Power distribution network recovery method, device and equipment under waterlogging disaster and storage medium

Abstract

The invention discloses a power distribution network recovery method, device and equipment under a waterlogging disaster and a storage medium, and the method comprises the steps: determining the fault probability of i lines according to the wind speed corresponding to each line in i lines in a power distribution network under the waterlogging disaster; determining i line states according to the i line fault probabilities; according to the immersion depth of each power distribution node in the j power distribution nodes of the power distribution network under the waterlogging disaster, determining the fault probability of the j nodes; determining states of the j nodes according to the fault probabilities of the j nodes; determining y power distribution network recovery schemes according to the i line states and the j node states; determining the total value of each power distribution network recovery scheme in the y power distribution network recovery schemes to obtain y total values; and selecting one power distribution network recovery scheme from the y power distribution network recovery schemes as a target power distribution network recovery scheme according to the y total values. The method is beneficial for improving the accuracy of the power distribution network recovery scheme.

Description

Technical Field

[0001] The present application relates to the technical field of improving the resilience of distribution networks, and in particular to a method, device, equipment and storage medium for restoring distribution networks under waterlogging disasters. Background Art

[0002] In recent years, low-probability, high-loss extreme events, such as flooding, have posed a great threat to the safe and stable operation of power systems, and the development of resilient power systems has become a general trend. Urban distribution networks are directly related to load supply. In order to solve the problem of load supply in extreme events, improving the resilience of distribution networks has become a key research topic. Energy storage, as a resource with time-shifting flexibility, is widely used in resilience improvement strategies. Most existing studies focus on mobile energy storage systems (MESS), which are essentially chemical batteries. Related research includes the location and capacity of pre-deployed MESS before disasters, and path selection and scheduling after disasters.

[0003] However, in the existing distribution network post-disaster recovery methods, the line faults of the distribution network are often analyzed through experience, and a distribution network recovery plan is formulated, and the accuracy of the distribution network recovery plan is low. Summary of the invention

[0004] In order to solve the above problems existing in the prior art, the embodiments of the present application provide a method, device, equipment and storage medium for restoring a distribution network under a waterlogging disaster. According to the wind speed corresponding to each line section in the i-line of the distribution network under the waterlogging disaster, the line state of each line section is predicted, and then, according to the water depth of each distribution node in the j distribution nodes of the distribution network under the waterlogging disaster, the node state of each distribution node is predicted, and finally, according to the line state of each line section and the node state of each distribution node, y distribution network restoration plans are determined, and a distribution network restoration plan with the highest total value is selected from the y distribution network restoration plans as the target distribution network restoration plan, thereby improving the accuracy of the distribution network restoration plan.

[0005] In a first aspect, an embodiment of the present application provides a method for restoring a distribution network under a flood disaster, comprising:

[0006] Obtain the wind speed corresponding to each section of the i-section line in the distribution network under the waterlogging disaster, and obtain i wind speeds, and obtain the water immersion depth of each of the j distribution nodes of the distribution network under the waterlogging disaster, and obtain j water immersion depths; the distribution network is coupled to the heat network through compressed air energy storage and a heat pump, the first distribution node of the j distribution nodes is connected to the compressor of the compressed air energy storage, the second distribution node of the j distribution nodes is connected to the steam turbine of the compressed air energy storage, the heat source node of the heat network is connected to the heat storage system of the compressed air energy storage, and is connected to the heat pump, and the heat source node is any one of the n heating nodes of the heat network; the water immersion depth is the depth of the distribution equipment of the distribution node corresponding to the water immersion depth; i and n are both integers greater than 1, and j=i+1;

[0007] Determine the line failure probability corresponding to each line segment in the i line segments according to the i wind speeds, and obtain i line failure probabilities;

[0008] According to the i line failure probabilities, determining the line state of each line in the i line sections to obtain i line states;

[0009] Determine, according to the j flooding depths, a node failure probability corresponding to each of the j power distribution nodes, to obtain j node failure probabilities;

[0010] Determine the node state of each of the j power distribution nodes according to the j node failure probabilities to obtain j node states;

[0011] Determine y power distribution network restoration plans according to the i line states and the j node states; the power distribution network restoration plans are used to allocate the restored electric load of each of the j power distribution nodes and the restored heat load of each of the n heat supply nodes; y is an integer greater than 1;

[0012] Determine the total value of each distribution network restoration plan in the y distribution network restoration plans to obtain y total values; the total value refers to the value of the total restored electrical load of the distribution network and the total restored thermal load of the thermal network in the distribution network restoration plan corresponding to the total value;

[0013] According to the y total values, a distribution network restoration scheme is selected from the y distribution network restoration schemes as a target distribution network restoration scheme.

[0014] In a second aspect, an embodiment of the present application provides a distribution network restoration device, including:

[0015] An acquisition unit is used to acquire the wind speed corresponding to each section of the i-section line in the distribution network under the waterlogging disaster, obtain i wind speeds, and acquire the flooding depth of each of the j distribution nodes of the distribution network under the waterlogging disaster, obtain j flooding depths; the distribution network is coupled to the heat network through compressed air energy storage and a heat pump, the first distribution node of the j distribution nodes is connected to the compressor of the compressed air energy storage, the second distribution node of the j distribution nodes is connected to the steam turbine of the compressed air energy storage, the heat source node of the heat network is connected to the heat storage system of the compressed air energy storage, and is connected to the heat pump, and the heat source node is any one of the n heating nodes of the heat network; the flooding depth is the depth of the distribution equipment of the distribution node corresponding to the flooding depth immersed in water; i and n are both integers greater than 1, j=i+1;

[0016] A processing unit, configured to determine, according to the i wind speeds, a line failure probability corresponding to each line segment in the i line segments, to obtain i line failure probabilities;

[0017] According to the i line failure probabilities, determining the line state of each line in the i line sections to obtain i line states;

[0018] Determine, according to the j flooding depths, a node failure probability corresponding to each of the j power distribution nodes, to obtain j node failure probabilities;

[0019] Determine the node state of each of the j power distribution nodes according to the j node failure probabilities to obtain j node states;

[0020] Determine y power distribution network restoration plans according to the i line states and the j node states; the power distribution network restoration plans are used to allocate the restored electric load of each of the j power distribution nodes and the restored heat load of each of the n heat supply nodes; y is an integer greater than 1;

[0021] Determine the total value of each distribution network restoration plan in the y distribution network restoration plans to obtain y total values; the total value refers to the value of the total restored electrical load of the distribution network and the total restored thermal load of the thermal network in the distribution network restoration plan corresponding to the total value;

[0022] According to the y total values, a distribution network restoration scheme is selected from the y distribution network restoration schemes as a target distribution network restoration scheme.

[0023] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor and a memory, the processor being connected to the memory, the memory being used to store a computer program, and the processor being used to execute the computer program stored in the memory, so that the electronic device performs the method described in the first aspect.

[0024] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method described in the first aspect.

[0025] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program product is operable to cause a computer to execute the method described in the first aspect.

[0026] Implementing the embodiments of the present application has the following beneficial effects:

[0027] In an embodiment of the present application, the wind speed corresponding to each section of the i-section line in the distribution network under the waterlogging disaster is first obtained to obtain i wind speeds, and the flooding depth of each distribution node in the j distribution nodes of the distribution network under the waterlogging disaster is obtained to obtain j flooding depths. Then, according to the i wind speeds, the line failure probability corresponding to each section of the i-section line is determined to obtain i line failure probabilities. According to the i line failure probabilities, the line state of each section of the i-section line can be determined to obtain i line failure states. Further, according to the j flooding depths, the node failure probability corresponding to each distribution node in the j distribution nodes can be determined to obtain j node failure probabilities. According to the j node failure probabilities, the node state of each distribution node in the j distribution nodes can be determined to obtain j node states. Further, according to the i line states and the j node states, y distribution network recovery plans can be determined. The total value of each distribution network recovery plan in the y distribution network recovery plans is determined to obtain y total values. Finally, according to the y total values, a distribution network restoration scheme can be selected from the y distribution network restoration schemes as the target distribution network restoration scheme. Therefore, the line state of each line section in the distribution network can be predicted by the wind speed corresponding to the line section, and the node state of each distribution node in the distribution network can be predicted by the water depth of each distribution node in the distribution network. Thus, according to the line state of each line section in the distribution network and the node state of each distribution node, y distribution network restoration schemes are determined. Each distribution network restoration scheme is related to the line state of each line section and the node state of each distribution node, which improves the accuracy of the distribution network restoration scheme. In addition, by determining the total value of each distribution network restoration scheme among the y distribution network restoration schemes, the target distribution network restoration scheme with the highest value of restoring electric load and restoring thermal load can be selected from the y distribution network restoration schemes, further improving the accuracy of the distribution network restoration scheme. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0029] Figure 1 A schematic diagram of an application scenario of a method for restoring a distribution network under a waterlogging disaster provided in an embodiment of the present application;

[0030] Figure 2 A schematic diagram of a flow chart of a method for restoring a distribution network under a waterlogging disaster provided in an embodiment of the present application;

[0031] Figure 3A schematic diagram of a distribution network restoration device provided in an embodiment of the present application;

[0032] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0034] The terms "first", "second", "third" and "fourth" etc. in the specification and claims of the present application and the drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0035] Reference to "embodiments" herein means that a particular feature, result, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0036] First, see Figure 1 , Figure 1 A schematic diagram of an application scenario of a method for restoring a distribution network under a flood disaster provided by an embodiment of the present application. Figure 1 The scenario shown includes: distribution network, compressed air energy storage (CAES), heating network, heat pump and processing equipment. Among them, the distribution network is coupled with the heating network through compressed air energy storage and heat pump.

