated distribution network, so that when the high probability fault occurs in the second simulated distribution network, the fault response plan is executed to make the second simulated distribution network comply with a specified transient stability constraint; wherein the transient stability constraint is used to represent the transient stability requirement when a fault occurs.

[0005] Optionally, the step of obtaining the second simulated distribution network by adjusting the grid-forming energy storage device in the first simulated distribution network includes: determining multiple basic operating conditions of the urban distribution network based on the historical operating data; adjusting the grid-forming energy storage device in the first simulated distribution network so that the short-circuit ratio of the grid node in each basic operating condition is higher than a specified threshold.

[0006] Optionally, the step of adjusting the grid-forming energy storage device in the first simulated distribution network so that the short-circuit ratio of the grid nodes in each basic operating condition is higher than a specified threshold comprises: obtaining the short-circuit ratio of the grid nodes in the first simulated distribution network under the multiple basic operating conditions through simulation to obtain a target grid node whose short-circuit ratio is less than the specified threshold under the basic operating conditions; and increasing the grid-forming energy storage capacity or the grid-forming energy storage device near the target grid node so that the short-circuit ratio of the target grid node is higher than the specified threshold.

[0007] Optionally, for a high probability fault determined based on the historical operating data, a step of formulating a fault response plan corresponding to the second simulated distribution network includes: determining a target grid-type energy storage device in the second simulated distribution network; adjusting the inertia and damping parameters of the target grid-type energy storage device with the maintenance of the power angle stability of the second simulated distribution network as a constraint to obtain a fault response plan.

[0008] Optionally, the step of determining a target grid-type energy storage device in the second simulated distribution network includes: obtaining, through simulation, a participation factor of the grid-type energy storage device for the high probability failure in the second simulated distribution network; and selecting a grid-type energy storage device as the target grid-type energy storage device in the second simulated distribution network according to the participation factor; wherein the participation factor of the target grid-type energy storage device is greater than the participation factors of other grid-type energy storage devices.

[0009] Optionally, for a high probability fault determined based on the historical operating data, the step of formulating a fault response plan corresponding to the second simulated distribution network includes: determining a target grid-following power source in the second simulated distribution network; adjusting a proportional coefficient and / or an integral coefficient of the target grid-following power source with the constraint of maintaining the transient stability of the second simulated distribution network to obtain a fault response plan.

[0010] Optionally, the grid-following power source includes a grid-following wind turbine and / or a grid-following photovoltaic system; the step of determining a target grid-following power source in the second simulated distribution network comprises: obtaining, through simulation, a participation factor of the grid-following wind turbine and / or the grid-following photovoltaic system for the high probability failure in the second simulated distribution network; according to the participation factor, selecting a grid-following wind turbine and / or a grid-following photovoltaic system as the target grid-following power source in the second simulated distribution network; wherein the participation factor of the target grid-following power source is greater than the participation factors of other grid-following wind turbines and / or grid-following photovoltaic systems.

[0011] Optionally, based on historical operating data of the urban distribution network, the step of improving the urban distribution network in accordance with power supply and load balance constraints to obtain a first simulated distribution network includes: determining, in accordance with the power supply and load balance constraints, facility information of power facilities added to the urban distribution network to obtain the first simulated distribution network; wherein the facility information includes at least one of the following: the location and number of new lines, the location of renewable energy, the location of electric vehicle charging stations, or the capacity of energy storage facilities.

[0012] In a second aspect, an embodiment of the present application provides a planning system for an urban distribution network, comprising: an improvement module, used to improve the urban distribution network according to the historical operation data of the urban distribution network and in accordance with the power supply and load balance constraints to obtain a first simulated distribution network; an adjustment module, used to obtain a second simulated distribution network by adjusting the grid-forming energy storage device in the first simulated distribution network; wherein the short-circuit ratio of the grid nodes in the second simulated distribution network is higher than a specified threshold; a formulation module, used to formulate a fault response plan for the second simulated distribution network for a high probability fault determined according to the historical operation data, so that when the high probability fault occurs in the second simulated distribution network, the fault response plan is executed to make the second simulated distribution network meet the specified transient stability constraint; wherein the transient stability constraint is used to represent the transient stability requirement when a fault occurs.

[0013] In a third aspect, an embodiment of the present application provides a computer device, comprising a memory and a processor, wherein the memory stores at least one computer program, and the at least one computer program is loaded and executed by the processor to implement the urban distribution network planning method as described above.

[0014] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, characterized in that at least one computer program is stored in the computer-readable storage medium, and when the at least one computer program is executed by a processor, it can implement the urban distribution network planning method as described above.

[0015] In a fifth aspect, an embodiment of the present application provides a computer program product, which, when executed by a processor, implements the aforementioned urban distribution network planning method.

[0016] In multiple implementations provided in the present application, the urban distribution network is improved according to the power and load balance constraints based on the historical operation data of the urban distribution network, and combined with the optimization of the grid-type energy storage device, so that the short-circuit ratio of the distribution network nodes meets the requirements of the specified threshold, thereby enhancing the voltage support capability and anti-disturbance capability of the distribution network in dynamic operation. Furthermore, by formulating fault response plans for high-probability faults, the urban distribution network meets the constraints of transient stability when a fault occurs, and the distribution network can be quickly recovered under fault conditions, thereby improving the stability of the urban distribution network as a whole. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0018] Figure 1 A flow chart of a method for planning an urban distribution network is provided for one embodiment of the present application.

