Power distribution network situation awareness method and system

Abstract

The invention discloses a power distribution network situation awareness method and system, and relates to the technical field of power distribution network situations, and the method comprises the steps: collecting power distribution network situation factors in real time, and evaluating the operation state of a power distribution network based on the power distribution network situation factors; based on the real-time operation data of the power distribution network, calculating the load rate of the power equipment and evaluating the risk state of the power equipment; constructing a power distribution system power supply model to evaluate the power supply capability of the power distribution system by taking the maximum power capacity of the power distribution network as a target; and integrating the evaluation results to optimize the operation strategy of the power distribution network. According to the invention, the operation state and risk of the power distribution network can be evaluated in real time in a complex load and fault scene, the defects of data acquisition and processing in the prior art are effectively overcome, and the accuracy and real-time performance of situation awareness are improved.

Description

Technical Field

[0001] This application relates to the technical field of distribution network status, and in particular to a distribution network status perception method and system. Background Technology

[0002] In recent years, with the continuous advancement of phasor measurement units and hybrid measurement technologies, distribution network situational awareness methods have been continuously developing, enabling high-precision real-time monitoring of key parameters such as voltage, current, and phase angle, providing effective support for power grid fault diagnosis and load forecasting. However, despite significant progress in some distribution network situational awareness systems, many problems remain to be solved in practical applications. First, existing technologies often rely on traditional single measurement methods for data acquisition and processing, failing to effectively integrate multi-source data, resulting in insufficient monitoring accuracy and reliability. Furthermore, existing state estimation methods are mostly based on static models, failing to fully consider the dynamic characteristics of the distribution network. Equipment failures, load fluctuations, and dynamic changes make it difficult for distribution networks to quickly and accurately assess their operational status in the face of emergencies, affecting the system's emergency response capabilities. Secondly, existing distribution network risk assessment methods lack comprehensive evaluation of multiple fault scenarios, especially under complex fault modes such as N-1+1, where existing technologies struggle to fully assess the reliability and power supply capacity of the distribution network, thus failing to effectively guarantee the safety and stability of the power grid. Furthermore, the economic efficiency and optimal scheduling of distribution networks are also weak points in existing technologies. Many traditional methods cannot dynamically adjust the power supply capacity and load distribution of the power grid, leading to energy waste and increased operating costs. Summary of the Invention

[0003] In view of the aforementioned existing problems, this application is hereby filed.

[0004] Therefore, this application provides a distribution network situation awareness method and system to solve the problem that the existing distribution network operation situation awareness system is unable to meet the development needs of smart distribution networks in many aspects such as calculation speed and security assessment.

[0005] To solve the above-mentioned technical problems, this application provides the following technical solution:

[0006] In a first aspect, embodiments of this application provide a power distribution network situation awareness method, including:

[0007] Real-time acquisition of distribution network status elements, and assessment of distribution network operating status based on the distribution network status elements;

[0008] Based on real-time data from the power distribution network operation, the load rate of the power equipment is calculated to assess the risk status of the power equipment.

[0009] Using the maximum power capacity of the distribution network as the target, a power supply model of the distribution system is constructed to evaluate the power supply capacity of the distribution system;

[0010] Integrate assessment results to optimize distribution network operation strategies.

[0011] As a preferred embodiment of the power distribution network situation awareness method described in this application, the power distribution network situation elements include voltage, current and phase angle data of each node in the power distribution network.

[0012] As a preferred embodiment of the distribution network situation awareness method described in this application, the method for assessing the operating status of the distribution network based on the distribution network situation elements includes:

[0013] Initialize the voltage value of any node. For each node, calculate the real and imaginary parts of the voltage change based on the impedance between each node and its neighboring nodes, as well as the active and reactive power of the node.

[0014] Update the voltage of the next node based on the calculation results, and determine whether the difference between the node voltage calculated in the current iteration and the result of the previous iteration is less than the preset tolerance error.

[0015] If the difference between the node voltage calculated in the current iteration and the result of the previous iteration is less than the preset tolerance error, then the current node voltage data is obtained and the iteration ends; if the difference between the node voltage calculated in the current iteration and the result of the previous iteration is not less than the preset tolerance error, then the calculation is performed traversally based on the current node voltage value until the error requirement is met.

[0016] When all nodes meet the error requirements, the safety status elements of each node in the distribution network are determined based on the final voltage, current, and phase angle data, and are expressed as follows:

[0017] ;

[0018] ;

[0019] in, For nodes phase angle, It is the arctangent function. For nodes active power, For line impedance, For line resistance, For nodes reactive power, For nodes phase angle, Voltage amplitude, For nodes The current phasor, For nodes voltage amplitude, For nodes The complex power.

[0020] As a preferred embodiment of the power distribution network situational awareness method described in this application, the method for calculating the load rate of power equipment and assessing the overload status of power equipment based on real-time data of the power distribution network operation includes:

[0021] Calculate the load rate of main transformers, distribution transformers and distribution lines based on the power system operating load;

[0022] For each power device, when the current device load exceeds the rated load, record the time the device is in an overload state; if the overload time of any device is not less than a preset threshold, then the device is determined to be overloaded.

