Detection Method, Device and Computer Equipment for Harmonic Oscillation in Power System

Abstract

The present application relates to a detection method, device and computer equipment for harmonic oscillation in a power system. By based on the voltage values of each power equipment with a connection relationship in the network structure of the power system to be detected and determining the electrical distance between the power equipment, according to the power transmission capacity of the connection edge and the rated capacity of the power system to be detected, determining the first weight corresponding to the connection edge, based on the power transmission capacity of each power equipment and the rated capacity of the power system to be detected to determine the second weight corresponding to each power equipment, according to the above weights, network structure coefficient, power parameter offset, electrical distance and preset component parameter coefficient, determining the harmonic oscillation risk value of the power system to be detected. Compared with the traditional method of detecting harmonic oscillation based on the admittance matrix, this solution determines the harmonic oscillation risk based on the weights and electrical distances of each node and connection edge in the network structure by constructing the network structure of the power system, improving the applicability of detecting the harmonic oscillation risk.

Description

Technical Field

[0001] The present application relates to the technical field of electric power, and in particular, to a method, device, computer device, storage medium, and computer program product for detecting harmonic oscillations in a power system. Background Art

[0002] With a large number of power electronic devices being connected to the system, including renewable energy sources such as wind power and photovoltaic power on the power supply side, a large number of conventional and flexible direct currents on the transmission grid side, and various power electronic loads on the load side, the harmonic characteristics of the AC-DC system have become increasingly complex. The harmonic problems faced in the safe and stable operation of the power grid have changed from mainly solving the problem of excessive harmonic content in the low-voltage side in the past to the problem of excessive harmonic current or even resonance amplification that needs to be faced on both the high-voltage and low-voltage sides. Therefore, it is necessary to detect the harmonic oscillation information in the power system. Currently, the method for detecting harmonic oscillations in the power system is usually carried out through the nodal admittance matrix. However, the detection of harmonic oscillations based on the nodal admittance matrix belongs to local sensitivity analysis and has insufficient applicability to the DC-fed AC network.

[0003] Therefore, the current method for detecting harmonic oscillations in the power system has the defect of insufficient detection applicability. Summary of the Invention

[0004] Based on this, in view of the above technical problems, it is necessary to provide a method, device, computer device, computer-readable storage medium, and computer program product for detecting harmonic oscillations in a power system that can improve the detection applicability.

[0005] In a first aspect, the present application provides a method for detecting harmonic oscillations in a power system, the method comprising:

[0006] Obtaining the network structure of the power system to be detected; the network structure includes a plurality of power devices included in the power system and the connection relationships between the power devices;

[0007] Determining the connection edges included in each connection relationship according to the connection relationships of the power devices, and determining the electrical distances between the power devices according to the voltage values of the power devices with existing connection relationships and the energy loss values corresponding to the connection edges;

[0008] Determining a first weight corresponding to the connection edge according to the power transmission capacity corresponding to the connection edge and the rated capacity of the power system to be detected, and determining a second weight corresponding to each power device based on the power transmission capacity corresponding to each power device and the rated capacity of the power system to be detected;

[0009] Determine the harmonic oscillation risk value of the power system to be detected according to the first weight, the second weight, the network structure coefficient corresponding to the network structure, the power parameter offset between the power devices, the electrical distance between the power devices, and the preset component parameter coefficient.

[0010] In one embodiment, the obtaining the network structure of the power system to be detected includes:

[0011] Obtain a plurality of power devices included in the power system with DC feeding into AC to be detected and the connection relationship between the power devices to obtain the network structure of the power system to be detected.

[0012] In one embodiment, the determining the electrical distance between the power devices according to the voltage values of the power devices with connection relationships and the energy loss value corresponding to the connection edge includes:

[0013] Obtain multiple groups of power devices with connection relationships among the power devices;

[0014] For each group of power devices, obtain the number of connection edges corresponding to the group of power devices, determine the voltage transmission loss value and the power transmission loss value between the power devices in the group according to the number of connection edges, and obtain the electrical distance between the power devices in the group according to the ratio of the square of the voltage transmission loss value to the power transmission loss value.