[0037] In the embodiment of the present application, the distribution network refers to a power network that receives electric energy from a transmission network or a power plant and transmits the electric energy to power users through distribution equipment. The distribution network includes j distribution nodes, wherein the first distribution node among the j distribution nodes is connected to the compressor of the CAES, such as Figure 1The device connected to the "M" node shown is the compressor. The second distribution node among the j distribution nodes is connected to the steam turbine of the CAES, such as Figure 1 The device connected to the "G" node in the compressed air energy storage shown is the steam turbine, such as Figure 1 The "G" node in the distribution network shown is the second distribution node. Any two distribution nodes in the distribution network connect a line, forming a total of i lines, i is an integer greater than 1, j = i + 1. It should be noted that the j distribution nodes also include generator nodes. When the line works normally, the power load of the distribution network is supplied by the generator node. When a line fault or node fault occurs in the distribution network, the faulty node is powered by CAES.

[0038] In the embodiment of the present application, CAES is a relatively mature energy storage technology, which can convert electricity into high-pressure air through motors and compressors and store it in the form of potential energy. When the power is insufficient, the high-pressure air drives the steam turbine and generator to output electricity to the outside. Heat exchange is required for air cooling during compression and air heating during expansion. In the embodiment of the present application, CAES can be a non-supplementary compressed air energy storage, including: a compressor, a steam turbine, an air storage chamber and a heat storage system. When there is excess electricity in the distribution network, the excess electricity drives the compressor through the motor to compress the air and store it in the air storage chamber, and heat is transferred to the heat storage system during the compression process. When the distribution network has a line failure or a distribution node failure due to waterlogging disasters, resulting in a distribution node being separated from the main grid, CAES can drive the distribution node separated from the main grid to form a local microgrid. At this time, the air storage chamber absorbs heat from the heat storage system to expand the high-pressure air in the air storage chamber, and the expanded gas drives the steam turbine and generator to operate, thereby transmitting electricity to the distribution network to supply power to the distribution node separated from the main grid.

[0039] In the embodiment of the present application, the heat network is a heat supply network formed for user nodes with heat supply demand. The heat network includes n heat supply nodes, where n is an integer greater than 1. The heat source node of the heat network is connected to the heat storage system of the compressed air energy storage and to the heat pump. The heat source node is any one of the n heat supply nodes, such as Figure 1 The shaded nodes in the heat network shown in the figure are mainly supplied by heat source nodes. The heat of the heat source nodes is mainly supplied by the heat storage system and the heat pump, where the heat pump can also provide heat for the heat storage system. Each heating node is connected by two pipes, namely the water supply pipe and the return pipe, as shown in Figure 1 As shown in the figure, the direction of the arrow pointing outward from the heat source node is the direction of the liquid flow in the water supply pipe, and the direction of the arrow pointing from other heating nodes to the heat source node is the direction of the liquid flow in the return pipe. The heat pump obtains electricity from the distribution network and pumps the liquid from the heat source node into the water supply pipe. Through the circulation of the water supply pipe and the return pipe, the heat of the heat source node can be distributed to each heating node.

[0040] In the embodiment of the present application, the processing device is mainly used to obtain the wind speed corresponding to each section of the line, the flooding depth corresponding to each distribution node, and the like when the distribution network experiences a disaster, and predict the line state of each section of the line and the node state of each distribution node based on the above data, so as to determine the distribution network recovery plan. Among them, the processing device can be a server for data processing and data storage functions, including: application server, virtual private server (Virtual Private Server, VPS), database server, etc. The processing device can be a processor for data processing, including: Central Processing Unit (CPU), Digital Signal Processing (DSP), Micro Processor Unit (MPU), etc. Among them, the processing device can also obtain real-time working data of the distribution network, compressed air energy storage and heat network, for example, the electric load of the distribution network, the electric power of the compressor in the compressed air energy storage, the heat load of the heat network, etc., which are not limited here.

[0041] It should be noted that after experiencing a flood disaster, some lines and nodes in the distribution network may fail. The failure of the distribution network will affect the operation of the heat pump and the heat storage system in the compressed air energy storage, resulting in insufficient heat load supply in the heat network. Therefore, it is necessary to formulate a distribution network restoration plan to restore the supply of electrical load and heat load to the greatest extent possible after a flood disaster. Existing distribution network restoration plans are usually specified based on the experience of technicians, and the accuracy of the distribution network restoration plan is poor.

[0042] To this end, applied to the above scenario, in the distribution network recovery method under waterlogging disaster provided in the embodiment of the present application, the processing device obtains the wind speed corresponding to each line in the i-line section of the distribution network under waterlogging disaster, obtains i wind speeds, and obtains the water immersion depth of each distribution node in the j distribution nodes of the distribution network under waterlogging disaster, obtains j water immersion depths; the water immersion depth is the depth of the distribution equipment of the distribution node corresponding to the water immersion depth immersed in water;

[0043] The processing device determines the line failure probability corresponding to each line in the i-line segment according to the i wind speeds, and obtains the i-line failure probability;

[0044] The processing device determines the line state of each line in the i-line segment according to the i-line fault probability, and obtains i-line states;

[0045] The processing device determines the node failure probability corresponding to each of the j distribution nodes according to the j flooding depths, and obtains the j node failure probabilities;

[0046] The processing device determines the node state of each of the j power distribution nodes according to the j node failure probabilities, and obtains j node states;

[0047] The processing device determines y distribution network restoration plans according to the i line states and the j node states; the distribution network restoration plan is used to allocate the restored electric load of each of the j distribution nodes and the restored heat load of each of the n heating nodes; y is an integer greater than 1;

[0048] The processing device determines the total value of each distribution network restoration plan in the y distribution network restoration plans to obtain y total values; the total value refers to the value of the total restored electrical load of the distribution network and the total restored thermal load of the thermal network in the distribution network restoration plan corresponding to the total value;

[0049] The processing device selects a distribution network restoration scheme from the y distribution network restoration schemes as the target distribution network restoration scheme according to the y total values.

[0050] It can be seen that, applied to the above scenario, the processing equipment can determine the line failure probability of each section of the line according to the wind speed of each section of the i-section line in the distribution network under the waterlogging disaster, thereby determining the line state of the line according to the line failure probability of each section of the line. Then, according to the flooding depth of each distribution node in the j distribution nodes, the node failure probability of each distribution node is determined, thereby determining the node state of the distribution node according to the node failure probability of each distribution node. According to the line state of each section of the line and the node state of each distribution node, y distribution network restoration plans can be determined, and each distribution network restoration plan is determined by the line state and node state of the distribution network, which improves the accuracy of the distribution network restoration plan. In addition, according to the total value of the restored electric load and the restored thermal load of each distribution network restoration plan, the target distribution network restoration plan can be determined from the y distribution network restoration plans, further improving the accuracy of the distribution network restoration plan.

[0051] See also Figure 2 , Figure 2 A flow chart of a method for restoring a distribution network under a flood disaster provided in an embodiment of the present application. The method is applied to the above scenario, and the method includes but is not limited to the following steps:

[0052] 201: Obtain the wind speed corresponding to each line in the i-line of the distribution network under the waterlogging disaster, and obtain i wind speeds; and obtain the flooding depth of each distribution node in the j distribution nodes of the distribution network under the waterlogging disaster, and obtain j flooding depths.

[0053] In the embodiment of the present application, the immersion depth is the depth of the distribution equipment of the distribution node corresponding to the immersion depth. The distribution node may include: a substation, a distribution room, etc. The distribution equipment may include: a transformer, a circuit breaker, a switch cabinet, etc.

[0054] Specifically, multiple wind speed sensors can be provided on each of the i-section lines in the distribution network to detect the wind speed on the section. The processing device can obtain multiple sub-wind speeds detected by multiple wind speed sensors in each section, each wind speed sensor detects a sub-wind speed, and the average wind speed of the multiple sub-wind speeds is used as the wind speed corresponding to the section. Based on the above processing method, i wind speeds are obtained. Each of the j distribution nodes in the distribution network is provided with a liquid level height sensor to detect the water depth of each distribution node. The processing device can obtain the water depth of each distribution node from the liquid level height sensor of each distribution node in the j distribution nodes, and obtain j water depths.

[0055] It is understandable that waterlogging disasters are always accompanied by strong winds, and when the wind speed is high, it may cause line failures in the distribution network. In addition, under waterlogging disasters, there will be distribution nodes with deeper water depths among the j distribution nodes, causing damage to the distribution equipment of the distribution node. Therefore, the processing device will obtain the wind speed corresponding to each line section and the water depth corresponding to each distribution node to predict possible line failures and node failures in the distribution network.

[0056] 202: According to i wind speeds, determine the line failure probability corresponding to each line in the i line sections, and obtain i line failure probabilities.

[0057] In the embodiment of the present application, the fault of the line in the distribution network is mainly related to the wind speed of the line section, and the conductors and towers in the line are easily damaged by the stress of the high wind speed. The processing device can determine the line failure probability corresponding to each line section in the i-section line according to i wind speeds, and obtain i line failure probabilities.