[0023] When an overload is detected, the number of overloaded devices is counted and the overload ratio of each device is calculated; the voltage qualification rate is calculated based on the number of overloaded devices and the total number of devices.

[0024] As a preferred embodiment of the distribution network situational awareness method described in this application, the method involves: constructing a power supply model of the distribution system to evaluate its power supply capacity, with the maximum power supply capacity of the distribution network as the objective, including:

[0025] The power supply model of the power distribution system is represented as follows:

[0026] ;

[0027] ;

[0028] in, The maximum load that can be supplied with electricity in the area. For nodes The current actual load, This represents the total number of load nodes. This is the load growth factor. This is a coefficient used to adjust the system's maximum power supply capacity. The value represents the maximum power supply capacity of the power distribution network, when When the variable reaches its maximum value, The value is ;

[0029] The power supply model constraints of the power distribution system include power constraints, node voltage constraints, and capacity constraints of lines and transformers.

[0030] As a preferred embodiment of the power distribution network situational awareness method described in this application, it further includes: calculating the loss rate of a single line and the line loss rate, line load rate, and line light load rate of the power distribution system, and determining the maximum power supply capacity and remaining power supply margin of the power distribution network through repeated power flow calculation method.

[0031] The loss rate of a single line is expressed as:

[0032] ;

[0033] in, This refers to the active power lost in the line. This refers to the active power transmitted at the beginning of the line.

[0034] The line loss rate of a power distribution system is expressed as:

[0035] ;

[0036] in, For load power changes Relative to total power proportion, This represents the active power lost across all lines. The active power transmitted at the beginning of all lines;

[0037] The line load of the power distribution system is represented as follows:

[0038] ;

[0039] in, For any load current With the system's maximum load current The ratio between them;

[0040] The light load rate of the power distribution system is expressed as:

[0041] ;

[0042] in, The number of lines lightly loaded. This represents the total number of lines.

[0043] As a preferred embodiment of the distribution network situational awareness method described in this application, determining the maximum power supply capacity and remaining power supply margin of the distribution network through repeated power flow calculation includes:

[0044] The load growth mode of the distribution network is set according to the operating status of the distribution network, and the critical point of the load growth mode is determined.

[0045] If the critical state quantity will exceed the limit when the load continues to increase at the critical point, then the critical point is the corresponding maximum power supply capacity of the distribution network, and the difference between the maximum power supply capacity and the current supplied load is the remaining power supply margin.

[0046] If a critical state variable exceeds its limit, the reactive power compensation capacity should be reset and the verification performed again.

[0047] Secondly, this application provides a power distribution network situation awareness system, comprising:

[0048] The status assessment module is used to collect distribution network status elements in real time and assess the operating status of the distribution network based on the distribution network status elements.

[0049] The risk assessment module is used to calculate the load rate of power equipment and assess the risk status of the power equipment based on real-time data of power distribution network operation.

[0050] The power supply capacity assessment module is used to construct a power supply model of the distribution system with the maximum power supply capacity of the distribution network as the target to assess the power supply capacity of the distribution system.

[0051] The decision-making module is used to integrate evaluation results to optimize distribution network operation strategies.

[0052] Thirdly, this application provides an electronic device, comprising:

[0053] Memory and processor;

[0054] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the power distribution network situation awareness method are implemented.

[0055] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the power distribution network situational awareness method.

[0056] Compared with existing technologies, the beneficial effects of this application are as follows: This application combines real-time data acquisition, network topology analysis, and multi-layer parallel iterative state estimation methods, enabling real-time assessment of the operating status and risks of the distribution network under complex load and fault scenarios; by employing high-precision data acquisition based on PMU and combining it with hierarchical network topology analysis, this application effectively overcomes the shortcomings of data acquisition and processing in existing technologies, improving the accuracy and real-time performance of situational awareness; in terms of distribution network security and reliability assessment, this application proposes a dynamic assessment method based on N-1+1 fault modes, which can more comprehensively analyze the system's security, especially providing more reliable decision support when facing complex faults; by introducing optimized scheduling and economic assessment, this application can effectively improve the power supply capacity and economy of the distribution network, reduce operating costs, and enhance the overall efficiency and sustainability of the power grid. Attached Figure Description

[0057] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0058] Figure 1 This is a flowchart of a power distribution network situational awareness method according to one embodiment of this application;

[0059] Figure 2 This is a schematic diagram of the process for constructing a distribution network operation status index system according to an embodiment of the distribution network situation awareness method described in this application;

[0060] Figure 3 This is a schematic diagram of the line equivalent circuit model of a power distribution network situational awareness method according to an embodiment of this application;

[0061] Figure 4 This is a schematic diagram of a method for acquiring zero-injection power node situational elements in a distribution network situational awareness method according to an embodiment of this application, wherein... Figure 4 (a) in the diagram is a schematic of the series impedance mode. Figure 4 (b) in the middle is Schematic diagram of a type of branch road. Detailed Implementation

[0062] Example 1, referring to Figures 1-4 This is one embodiment of the present application, which provides a power distribution network situation awareness method, such as... Figure 1 As shown, it includes:

[0063] S100: Real-time acquisition of distribution network status elements, and assessment of distribution network operation status based on distribution network status elements;

[0064] In this embodiment of the application, the power distribution network status elements include voltage, current and phase angle data of each node in the power distribution network.