[0019] Figure 2 A module diagram of a planning system for an urban distribution network provided for one embodiment of the present application.

[0020] Figure 3 A schematic diagram of a computer device provided for one embodiment of the present application. DETAILED DESCRIPTION

[0021] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0022] In the description of the embodiments of the present application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present application, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0023] In related technologies, the planning method of urban distribution networks is usually optimized based on static power and load balance constraints, and the power and load configuration of some nodes are adjusted according to the existing distribution network structure and historical operation data. However, with the increasing access ratio of distributed energy (such as wind power and photovoltaics), the problem of insufficient short-circuit ratio of distribution network nodes has gradually emerged. Short Circuit Ratio (SCR) is a key indicator reflecting the strength of the node power grid. When the short-circuit ratio is lower than a certain threshold, the distribution network is more prone to voltage fluctuations during operation, and even in the event of high-probability faults (such as three-phase short circuit and single-phase short circuit), it is impossible to effectively maintain transient stability, thereby affecting the overall safety of the power grid.

[0024] Specifically, the relevant technologies lack dynamic adjustment strategies for short-circuit ratio optimization, and it is difficult to improve the node short-circuit ratio through energy storage configuration to meet specific requirements. In addition, the planning methods in the relevant technologies usually ignore the dynamic response of urban distribution networks under high-probability fault scenarios, especially in terms of transient stability, and fail to provide a comprehensive fault response solution. This may cause the power grid to have large oscillations when a fault occurs, reduce the system recovery speed, and further weaken the operational reliability of the power grid.

[0025] Therefore, it is necessary to provide a planning method for urban distribution networks, which can improve the short-circuit ratio of distribution network nodes by combining the dynamic configuration optimization of grid-type energy storage devices, and formulate effective fault response plans for high-probability faults, so that the urban distribution network can meet the transient stability constraint requirements when a fault occurs, and achieve rapid recovery and stable operation of the power grid.

[0026] See also Figure 1 . An embodiment of the present application provides a planning method for an urban distribution network. The planning method for an urban distribution network can be applied to a planning device for an urban distribution network. The planning device for an urban distribution network can be an electronic device with certain computing capabilities. For example, the electronic device can be a desktop computer, a laptop computer, a workstation or a server, etc. Of course, the planning device for an urban distribution network can also refer to a program module running in an electronic device.

[0027] The planning method of the urban distribution network may include the following steps.

[0028] Step S110: According to historical operation data of the urban distribution network, the urban distribution network is improved in accordance with power supply and load balance constraints to obtain a first simulated distribution network.

[0029] Step S120: obtaining a second simulated distribution network by adjusting the grid-forming energy storage device in the first simulated distribution network; wherein the short-circuit ratio of the grid nodes in the second simulated distribution network is higher than a specified threshold.

[0030] Step S130: For the high-probability fault determined according to the historical operation data, a fault response plan is formulated for the second simulated distribution network, so that when the high-probability fault occurs in the second simulated distribution network, the fault response plan is executed to make the second simulated distribution network comply with the specified transient stability constraint; wherein the transient stability constraint is used to represent the transient stability requirement when a fault occurs.

[0031] In this embodiment, the historical operation data of the urban distribution network includes but is not limited to the load distribution in different time periods, the access status of distributed power sources, the power flow distribution, and the node operation status. The power and load balance constraint means that at any time, the sum of the power injection power and the load consumption power of all nodes in the distribution network must meet the power conservation condition. On the basis of power and load balance, the topology of the distribution network is improved by optimizing the location and capacity distribution of power facilities to form a first simulated distribution network.

[0032] Specifically, the construction process of the first simulated distribution network may include: extracting the load growth trend, the distributed power access area and the load abnormal fluctuation area according to the historical operation data of the distribution network. By analyzing the power flow distribution, load density and power quality of important power grid nodes, the nodes and areas that need to be optimized are determined. For example, a node faces a low voltage problem for a long time during high load periods, which may be due to excessive load or insufficient line capacity. At this time, the node is marked as an area that needs to be optimized. According to the above analysis results, combined with the power supply and load balance constraints, the configuration of power facilities is optimized through a mathematical programming model, including the location of new transmission and distribution lines, increasing the capacity of energy storage devices, and adjusting the distribution of power supply nodes in distributed energy-intensive areas. For example, in areas where the load is growing rapidly, energy storage facilities can be added near the load center to reduce the transmission pressure of existing lines. By adjusting the output power and load control capability of distributed power sources, typical load scenarios are simulated in historical operation data. For example, in areas with a high proportion of wind power access, by increasing the grid-type energy storage capacity, the impact of wind power output fluctuations on the load balance of the distribution network is alleviated, so that the power distribution of the power grid is more uniform, forming an optimized first simulated distribution network.