[0058] Exemplarily, each of the i-section lines is erected on k towers, where k is an integer greater than 1. Determining the line failure probability corresponding to each of the i-section lines according to the i wind speeds to obtain the i-section line failure probabilities may include:

[0059] According to i wind speeds, determine the conductor failure probability corresponding to each line in i lines, and obtain i conductor failure probabilities;

[0060] According to i wind speeds, determine the damage probability of k towers corresponding to each line section in i lines, and obtain the damage probability of x towers;

[0061] According to the probability of i conductor failure and x tower damage, the probability of i line failure is obtained.

[0062] Wherein, k and x are integers greater than 1, and x=i*k. It can be understood that as long as one of the conductors and k towers of each line section fails, it is determined that the line has a fault.

[0063] Specifically, the processing device first determines the conductor failure probability corresponding to each line segment in the i-segment line according to the i wind speeds, and obtains i conductor failure probabilities, wherein the conductor failure probability can be expressed as the normal distribution of the natural logarithm of the wind speed corresponding to the conductor failure probability. The conductor failure probability can be expressed by formula (1):

[0064]

[0065] Where v represents any one of the i wind speeds, P line (v) represents the conductor failure probability of the line corresponding to the wind speed, v min1 Indicates the minimum wind speed at which the probability of conductor failure increases sharply. max1 Indicates the maximum wind speed that the conductor can withstand. σ1 indicates the standard deviation of the natural logarithm of the wind speed that causes conductor failure. m1 The median wind speed that causes conductor failure. line，min It indicates the failure probability of the conductor under normal operation. min1 、v max1 ,σ1 and v m1 Both can be preset according to actual test results.

[0066] It can be seen from formula (1) that when the wind speed is less than the lowest wind speed when the conductor fault probability increases sharply, the conductor fault probability is the fault probability during normal operation. When the wind speed is greater than or equal to the lowest wind speed when the conductor fault probability increases sharply, and less than the maximum wind speed that the conductor can withstand, the conductor fault probability is a normal distribution of the natural logarithm of the wind speed. When the wind speed is greater than or equal to the maximum wind speed that the conductor can withstand, the conductor fault probability is 1. Therefore, the processing device can determine the conductor fault probability of each line in the i-segment line according to the i wind speeds, and obtain i conductor fault probabilities.

[0067] Furthermore, the processing device determines the tower damage probability of the k towers corresponding to each line section in the i-line according to the i wind speeds, and obtains the x tower damage probability. Among them, the formula corresponding to the tower damage probability is similar to formula (1). When the wind speed is less than the lowest wind speed when the tower failure probability increases sharply, the tower failure probability is the failure probability during normal operation, and optionally, the failure probability can be 0. When the wind speed is greater than or equal to the lowest wind speed when the tower failure probability increases sharply, and is less than the maximum wind speed that the tower can withstand, the tower failure probability is the normal distribution of the natural logarithm of the wind speed. When the wind speed is greater than or equal to the maximum wind speed that the tower can withstand, the tower failure probability is 1. Therefore, the processing device can determine the x tower damage probabilities according to the above method. Each line section corresponds to the k tower damage probability.

[0068] Finally, the processing device determines the line failure probability corresponding to each line segment according to the conductor failure probability corresponding to each line segment in the i-segment line and the damage probability of k towers, and obtains the i-line failure probabilities. The line failure probability of each line segment can be expressed by formula (2):

[0069]

[0070] Among them, P L represents the line failure probability of the line corresponding to the wind speed v, P tow,t represents the tower damage probability of the t-th tower on the line. It can be seen from formula (2) that the fault of the conductor is independent of the fault of any tower. The fault of the conductor or any tower indicates that the line section has a fault. Therefore, the processing device can determine the line failure probability corresponding to each line section according to the conductor failure probability corresponding to each line section and the k tower damage probabilities, thereby determining the line failure probability of each line section in the i-line section in turn, and obtaining the i-line failure probabilities.

[0071] It can be seen that according to the i wind speeds, the conductor failure probability of each section of the i lines and the tower damage probability of the k towers corresponding to each section of the line can be determined. Therefore, according to the conductor failure probability corresponding to each section of the line and the k tower damage probability, the line failure probability corresponding to each section of the line can be determined. Therefore, the line status of each section of the conductor can be determined, and a distribution network restoration plan can be formulated according to the line status to ensure the accuracy of the distribution network restoration plan.

[0072] 203: According to the failure probabilities of the i lines, determine the line state of each line in the i line sections to obtain i line states.

[0073] In an embodiment of the present application, the processing device can simulate the line state of each line in the i-segment line by Monte Carlo simulation method according to the failure probability of i lines in the distribution network, and obtain i line states. The line state may include: access to the main network, line failure, line off-grid, etc.

[0074] It is understandable that, since the line state of each line segment in the i-segment line is simulated based on the line failure probability of the line segment, the line state corresponding to the line segment may be different from the actual line state, but it can help technicians eliminate some lines that are unlikely to fail more quickly, thereby reducing the waste of manpower and resources caused by manual detection and analysis.

[0075] 204: Determine the node failure probability corresponding to each of the j distribution nodes according to the j flooding depths, and obtain the j node failure probabilities.

[0076] In the embodiment of the present application, the processing device may determine the node failure probability corresponding to each power distribution node according to the water immersion depth corresponding to the power distribution node.

[0077] Among them, the formula corresponding to the node failure probability of each distribution node is similar to formula (1). When the flooding depth is less than the minimum flooding depth when the node failure probability increases sharply, the node failure probability corresponding to the flooding depth is the failure probability when the distribution node is working normally. Optionally, the failure probability can be 0. When the flooding depth is greater than or equal to the minimum flooding depth when the node failure probability increases sharply, and is less than the maximum flooding depth that the distribution node can withstand, the node failure probability corresponding to the flooding depth is the normal distribution of the natural logarithm of the flooding depth. When the flooding depth is greater than or equal to the maximum flooding depth that the distribution node can withstand, the node failure probability is 1. Therefore, the processing device can determine the node failure probability corresponding to each of the j distribution nodes according to the j flooding depths, and obtain the j node failure probabilities.

[0078] 205: Determine the node state of each of the j distribution nodes according to the j node failure probabilities, and obtain j node states.

[0079] In an embodiment of the present application, the processing device can simulate the node state of each of the j distribution nodes according to the failure probability of the j nodes of the distribution network through the Monte Carlo simulation method to obtain j node states. The node state may include: normal power supply, node failure, node off-grid, etc.

[0080] It can be understood that since the node state of each of the j distribution nodes is simulated based on the node failure probability of the distribution node, the node state corresponding to the distribution node may be different from the actual node state, but it can help technicians eliminate some distribution nodes that are unlikely to fail more quickly, thereby reducing the waste of manpower and resources caused by manual detection and analysis.

[0081] 206: Determine y distribution network restoration plans according to the i line states and the j node states.

[0082] In an embodiment of the present application, the distribution network restoration scheme is used to allocate the restored electric load of each of the j distribution nodes and the restored heat load of each of the n heating nodes. y is an integer greater than 1. After determining i line states and j node states, the processing device may determine y distribution network restoration schemes matching the i line states and the j node states.

[0083] Exemplarily, according to i line states and j node states, y distribution network restoration schemes are determined, including:

[0084] Obtain the path lengths of multiple traffic roads between any two distribution nodes among j distribution nodes;

[0085] Determine the shortest path between any two distribution nodes among j distribution nodes according to the path lengths of multiple traffic roads between any two distribution nodes;

[0086] Get the water depth of the shortest path between any two distribution nodes;

[0087] Determine the travel time between any two distribution nodes among j distribution nodes according to the water depth of the shortest path between any two distribution nodes;

[0088] According to the i line states and the j node states, m deployment nodes are determined from the j distribution nodes;

[0089] According to the travel time between any two distribution nodes among the j distribution nodes, the charge and discharge state variables corresponding to each deployment node among the m deployment nodes are determined to obtain m charge and discharge state variables;

[0090] According to the m charging and discharging state variables, establishing first operation constraints corresponding to the m mobile energy storage systems;

[0091] According to the first operating constraint, y distribution network restoration schemes are determined.

[0092] In the embodiment of the present application, the water depth refers to the road water depth on the shortest path corresponding to the water depth. m deployment nodes are used to deploy m mobile energy storage systems (Mobile Energy Storage System, MESS), each deployment node deploys a mobile energy storage system, and the mobile energy storage system is used to supply power to the faulty nodes in j distribution nodes, m is an integer greater than or equal to the target number and less than or equal to j, and the target number is the number of faulty nodes in j distribution nodes.

[0093] Specifically, the processing device first obtains the path length of each of the multiple traffic roads between any two of the j distribution nodes, and determines the shortest path between any two of the j distribution nodes based on the path length of each of the multiple traffic roads between any two of the j distribution nodes.

[0094] It should be noted that when a line failure or node failure occurs in the distribution network, CAES and generators alone cannot supply power to all distribution nodes. Therefore, it is necessary to deploy a mobile energy storage system as an emergency power supply in distribution nodes that CAES and generators cannot cover to supply power to distribution nodes that CAES and generators cannot cover. Therefore, the processing device needs to determine the shortest path between any two distribution nodes among j distribution nodes to determine the travel time between any two distribution nodes, thereby determining the deployment nodes of the MESS.