[0065] In this embodiment of the application, assessing the operating status of the distribution network based on distribution network status elements includes:

[0066] Initialize the voltage value of any node. For each node, calculate the real and imaginary parts of the voltage change based on the impedance between each node and its neighboring nodes, as well as the active and reactive power of the node.

[0067] Update the voltage of the next node based on the calculation results, and determine whether the difference between the node voltage calculated in the current iteration and the result of the previous iteration is less than the preset tolerance error.

[0068] If the difference between the node voltage calculated in the current iteration and the result of the previous iteration is less than the preset tolerance error, then the current node voltage data is obtained and the iteration ends; if the difference between the node voltage calculated in the current iteration and the result of the previous iteration is not less than the preset tolerance error, then the calculation is performed traversally based on the current node voltage value until the error requirement is met.

[0069] When all nodes meet the error requirements, the safety status elements of each node in the distribution network are determined based on the final voltage, current, and phase angle data, and are expressed as follows:

[0070] ;

[0071] ;

[0072] in, For nodes phase angle, It is the arctangent function. For nodes active power, For line impedance, For line resistance, For nodes reactive power, For nodes phase angle, Voltage amplitude, For nodes The current phasor, For nodes voltage amplitude, For nodes The complex power.

[0073] It should be noted that by collecting real-time status elements of the distribution network, such as voltage, current, and power, the most direct data support for the health status of the distribution network can be provided. By estimating the status of these elements, the accurate operating status of the distribution network can be obtained, and potential faults or abnormal fluctuations can be detected in a timely manner. This not only improves the monitoring accuracy of the distribution network, but also provides reliable basic data for subsequent risk assessment, fault location, and emergency response, avoiding the delay problem of traditional monitoring methods that cannot provide real-time feedback.

[0074] In an optional embodiment, such as Figure 3 As shown, voltage, current, and phase angle are collected at measurement points through a phasor measurement unit (PMU), and network topology is layered, dividing the distribution network into bottom, middle, and top layers. Based on the network topology layering results, the load data and PMU measurement results (including voltage, current, and phase angle) of the bottom, middle, and top layers are used as input values ​​for synchronous parallel iteration of the multi-layer network. Real-time measurement data from PMU, including voltage Current and phase angle As a situational element, solving for the first... Real-time measurements of node voltage and current and The security status elements of each node in the entire network are then obtained sequentially. The specific solution steps are as follows:

[0075] To determine the power distribution at each node, the power distribution at each node is determined sequentially from the bottom layer to the top layer using the line's rated voltage.

[0076] ;

[0077] in, This refers to the change in power, specifically calculated based on actual work done. reactive power Standard voltage and network impedance To adjust, For nodes The square of the magnitude of the composite power, where the node Composite power is calculated using the active and reactive power of the node. Represents a node Updated complex power, It is a node The initial complex power, For the adjusted nodes Complex power, and Represents nodes The susceptance parameter between it and its adjacent nodes, The square of the system standard voltage, where It is the matrix number in the susceptance matrix. To represent column indexes, Indicates row index;

[0078] To solve for the voltage at each node of the system, the voltage at the PMU configuration point is used as the starting node voltage and converted to a per-unit value. The voltage drop at each adjacent node is then calculated.

[0079] ;

[0080] in, and Represents a node and nodes Complex voltage, It is the impedance between nodes, where It is a resistor. It is a reactance. It's the phase difference. It is the phase angle. Based on the network topology layering results based on PMU, the line voltage drop of each node is calculated sequentially by the following formula.

[0081] ;

[0082] in, Represents a node The real part of the voltage change, Represents a node The imaginary part of the voltage change, Represents a node active power, Represents a node The reactive power is calculated, the voltage at each node of the system is obtained, and it is determined whether the error ε requirement is met. If it is met, the iteration is terminated.

[0083] ;

[0084] ;

[0085] in, Represents a node The complex voltage contains amplitude and phase information. This represents a small tolerance error, used to judge the convergence accuracy of the voltage calculation, and is compared with the maximum value of the voltage difference;

[0086] Based on the line voltage drop and the voltage of each node, the phase angle and current phasor of each node are calculated, and the real-time safety status elements of each node in the system are obtained in the same way.

[0087] In an optional embodiment, such as Figure 4 As shown, the zero-injection power node in the distribution network is calculated. No current flows into the system through this node. It is assumed that all adjacent nodes of the zero-injection power node can have their operational status elements obtained using the above formula. Based on this, the series impedance mode and π-type branch are explained:

[0088] Assuming node 1 is a zero-injection power node, the state variables of node n0 are derived, and the voltage of node 1 is obtained by combining Kirchhoff's laws.