[0033] In this embodiment, the second simulated distribution network is obtained by adjusting the grid-forming energy storage device in the first simulated distribution network. The grid-forming energy storage device refers to the deployment of the grid-forming energy storage device at a specific node of the distribution network to optimize the capacity, power and coordinated operation mode of the grid-forming energy storage device with other power grid equipment. For example, when the short-circuit ratio of some nodes is lower than a specified threshold, the capacity of the grid-forming energy storage device can be increased or its charging and discharging strategy can be adjusted to increase the node short-circuit ratio to above the specified threshold. The short-circuit ratio (Short Circuit Ratio, SCR) can be the ratio of the short-circuit capacity of the grid at a certain grid node to the rated capacity of the device connected to the grid node. The short-circuit capacity refers to the maximum current that the grid can provide in the event of a short circuit, reflecting the strength of the grid. In this embodiment, the short-circuit ratio of the node is optimized to meet the operating requirements of the grid by dynamically adjusting the grid-forming energy storage device.

[0034] In this embodiment, a fault response plan is formulated for high-probability faults determined according to the historical operation data. High-probability faults include three-phase permanent short circuit, single-phase permanent short circuit, and two-phase phase-to-phase permanent short circuit. The probability of occurrence of these faults can be statistically analyzed based on the historical operation records of the distribution network. For example, when the frequency of short-circuit faults in certain areas is high, the short-circuit faults in these areas can be classified as high-probability faults.

[0035] In this embodiment, the formulation of the fault response plan includes simulating and analyzing the dynamic response characteristics of the distribution network for each high probability fault, and optimizing the inertia and damping parameters of the grid-type energy storage device during the fault to meet the requirements of the transient stability constraint. The transient stability constraint refers to the fact that the dynamic changes of the system voltage, power angle and other key variables of the distribution network can quickly converge to a stable state within a short period of time after the fault occurs, without continuous oscillation or excessive deviation.

[0036] Specifically, for example, in the case of a three-phase short circuit fault at a certain grid node, the inertia parameters of the grid-connected energy storage device near the node are adjusted to enhance the short-term voltage support capability, while the damping parameters are optimized to reduce the overshoot of the power angle to ensure system stability during the fault and fault recovery process. In actual operation, the effectiveness of the fault response plan can be verified through simulation tools to ensure that the developed plan can meet the operation requirements of the distribution network.

[0037] In multiple implementations provided in the present application, the urban distribution network is improved according to the power and load balance constraints based on the historical operation data of the urban distribution network, and combined with the optimization of the grid-type energy storage device, so that the short-circuit ratio of the distribution network nodes meets the requirements of the specified threshold, thereby enhancing the voltage support capability and anti-disturbance capability of the distribution network in dynamic operation. Furthermore, by formulating fault response plans for high-probability faults, the urban distribution network meets the constraints of transient stability when a fault occurs, and the distribution network can be quickly recovered under fault conditions, thereby improving the stability of the urban distribution network as a whole.

[0038] In some embodiments, the planning device of the urban distribution network can determine multiple basic operating conditions of the urban distribution network based on the historical operating data; adjust the grid-forming energy storage device in the first simulated distribution network so that the short-circuit ratio of the grid node in each basic operating condition is higher than a specified threshold.

[0039] In this embodiment, the planning device of the urban distribution network can determine multiple basic operating conditions of the urban distribution network based on the historical operation data of the urban distribution network. The basic operating conditions refer to a series of typical scenarios that can reflect the operation status of the power grid, which are extracted by analyzing the characteristics of the power grid load distribution, distributed power output and power flow distribution in typical time periods in the historical operation data. Each basic operating condition may include the load level, the fluctuation range of the distributed power output, the power grid flow direction, etc. in a specific time period. For example, in a certain urban distribution network, the typical operating conditions of high-load periods and low-load periods are determined based on historical data analysis: High-load operating conditions: During the period from 18:00 to 22:00 on weekdays, the residential power load reaches a peak, the distributed photovoltaic output is low, the flow is mainly concentrated in the backbone network line, and the voltage of some nodes may be close to the lower limit. Low-load operating conditions: During the period from 2:00 to 5:00 in the morning, the industrial power load drops significantly, and the distributed wind power output is dominant, resulting in the power of some areas being fed back to the main grid. Based on the above basic operating conditions, the planning device of the urban distribution network can adjust the grid-forming energy storage device in the first simulated distribution network so that the short-circuit ratio of the grid node in each basic operating condition is higher than the specified threshold value of 1.5.

[0040] In this embodiment, the grid-type energy storage device includes deploying energy storage equipment at specific nodes to increase its short-circuit capacity, while optimizing the charging and discharging strategy and dynamic response capability of the energy storage equipment. For example, under high load conditions, the short-circuit ratio of grid node A is 1.3, which is lower than the specified threshold of 1.5. By adding a 1MW grid-type energy storage device at node A, the short-circuit capacity of grid node A is increased from the original 6MVA to 7.5MVA, and the short-circuit ratio is increased to 1.6, meeting the operating requirements.

[0041] In this embodiment, the network-type energy storage device in the first simulated distribution network is adjusted by the planning device so that the short-circuit ratio of the grid node in each basic working condition is higher than the specified threshold, which can significantly enhance the operating reliability and dynamic stability of the distribution network, and provide a better basic condition for the subsequent fault response plan. In this embodiment, the specified threshold is not limited to 1.5, and the technicians in the relevant field can set the value according to actual needs. For example, the specified threshold can also be 1.6, 1.8, 1.9..., 2.5, etc., which will not be repeated.