[0095] Specifically, the processing device obtains the water depth on the traffic road corresponding to the shortest path between any two distribution nodes. Wherein, a liquid level sensor is arranged on each traffic road, and the processing device can directly obtain the water depth corresponding to the shortest path from the liquid level sensor on the traffic road corresponding to the shortest path between any two distribution nodes. It should be noted that in the case of waterlogging on the road, the driving speed of the vehicle deployed with the MESS can be determined according to the water depth. The driving speed of the vehicle can be expressed by the following formula (3):

[0096]

[0097] Where d is the depth of water accumulation, v M represents the speed of the vehicle on the shortest path corresponding to the water depth, v M0 represents the speed of the vehicle when there is no water on the shortest path. a represents half the depth of the water when vehicles are prohibited from passing, and b represents the attenuation coefficient. M0 , a and b can be preset according to actual test results.

[0098] Therefore, based on formula (2), the processing device can determine the driving speed of the vehicle on the shortest path between any two distribution nodes according to the water depth of the shortest path between any two distribution nodes. Then, the processing device obtains the path length of the shortest path between any two distribution nodes. According to the path length of the shortest path between any two distribution nodes among the j distribution nodes and the driving speed of the vehicle on the shortest path between any two distribution nodes, the travel time between any two distribution nodes among the j distribution nodes can be determined.

[0099] Further, the processing device needs to determine m MESSs corresponding to m deployment nodes in j distribution nodes according to i line states and j node states. Exemplarily, determining m deployment nodes in j distribution nodes according to i line states and j node states may include:

[0100] According to the i line states, determine the first virtual commodity flow of each of the i line segments, and obtain i first virtual commodity flows;

[0101] According to the j node states and the i first virtual commodity flows, determine the second virtual commodity flow corresponding to each of the j distribution nodes to obtain j second virtual commodity flows;

[0102] According to the j second virtual commodity flows, determine the third virtual commodity flow corresponding to each of the j distribution nodes to obtain j third virtual commodity flows;

[0103] According to the j third virtual commodity flows, a deployment node of each of the m mobile energy storage systems is determined in the j distribution nodes to obtain m deployment nodes.

[0104] In an embodiment of the present application, the first virtual commodity flow is used to indicate whether the compressed air energy storage supplies power to the line section. The second virtual commodity flow is used to indicate whether the compressed air energy storage supplies power to the distribution node corresponding to the second virtual commodity flow. The third virtual commodity flow is used to indicate whether the distribution node corresponding to the third virtual commodity flow is deployed with a mobile energy storage system.

[0105] It should be noted that after some lines and distribution nodes in the distribution network fail, the backup lines will be temporarily closed, and the entire distribution network will be reconstructed to form multiple microgrids through network reconstruction. The number of microgrids is equal to the number of non-faulty distribution nodes minus the number of non-faulty lines, and each microgrid is interconnected. Since each microgrid can only be powered by one power source, which can be a generator or a CAES in power generation state, the number of microgrids is the sum of the number of nodes covered by the generator and the CAES power generation state variable. Therefore, according to the line state of each line section in the distribution network and the node state of each distribution node, all distribution nodes that can be supplied by generators and CAES in the distribution network, as well as all distribution nodes that cannot be supplied by generators and CAES, can be determined, thereby determining the deployment nodes of each mobile energy storage system in the m mobile energy storage systems, and obtaining m deployment nodes.

[0106] Specifically, the processing device first determines the first virtual commodity flow corresponding to each line segment in the i-segment line according to the i line states. For example, when the line state is connected to the main network, it means that the compressed air energy storage or the generator can supply power to the line corresponding to the line state, and the first virtual commodity flow is a preset value greater than 1. When the line state is a line fault or the line is off the grid, it means that the compressed air energy storage or the generator cannot supply power to the line corresponding to the line state, and the first virtual commodity flow is 0. Therefore, the processing device can determine the first virtual commodity flow corresponding to each line segment in the i-segment line according to the i line states, and obtain i first virtual commodity flows.

[0107] Then, the processing device determines the second virtual commodity flow corresponding to each of the j distribution nodes according to the j node states and the i first virtual commodity flows, and obtains j second virtual commodity flows. Wherein, due to the connectivity between adjacent distribution nodes, when the first virtual commodity flow is a preset value, the second virtual commodity flow of the two nodes connected by the line corresponding to the first virtual commodity flow is a preset value greater than 1. At the same time, according to the j node states, it can be determined that when the node state is normal power supply, the second virtual commodity flow corresponding to the node state is a preset value greater than 1. When the node state is a node failure or the node is off-grid, the second virtual commodity flow corresponding to the node state is 0. Therefore, the processing device can determine the second virtual commodity flow corresponding to each of the j distribution nodes according to the j node states and the i first virtual commodity flows, and obtain j second virtual commodity flows.

[0108] Further, after determining the j second virtual commodity flows, the processing device can determine the distribution nodes that the generator and MESS cannot cover among the j distribution nodes, that is, the distribution nodes whose second virtual commodity flows are 0. Therefore, the processing device can determine j third virtual commodity flows based on the j second virtual commodity flows to ensure that each distribution node in the distribution network can be powered normally. Among them, when the MESS is in a discharging state at the distribution node, the third virtual commodity flow corresponding to the distribution node is a preset value greater than 1. When the MESS is in a charging state at the distribution node, the third virtual commodity flow corresponding to the distribution node is 0. Among them, the correspondence between the j third virtual commodity flows and the j second virtual commodity flows can be pre-set according to the actual test results. Therefore, the processing device can determine the third virtual commodity flow corresponding to each distribution node among the j distribution nodes based on the j second virtual commodity flows, and obtain j third virtual commodity flows.

[0109] Finally, according to the j third virtual commodity flows, the deployment node of each of the m mobile energy storage systems is determined in the j distribution nodes, and m deployment nodes are obtained. Among them, the m deployment nodes include the distribution node whose third virtual commodity flow is 0 and the distribution node whose travel time with the distribution node whose third virtual commodity flow is 0 is the shortest.

[0110] It can be seen that the processing device can determine the first virtual commodity flow of each line in the i-line segment according to the i-line status, and obtain i-first virtual commodity flows. Then, according to the j-node status and the i-first virtual commodity flows, determine the second virtual commodity flow corresponding to each of the j-distribution nodes, and obtain j-second virtual commodity flows. Further, according to the j-second virtual commodity flows, determine the third virtual commodity flow corresponding to each of the j-distribution nodes. Finally, according to the j-third virtual commodity flows, determine the deployment node of each of the m-mobile energy storage systems in the j-distribution nodes, and obtain m-deployment nodes. Therefore, by deploying MESS at the m-deployment nodes, the distribution nodes that cannot be covered by the generator and CAES can be powered, thereby improving the stability of the power supply of the distribution network.

[0111] Further, according to the travel time between any two of the j distribution nodes, the charge and discharge state variables corresponding to each of the m deployment nodes can be determined, and m charge and discharge state variables can be obtained. For example, the processing device first determines that according to the third virtual commodity flow corresponding to the m deployment nodes, all faulty nodes and off-grid nodes in the m deployment nodes can be determined. Then, the charge and discharge state variables corresponding to all faulty nodes and off-grid nodes are determined to be discharge state values, for example, -1, and the charge and discharge state variables corresponding to the nodes with normal power supply in the m deployment nodes are determined to be charge state values, for example, 1.

[0112] Next, according to the m charging and discharging state variables, the first operation constraints corresponding to the m mobile energy storage systems can be established. The first operation constraints may include: the state of charge (SOC) constraints of each of the m mobile energy storage systems, the active power and reactive power constraints of each mobile energy storage system, the active output and reactive output constraints of the MESS corresponding to each of the j distribution nodes, and so on.

[0113] Finally, according to the first operating constraint, y distribution network restoration schemes can be determined.

[0114] Thus, the processing device can determine the travel time between any two of the j distribution nodes through the shortest path between any two of the j distribution nodes and the depth of water accumulation on the shortest path. Then, m deployment nodes are determined among the j distribution nodes according to the i line states and the j node states. According to the travel time between any two of the j distribution nodes, the charge and discharge state variables corresponding to each of the m deployment nodes are determined to obtain m charge and discharge state variables. According to the m charge and discharge variables, the first operating constraints corresponding to the m mobile energy storage systems are established. Finally, according to the first operating constraints, y distribution network recovery plans can be determined. In this way, the deployment nodes of m MESS can be determined to help the distribution network restore the power load, and y distribution network recovery plans can be determined according to the first operating constraints of the m MESS, thereby improving the accuracy of the distribution network recovery plan.

[0115] Exemplarily, determining y distribution network restoration solutions according to the first operation constraint may include:

[0116] Acquire a first air mass flow rate during the air compression process of the compressor; and acquire a second air mass flow rate during the air expansion process of the steam turbine;

[0117] determining an electrical power of the compressor based on the first air mass flow rate;

[0118] determining an electrical power of the steam turbine based on the second air mass flow rate;

[0119] Determine the thermal power provided by the thermal storage system to the thermal network;

[0120] A second operation constraint corresponding to the compressed air energy storage is established according to the electric power of the compressor, the electric power of the steam turbine, and the thermal power provided by the thermal storage system to the thermal network;

[0121] Obtaining the water supply temperature of each of the n heating nodes to obtain n water supply temperatures; and obtaining the return water temperature of each of the n heating nodes to obtain n return water temperatures; and obtaining the ambient temperature of each of the n heating nodes to obtain n ambient temperatures;

[0122] According to n water supply temperatures and n ambient temperatures, n water supply heat losses are obtained;

[0123] According to n return water temperatures and n ambient temperatures, n return water heat losses are obtained;

[0124] According to n supply water temperatures, n return water temperatures, n ambient temperatures, n supply water heat losses and n return water heat losses, a third operation constraint corresponding to the heat network is established;

[0125] According to the first operation constraint, the second operation constraint and the third operation constraint, y distribution network restoration schemes are determined.