[0089] ;

[0090] in, Represents a node and nodes Line impedance between Represents a node Phase voltage amplitude, Represents a node The phase voltage amplitude;

[0091] In a π-type branch, nodes are set. For zero-injection power nodes, when the node When configuring nodes for the PMU, the state variables of nodes 2 and 4 can be derived. According to Kirchhoff's laws, = Given the line impedance between node 2 and node 3, the voltage at node 3 can be calculated:

[0092] ;

[0093] in, and This represents the voltage at nodes 2 and 3. This represents the current between node 2 and node 3, and the impedance between node 2 and node 3.

[0094] Set nodes For a node with zero injected power, then , , can be obtained :

[0095] ;

[0096] ;

[0097] in, For nodes and nodes Line impedance between; For nodes and nodes Line impedance between;

[0098] In this embodiment, the power quality operation of the distribution network is evaluated by obtaining the distribution network status, calculating the maximum power supply capacity and margin in real time, using a dynamic threshold setting method, and calculating the zero-injection power node.

[0099] S200: Based on real-time data from power distribution network operation, calculate the load rate of power equipment and assess the risk status of power equipment;

[0100] In this embodiment of the application, calculating the load rate of power equipment and assessing the overload status of power equipment based on real-time data of power distribution network operation includes:

[0101] Calculate the load rate of main transformers, distribution transformers and distribution lines based on the power system operating load;

[0102] For each power device, when the current device load exceeds the rated load, record the time the device is in an overload state; if the overload time of any device is not less than a preset threshold, then the device is determined to be overloaded.

[0103] When an overload is detected, the number of overloaded devices is counted and the overload ratio of each device is calculated; the voltage qualification rate is calculated based on the number of overloaded devices and the total number of devices.

[0104] It should be noted that, as Figure 2 As shown in the embodiment of this application, before calculating the load rate of power equipment to assess the risk status of power equipment, a distribution network operation status index system is also constructed to assess the safety of the distribution network operation process.

[0105] Furthermore, a load factor index is constructed to collect real-time data on the operating status of the distribution network. The system's data update cycle is set to 1 second to track and analyze load changes in the power system in real time, and to calculate the load factor of the main transformers, distribution transformers, and distribution lines.

[0106] The system calculates the overload time of the equipment. If the load of a certain equipment exceeds its rated load, the system will recalculate the time that the equipment is in an overload state. If the overload time reaches or exceeds the threshold, the equipment is considered to be overloaded. The threshold is initially set.

[0107] When the system detects that the device is overloaded, it begins to count the number of overloaded devices.

[0108] For each device, the system will further calculate its overload ratio;

[0109] Based on the number of overloaded devices and the total equipment assessment, calculate the voltage compliance rate and perform K-verification.

[0110] Specifically, it is an N-1+1 verification, which means that after the studied equipment is removed, another equipment is put in to restore the load of the non-faulty area. K is an arbitrary scheme. This time, under the N-1+1 criterion, the load rate and voltage qualification rate indicators are calculated.

[0111] It should be noted that, in the embodiments of this application, a series of innovative steps, including real-time load rate calculation, overload time monitoring, heavy load ratio calculation, voltage qualification rate assessment, and N-1+1 verification, effectively improve the operating efficiency, reliability, and safety of the distribution network. Compared with existing technologies, this application can respond to load changes in real time, promptly identify overloaded equipment, and provide more accurate fault warnings and emergency responses when equipment fails or load fluctuates. This not only ensures the stable operation of the distribution network but also greatly improves power quality and equipment lifespan, laying the foundation for intelligent management of the distribution network.

[0112] Furthermore, power supply reliability and economic indicators for the distribution network are set to evaluate the power supply capacity of the distribution system.

[0113] S300: Using the maximum power capacity of the distribution network as the target, construct a power supply model for the distribution system to evaluate the power supply capacity of the distribution system;

[0114] In this embodiment of the application, the evaluation of the power supply capacity of the distribution system by constructing a power supply model based on the maximum power capacity of the distribution network includes:

[0115] The power supply model of the power distribution system is represented as follows:

[0116] ;

[0117] ;

[0118] in, The maximum load that can be supplied with electricity in the area. For nodes The current actual load, This represents the total number of load nodes. This is the load growth factor. This is a coefficient used to adjust the system's maximum power supply capacity. The value represents the maximum power supply capacity of the power distribution network, when When the variable reaches its maximum value, The value is ;

[0119] The power supply model constraints of the power distribution system include power constraints, node voltage constraints, and capacity constraints of lines and transformers.