[0042] In some embodiments, the planning device of the urban distribution network can obtain the short-circuit ratio of the grid nodes in the first simulated distribution network under the multiple basic operating conditions through simulation, so as to obtain the target grid node whose short-circuit ratio is less than the specified threshold under the basic operating conditions; by increasing the grid-forming energy storage capacity or adding a grid-forming energy storage device near the target grid node, the short-circuit ratio of the target grid node is higher than the specified threshold.

[0043] In this embodiment, the planning device of the urban distribution network can use historical operation data to conduct a detailed analysis of the short-circuit ratio of the distribution network through simulation. The planning device first establishes a simulation model of the urban distribution network according to the historical operation data of the urban distribution network in accordance with the power supply and load balance constraints. The simulation process includes calculating the short-circuit ratio of the grid node based on multiple basic working conditions, and screening out the target grid nodes whose short-circuit ratio is less than the specified threshold. Specifically, when the short-circuit ratio is lower than a preset threshold, the stability and anti-disturbance ability of the grid node will be greatly reduced, and voltage fluctuations are prone to occur, affecting the normal operation of the grid. After obtaining the target grid node, the planning device takes measures to improve the short-circuit ratio of these nodes by adjusting the layout of the power facilities near the node. For example, the grid strength of the target grid node can be enhanced by increasing the capacity of the grid-forming energy storage or adding a grid-forming energy storage device. The grid-forming energy storage device refers to the deployment of energy storage facilities at the grid node, and dynamically adjusting the capacity and charging and discharging strategy of the energy storage device to improve the short-circuit ratio of the grid node to ensure that it reaches or exceeds the specified threshold. In some scenarios, increasing the capacity of energy storage devices or changing the configuration of energy storage facilities can effectively alleviate the impact of grid load fluctuations and distributed energy fluctuations on grid stability.

[0044] Through the simulation analysis of the planning device, the nodes that need to be optimized can be accurately identified, and effective measures can be taken to enhance the grid stability of these nodes. In practical applications, the planning device of the urban power grid can automatically optimize the layout of energy storage facilities, thereby improving the stability and reliability of the urban distribution network under dynamic load and fault conditions. This dynamic optimization strategy greatly improves the anti-interference ability of the distribution network to sudden faults and reduces the recovery time after the power grid fails.

[0045] In some embodiments, a planning device of an urban distribution network may determine a target grid-type energy storage device in the second simulated distribution network; and adjust the inertia and damping parameters of the target grid-type energy storage device under the constraint of maintaining the power angle stability of the second simulated distribution network to obtain a fault response plan.

[0046] In this embodiment, for high probability faults determined according to the historical operation data of the urban distribution network, a fault response plan is formulated for the second simulated distribution network. High probability faults refer to those fault types that occur frequently in historical operation data and may have a significant impact on the safety and stability of the power grid, such as three-phase short circuit, single-phase short circuit and two-phase short circuit. The occurrence of these faults is usually closely related to the load fluctuations in certain areas of the distribution network, the proportion of distributed energy access, and the operating status of the equipment. For these high probability faults, in the second simulated distribution network, it is first necessary to determine the target grid-type energy storage device. The target grid-type energy storage device refers to an energy storage node that can provide effective power support and regulation by deploying or optimizing the configuration of energy storage devices in the distribution network, especially when a fault occurs. The configuration of these energy storage devices is determined according to the power flow, load fluctuations of the distribution network nodes, and the coordinated operation requirements of the energy storage devices and other power grid devices. In particular, for those areas where the node short circuit is relatively low and voltage fluctuations are prone to occur when a fault occurs, the selection of energy storage devices is crucial.

[0047] In this embodiment, in order to enable the urban distribution network to recover quickly and maintain stability when a fault occurs, the fault response plan is optimized by adjusting the inertia and damping parameters of the target grid-type energy storage device. Inertia and damping parameters refer to the energy storage capacity and regulation capacity of the energy storage device during the dynamic response process. After a fault occurs, the system of the urban distribution network may produce large transient fluctuations due to load fluctuations, equipment failures or short circuits, resulting in fluctuations in key parameters such as the system power angle and voltage. By adjusting the inertia and damping characteristics of the energy storage device, these fluctuations can be effectively controlled, so that the urban distribution network can be stably restored in a short time after a fault occurs.

[0048] In this embodiment, when adjusting the inertia and damping parameters of the target grid-type energy storage device, it is necessary to combine the fault type and its impact on the stability of the urban distribution network. For example, for a three-phase short circuit fault, the inertia and damping adjustment strategy of the energy storage device needs to focus on the energy balance and power angle stability of the power grid in a short period of time; while for a single-phase short circuit or a two-phase short circuit fault, the energy storage device needs to be flexibly adjusted to alleviate voltage fluctuations and quickly restore to a stable state.

[0049] Through the above method, the power angle stability of the urban distribution network can be effectively maintained when a high probability fault occurs, so that the urban distribution network meets the transient stability constraint requirements. Transient stability constraints mean that within a short period of time after a fault occurs, key variables in the power grid (such as voltage and power angle) should be able to quickly return to a stable state without continuous oscillation or excessive deviation, which is crucial for the long-term stable operation of the distribution network.