[0015] In one embodiment, the determining the first weight corresponding to the connection edge according to the power transmission capacity corresponding to the connection edge and the rated capacity of the power system to be detected includes:

[0016] Obtain the rated capacity corresponding to the connection edge and the power transmission loss value between the power devices connected by the connection edge;

[0017] Obtain the power transmission capacity corresponding to the connection edge according to the difference between the sum of the rated capacities of the connection edges included between the power devices and the absolute value of the power transmission loss value;

[0018] Determine the first weight corresponding to the connection edge according to the ratio of the power transmission capacity to the rated capacity of the power system to be detected.

[0019] In one embodiment, the determining the second weight corresponding to each power device based on the power transmission capacity corresponding to each power device and the rated capacity of the power system to be detected includes:

[0020] Obtain the connection edges corresponding to the power devices with connection relationships in the power system to be detected;

[0021] For each power device, obtain the power transmission capacity corresponding to the target connection edge with the power device as the sender;

[0022] Determine the second weight corresponding to the power device according to the ratio of the sum of the power transmission capacities corresponding to the multiple target connection edges to the rated capacity of the power system to be detected.

[0023] In one embodiment, the determining the harmonic oscillation risk value of the power system to be detected according to the first weight corresponding to the connection edge, the second weight corresponding to each power device, the network structure coefficient corresponding to the network structure, the power parameter offset between each power device, the electrical distance between each power device, and the preset element parameter coefficient includes:

[0024] Obtain the node voltage offset corresponding to the power device and the branch current offset corresponding to the connection edge as the power parameter offset between the power devices;

[0025] Obtain the first ratio of the electrical distance between each power device to the maximum electrical distance among the electrical distances, and obtain the first weight corresponding to the connection edge included between each power device and the branch current offset corresponding to the connection edge included between each power device;

[0026] Obtain the sum of the first products of the first ratio, the first weight, and the branch current offset corresponding to the connection edge included in each power device, and obtain the product of the sum of the first products and the preset element parameter coefficient to obtain the first harmonic oscillation value corresponding to the power system to be detected;

[0027] Obtain the network structure coefficient according to the difference between 1 and the preset element parameter coefficient;

[0028] Obtain the second weight corresponding to each power device, and obtain the sum of the second products of the second ratio of each second weight to the maximum second weight in the power system and the node voltage offset corresponding to each power device, and obtain the product of the sum of the second products and the network structure coefficient corresponding to the network structure to obtain the second harmonic oscillation value corresponding to the power system to be detected;

[0029] Determine the harmonic oscillation risk value of the power system to be detected according to the sum of the first harmonic oscillation value and the second harmonic oscillation value.

[0030] In one embodiment, after determining the harmonic oscillation risk value of the power system to be detected, it further includes:

[0031] Obtain the harmonic oscillation risk values respectively corresponding to the power system to be detected under different network structure coefficients and different preset element parameter coefficients to obtain a plurality of harmonic oscillation risk values;

[0032] Obtain the target network structure coefficient and the target preset component parameter coefficient corresponding to the maximum harmonic oscillation risk value among the multiple harmonic oscillation risk values, determine the network structure corresponding to the target network structure coefficient as the high-risk network structure, and use the preset component parameters corresponding to the target preset component parameter coefficient as the high-risk component parameters and output them.

[0033] In a second aspect, the present application provides a detection device for harmonic oscillation in a power system. The device includes:

[0034] An acquisition module, configured to acquire the network structure of the power system to be detected; the network structure includes a plurality of power devices included in the power system and the connection relationships between the power devices;

[0035] A first determination module, configured to determine the connection edges included in each connection relationship according to the connection relationships of the power devices, and determine the electrical distances between the power devices according to the voltage values of the power devices with existing connection relationships and the energy loss values corresponding to the connection edges;

[0036] A second determination module, configured to determine the first weight corresponding to the connection edge according to the power transmission capacity corresponding to the connection edge and the rated capacity of the power system to be detected, and determine the second weight corresponding to each power device based on the power transmission capacity corresponding to each power device and the rated capacity of the power system to be detected;

[0037] A detection module, configured to determine the harmonic oscillation risk value of the power system to be detected according to the first weight, the second weight, the network structure coefficient corresponding to the network structure, the power parameter offset between the power devices, the electrical distances between the power devices, and the preset component parameter coefficient.

[0038] In a third aspect, the present application provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the above method are implemented.

[0039] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are implemented.

[0040] In a fifth aspect, the present application provides a computer program product, including a computer program. When the computer program is executed by a processor, the steps of the above method are implemented.