[0120] Furthermore, calculate the utilization rate of the system's power supply capacity:

[0121] ;

[0122] ;

[0123] in, The actual load carried by the system The power factor of the system For composite power, To improve the utilization rate of system power supply capacity, The reasonable range also varies, when At that time, the system power supply capacity utilization rate is considered to be the ideal utilization rate. If the annual load fluctuation in the region is large, the system power supply capacity utilization rate should be reduced to the ideal rate. When the system power supply capacity utilization rate of the area is considered to be relatively ideal;

[0124] Let the system be the first The power supply capacity of the device is When the system reaches its maximum power supply capacity, all devices will be under maximum load. At this time, the total load of the system is... , No. The power supply capacity of the device is Its power supply capacity utilization rate is calculated using the following formula:

[0125] ;

[0126] in, Total power supply capacity for all devices in the system;

[0127] In this embodiment, the stability, reliability, and economy of the distribution network are significantly improved through real-time load rate monitoring, power factor optimization, power supply capacity assessment, application of the N-1+1 criterion, and equipment overload time management. Compared with the prior art, this application can perform real-time scheduling under grid load fluctuations and equipment failures, reduce the probability of failures, optimize resource utilization, and improve the overall efficiency of the grid. Through real-time voltage qualification rate calculation and equipment overload time monitoring, it provides strong support for the intelligent management of the grid.

[0128] In this embodiment of the application, it further includes: calculating the loss rate of a single line and the line loss rate, line load rate, and line light load rate of the power distribution system, and determining the maximum power supply capacity and remaining power supply margin of the power distribution network through a repetitive power flow calculation method.

[0129] The loss rate of a single line is expressed as:

[0130] ;

[0131] in, This refers to the active power lost in the line. This refers to the active power transmitted at the beginning of the line.

[0132] The line loss rate of a power distribution system is expressed as:

[0133] ;

[0134] in, For load power changes Relative to total power proportion, This represents the active power lost across all lines. The active power transmitted at the beginning of all lines;

[0135] The actual current of the line is 20-50% of the rated current. Due to defects in energy transfer to the load, the operating condition is flawed. The line load of the power distribution system is represented as follows:

[0136] ;

[0137] in, For any load current With the system's maximum load current The ratio between them;

[0138] The light load rate of the power distribution system is expressed as:

[0139] ;

[0140] in, The number of lines lightly loaded. This represents the total number of lines.

[0141] It should be noted that a higher light load rate indicates more lightly loaded lines, which is used to calculate the power supply capacity of the distribution network.

[0142] In this embodiment of the application, determining the maximum power supply capacity and remaining power supply margin of the distribution network through repeated power flow calculation includes:

[0143] The load growth mode of the distribution network is set according to the operating status of the distribution network, and the critical point of the load growth mode is determined.

[0144] If the critical state quantity will exceed the limit when the load continues to increase at the critical point, then the critical point is the corresponding maximum power supply capacity of the distribution network, and the difference between the maximum power supply capacity and the current supplied load is the remaining power supply margin.

[0145] If a critical state variable exceeds its limit, the reactive power compensation capacity should be reset and the verification performed again.

[0146] In an optional embodiment, the power supply capacity of the distribution network is evaluated. Under a given operating mode and load growth pattern, a critical point is determined. At this critical point, a critical state quantity will exceed its limit when the load increases slightly. This critical point corresponds to the maximum power supply capacity of the distribution network. The difference between the maximum power supply capacity and the currently supplied load is the remaining power supply margin. A repetitive power flow calculation method is adopted to evaluate the power supply capacity of the distribution network in real time.

[0147] Starting from the current running point, select a step size h;

[0148] By continuously increasing the load according to a certain load growth pattern, the power flow solution can be obtained.

[0149] Until a limit is exceeded;

[0150] The step size h is continuously adjusted until any preset precision is met;

[0151] The load corresponding to the critical point where the limit is about to be exceeded is the maximum load that the distribution network can supply under the current operating mode.

[0152] Among them, the load growth factor is used in the process of obtaining the power flow solution. The step size h is selected as follows:

[0153] The search proceeds step by step using an automatic variable step size method. If no limit is exceeded, the search continues with the original step size.

[0154] If the limit is exceeded, the step size is halved;

[0155] The above process is repeated until the step size is reduced to meet the required accuracy.

[0156] The specific steps are as follows:

[0157] a1: Determine the initial search step size h>0 and the convergence accuracy. >0;

[0158] a2: Determine the load growth pattern ,make Equal to the current actual load , = , = ;

[0159] a3: If > If h < The calculation ends and returns. and , This refers to the maximum load that the distribution network can supply under the current operating mode. - This refers to the remaining power supply margin. This is the power supply multiple;

[0160] a4: Calculation ;

[0161] a5: with Perform power flow calculations based on the baseline to determine if any limit violations have occurred. If no limit violations have occurred, proceed to the next step; otherwise, go to step a7.

[0162] a6: Let S = S', then proceed to step a4;

[0163] a7: Reduce the step size to half of the original, i.e., h = h / 2, then go to step a3;

[0164] Therefore, the maximum power supply capacity of the system is evaluated in real time based on repetitive power flow calculation;

[0165] In this embodiment, innovative steps such as precise line loss rate calculation, dynamic assessment of load power changes, calculation of line light load rate, real-time assessment of maximum power supply capacity, and step size adjustment are introduced to effectively improve the operating efficiency, stability, and reliability of the distribution network. Compared to traditional power systems, this application can monitor the operating status of the power grid in real time, flexibly respond to load fluctuations and equipment failures, optimize resource allocation, and reduce energy waste. Through precise critical point calculation and power supply capacity assessment, the system can ensure the safe and stable operation of the power grid under high load conditions.