[0050] In some embodiments, a planning device for an urban distribution network may derive, through simulation, a participation factor of a grid-type energy storage device for the high probability failure in the second simulated distribution network; and select a grid-type energy storage device as a target grid-type energy storage device in the second simulated distribution network according to the participation factor; wherein the participation factor of the target grid-type energy storage device is greater than the participation factors of other grid-type energy storage devices.

[0051] In this embodiment, the grid-forming energy storage device in the second simulated distribution network is optimized based on the dynamic response capability to high-probability faults. First, a simulation method is used to simulate the operation of the second simulated distribution network, especially to analyze the role of the grid-forming energy storage device when a high-probability fault occurs. These high-probability faults include but are not limited to three-phase permanent short circuit, single-phase permanent short circuit, two-phase permanent short circuit and other fault types. Through the simulation analysis of these faults, the participation factor of the grid-forming energy storage device in different nodes can be obtained. The participation factor is used to indicate the contribution of each grid-forming energy storage device to the stability of the distribution network system when a fault occurs, specifically considering the impact of the energy storage device on voltage support and power angle stability.

[0052] During the simulation, the participation factor of the grid-connected energy storage device is obtained by detailed modeling and analysis of the charging and discharging strategy of the energy storage device under fault conditions, the inertia and damping characteristics of the energy storage device, etc. Energy storage nodes with larger participation factors can provide more voltage support and energy regulation when a fault occurs, alleviate the power angle oscillation caused by the fault, and thus help the distribution network maintain transient stability.

[0053] According to the calculation results of these participation factors, the node with the largest participation factor is selected as the target grid-forming energy storage device. These nodes are usually located in key areas of the distribution network, or show a high frequency of faults in historical operation data. The target grid-forming energy storage device can not only improve the short-circuit ratio of the node to meet the safety requirements of the distribution network operation, but also provide stronger stability support when a fault occurs. By selecting a grid-forming energy storage device with a larger participation factor, the distribution network can maximize the benefits of energy storage when facing a high probability of faults, ensuring the transient stability of the entire distribution network system.

[0054] Specifically, the calculation method of the participation factor can be carried out through the following steps: Node characteristic modeling: Establish an electrical characteristic model for each grid-type energy storage device, including the capacity of the grid-type energy storage device, the charging and discharging power, and the coordinated operation characteristics with other power grid equipment. Fault simulation analysis: Under high probability fault conditions, simulate the impact of each grid-type energy storage device on the power grid system, and calculate the contribution of the grid-type energy storage device to the voltage support, power angle adjustment, and transient stability of each node during different faults. Participation factor calculation: Based on the above simulation results, calculate the participation factor of each grid-type energy storage device. A node with a larger participation factor indicates that the node has a greater stability support role in the event of a fault. Select the target node: According to the calculated participation factor, select the grid-type energy storage device with the largest participation factor as the target grid-type energy storage device, so as to optimize the subsequent energy storage capacity and power configuration.

[0055] In a specific embodiment, the calculation process of the participation factor specifically includes: determining the group attributes of each grid-type energy storage device in the second simulated distribution network in each high probability fault. The group attributes include a leading group and a remaining group. According to the dominant mode result corresponding to the high probability fault, the group attribute of the grid-type energy storage device is determined. If the power angle of the grid-type energy storage device is leading, the group attribute of the grid-type energy storage device is the leading group; if the power angle of the grid-type energy storage device is lagging, the group attribute of the grid-type energy storage device is the remaining group. Calculation is performed based on the group attributes of the grid-type energy storage device to obtain the participation factor of each grid-type energy storage device in each high probability fault.

[0056] If the group attribute of the grid-type energy storage device in the high probability fault is the leading group, the maximum acceleration kinetic energy of the grid-type energy storage device in the leading group is used as the reference value, and the ratio of the actual acceleration kinetic energy of the grid-type energy storage device to the reference value is used as the participation factor. Specifically, the calculation formula for the participation factor of the grid-type energy storage device in the leading group with the group attribute can be formula (1).

[0057]

[0058] P i The group attribute is the participation factor of the grid-type energy storage device in the leading group, S represents the leading group, Represents the actual acceleration kinetic energy of the network-type energy storage device, It indicates the maximum acceleration kinetic energy of the grid-type energy storage device within the leading group when a failure with a high probability occurs.

[0059] If the grid-type energy storage device is the remaining group, the maximum acceleration kinetic energy of the grid-type energy storage device in the leading group is used as the reference value, and the inverse of the ratio of the actual deceleration kinetic energy of the grid-type energy storage device to the reference value is calculated as the participation factor. Specifically, the calculation formula for the participation factor of the grid-type energy storage device in the remaining group with the group attribute can be formula (2).

[0060]

[0061] P k The group attribute is the participation factor of the grid-type energy storage device in the remaining group, A represents the remaining group, Indicates the actual deceleration kinetic energy of the generator set.

[0062] By calculating the participation factor of each grid-forming energy storage device, the node with the largest participation factor is selected as the target grid-forming energy storage device.