[0126] In the embodiment of the present application, the compressed air energy storage is affected by three parameters during operation: air pressure, temperature and air mass flow. When the compressed air energy storage operates in a constant temperature and constant pressure mode, the electrical power of the equipment in the compressed air energy storage is only related to the air mass flow.

[0127] Specifically, the compressor and the steam turbine are both provided with gas flow detectors. The processing device can obtain the first air mass flow rate during the air compression process of the compressor from the gas flow detector of the compressor, and obtain the second air mass flow rate during the air expansion process of the steam turbine from the gas flow detector of the steam turbine.

[0128] Then, the processing device determines the compression level of the compressor or the expansion level of the steam turbine according to the target number of fault nodes in the j distribution nodes. For example, when the target number is greater than or equal to the preset number, the steam turbine in the CAES is working at this time, and the processing can determine the difference between the target number and the preset number, and determine the expansion level of the steam turbine according to the difference between the target number and the preset number. When the target number is less than the preset number, the compressor in the CAES is working at this time, and the processing can determine the difference between the preset number and the target number, and determine the compression level of the compressor according to the difference between the preset number and the target number. Among them, the mapping relationship between the difference between the target number and the preset number and the expansion level of the steam turbine can be preset according to the actual test results. The mapping relationship between the difference between the preset number and the target number and the compression level of the compressor can be preset according to the actual test results. Based on this, the electrical power of the compressor can be determined according to the first air mass flow rate and the compression level of the compressor. The electrical power of the steam turbine can be determined according to the second air mass flow rate and the expansion level of the steam turbine.

[0129] Furthermore, the processing device can obtain the amount of heat stored in the heat storage system, and determine the amount of heat circulation between the heat storage system and the compressor and the steam turbine according to the electrical power of the compressor and the electrical power of the steam turbine. According to the amount of heat circulation between the heat storage system and the compressor and the steam turbine, the amount of heat provided by the heat storage system to the heat network is determined. Thus, according to the amount of heat provided by the heat storage system to the heat network, the thermal power provided by the heat storage system to the heat network is determined.

[0130] Finally, according to the electric power of the compressor, the electric power of the steam turbine, and the thermal power provided by the heat storage system to the heat network, the second operation constraint corresponding to the compressed air energy storage can be established. Among them, the second operation constraint may include: the constraints of the active power and reactive power of the compressor, the constraints of the active power and reactive power of the steam turbine, the constraints of the air mass flow in the air storage chamber, the constraints of the thermal power provided by the heat storage system to the heat network, the constraints of the recovery heat load corresponding to each of the n heating nodes, etc. The mapping relationship between the electric power of the compressor, the electric power of the steam turbine, and the thermal power provided by the heat storage system to the heat network and the second operation constraint can be preset according to the actual test results.

[0131] Furthermore, the processing device obtains the water supply temperature of each of the n heating nodes in the heating network, and obtains n water supply temperatures. The return water temperature of each of the n heating nodes is obtained, and n return water temperatures are obtained. The ambient temperature of each of the n heating nodes is obtained, and n ambient temperatures are obtained. It should be noted that the water supply pipe and the return water pipe of each heating node are provided with a temperature sensor, and the processing device can directly obtain the water supply temperature of each heating node from the temperature sensor of the water supply pipe of the heating node, and obtain the return water temperature of the heating node from the temperature sensor of the return water pipe of each heating node. At the same time, the processing device can obtain the ambient temperature of each heating node from the ambient temperature sensor of the heating node.

[0132] Then, according to n supply water temperatures and n ambient temperatures, n supply water heat losses can be obtained. According to n return water temperatures and n ambient temperatures, n return water heat losses can be obtained. Among them, one supply water temperature and one ambient temperature correspond to one supply water heat loss. One return water temperature and one ambient temperature correspond to one return water heat loss. The corresponding relationship between the supply water temperature, the ambient temperature and the supply water heat loss, and the corresponding relationship between the return water temperature, the ambient temperature and the return water heat loss can be preset according to the actual test results.

[0133] Next, according to n water supply temperatures, n return water temperatures, n ambient temperatures, n water supply heat losses and n return water heat losses, the third operation constraint corresponding to the heat network can be established. The third operation constraint includes: constraints on the water supply temperature and return water temperature of each of the n heating nodes, constraints on the water supply heat loss and return water heat loss of each of the n heating nodes, constraints on the water supply flow of the water supply pipe of each of the n heating nodes and the return water flow of the return pipe, constraints on the electric power of the heat pump, etc. Among them, the mapping relationship between the n water supply temperatures, n return water temperatures, n ambient temperatures, n water supply heat losses and n return water heat losses and the third operation constraint can be preset according to the actual test results.

[0134] Finally, according to the first operating constraint, the second operating constraint and the third operating constraint, y distribution network restoration schemes can be determined.

[0135] It can be seen that the electric power of the compressor can be determined according to the first air mass flow rate during the air compression process of the compressor. The electric power of the steam turbine can be determined according to the second air mass flow rate during the air expansion process of the steam turbine. According to the electric power of the compressor, the electric power of the steam turbine and the thermal power provided by the heat storage system to the heat network, the second operating constraint corresponding to the compressed air energy storage can be established. According to the supply water temperature, return water temperature, ambient temperature, supply water heat loss and return water heat loss of each of the n heating nodes in the heat network, the third operating constraint corresponding to the heat network can be established. Therefore, according to the first operating constraint corresponding to the m mobile energy storage systems, the second operating constraint corresponding to the CAES and the third operating constraint of the heat network, y distribution network recovery plans can be determined, thereby improving the accuracy of the distribution network recovery plan.

[0136] Exemplarily, determining y distribution network restoration solutions according to the first operation constraint, the second operation constraint, and the third operation constraint may include:

[0137] According to the first operation constraint, determine the first active power and the first reactive power of the mobile energy storage system corresponding to each of the m deployment nodes, and obtain m first active powers and m first reactive powers;

[0138] determining a second active power and a second reactive power of the compressor according to a second operating constraint;

[0139] determining a third active power and a third reactive power of the steam turbine according to the second operation constraint;

[0140] determining the electrical power of the heat pump according to a third operating constraint;

[0141] Establishing a fourth operation constraint corresponding to the distribution network according to the m first active powers, the m first reactive powers, the second active power, the second reactive power, the third active power, the third reactive power and the electric power of the heat pump;

[0142] According to the second operation constraint, y recovery heat loads corresponding to each of the n heating nodes are determined to obtain s recovery heat loads;

[0143] According to the fourth operation constraint, determine y restored electric loads corresponding to each of the j distribution nodes to obtain a restored electric loads;

[0144] According to the s restored thermal loads and a restored thermal loads, y distribution network restoration schemes are determined.

[0145] In the embodiment of the present application, s = n*y. a = j*y. Each heat source node in each power distribution network restoration scheme corresponds to a restored heat load, and each power distribution node corresponds to a restored power load.

[0146] Specifically, the first operation constraint includes constraints on the active power and reactive power of the mobile energy storage system corresponding to each of the m deployment nodes, and the constraint is a value range of the active power and reactive power of the mobile energy storage system corresponding to each deployment node. The processing device can determine the first active power and the first reactive power of the mobile energy storage system corresponding to each of the m deployment nodes from the first operation constraint according to the power demand of each of the m deployment nodes, and obtain m first active powers and m first reactive powers.

[0147] Similarly, the second operating constraint includes constraints on the active power and reactive power of the compressor, which are the value ranges of the active power and reactive power of the compressor. The processing device can obtain the excess power in the distribution network, and determine the second active power and second reactive power of the compressor from the second operating constraint based on the excess power in the distribution network. The second operating constraint also includes constraints on the active power and reactive power of the steam turbine, which are the value ranges of the active power and reactive power of the steam turbine. The processing device can determine the third active power and third reactive power of the steam turbine from the third operating constraint based on the total power demand of the distribution network. Then, the electric power of the heat pump is determined based on the third operating constraint.

[0148] Further, the processing device establishes a fourth operation constraint corresponding to the distribution network according to the m first active powers, the m first reactive powers, the second active powers, the second reactive powers, the third active powers, the third reactive powers and the electric power of the heat pump. The fourth operation constraint includes: a constraint on the restored electric load of each of the j distribution nodes, a constraint on the node voltage of each of the j distribution nodes, and the like.

[0149] Then, since the second operation constraint includes the constraint of the recovery heat load corresponding to each of the n heating nodes, the processing device can randomly obtain y recovery heat loads from the constraint as the y recovery heat loads corresponding to each heating node, thereby obtaining s recovery heat loads. Since the fourth operation constraint includes the constraint of the recovery electric load of each of the j power distribution nodes, the processing device can randomly obtain y recovery electric loads from the constraint as the y recovery electric loads corresponding to each power distribution node, thereby obtaining a recovery electric loads.

[0150] Finally, the processing device corresponds each of the j distribution nodes to a restored electric load and each of the n heating nodes to a restored thermal load to determine a distribution network restoration plan. Based on the above method, y distribution network restoration plans can be determined.