[0166] In an optional embodiment, the power supply capacity of line N-1+1 is evaluated in real time based on the operating status of the distribution network. The implementation steps include:

[0167] The N-1 simulation verification method is used to verify whether the power grid can continue to supply power safely when a component fails under a given load level.

[0168] Considering the K(N-1+1) criterion for lines, the maximum power supply capacity is evaluated for each N-1+1 case. Based on the simulation results, the maximum power supply capacity under different power transfer schemes is obtained, providing auxiliary decision-making for line power transfer.

[0169] Based on the system voltage without reactive power compensation, reactive power compensation is added to some nodes;

[0170] Observe the voltage at the end of each feeder and compare it with the voltage at the end without N-1+1 verification to see if the voltage exceeds the limit.

[0171] If it exists, reset the reactive power compensation capacity to fully compensate for the reactive power of the system, and then perform the verification again.

[0172] Assess the power supply capacity of the distribution network based on the observation results;

[0173] In this embodiment, N-1 simulation verification is a key method for evaluating the power grid after a single equipment failure. It ensures that after equipment failure, the distribution network can maintain stable operation by activating backup equipment or adjusting loads. This step can promptly identify potential weaknesses or fault points in the power grid, providing data support regarding system recovery capabilities. In power grid management, N-1 simulation verification not only improves the grid's fault tolerance but also provides decision-making basis for maintenance and spare parts management, ensuring high reliability and security of the power grid. The line K(N-1+1) criterion plays an important role in power grid failures, enabling the evaluation of the effectiveness of backup equipment activation and load dispatching after equipment failure based on simulation results. Through maximum power supply capacity assessment, it can provide power grid... This application provides guidance for grid load management, ensuring a smooth transition of the distribution network during equipment failures and avoiding power outages. The assessment process helps provide data support for grid load dispatching and equipment redundancy configuration, further optimizing grid operation strategies. Reactive power compensation is a crucial means in power systems to maintain voltage stability and improve power supply capacity. Insufficient reactive power leads to voltage drops, affecting grid operating efficiency. By adding reactive power compensation at certain nodes, this application can rapidly adjust voltage during grid faults or load fluctuations, ensuring that the distribution network voltage remains within the standard range. Especially under heavy loads or equipment failures, appropriate reactive power compensation not only stabilizes voltage but also improves the overall operating efficiency of the grid. Compared with traditional methods, this application... By accurately calculating the reactive power compensation capacity, over- or under-compensation is avoided, ensuring the stability of the power grid during load fluctuations and equipment failures. Terminal voltage is a crucial indicator in power grid operation, directly impacting the power quality for end users. This application, through real-time monitoring of the terminal voltage of each feeder and comparison with the voltage before N-1+1 verification, can quickly identify the risk of voltage exceeding limits. By adjusting reactive power compensation and resetting the compensation capacity, the voltage level of the power grid can be effectively optimized, ensuring that the terminal voltage remains stable within a reasonable range. This method effectively improves the power quality of the power grid and reduces equipment damage or power outages caused by voltage instability. The implementation steps of this application employ a dynamic load growth model and utilize repeated power flow metering. The system calculates the maximum power supply capacity of the distribution network in real time. When a slight increase in load causes critical state quantities to exceed limits, the system can accurately determine the maximum power supply capacity of the grid and calculate the power supply margin. Compared with traditional static calculation methods, this method is more adaptable to dynamic changes in the load in the grid, ensuring that the grid can cope with uncertainties such as load fluctuations and equipment failures in actual operation. By assessing the maximum power supply capacity in real time, grid operators can adjust load distribution and optimize power supply capacity in a timely manner, improving the system's emergency response speed. The repetitive power flow calculation uses a dynamic adjustment step size for load forecasting, and automatically adjusts the step size during load changes, thereby avoiding overly coarse calculations. This process can accurately capture subtle changes when the grid load increases.It also promptly detects potential overload issues in the power grid, and the automatic adjustment of the step size makes load forecasting more accurate, effectively avoiding the problems of insufficient accuracy or excessive computation in traditional methods, thus greatly improving the efficiency and accuracy of calculations.

[0174] By introducing innovative technologies such as N-1 simulation verification, line K(N-1+1) criterion, reactive power compensation, and repetitive power flow calculation, the power supply capacity, stability, and reliability of the distribution network are significantly improved. Compared with traditional technologies, this application can more efficiently cope with load fluctuations, equipment failures, and voltage instability in the power grid, ensuring the safe and stable operation of the power grid under various conditions. Through precise reactive power compensation, end-point voltage monitoring, and real-time power supply capacity assessment, the operating efficiency and power quality of the power grid are optimized, further enhancing the intelligent management capabilities of the power grid.

[0175] S400: Integrate assessment results to optimize distribution network operation strategies.