[0063] Through this process, the configuration of the target grid-type energy storage device can effectively improve the stability of the distribution network, especially in the case of high probability of failure. By dynamically adjusting the energy storage configuration, the power grid can recover to a stable state more quickly and smoothly, reduce the oscillation and recovery time caused by the failure, and improve the anti-disturbance ability of the distribution network. For example, suppose that in the distribution network of a certain area, the probability of a three-phase short circuit failure is high. In the simulation analysis, the participation factor of a certain grid-type energy storage device is higher than that of other nodes, indicating that the node can provide greater voltage support and short-term energy regulation when a fault occurs. Therefore, this node will be selected as the target grid-type energy storage device, and then the capacity and charging and discharging strategy of its energy storage equipment will be optimized to improve the short-circuit ratio and transient stability of the node, ensuring that the power grid can maintain a stable power angle and voltage response under high probability of failure.

[0064] In some embodiments, the planning device of the urban distribution network can determine the target grid-type power source in the second simulated distribution network; with the maintenance of the transient stability of the second simulated distribution network as a constraint, adjust the proportional coefficient and / or integral coefficient of the target grid-type power source to obtain a fault response plan.

[0065] In this embodiment, for high-probability faults determined based on historical operating data of the urban distribution network, the steps of formulating a fault response plan are further refined as follows: First, determine the target grid-type power source in the second simulated distribution network. The target grid-type power source refers to a power supply device that can provide flexible power supply response according to changes in the operating status of the urban distribution network, usually an energy storage device or a distributed renewable energy system, such as wind power, photovoltaic power supply, etc. The response characteristics of these power sources are crucial to ensuring the transient stability of the distribution network when a fault occurs.

[0066] Further, the proportional coefficient and / or integral coefficient of the target grid-type power supply are adjusted to maintain the transient stability of the second simulated distribution network as a constraint condition, and then the corresponding fault response plan is obtained. The proportional coefficient and the integral coefficient are commonly used adjustment parameters in the control strategy, which affect the rate and accuracy of the system response respectively. The proportional coefficient controls the speed of the system response, and the integral coefficient mainly adjusts the steady-state error of the system. In this embodiment, the purpose of adjusting these coefficients is to optimize the output power of the target grid-type power supply so that the transient stability of the distribution network can be quickly and effectively restored in the event of a fault, avoiding problems such as power angle oscillation or voltage instability. For example, assuming that in an area with high wind energy access, wind power and energy storage systems together constitute the target grid-type power supply. In this area, when a high probability fault such as a single-phase permanent short circuit occurs, by increasing the participation of the energy storage system and adjusting the output ratio of the wind power system, the short-circuit capacity of the distribution network can be effectively enhanced, and the short-circuit ratio of the distribution network node can be improved, thereby ensuring that the distribution network meets the transient stability requirements in the event of a fault.

[0067] In addition, the adjustment strategy of the target grid-following power source also needs to consider the load fluctuations of each node and the changes in the grid topology. For example, in the area where the fault occurs, the short-circuit current may cause a sharp fluctuation in the local grid load. At this time, by dynamically adjusting the control coefficient of the target grid-following power source, the load control of the area can be achieved, thereby ensuring the transient stability of the grid.

[0068] By optimizing the above steps, adaptive fault response plans can be formulated according to different types of high-probability faults, thereby ensuring the transient stability of the distribution network when a fault occurs and accelerating the system recovery process after the fault.

[0069] In some embodiments, the grid-based power source includes a grid-based wind turbine and / or a grid-based photovoltaic system; the planning device of the urban distribution network can obtain the participation factor of the grid-based wind turbine and / or the grid-based photovoltaic system for the high probability failure in the second simulated distribution network through simulation; according to the participation factor, the grid-based wind turbine and / or the grid-based photovoltaic system is selected as the target grid-based power source in the second simulated distribution network; wherein the participation factor of the target grid-based power source is greater than the participation factor of other grid-based wind turbines and / or grid-based photovoltaic systems.

[0070] In this embodiment, the target grid-type power source in the second simulated distribution network includes a grid-type wind turbine and a grid-type photovoltaic system. Grid-type wind turbines and photovoltaic systems play an important role in the distribution network, especially in providing stable power supply support in fault response. The operating characteristics of grid-type wind turbines and photovoltaic systems make them important fault response resources, which can provide temporary power support for the power grid when a fault occurs.

[0071] Specifically, in order to effectively formulate a fault response plan, the participation factor of the grid-following wind turbine and / or grid-following photovoltaic system in the second simulated distribution network is first obtained through simulation. In the simulation, the participation factor can be determined by analyzing the impact of various power sources on maintaining transient stability and power angle stability when a fault occurs. Through simulation, the response capability of each power source can be evaluated, for example, the output change and frequency regulation capability of the grid-following wind turbine and photovoltaic system under specific fault scenarios.

[0072] According to the above participation factors, the most suitable target grid-type power source can be selected in the second simulated distribution network. The target grid-type power source refers to the power source whose participation factor is greater than that of other grid-type wind turbines and photovoltaic systems. In a high probability failure scenario, selecting a grid-type power source with a larger participation factor as the target grid-type power source can improve the recovery capability of the power grid in the event of a failure. These target power sources can achieve effective response to grid failures by adjusting their power output or control strategy to ensure that the urban distribution network can maintain power angle and transient stability. For example, under certain high wind speed or high light conditions, the power output of grid-type wind turbines or photovoltaic systems may be higher, and the participation factor is correspondingly increased, so they can quickly provide sufficient power support when a failure occurs. On the contrary, if the output of these power sources is lower when a failure occurs, the participation factor may be smaller.