[0151] Therefore, by establishing the fourth operation constraint corresponding to the distribution network, and determining the y restoration electric loads corresponding to each of the j distribution nodes according to the fourth operation constraint, a restoration electric load can be obtained. According to the second operation constraint, the y restoration heat loads corresponding to each of the n heating nodes can be determined to obtain s restoration heat loads, and then according to the s restoration heat loads and the a restoration heat loads, y distribution network restoration plans are determined, each distribution network restoration plan is related to the operating state of the distribution network, and the accuracy of the distribution network restoration plan is improved.

[0152] 207: Determine the total value of each distribution network restoration plan in the y distribution network restoration plans to obtain y total values.

[0153] In the embodiment of the present application, the total value refers to the value of the total restored electric load of the distribution network and the total restored thermal load of the heating network in the distribution network restoration plan corresponding to the total value.

[0154] Exemplarily, determining the total value of each distribution network restoration scheme in y distribution network restoration schemes to obtain y total values ​​may include:

[0155] Determine the sum of the restored heat loads of the n heating nodes corresponding to each distribution network restoration scheme in the y distribution network restoration schemes as the total restored heat load of the distribution network restoration scheme, and obtain y total restored heat loads;

[0156] Determine that the sum of the restored power loads of the j distribution nodes corresponding to each distribution network restoration scheme in the y distribution network restoration schemes is the total restored power load of the distribution network restoration scheme, and obtain y total restored power loads;

[0157] Obtain the electrical load value coefficient and the thermal load value coefficient;

[0158] Determine a heat load value according to the heat load value coefficient and each of the y total recovery heat loads to obtain y heat load values;

[0159] Determine an electric load value according to the electric load value coefficient and each of the y total restored electric loads to obtain y electric load values;

[0160] Based on y thermal load values ​​and y electrical load values, determine y total values.

[0161] In an embodiment of the present application, the higher the total restored electric load corresponding to the j distribution nodes in the distribution network, the greater the value of the distribution network restoration plan corresponding to the total restored electric load. Similarly, the higher the total restored thermal load of the n heating nodes in the heating network, the greater the value of the distribution network restoration plan corresponding to the total restored thermal load. The processing device can determine the total value of each distribution network restoration plan based on the total restored electric load and the total restored thermal load of each distribution network restoration plan.

[0162] Specifically, the processing device first determines that the sum of the restored heat loads of the n heating nodes corresponding to each distribution network restoration scheme in the y distribution network restoration schemes is the total restored heat load of the distribution network restoration scheme, and obtains y total restored heat loads, wherein each total restored heat load is the restored heat load corresponding to the heat source node of the heat network in the distribution network restoration scheme. Then, the sum of the restored electric loads of the j distribution nodes corresponding to each distribution network restoration scheme in the y distribution network restoration schemes is determined as the total restored electric load of the distribution network restoration scheme, and obtains y total restored electric loads. The total restored electric load is jointly supplied by the generator, CAES and m MESS.

[0163] Furthermore, the processing device obtains the energy load value coefficient and the heat load value coefficient. The electric load value coefficient and the heat load value coefficient can be preset according to user needs. Then, the processing device multiplies the electric load value coefficient by j to obtain the total electric load value coefficient. The product of the total electric load value coefficient and each of the y total restored electric loads is used as the electric load value corresponding to the total restored electric load to obtain y electric load values.

[0164] Further, the processing device multiplies the heat load value coefficient by n to obtain a total heat load value coefficient. The product of the total heat load value coefficient and each of the y total recovery heat loads is used as the heat load value corresponding to the total recovery heat load to obtain y heat load values.

[0165] Finally, the processing device uses the sum of the heat load value and the electric load value corresponding to each distribution network restoration scheme as the total value corresponding to the distribution network restoration scheme according to the distribution network restoration scheme corresponding to each heat load value in the y heat load values ​​and the distribution network restoration scheme corresponding to each electric load value in the y electric load values. Based on this, the total value of each distribution network restoration scheme in the y distribution network restoration schemes can be determined to obtain y total values.

[0166] Thus, by determining the sum of the restored heat loads of the n heating nodes corresponding to each distribution network restoration scheme in the y distribution network restoration schemes, y total restored heat loads can be obtained. By determining the sum of the restored electric loads of the j distribution nodes corresponding to each distribution network restoration scheme in the y distribution network restoration schemes, y total restored electric loads can be obtained. According to the y total restored heat loads and the heat load value coefficient, y heat load values ​​can be determined. According to the y total restored electric loads and the electric load value coefficient, y electric load values ​​can be determined. Finally, according to the y heat load values ​​and the y electric load values, the y total values ​​corresponding to the y distribution network restoration schemes are determined, so that the distribution network restoration scheme with the highest total value can be determined according to the y total values, thereby improving the accuracy of the distribution network restoration scheme.

[0167] 208: According to the y total values, select a distribution network restoration scheme from the y distribution network restoration schemes as the target distribution network restoration scheme.

[0168] In the embodiment of the present application, the processing device can determine the distribution network restoration plan with the highest total value from y distribution network restoration plans as the target distribution network restoration plan based on y total values, so as to make the total restored electric load of the distribution network and the total restored thermal load of the heat network have the highest value, thereby improving the accuracy of the distribution network restoration plan. Thus, technicians can dispatch the distribution network, CAES, m MESSs and heat pumps according to the distribution network restoration plan, and repair the faulty lines in the i-segment lines and the faulty nodes in the j distribution nodes, thereby ensuring the stability of the distribution network.

[0169] In summary, in an embodiment of the present application, the wind speed corresponding to each section of the i-section line in the distribution network under the waterlogging disaster is first obtained to obtain i wind speeds, and the flooding depth of each distribution node in the j distribution nodes of the distribution network under the waterlogging disaster is obtained to obtain j flooding depths. Then, according to the i wind speeds, the line failure probability corresponding to each section of the i-section line is determined to obtain i line failure probabilities. According to the i line failure probabilities, the line state of each section of the i-section line can be determined to obtain i line failure states. Further, according to the j flooding depths, the node failure probability corresponding to each distribution node in the j distribution nodes can be determined to obtain j node failure probabilities. According to the j node failure probabilities, the node state of each distribution node in the j distribution nodes can be determined to obtain j node states. Further, according to the i line states and the j node states, y distribution network recovery plans can be determined. The total value of each distribution network recovery plan in the y distribution network recovery plans is determined to obtain y total values. Finally, according to the y total values, a distribution network restoration scheme can be selected from the y distribution network restoration schemes as the target distribution network restoration scheme. Therefore, the line state of each line section in the distribution network can be predicted by the wind speed corresponding to the line section, and the node state of each distribution node in the distribution network can be predicted by the water depth of each distribution node in the distribution network. Thus, according to the line state of each line section in the distribution network and the node state of each distribution node, y distribution network restoration schemes are determined. Each distribution network restoration scheme is related to the line state of each line section and the node state of each distribution node, which improves the accuracy of the distribution network restoration scheme. In addition, by determining the total value of each distribution network restoration scheme among the y distribution network restoration schemes, the target distribution network restoration scheme with the highest value of restoring electric load and restoring thermal load can be selected from the y distribution network restoration schemes, further improving the accuracy of the distribution network restoration scheme.

[0170] See also Figure 3 , Figure 3 Schematic diagram of a power distribution network restoration device provided in an embodiment of the present application. The power distribution network restoration device 300 may be a processing device in any of the above embodiments. Figure 3 As shown, the power distribution network restoration device 300 includes an acquisition unit 301 and a processing unit 302 .

[0171] The acquisition unit 301 is used to acquire the wind speed corresponding to each line section in the i-line section of the distribution network under the waterlogging disaster, and obtain i wind speeds, and acquire the flooding depth of each distribution node in the j distribution nodes of the distribution network under the waterlogging disaster, and obtain j flooding depths;

[0172] The processing unit 302 is used to determine the line failure probability corresponding to each line section in the i line sections according to the i wind speeds, and obtain the i line failure probabilities;

[0173] According to the failure probability of i lines, the line state of each line in the i lines is determined to obtain i line states;

[0174] According to the j flooding depths, the node failure probability corresponding to each of the j distribution nodes is determined to obtain the j node failure probability;

[0175] According to the failure probability of j nodes, the node state of each distribution node in the j distribution nodes is determined to obtain j node states;

[0176] Determine y distribution network restoration plans according to i line states and j node states; the distribution network restoration plan is used to allocate the restored electric load of each of the j distribution nodes and the restored heat load of each of the n heating nodes;

[0177] Determine the total value of each of the y distribution network restoration plans to obtain y total values;

[0178] According to the y total values, a distribution network restoration scheme is selected from the y distribution network restoration schemes as the target distribution network restoration scheme.

[0179] In a possible embodiment, each of the i-section lines is installed on k towers, where k is an integer greater than 1; in determining the line failure probability corresponding to each of the i-section lines according to the i wind speeds to obtain the i line failure probabilities, the processing unit 302 is specifically configured to:

[0180] According to i wind speeds, determine the conductor failure probability corresponding to each line in i lines, and obtain i conductor failure probabilities;

[0181] According to i wind speeds, determine the tower damage probability of k towers corresponding to each line section in i lines, and obtain x tower damage probabilities; x is an integer greater than 1, x = i*k;

[0182] According to the probability of i conductor failure and x tower damage, the probability of i line failure is obtained.