[0176] Furthermore, in this embodiment, the PMU is used to collect voltage, current and phase angle data in the power grid in real time, and the power grid is divided into different levels through network topology layering, which can more accurately estimate the state of the distribution network. Traditional distribution network monitoring technology usually relies on static data acquisition and analysis methods and lacks dynamic response capabilities. However, through layered topology analysis, targeted calculations can be performed according to the characteristics of nodes at different levels, which improves the accuracy and real-time performance of data analysis and enhances the adaptability to the operating state of the distribution network.

[0177] Furthermore, in this embodiment, by inputting the load data and PMU measurement results after network topology layering into the synchronous and parallel iterative process of the multi-layer network, the real-time status of each node in the distribution network can be calculated quickly and efficiently. This not only improves the accuracy of the calculation but also greatly increases the calculation speed. Compared with the traditional step-by-step calculation method, it can respond quickly to complex power grid operating conditions. Through this iterative method, the dynamic balance of key parameters such as power flow, voltage, current, and phase angle between each node in the distribution network can be guaranteed, ensuring the stable operation of the system. By calculating the power of each node in the distribution network layer by layer based on the line rated voltage and network impedance, this application can accurately determine the power distribution of each node, avoiding the uneven power distribution problem that may occur in traditional methods. Especially when the power grid load changes significantly, this application can effectively adjust the load of each part of the power grid through this refined power distribution method, ensuring the power balance of the power grid and the stable operation of equipment. By using the PMU configuration point voltage as the starting point and converting it to per-unit value, the voltage and voltage drop process of each node are calculated one by one. Traditional power grid calculation methods are often relatively simple in dealing with voltage drops between nodes and cannot accurately reflect the power grid. In contrast, this application, by accurately calculating the voltage drop and voltage change at each node, effectively avoids grid instability caused by voltage instability and enhances the grid's voltage control capability. The calculation of node phase angles and current phasors is a crucial step in distribution network state estimation, accurately reflecting the direction and magnitude of power flow in the power system. In this application, by calculating the phase angles and current phasors of each node in real time, comprehensive security situation elements of the distribution network can be obtained. This enables the system to quickly respond to emergencies such as load fluctuations and equipment failures, and to perform real-time monitoring and evaluation of system security, compared to traditional methods. This application provides higher precision power grid situational awareness, significantly improving the reliability of power grid operation. In the calculation of zero-injection power nodes, this application utilizes the susceptance and conductance parameters between nodes, combined with Kirchhoff's laws, to ensure that the impact of zero-injection nodes on the overall distribution network status is accurately estimated. This innovative method can help identify potential critical nodes in the distribution network and promptly discover vulnerabilities in the system. Through dynamic evaluation of these nodes, the power quality operation efficiency of the distribution network can be effectively improved, avoiding the neglect of critical nodes in traditional methods, thereby improving the stability and power supply capacity of the power grid.

[0178] Example 2: This example is an illustrative scheme of a distribution network situational awareness method. It should be noted that the technical solution of this distribution network situational awareness system belongs to the same concept as the technical solution of the aforementioned distribution network situational awareness method. Details not described in detail in this example can be found in the description of the technical solution of the aforementioned distribution network situational awareness method.

[0179] In this embodiment, the power distribution network situation awareness system includes:

[0180] The status assessment module is used to collect distribution network status elements in real time and assess the operating status of the distribution network based on the distribution network status elements.

[0181] The risk assessment module is used to calculate the load rate of power equipment and assess the risk status of power equipment based on real-time data of power distribution network operation.

[0182] The power supply capacity assessment module is used to construct a power supply model of the distribution system with the maximum power supply capacity of the distribution network as the target to assess the power supply capacity of the distribution system.

[0183] The decision-making module is used to integrate evaluation results to optimize distribution network operation strategies.

[0184] In an optional embodiment, the decision module is also used to display information such as the real-time status, power supply capacity, and risk assessment of the distribution network, and to provide a graphical interface for users to view it; to provide decision support based on real-time data and assessment results, to optimize the dispatching scheme of the distribution network, and to assist the emergency response of the distribution network.

[0185] This embodiment also provides a computing device applicable to the distribution network situation awareness method, including:

[0186] The system includes a memory and a processor. The memory stores computer-executable instructions, and the processor executes these instructions to implement the power distribution network situation awareness method proposed in the above embodiments.

[0187] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the power distribution network situation awareness method as proposed in the above embodiments.

[0188] The storage medium proposed in this embodiment belongs to the same inventive concept as the distribution network situation awareness method proposed in the above embodiments. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0189] Based on the above description of the implementation methods, those skilled in the art can clearly understand that this application can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0190] It should be noted that the above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it. Although this application has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of this application without departing from the spirit and scope of the technical solutions of this application, and all such modifications and substitutions should be covered within the scope of the claims of this application.

Claims

1. A power distribution grid situation awareness method, characterized in that, The method comprises: real-time acquisition of power distribution network situation elements, evaluation of power distribution network operation state based on the power distribution network situation elements; calculation of power equipment load rate based on real-time data of power distribution network operation to evaluate the risk state of the power equipment; construction of a power distribution system power supply model to evaluate the power supply capacity of the power distribution system with the maximum power supply capacity of the power distribution network as the target; integration of the evaluation results to optimize the operation strategy of the power distribution network.