[0041] The above detection method, device, computer equipment, storage medium and computer program product for power system harmonic oscillation determine the connection edges included in each connection relationship based on the connection relationships of each power equipment in the network structure of the power system to be detected, determine the electrical distance between each power equipment according to the voltage values of the power equipment with existing connection relationships and the energy loss value corresponding to the connection edge, determine the first weight corresponding to the connection edge according to the power transmission capacity corresponding to the connection edge and the rated capacity of the power system to be detected, determine the second weight corresponding to each power equipment based on the power transmission capacity corresponding to each power equipment and the rated capacity of the power system to be detected, and determine the harmonic oscillation risk value of the power system to be detected according to the above first weight, second weight, network structure coefficient, power parameter offset, electrical distance and preset component parameter coefficient. Compared with the traditional method of detecting harmonic oscillation based on the nodal admittance matrix, this solution constructs the network structure of the power system and determines the harmonic oscillation risk based on the weights and electrical distances of each node and connection edge in the network structure, improving the applicability of detecting harmonic oscillation risk. Brief Description of the Drawings

[0042] Figure 1 It is an application environment diagram of the detection method for power system harmonic oscillation in an embodiment;

[0043] Figure 2 It is a schematic flowchart of the detection method for power system harmonic oscillation in an embodiment;

[0044] Figure 3 It is a schematic flowchart of the detection method for power system harmonic oscillation in another embodiment;

[0045] Figure 4 It is a structural block diagram of the detection device for power system harmonic oscillation in an embodiment;

[0046] Figure 5 It is an internal structure diagram of computer equipment in an embodiment. Detailed Description of the Embodiments

[0047] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0048] The detection method for power system harmonic oscillation provided by the embodiments of the present application can be applied to, for example Figure 1In the application environment shown. Among them, the terminal 102 communicates with the power system 104 through the network. The power system 104 may include multiple power devices, and there are corresponding connection relationships among the power devices. The terminal 102 can generate a network structure model corresponding to the power system 104 based on the structure of the power system 104, determine the weights of each power device and connection relationship in the model, and determine the harmonic oscillation risk value based on the weights. Among them, the terminal 102 can be, but is not limited to, various personal computers, laptop computers, smart phones, and tablet computers.

[0049] In one embodiment, as Figure 2 shown, a method for detecting harmonic oscillation of a power system is provided. Taking the terminal in Figure 1 as an example, the method includes the following steps:

[0050] Step S202, obtain the network structure of the power system to be detected; the network structure includes multiple power devices included in the power system and the connection relationships among the power devices.

[0051] Among them, the power system to be detected can be a power system for which the harmonic oscillation risk value needs to be determined. The power system can be a DC-fed AC system; harmonics are generated by non-linear devices, and during the propagation in the power network, harmonic amplification and resonance phenomena often occur due to the matching of network element parameters and harmonic source parameters. The harmonic oscillations occurring in the above power system can be divided into two types, namely, the DC system causes the AC network to oscillate, that is, local oscillation; the AC network itself oscillates, that is, non-local oscillation. When detecting the harmonic oscillation risk of the power system to be detected, the terminal can obtain the network structure of the power system to be detected, where the network structure includes multiple power devices included in the power system and the connection relationships among the power devices. The terminal 102 can build an equivalent AC network model according to the network structure. For example, the terminal 102 divides the above power system to be detected accordingly to form multiple equivalent devices, and uses each equivalent power device and its connection relationship as the network structure of the power system to be detected, and constructs an equivalent AC network model.

[0052] Among them, the power system to be detected can be a DC-fed AC power system, and what the terminal 102 obtains can be the network structure of the DC-fed AC power system to be detected. For example, in one embodiment, obtaining the network structure of the power system to be detected includes: obtaining a plurality of power devices included in the DC-fed AC power system to be detected and the connection relationships between the power devices, so as to obtain the network structure of the power system to be detected. In this embodiment, the terminal can obtain a plurality of power devices included in the DC-fed AC power system to be detected in an actual project and the connection relationships between the power devices, so as to obtain the network structure of the power system to be detected. Among them, the network structure of the power system to be detected can be an equivalent AC network model, which includes various equivalent power devices in the power system to be detected and the connection relationships between the various equivalent power devices. The terminal can detect the harmonic oscillation risk of the power system to be detected in a simulation manner based on the network structure of the power system to be detected.