[0183] In a possible embodiment, in determining y distribution network restoration solutions according to i line states and j node states, the processing unit 302 is specifically configured to:

[0184] Obtain the path lengths of multiple traffic roads between any two distribution nodes among j distribution nodes;

[0185] Determine the shortest path between any two distribution nodes among j distribution nodes according to the path lengths of multiple traffic roads between any two distribution nodes;

[0186] Obtain the water depth of the shortest path between any two distribution nodes; the water depth refers to the road water depth on the shortest path corresponding to the water depth;

[0187] Determine the travel time between any two distribution nodes among j distribution nodes according to the water depth of the shortest path between any two distribution nodes;

[0188] According to i line states and j node states, m deployment nodes are determined in j distribution nodes; the m deployment nodes are used to deploy m mobile energy storage systems, one mobile energy storage system is deployed on each deployment node, and the mobile energy storage system is used to supply power to the faulty nodes in the j distribution nodes, where m is an integer greater than or equal to the target number and less than or equal to j, and the target number is the number of faulty nodes in the j distribution nodes;

[0189] According to the travel time between any two distribution nodes among the j distribution nodes, the charge and discharge state variables corresponding to each deployment node among the m deployment nodes are determined to obtain m charge and discharge state variables;

[0190] According to the m charging and discharging state variables, establishing first operation constraints corresponding to the m mobile energy storage systems;

[0191] According to the first operating constraint, y distribution network restoration schemes are determined.

[0192] In a possible embodiment, in determining y distribution network restoration solutions according to the first operation constraint, the processing unit 302 is specifically configured to:

[0193] Acquire a first air mass flow rate during the air compression process of the compressor; and acquire a second air mass flow rate during the air expansion process of the steam turbine;

[0194] determining an electrical power of the compressor based on the first air mass flow rate;

[0195] determining an electrical power of the steam turbine based on the second air mass flow rate;

[0196] Determine the thermal power provided by the thermal storage system to the thermal network;

[0197] A second operation constraint corresponding to the compressed air energy storage is established according to the electric power of the compressor, the electric power of the steam turbine, and the thermal power provided by the thermal storage system to the thermal network;

[0198] Obtaining the water supply temperature of each of the n heating nodes to obtain n water supply temperatures; and obtaining the return water temperature of each of the n heating nodes to obtain n return water temperatures; and obtaining the ambient temperature of each of the n heating nodes to obtain n ambient temperatures;

[0199] According to n water supply temperatures and n ambient temperatures, n water supply heat losses are obtained;

[0200] According to n return water temperatures and n ambient temperatures, n return water heat losses are obtained;

[0201] According to n supply water temperatures, n return water temperatures, n ambient temperatures, n supply water heat losses and n return water heat losses, a third operation constraint corresponding to the heat network is established;

[0202] According to the first operation constraint, the second operation constraint and the third operation constraint, y distribution network restoration schemes are determined.

[0203] In a possible embodiment, in determining m deployment nodes from j distribution nodes according to i line states and j node states, the processing unit 302 is specifically configured to:

[0204] According to the states of i lines, determine the first virtual commodity flow of each line in the i lines, and obtain i first virtual commodity flows; the first virtual commodity flow is used to indicate whether the compressed air energy storage supplies power to the line;

[0205] According to j node states and i first virtual commodity flows, determine the second virtual commodity flow corresponding to each of the j distribution nodes, and obtain j second virtual commodity flows, where the second virtual commodity flows are used to indicate whether the compressed air energy storage supplies power to the distribution node corresponding to the second virtual commodity flow;

[0206] According to the j second virtual commodity flows, determine the third virtual commodity flow corresponding to each of the j distribution nodes, and obtain j third virtual commodity flows, where the third virtual commodity flow is used to indicate whether the distribution node corresponding to the third virtual commodity flow is deployed with a mobile energy storage system;

[0207] According to the j third virtual commodity flows, a deployment node of each of the m mobile energy storage systems is determined in the j distribution nodes to obtain m deployment nodes.

[0208] In a possible embodiment, in determining y distribution network restoration solutions according to the first operation constraint, the second operation constraint and the third operation constraint, the processing unit 302 is specifically configured to:

[0209] According to the first operation constraint, determine the first active power and the first reactive power of the mobile energy storage system corresponding to each of the m deployment nodes, and obtain m first active powers and m first reactive powers;

[0210] determining a second active power and a second reactive power of the compressor according to a second operating constraint;

[0211] determining a third active power and a third reactive power of the steam turbine according to the second operation constraint;

[0212] determining the electrical power of the heat pump according to a third operating constraint;

[0213] Establishing a fourth operation constraint corresponding to the distribution network according to the m first active powers, the m first reactive powers, the second active power, the second reactive power, the third active power, the third reactive power and the electric power of the heat pump;

[0214] According to the second operation constraint, y recovery heat loads corresponding to each of the n heating nodes are determined to obtain s recovery heat loads; s = n*y;

[0215] According to the fourth operation constraint, y restored electric loads corresponding to each of the j distribution nodes are determined to obtain a restored electric loads; a=j*y;

[0216] According to the s restored heat loads and the a restored heat loads, y distribution network restoration schemes are determined, wherein each heat source node in each distribution network restoration scheme corresponds to a restored heat load, and each distribution node corresponds to a restored electric load.

[0217] In a possible embodiment, in determining the total value of each distribution network restoration scheme in y distribution network restoration schemes to obtain y total values, the processing unit 302 is specifically configured to:

[0218] Determine the sum of the restored heat loads of the n heating nodes corresponding to each distribution network restoration scheme in the y distribution network restoration schemes as the total restored heat load of the distribution network restoration scheme, and obtain y total restored heat loads;

[0219] Determine that the sum of the restored power loads of the j distribution nodes corresponding to each distribution network restoration scheme in the y distribution network restoration schemes is the total restored power load of the distribution network restoration scheme, and obtain y total restored power loads;

[0220] Obtain the electrical load value coefficient and the thermal load value coefficient;

[0221] Determine a heat load value according to the heat load value coefficient and each of the y total recovery heat loads to obtain y heat load values;

[0222] Determine an electric load value according to the electric load value coefficient and each of the y total restored electric loads to obtain y electric load values;

[0223] Based on y thermal load values ​​and y electrical load values, determine y total values.

[0224] See also Figure 4 , Figure 4This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 4 As shown, the electronic device 400 includes a transceiver 401, a processor 402 and a memory 403. They are connected via a bus 404. The memory 403 is used to store computer programs and data, and can transmit the data stored in the memory 403 to the processor 402. The electronic device 400 can be a power distribution network restoration device 300. The electronic device 400 can also be a processing device of any of the above embodiments.

[0225] The processor 402 is used to read the computer program in the memory 403 and perform the following operations:

[0226] Obtain the wind speed corresponding to each line in the i-line of the distribution network under the waterlogging disaster, obtain i wind speeds, and obtain the flooding depth of each distribution node in the j distribution nodes of the distribution network under the waterlogging disaster, obtain j flooding depths;

[0227] According to i wind speeds, the line failure probability corresponding to each line in i lines is determined to obtain the i line failure probability;

[0228] According to the failure probability of i lines, the line state of each line in the i lines is determined to obtain i line states;

[0229] According to the j flooding depths, the node failure probability corresponding to each of the j distribution nodes is determined to obtain the j node failure probability;

[0230] According to the failure probability of j nodes, the node state of each distribution node in the j distribution nodes is determined to obtain j node states;

[0231] Determine y distribution network restoration plans based on i line states and j node states;

[0232] Determine the total value of each of the y distribution network restoration plans to obtain y total values;

[0233] According to the y total values, a distribution network restoration scheme is selected from the y distribution network restoration schemes as the target distribution network restoration scheme.

[0234] The above mainly introduces the scheme of the embodiment of the present application from the perspective of the execution process of the method side. It is understandable that the electronic device 400 includes a hardware structure and / or software module corresponding to each function in order to realize the above functions. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiment provided herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware 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 the present application.

[0235] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. The computer program is executed by a processor to implement part or all of the steps of any one of the methods described in the above method embodiments.

[0236] An embodiment of the present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute part or all of the steps of any one of the methods recorded in the above method embodiments.

[0237] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0238] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0239] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which 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, and the indirect coupling or communication connection of the device or unit can be electrical or other forms.

[0240] 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.

[0241] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of a software program module.

[0242] If the integrated unit is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or CD-ROM and other media that can store program codes.

[0243] A person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (English: Read-Only Memory, abbreviated as: ROM), a random access memory (English: Random Access Memory, abbreviated as: RAM), a magnetic disk or an optical disk, etc.