2. The power distribution grid situation awareness method of claim 1, wherein: The power distribution network situation elements include voltage, current and phase angle data of each node of the power distribution network.

3. The power distribution grid situation awareness method of claim 2, wherein, The evaluation of the power distribution network operation state based on the power distribution network situation elements comprises: initialization of voltage value of any node, for each node, calculation of real part and imaginary part of voltage change according to impedance between each node and adjacent node and active power and reactive power of the node; updating of voltage of the next node according to the calculation result, judgment of whether the difference between the node voltage obtained by the current iteration calculation and the previous iteration result is less than a preset tolerance error; if the difference between the node voltage obtained by the current iteration calculation and the previous iteration result is less than the preset tolerance error, the current node voltage data is obtained and the iteration is ended; if the difference between the node voltage obtained by the current iteration calculation and the previous iteration result is not less than the preset tolerance error, the current node voltage value is used for traversal calculation until the error requirement is met; when all nodes meet the error requirement, the safety situation elements of each node of the power distribution network are determined based on the final voltage, current and phase angle data, which are represented as: ； ； wherein is the phase angle of the node , is the arctangent function, is the active power of the node , is the line impedance, is the line resistance, is the reactive power of the node , is the phase angle of the node , is the voltage magnitude, is the current phasor of the node , is the voltage magnitude of the node , is the complex power of the node .

4. The power distribution grid situation awareness method of claim 3, wherein, The evaluation of the overload state of the power equipment based on the real-time data of the power distribution network operation comprises: calculation of load rate of main transformer, power distribution transformer and power distribution line based on power system operation load; for each power equipment, when the current equipment load exceeds the rated load, the time when the current equipment is in an overload state is recorded; if the overload time of any equipment is not less than a preset threshold, it is determined that the equipment is in an overload state; when it is detected that the equipment is in an overload state, the number of overloaded equipment is counted and the overload ratio of each equipment is calculated; the voltage qualification rate is calculated according to the number of overloaded equipment and the total number of equipment.

5. The power distribution grid situation awareness method of claim 4, wherein, The construction of the power distribution system power supply model to evaluate the power supply capacity of the power distribution system with the maximum power supply capacity of the power distribution network as the target comprises: The power distribution system power supply model is represented as: ； ； wherein, is the maximum load available in the area, is the node current actual load, is the total number of load nodes, is the load growth factor, is the coefficient for adjusting the maximum power supply capacity of the system, value represents the maximum power supply capacity of the power distribution network, when reaches the maximum value, the value of the variable is ; The constraints of the power distribution system power supply model include power constraint, node voltage constraint and capacity constraint of line and transformer.

6. The power distribution grid situation awareness method of claim 5, wherein, The method further comprises: calculation of single line loss rate, line loss rate, line load rate and line light load rate of the power distribution system, and determination of the maximum power supply capacity and the remaining power supply margin of the power distribution network through repeated power flow calculation method; The single line loss rate is represented as: ； wherein, Pline is the active power of the line loss, Pline is the active power of the line loss, The line loss rate of the power distribution system is represented as: ； wherein, is the change in load power relative to the total power of the proportion, is the active power of all line losses, is the active power of all line head transmissions; The line load of the power distribution system is represented as: ； wherein, is the ratio between the system maximum load current and the system minimum load current ; The line light load rate of the power distribution system is represented as: ； wherein, is the number of lines that are lightly loaded, is the total number of lines.

7. The power distribution grid situation awareness method of claim 6, wherein, The determination of the maximum power supply capacity and the remaining power supply margin of the power distribution network through the repeated power flow calculation method comprises: setting of power distribution network load growth mode according to the power distribution network operation state, and finding of critical point of the load growth mode; If the critical point is the maximum power supply capacity of the power distribution network, the difference between the maximum power supply capacity and the current supplied load is the remaining power supply margin. If the critical point is the maximum power supply capacity of the power distribution network, the difference between the maximum power supply capacity and the current supplied load is the remaining power supply margin.

8. A power distribution grid situation awareness system applying the power distribution grid situation awareness method of any one of claims 1-7. The method comprises the following steps: A state evaluation module is configured to collect power distribution network state elements in real time and evaluate the operation state of the power distribution network based on the power distribution network state elements. A risk evaluation module is configured to calculate the risk state of the power equipment based on power distribution network operation real-time data. A power supply capacity evaluation module is configured to take the maximum power source capacity of the power distribution network as a target, construct a power supply model of the power distribution system, and evaluate the power supply capacity of the power distribution system. A decision module is configured to integrate the evaluation results to optimize the operation strategy of the power distribution network.

9. An electronic device, comprising: a memory and a processor; The memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions, which realize the steps of the power distribution network situation awareness method according to any one of claims 1 to 7 when executed by the processor.

10. A computer readable storage medium storing computer executable instructions, which realize the steps of the power distribution network situation awareness method according to any one of claims 1 to 7 when executed by the processor.

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