[0053] Step S204: Determine the connection edges included in each connection relationship according to the connection relationships of the power devices, and determine the electrical distances between the power devices according to the voltage values of the power devices with existing connection relationships and the energy loss values corresponding to the connection edges.

[0054] Among them, the network structure includes the connection relationships of the power devices in the power system to be detected. The connection relationship represents that there is a power transmission relationship between two power devices. The terminal 102 can represent the connection relationship between the power devices in the network structure in the form of connection edges. The connection edges can include information such as the power transmission direction and the power transmission capacity of the connection edge. And there can be at least one connection edge between two power devices with a connection relationship. For example, if there is a connection relationship between two power devices through multiple other power devices, the connection edges corresponding to these two power devices are all the connection edges included between these two devices. Each power device in the network structure can be regarded as a node, and each power device can also include a voltage value. After the terminal 102 determines the connection edges included in each connection relationship according to the connection relationships of the power devices, it can determine the electrical distances between the power devices according to the voltage values of the power devices with existing connection relationships and the energy loss values corresponding to the connection edges. The energy loss value represents the energy lost when the power device transmits power to another power device through the connection edge. The electrical distance represents the electrical coupling degree between the nodes. Its meaning is that the number of edges passed from node i to node j is the distance from node i to node j. Specifically, the above connection relationship can also be called a generalized branch. When there is a power transmission relationship between node i and node j, it is considered that there is a branch between the two nodes. The terminal 102 can determine the electrical distances between the power device nodes based on the impedance of the generalized branch.

[0055] Step S206: Determine the first weight corresponding to the connection edge based on the power transmission capacity corresponding to the connection edge and the rated capacity of the power system to be detected, and determine the second weight corresponding to each power device based on the power transmission capacity corresponding to each power device and the rated capacity of the power system to be detected.

[0056] Among them, the above-mentioned power system has a corresponding rated capacity, which can be the preset rated capacity of the entire power grid. The terminal 102 determines the weights of each power device and each connection edge in the network structure corresponding to the above-mentioned power system to be detected, and forms a weighted network model. By weighting the above-mentioned power system to be detected, the terminal 102 indicates the influence of each node and edge in the system in the entire system. The terminal 102 can first determine the first weight corresponding to each connection edge according to the power transmission capacity corresponding to the connection edge and the rated capacity of the power system to be detected. For example, the terminal 102 can determine the first weight corresponding to each connection edge by means of ratio calculation. In addition, the terminal can also determine the second weight corresponding to each power device based on the power transmission capacity corresponding to each power device and the rated capacity of the power system to be detected. For example, the terminal 102 can determine the second weight corresponding to each power device by means of ratio calculation after summation. After the terminal 102 determines the weights of each power device and each connection edge in the above-mentioned network structure, the weighted network model corresponding to the above-mentioned power system to be detected can be obtained.

[0057] Step S208: Determine the harmonic oscillation risk value of the power system to be detected according to the first weight, the second weight, the network structure coefficient corresponding to the network structure, the power parameter offset between each power device, the electrical distance between each power device, and the preset component parameter coefficient.

[0058] Among them, after the terminal obtains the first weight corresponding to the connection edge and the second weight corresponding to each power device, it can obtain the network structure coefficient corresponding to the above-mentioned network structure. The network structure coefficient can be determined according to the type of the network structure and the preset component parameter coefficient, and the preset component parameter coefficient can represent the influence degree on the current offset of the connection edge. Specifically, the sum of the network structure coefficient and the preset component parameter coefficient can be one. If the focus is on the influence of the network structure, the value of the network structure coefficient is large and the value of the preset component parameter coefficient is small. This is because after the line is disconnected, the influence on the weight value of the node is the largest and the voltage offset of the node is the most obvious. If the focus is on the influence of the component parameters, the value of the network structure coefficient is small and the value of the preset component parameter coefficient is large. This is because after the component parameters change, the influence on the weight value of the edge is the largest and the branch current offset is the most obvious.