[0073] Finally, the selected target grid-type power sources will be included in the fault response plan according to the order of participation factors. On this basis, combined with the power and load balance constraints, transient stability requirements, and power angle stability requirements, the participation ratio of these power sources can be further adjusted to ensure that when a high probability fault occurs, the urban distribution network can quickly and stably resume operation, minimizing the impact of the fault on the urban distribution network.

[0074] In some embodiments, the planning device of the urban distribution network can determine the facility information of the power facilities added on the basis of the urban distribution network according to the power supply and load balance constraints, and obtain the first simulated distribution network; wherein the facility information includes at least one of the following: the location and number of new lines, the location of renewable energy, the location of electric vehicle charging stations or the capacity of energy storage facilities.

[0075] In this embodiment, the historical operation data of the urban distribution network includes but is not limited to the load distribution in different time periods, the access status of distributed power sources, the power flow distribution, and the node operation status. The power and load balance constraint means that at any time, the sum of the power injection power and the load consumption power of all nodes in the urban distribution network must meet the power conservation condition. Based on these data, the power facilities of the urban distribution network are first analyzed and optimized to meet the future load growth and power access requirements.

[0076] In this embodiment, according to the power supply and load balance constraints, the newly added power facilities on the basis of the urban distribution network are determined, including but not limited to the location and number of new transmission lines, increasing the access of renewable energy (such as wind power, photovoltaic power generation system), setting up electric vehicle charging stations and deploying energy storage facilities. Specifically, the load demand and power flow of the urban area can be predicted first, and the areas with faster load growth and areas with abundant renewable energy resources can be identified, and then the power facilities that need to be newly built or renovated can be determined. For example, in urban areas with faster load growth, it may be necessary to add a new transmission line or increase energy storage facilities on the basis of existing lines to ensure the stability and security of power supply. For example, in areas with abundant wind resources, the layout of existing wind turbines can be optimized or new photovoltaic power generation facilities can be added to better utilize renewable energy, thereby reducing dependence on traditional power sources and improving the flexibility and response capabilities of the distribution network. The location of the electric vehicle charging station can be reasonably planned based on the traffic-intensive area and the future growth trend of the number of electric vehicles, to ensure that it matches the load distribution of the distribution network and avoid local power grid overload.

[0077] See also Figure 2 The embodiment of the present application provides a planning system for a city distribution network. The planning system includes: an improvement module, an adjustment module and a formulation module.

[0078] An improvement module, used for improving the urban distribution network according to historical operation data of the urban distribution network and in accordance with power supply and load balance constraints to obtain a first simulated distribution network;

[0079] An adjustment module, configured to obtain a second simulated distribution network by adjusting the grid-forming energy storage device in the first simulated distribution network; wherein the short-circuit ratio of the grid nodes in the second simulated distribution network is higher than a specified threshold;

[0080] A formulation module is used to formulate a fault response plan for the second simulated distribution network for a high probability fault determined based on the historical operation data, so that when the high probability fault occurs in the second simulated distribution network, the fault response plan is executed to make the second simulated distribution network comply with the specified transient stability constraint; wherein the transient stability constraint is used to represent the transient stability requirement when a fault occurs.

[0081] In this embodiment, the functions and effects achieved by the planning system of the urban distribution network can be explained in comparison with the aforementioned embodiments and will not be described in detail.

[0082] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the processor implements the urban distribution network planning method as described above.

[0083] An embodiment of the present application also provides a computer program product comprising instructions, which, when executed by a processor, implements the urban distribution network planning method as described above.

[0084] See also Figure 3 The present embodiment may provide a computer device, the computer device comprising: a memory, and one or more processors communicatively connected to the memory; the memory stores instructions executable by the one or more processors, the instructions are executed by the one or more processors, so that the one or more processors implement the above-mentioned urban distribution network planning method.

[0085] In some embodiments, the computer device may include a processor, a non-volatile storage medium, an internal memory, a communication interface, a display device, and an input device connected by a system bus. The non-volatile storage medium may store an operating system and related computer programs.

[0086] It can be understood that the “connection” in the following embodiments should be understood as “electrical connection”, “communication connection”, etc. if the connected circuits, modules, units, etc. can transmit electrical signals or data to each other.

[0087] It should be understood that the specific examples in this article are only intended to help those skilled in the art to better understand the embodiments of the present application, rather than to limit the scope of the present invention.

[0088] It can be understood that in the various embodiments of the present application, the size of the serial number of each process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0089] It can be understood that the various embodiments described in this application can be implemented individually or in combination, and the embodiments of this application are not limited to this.

[0090] Unless otherwise stated, all technical and scientific terms used in the embodiments of the present application are the same as the meanings generally understood by those skilled in the art of the technical field of the present application. The terms used in the present application are only for the purpose of describing specific embodiments and are not intended to limit the scope of the present application. The term "and / or" used in the present application includes any and all combinations of one or more related listed items. The singular forms "a kind of", "above" and "the" used in the embodiments of the present application and the appended claims are also intended to include majority forms, unless the context clearly indicates other meanings.