[0244] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for restoring a distribution network under a flood disaster, characterized in that: include: Obtain the wind speed corresponding to each section of the i-section line in the distribution network under the waterlogging disaster, and obtain i wind speeds, and obtain the water immersion depth of each of the j distribution nodes of the distribution network under the waterlogging disaster, and obtain j water immersion depths; the distribution network is coupled to the heat network through compressed air energy storage and a heat pump, the first distribution node of the j distribution nodes is connected to the compressor of the compressed air energy storage, the second distribution node of the j distribution nodes is connected to the steam turbine of the compressed air energy storage, the heat source node of the heat network is connected to the heat storage system of the compressed air energy storage, and is connected to the heat pump, and the heat source node is any one of the n heating nodes of the heat network; the water immersion depth is the depth of the distribution equipment of the distribution node corresponding to the water immersion depth; i and n are both integers greater than 1, j=i+1; Determine the line failure probability corresponding to each line segment in the i line segments according to the i wind speeds, and obtain i line failure probabilities; According to the i line failure probabilities, determining the line state of each line in the i line sections to obtain i line states; Determine, according to the j flooding depths, a node failure probability corresponding to each of the j power distribution nodes, to obtain j node failure probabilities; Determine the node state of each of the j power distribution nodes according to the j node failure probabilities to obtain j node states; Determine y distribution network restoration plans according to the i line states and the j node states; The distribution network restoration scheme is used to allocate the restored electric load of each of the j distribution nodes and the restored heat load of each of the n heating nodes; y is an integer greater than 1; Determine the total value of each distribution network restoration plan in the y distribution network restoration plans to obtain y total values; the total value refers to the value of the total restored electrical load of the distribution network and the total restored thermal load of the thermal network in the distribution network restoration plan corresponding to the total value; According to the y total values, a distribution network restoration scheme is selected from the y distribution network restoration schemes as a target distribution network restoration scheme.

2. The method according to claim 1, characterized in that Each of the i-section lines is erected on k towers, where k is an integer greater than 1; determining the line failure probability corresponding to each of the i-section lines according to the i wind speeds to obtain i line failure probabilities, including: Determine the conductor failure probability corresponding to each section of the i sections of the line according to the i wind speeds, and obtain i conductor failure probabilities; According to the i wind speeds, determine the tower damage probability of k towers corresponding to each line section in the i line sections to obtain x tower damage probabilities; x is an integer greater than 1, x=i*k; The i line failure probabilities are obtained according to the i conductor failure probabilities and the x tower damage probabilities.

3. The method according to claim 1 or 2, characterized in that: Determining y distribution network restoration schemes according to the i line states and the j node states includes: Obtaining the path lengths of multiple traffic roads between any two of the j distribution nodes; Determine the shortest path between any two of the j distribution nodes according to the path lengths of the plurality of traffic roads between the any two distribution nodes; Obtaining the water depth of the shortest path between any two power distribution nodes; the water depth refers to the road water depth on the shortest path corresponding to the water depth; Determine the travel time between any two of the j distribution nodes according to the water depth of the shortest path between the any two distribution nodes; According to the i line states and the j node states, m deployment nodes are determined from the j distribution nodes; the m deployment nodes are used to deploy m mobile energy storage systems, one mobile energy storage system is deployed on each deployment node, and the mobile energy storage system is used to supply power to the faulty nodes in the j distribution nodes, m is an integer greater than or equal to a target number and less than or equal to j, and the target number is the number of faulty nodes in the j distribution nodes; Determine the charge and discharge state variable corresponding to each of the m deployment nodes according to the travel time between any two of the j distribution nodes, and obtain m charge and discharge state variables; Establishing first operation constraints corresponding to the m mobile energy storage systems according to the m charging and discharging state variables; The y distribution network restoration plans are determined according to the first operating constraint.

4. The method according to claim 3, characterized in that The determining the y distribution network restoration schemes according to the first operation constraint includes: Acquire a first air mass flow rate during the air compression process of the compressor; and acquire a second air mass flow rate during the air expansion process of the steam turbine; determining an electrical power of the compressor according to the first air mass flow rate; determining an electrical power of the steam turbine according to the second air mass flow rate; Determining the thermal power provided by the thermal storage system to the thermal network; Establishing a second operation constraint corresponding to the compressed air energy storage according to the electric power of the compressor, the electric power of the steam turbine, and the thermal power provided by the thermal storage system to the thermal network; Obtaining the water supply temperature of each of the n heating nodes to obtain n water supply temperatures; and obtaining the return water temperature of each of the n heating nodes to obtain n return water temperatures; and obtaining the ambient temperature of each of the n heating nodes to obtain n ambient temperatures; Obtain n water supply heat losses according to the n water supply temperatures and the n ambient temperatures; Obtaining n return water heat losses according to the n return water temperatures and the n ambient temperatures; Establishing a third operation constraint corresponding to the heating network according to the n supply water temperatures, the n return water temperatures, the n ambient temperatures, the n supply water heat losses and the n return water heat losses; The y distribution network restoration plans are determined according to the first operating constraint, the second operating constraint and the third operating constraint.

5. The method according to claim 3, characterized in that: The step of determining m deployment nodes from the j power distribution nodes according to the i line states and the j node states includes: According to the i line states, determining the first virtual commodity flow of each of the i line segments, and obtaining i first virtual commodity flows; the first virtual commodity flow is used to indicate whether the compressed air energy storage supplies power to the line segment; Determine, according to the j node states and the i first virtual commodity flows, a second virtual commodity flow corresponding to each of the j distribution nodes, to obtain j second virtual commodity flows, wherein the second virtual commodity flows are used to indicate whether the compressed air energy storage supplies power to the distribution node corresponding to the second virtual commodity flow; Determine, according to the j second virtual commodity flows, a third virtual commodity flow corresponding to each of the j distribution nodes, to obtain j third virtual commodity flows, wherein the third virtual commodity flow is used to indicate whether a mobile energy storage system is deployed at the distribution node corresponding to the third virtual commodity flow; According to the j third virtual commodity flows, a deployment node of each of the m mobile energy storage systems is determined in the j power distribution nodes to obtain the m deployment nodes.

6. The method according to claim 4, characterized in that The determining the y distribution network restoration schemes according to the first operation constraint, the second operation constraint and the third operation constraint comprises: According to the first operation constraint, determine a first active power and a first reactive power of the mobile energy storage system corresponding to each of the m deployment nodes, and obtain m first active powers and m first reactive powers; determining a second active power and a second reactive power of the compressor according to the second operating constraint; determining a third active power and a third reactive power of the steam turbine according to the second operation constraint; determining the electrical power of the heat pump according to the third operating constraint; Establishing a fourth operation constraint corresponding to the distribution network according to the m first active powers, the m first reactive powers, the second active power, the second reactive power, the third active power, the third reactive power and the electric power of the heat pump; According to the second operation constraint, y recovery heat loads corresponding to each of the n heating nodes are determined to obtain s recovery heat loads; s=n*y; According to the fourth operation constraint, y restored electric loads corresponding to each of the j distribution nodes are determined to obtain a restored electric loads; a=j*y; The y distribution network restoration schemes are determined according to the s restoration heat loads and the a restoration heat loads, wherein each heat source node in each distribution network restoration scheme corresponds to a restoration heat load, and each distribution node corresponds to a restoration electric load.

7. The method according to claim 6, characterized in that The determining the total value of each distribution network restoration scheme in the y distribution network restoration schemes to obtain y total values ​​comprises: Determine the sum of the restored heat loads of the n heating nodes corresponding to each distribution network restoration scheme in the y distribution network restoration schemes as the total restored heat load of the distribution network restoration scheme, and obtain y total restored heat loads; Determine that the sum of the restored power loads of the j distribution nodes corresponding to each distribution network restoration scheme in the y distribution network restoration schemes is the total restored power load of the distribution network restoration scheme, and obtain y total restored power loads; Obtain the electrical load value coefficient and the thermal load value coefficient; Determine a heat load value according to the heat load value coefficient and each of the y total recovery heat loads to obtain y heat load values; Determine an electric load value according to the electric load value coefficient and each of the y total restored electric loads to obtain y electric load values; The y total values ​​are determined based on the y thermal load values ​​and the y electrical load values.

8. A distribution network restoration device, characterized in that: include: An acquisition unit is used to acquire the wind speed corresponding to each section of the i-section line in the distribution network under the waterlogging disaster, obtain i wind speeds, and acquire the water immersion depth of each of the j distribution nodes of the distribution network under the waterlogging disaster, obtain j water immersion depths; the distribution network is coupled to the heat network through compressed air energy storage and a heat pump, the first distribution node of the j distribution nodes is connected to the compressor of the compressed air energy storage, the second distribution node of the j distribution nodes is connected to the steam turbine of the compressed air energy storage, the heat source node of the heat network is connected to the heat storage system of the compressed air energy storage, and is connected to the heat pump, and the heat source node is any one of the n heating nodes of the heat network; the water immersion depth is the depth of the distribution equipment of the distribution node corresponding to the water immersion depth; i and n are both integers greater than 1, j=i+1; A processing unit, configured to determine, according to the i wind speeds, a line failure probability corresponding to each line segment in the i line segments, to obtain i line failure probabilities; According to the i line failure probabilities, determining the line state of each line in the i line sections to obtain i line states; Determine, according to the j flooding depths, a node failure probability corresponding to each of the j power distribution nodes, to obtain j node failure probabilities; Determine the node state of each of the j power distribution nodes according to the j node failure probabilities to obtain j node states; Determine y distribution network restoration plans according to the i line states and the j node states; The distribution network restoration scheme is used to allocate the restored electric load of each of the j distribution nodes and the restored heat load of each of the n heating nodes; y is an integer greater than 1; Determine the total value of each distribution network restoration plan in the y distribution network restoration plans to obtain y total values; the total value refers to the value of the total restored electrical load of the distribution network and the total restored thermal load of the thermal network in the distribution network restoration plan corresponding to the total value; According to the y total values, a distribution network restoration scheme is selected from the y distribution network restoration schemes as a target distribution network restoration scheme.

9. An electronic device, characterized in that: include: A processor and a memory, wherein the processor is connected to the memory, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the electronic device executes the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method according to any one of claims 1 to 7.

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