[0059] The terminal can also obtain the power parameter offsets between the above power devices, where the power parameter offsets include voltage offsets and current offsets. The terminal can determine the harmonic oscillation risk value of the power system to be detected according to the first weights of the above respective connection edges, the second weights of the respective power devices, the above network structure coefficient, the power parameter offsets between the power devices, the electrical distances between the power devices, and the preset component parameter coefficient. Specifically, the terminal 102 can determine a first harmonic oscillation value according to the first weights of the above respective connection edges, the above preset component parameter coefficient, the above current offset, and the above electrical distance, where the first harmonic oscillation value represents the influence on the oscillation risk under the condition of parameter transformation in the power system. The terminal 102 can also determine a second harmonic oscillation value according to the second weights of the above respective power devices, the network structure coefficient, and the voltage offset, where the second risk value represents the influence on the oscillation risk of the power system to be detected with DC feeding into AC under different network structures such as N-1 and N-2. After obtaining the above first harmonic oscillation value and second harmonic oscillation value, the terminal 102 can obtain the harmonic oscillation risk value of the power system to be detected based on the first harmonic oscillation value and the second harmonic oscillation value.

[0060] In addition, there can be more than one of the above-mentioned network structure coefficients and preset component parameter coefficients. The terminal can obtain harmonic oscillation risk values in different situations by determining different network structure coefficients and preset component parameter coefficients. And based on the harmonic oscillation risk values under multiple coefficient conditions, a network structure with a higher risk level is determined. For example, in one embodiment, after determining the harmonic oscillation risk value of the power system to be detected, it further includes: obtaining the harmonic oscillation risk values respectively corresponding to the power system to be detected under different network structure coefficients and different preset component parameter coefficients, to obtain multiple harmonic oscillation risk values; obtaining the target network structure coefficient and the target preset component parameter coefficient corresponding to the maximum harmonic oscillation risk value among the multiple harmonic oscillation risk values, determining the network structure corresponding to the target network structure coefficient as the high-risk network structure, and taking the preset component parameters corresponding to the target preset component parameter coefficient as the high-risk component parameters and outputting them. In this embodiment, the terminal 102 can obtain the harmonic oscillation risk values respectively corresponding to the power system to be detected under different network structures and component parameter conditions, so that the terminal 102 can obtain multiple harmonic oscillation risk values. The terminal 102 can sort the multiple harmonic oscillation risk values, for example, in descending order, so that the terminal 102 can obtain the maximum harmonic oscillation risk value among the multiple harmonic oscillation risk values. The terminal 102 can take the network structure corresponding to this maximum harmonic oscillation risk value as the high-risk network structure, and take the preset component parameters corresponding to the maximum harmonic oscillation risk value as the high-risk component parameters. The terminal can also output the high-risk network structure and the high-risk component parameters, so that relevant personnel can avoid setting the above-mentioned power system to be detected with the high-risk network structure and the high-risk component parameters. In addition, the terminal 102 can also take the network structure corresponding to the minimum harmonic oscillation risk value as the low-risk network structure, and take the preset component parameters corresponding to the maximum harmonic oscillation risk value as the low-risk component parameters. The terminal can also output the low-risk network structure and the low-risk component parameters, so that relevant personnel can set the power system based on the above-mentioned low-risk network structure and low-risk component parameters to reduce the harmonic oscillation risk of the power system.

[0061] In the above method for detecting harmonic oscillations in a power system, based on the connection relationships of various power devices in the network structure of the power system to be detected, the connection edges included in each connection relationship are determined. The electrical distance between each pair of power devices is determined according to the voltage values of the power devices with existing connection relationships and the energy loss value corresponding to the connection edge. According to the power transmission capacity corresponding to the connection edge and the rated capacity of the power system to be detected, the first weight corresponding to the connection edge is determined. Based on the power transmission capacity corresponding to each power device and the rated capacity of the power system to be detected, the second weight corresponding to each power device is determined. According to the above first weight, second weight, network structure coefficient, power parameter offset, electrical distance, and preset component parameter coefficient, the harmonic oscillation risk value of the power system to be detected is determined. Compared with the traditional method of detecting harmonic oscillations based on the nodal admittance matrix, this solution determines the harmonic oscillation risk by constructing the network structure of the power system and based on the weights and electrical distances of each node and connection edge in the network structure, improving the applicability of detecting the harmonic oscillation risk.

[0062] In one embodiment, determining the electrical distance between each pair of power devices according to the voltage values of the power devices with existing connection relationships and the energy loss value corresponding to the connection edge includes: obtaining multiple groups of power devices with existing connection relationships in each power device; for each group of power devices, obtaining the number of connection edges corresponding to this group of power devices, determining the voltage transmission loss value and power transmission loss value between this group of power devices according to the number of connection edges, and obtaining the electrical distance between each pair of power devices in this group of power devices according to the ratio of the square of the voltage transmission loss value to the power transmission loss value.