[0091] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0092] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0093] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0094] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0095] The above is only a specific embodiment of the present application, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A planning method for an urban distribution network, characterized in that: include: According to historical operation data of the urban distribution network, the urban distribution network is improved according to power supply and load balance constraints to obtain a first simulated distribution network; A second simulated distribution network is obtained by adjusting the grid-forming energy storage device in the first simulated distribution network; wherein the short-circuit ratio of the grid nodes in the second simulated distribution network is higher than a specified threshold; For the high-probability fault determined according to the historical operation data, a fault response plan is formulated for the second simulated distribution network, so that when the high-probability fault occurs in the second simulated distribution network, the fault response plan is executed to make the second simulated distribution network comply with the specified transient stability constraint; wherein the transient stability constraint is used to represent the transient stability requirement when a fault occurs.

2. The planning method according to claim 1, characterized in that: The step of obtaining a second simulated distribution network by adjusting the grid-forming energy storage device in the first simulated distribution network includes: Determining a plurality of basic operating conditions of the urban distribution network according to the historical operating data; The grid-forming energy storage device in the first simulated distribution network is adjusted so that the short-circuit ratio of the grid node in each basic operating condition is higher than a specified threshold.

3. The planning method according to claim 2, characterized in that: The step of adjusting the grid-forming energy storage device in the first simulated distribution network so that the short-circuit ratio of the grid node in each basic working condition is higher than a specified threshold comprises: Determine, by simulation, the short-circuit ratio of the grid nodes under the plurality of basic operating conditions in the first simulated distribution network, so as to obtain a target grid node whose short-circuit ratio under the basic operating condition is less than a specified threshold; By increasing the grid-forming energy storage capacity or adding a grid-forming energy storage device near the target grid node, the short-circuit ratio of the target grid node is made higher than a specified threshold.

4. The planning method according to claim 1, characterized in that: The step of formulating a fault response plan for the second simulated distribution network for a high probability fault determined according to the historical operation data includes: Determining a target grid-forming energy storage device in the second simulated distribution network; Taking maintaining the power angle stability of the second simulated distribution network as a constraint, the inertia and damping parameters of the target grid-type energy storage device are adjusted to obtain a fault response plan.

5. The planning method according to claim 4, characterized in that: The step of determining a target grid-connected energy storage device in the second simulated distribution network includes: Determine, by simulation, the participation factor of the grid-connected energy storage device for the high probability fault in the second simulated distribution network; According to the participation factor, a grid-connected energy storage device is selected as a target grid-connected energy storage device in the second simulated distribution network; wherein the participation factor of the target grid-connected energy storage device is greater than the participation factors of other grid-connected energy storage devices.

6. The planning method according to claim 1, characterized in that: The step of formulating a fault response plan for the second simulated distribution network for a high probability fault determined according to the historical operation data includes: Determining a target grid-type power source in the second simulated distribution network; With the maintenance of the transient stability of the second simulated distribution network as a constraint, the proportional coefficient and / or integral coefficient of the target grid-following power source is adjusted to obtain a fault response plan.

7. The planning method according to claim 6, characterized in that: Grid-connected power sources include grid-connected wind turbines and / or grid-connected photovoltaic systems; The step of determining a target grid-type power source in the second simulated distribution network includes: Determining, by simulation, a participation factor of a grid-connected wind turbine and / or a grid-connected photovoltaic system for the high probability failure in the second simulated distribution network; According to the participation factor, a grid-following wind turbine and / or a grid-following photovoltaic system is selected as a target grid-following power source in the second simulated distribution network; wherein the participation factor of the target grid-following power source is greater than the participation factors of other grid-following wind turbines and / or grid-following photovoltaic systems.

8. The planning method according to claim 1, characterized in that: The step of improving the urban distribution network according to the historical operation data of the urban distribution network and the power supply and load balance constraint to obtain a first simulated distribution network includes: According to the power supply and load balance constraints, the facility information of the power facilities added on the basis of the urban distribution network is determined to obtain the first simulated distribution network; wherein the facility information includes at least one of the following: the location and number of new lines, the location of renewable energy, the location of electric vehicle charging stations or the capacity of energy storage facilities.

9. A planning system for an urban distribution network, characterized in that: include: An improvement module, used for improving the urban distribution network according to historical operation data of the urban distribution network and in accordance with power supply and load balance constraints to obtain a first simulated distribution network; An adjustment module, configured to obtain a second simulated distribution network by adjusting the grid-forming energy storage device in the first simulated distribution network; wherein the short-circuit ratio of the grid nodes in the second simulated distribution network is higher than a specified threshold; A formulation module is used to formulate a fault response plan for the second simulated distribution network for a high probability fault determined based on the historical operation data, so that when the high probability fault occurs in the second simulated distribution network, the fault response plan is executed to make the second simulated distribution network comply with the specified transient stability constraint; wherein the transient stability constraint is used to represent the transient stability requirement when a fault occurs.

10. A computer device, characterized in that: The computer device includes a memory and a processor, wherein at least one computer program is stored in the memory, and the at least one computer program is loaded and executed by the processor to implement the urban distribution network planning method as described in any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one computer program, and when the at least one computer program is executed by a processor, it can implement the urban distribution network planning method as described in any one of claims 1 to 8.

12. A computer program product, characterized in that When the computer program product is executed by a processor, the method for planning an urban distribution network as claimed in any one of claims 1 to 8 is implemented.

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