[0063] In this embodiment, the network structure of the above power system to be detected includes multiple groups of power devices with connection relationships. Each power device in each group of power devices can be directly connected through a connection edge, for example, two power devices are directly connected through a connection edge; or they can be indirectly connected, for example, two power devices are connected through multiple other power devices. For each group of power devices, the terminal 102 can obtain the number of connection edges corresponding to this group of power devices, and determine the voltage transmission loss value and power transmission loss value between this group of power devices according to the number of connection edges. The terminal 102 can obtain the square of the voltage transmission loss value, and obtain the ratio of this square to the power transmission loss value to obtain the electrical distance between each power device in this group of power devices. The terminal 102 can perform the above calculation process for each group of power devices, so as to obtain the electrical distance between each pair of power devices in the above power system to be detected.

[0064] Specifically, each power device in the above power system can be a node. The above electrical distance represents the electrical coupling degree between nodes. Taking i and j as different nodes as an example, the number of edges passed from node i to node j is the distance from node i to node j. If there is a power transmission relationship between node i and node j, it is considered that a branch is formed between the two nodes, called a generalized branch, that is, the above connection relationship. The impedance z of this generalized branch i can characterize the power loss caused by the power transmitted from node i to node j, and is called the equivalent transmission impedance. When there is a power transmission relationship between nodes, the transmission impedance is a finite value; if there is no transmission relationship, the transmission impedance is infinite. Then the terminal 102 can use the modulus |z i | of the transmission impedance as the electrical distance z between nodes. Its calculation formula can be as follows: z = |z i | = {(ΔU) 2 / |ΔS|}. Where z represents the electrical distance between two nodes, ΔU represents the voltage transmission loss value from node i to node j, and ΔS represents the power transmission loss value from node i to node j. After the terminal determines the electrical distances between the power devices in the to-be-detected power system, a non-weighted network model corresponding to the to-be-detected power system can be obtained.

[0065] Through this embodiment, the terminal 102 can determine the electrical distances between the power devices based on the voltage transmission loss value and the power transmission loss value. Thus, the terminal 102 can calculate the harmonic oscillation risk value of the to-be-detected power system based on the electrical distance, improving the calculation applicability of the harmonic oscillation risk value.

[0066] In one embodiment, determining the first weight corresponding to the connection edge according to the power transmission capacity corresponding to the connection edge and the rated capacity of the to-be-detected power system includes: obtaining the rated capacity corresponding to the connection edge and the power transmission loss values between the power devices connected by the connection edge; obtaining the power transmission capacity corresponding to the connection edge according to the difference between the sum of the rated capacities of the connection edges included between the power devices and the absolute value of the power transmission loss value; determining the first weight corresponding to the connection edge according to the ratio of the power transmission capacity to the rated capacity of the to-be-detected power system.

[0067] In this embodiment, each of the above-mentioned connection edges has a corresponding rated capacity. When electric energy is transmitted between power devices through the connection edges, corresponding power transmission loss values will be generated. The terminal 102 can obtain the rated capacity corresponding to the above-mentioned connection edges and the power transmission loss values between the power devices connected by the connection edges, and obtain the sum of the rated capacities of all the connection edges included between the power devices, and the difference between the sum of these rated capacities and the absolute value of the power transmission loss value, as the electric energy transmission capacity corresponding to the above-mentioned connection edge. The terminal 102 can obtain the ratio of the above-mentioned electric energy transmission capacity to the rated capacity of the power system to be detected, so as to obtain the first weight corresponding to the above-mentioned connection edge.

[0068] Specifically, the first weight of the above-mentioned connection edge can be denoted as w i , and its weight value is the ratio of the capacity S ij of the electric energy transmitted by this edge to the rated capacity S N defined for the entire power grid. S ij is the sum of the rated capacities of all the connection edges between nodes i and j minus the absolute value of the lost energy. Among them, the above-mentioned connection edge has a corresponding flow direction, for example, from node i to node j, or from node j to node i. Each flow direction has different senders and receivers. When the flow direction is from i to j, it is positive, and vice versa. The calculation formula of the above-mentioned first weight is as follows:

[0069] Among them, w represents the first weight, which can also be called w ij , representing the weight between node i and node j. S N ’ represents the sum of the rated capacities of all the connection edges between power devices. S N represents the rated capacity in the power system, and ΔS represents the power transmission loss value between node i and node j. After the terminal 102 determines the first weight for each connection edge between power devices with a connection relationship, a weighted network model with added connection edge weights corresponding to the power system to be detected can be obtained.

[0070] Through this embodiment, the terminal 102 can obtain the first weight of the connection edge through the rated capacity, power transmission loss value of each connection edge and the rated capacity of the power system, so that the terminal 102 can detect the harmonic oscillation risk based on the first weight, improving the detection applicability of the harmonic oscillation risk.

[0071] In one embodiment, determining the second weight corresponding to each power device based on the power transmission capacity corresponding to each power device and the rated capacity of the power system to be detected includes: obtaining the connection edges corresponding to the respective power devices having a connection relationship in the power system to be detected; for each power device, obtaining the power transmission capacity corresponding to the target connection edge with the power device as the sender; and determining the second weight corresponding to the power device according to the ratio of the sum of the power transmission capacities corresponding to the multiple target connection edges to the rated capacity of the power system to be detected.

[0072] In this embodiment, the terminal can determine the second weight of each power device to represent the influence of each node on the power system. The terminal 102 can obtain the connection edges corresponding to the respective power devices having a connection relationship in the above-mentioned power system to be detected. One power device can have multiple connection edges, and each connection edge can be one of the functions of outputting electric energy or receiving electric energy respectively. For each power device, the terminal 102 can obtain the power transmission capacity corresponding to the target connection edge with the power device as the sender from the multiple connection edges corresponding to the power device, and determine the second weight corresponding to the power device according to the ratio of the sum of the power transmission capacities corresponding to the multiple target connection edges and the rated capacity of the power system to be detected. The terminal 102 can perform the above calculations for each power device in the power system to be detected, so as to obtain the second weight corresponding to each power device in the power system to be detected.

[0073] Specifically, the above-mentioned respective power devices can be the respective nodes in the power system, and the second weight s of the node is defined as the capacity S currently transmitted by the node i Compared with the defined rated capacity S of the entire power grid N Ratio; S i Is the sum of all positive S ij The sum. Its calculation formula is as follows:

[0074] Among them, s represents the first weight, S N ’ Represents the sum of the rated capacities of all connection edges between power devices, S N Represents the rated capacity in the power system, ΔS represents the power transmission loss value between node i and node j, and ∑(S N ’-|ΔS|) represents the capacity S currently transmitted by the node i . After the terminal 102 determines the second weight for each power device, a weighted network model of the power system to be detected with the added connection edge weights and node weights can be obtained.

[0075] Through this embodiment, the terminal can obtain the second weight of the power equipment based on the power transmission capacity of each power equipment and the rated capacity of the power system. Thus, the terminal 102 can detect the harmonic oscillation risk based on the second weight, improving the applicability of the harmonic oscillation risk detection.

[0076] In one embodiment, according to the first weight corresponding to the connection edge, the second weight corresponding to each power equipment, the network structure coefficient corresponding to the network structure, the power parameter offset between each power equipment, the electrical distance between each power equipment, and the preset component parameter coefficient, determining the harmonic oscillation risk value of the power system to be detected includes: obtaining the node voltage offset corresponding to the power equipment and the branch current offset corresponding to the connection edge as the power parameter offset between the power equipment; obtaining the first ratio of the electrical distance between each power equipment to the maximum electrical distance among the electrical distances, and obtaining the first weight corresponding to the connection edge included between each power equipment and the branch current offset corresponding to the connection edge included between each power equipment; obtaining the sum of the first ratio, the first weight, and the first product of the branch current offset corresponding to the connection edge included in each power equipment, and obtaining the product of the sum of the first products and the preset component parameter coefficient to obtain the first harmonic oscillation value corresponding to the power system to be detected; obtaining the network structure coefficient according to the difference between one and the preset component parameter coefficient; obtaining the second weight corresponding to each power equipment, and obtaining the sum of the second product of the second ratio of each second weight to the maximum second weight in the power system and the node voltage offset corresponding to each power equipment, and obtaining the product of the sum of the second products and the network structure coefficient corresponding to the network structure to obtain the second harmonic oscillation value corresponding to the power system to be detected; determining the harmonic oscillation risk value of the power system to be detected according to the sum of the first harmonic oscillation value and the second harmonic oscillation value.

[0077] In this embodiment, when determining the harmonic oscillation risk in the system to be detected, the terminal 102 can determine the first harmonic oscillation value and the second harmonic oscillation value from two perspectives respectively, so as to obtain the harmonic oscillation risk value of the power system based on the first harmonic oscillation value and the second harmonic oscillation value. For example, the terminal 102 can obtain the node voltage offset corresponding to the power equipment and the branch current offset corresponding to the connection edge as the power parameter offset between the power equipment. The terminal 102 can obtain the first ratio of the electrical distance between each power equipment to the maximum electrical distance among all electrical distances, and obtain the first weight corresponding to the connection edge included between each power equipment, as well as the branch current offset corresponding to the connection edge included between each power equipment. The terminal 102 can obtain the first product of the first ratio, the first weight, and the branch current offset corresponding to the connection edge included in each of the above power equipment, obtain the sum of multiple first products, and then obtain the product of the sum of the first products and the preset element parameter coefficient to obtain the first harmonic oscillation value corresponding to the power system to be detected. The first harmonic oscillation value indicates the impact of the system on the oscillation risk under the condition of parameter transformation.

[0078] After determining the first harmonic oscillation value, the terminal 102 can obtain the network structure coefficient based on the difference between a value and the preset element parameter coefficient. Thus, the terminal 102 can obtain the second weight corresponding to each power equipment, obtain the second ratio of each second weight to the maximum second weight in the power system, and obtain the sum of the second products of the second ratio and the node voltage offset corresponding to each power equipment, and obtain the product of the sum of the second products and the network structure corresponding to the network structure to obtain the second harmonic oscillation value corresponding to the power system to be detected. The second harmonic oscillation value represents the impact of the DC feeding into the AC system on the oscillation risk under different network structures such as N-1 and N-2.

[0079] Thus, the terminal 102 can determine the harmonic oscillation risk value of the power system to be detected according to the sum of the above first harmonic oscillation value and the second harmonic oscillation value. Specifically, let the harmonic oscillation risk value be W, and its calculation formula is as follows:

[0080] Where n represents the number of nodes, k represents the network structure coefficient, l represents the preset element parameter coefficient, and k + l = 1; i and j represent node labels, ΔV i represents the node voltage offset of node i, ΔI ij is the branch current offset of the ij branch, s max is the maximum node weight in the complex network, z max is the maximum electrical distance value in the complex network, z ij represents the electrical distance between nodes, w ij represents the first weight between nodes, S i represents the capacity currently transmitted by the node.

[0081] Among them, for k and l, their values can be set according to the actual situation. If the focus is on the impact of the network structure, the value of k is large and the value of l is small. This is because after the line is disconnected, the impact on the node weights is the greatest, and the voltage offset of the node is the most obvious. If it is necessary to determine the impact of component parameters, the value of k is small and the value of l is large. This is because after the component parameters change, the impact on the edge weights is the greatest, and the branch current offset is the most obvious. If oscillations occur, the offsets of the node voltages and branch currents must be feedback. Therefore, the terminal 102 can perform sensitivity analysis through the oscillation risk index based on the weighted complex network model. The smaller the oscillation risk characteristic index, the lower the sensitivity to oscillations in this network structure or parameter situation, and vice versa. Thus, the terminal 102 can determine the level of the harmonic oscillation risk of the power system according to the above harmonic oscillation risk value.

[0082] Through this embodiment, the terminal 102 can determine the harmonic oscillation risk value based on the various weights, network structure coefficients, preset component parameter coefficients, offsets, and electrical distances in the power system, thereby improving the applicability of detecting the harmonic oscillation risk value.

[0083] In one embodiment, as Figure 3 shown, Figure 3 is a schematic flow chart of a method for detecting harmonic oscillations in a power system in another embodiment. In this embodiment, the following steps are included: The terminal 102 determines and constructs an equivalent AC network model according to the actual engineering DC feeding into the AC grid structure, that is, the above network structure; The terminal 102 establishes a weighted model of the complex network of the power system according to the actual situation and the simplified equivalent model. Specifically, it includes: There are multiple power devices in the above power system, and each power device represents a node. The terminal 102 uses the electrical distance calculation method based on the transfer impedance to establish an unweighted network model of the system. Define the electrical distance to represent the electrical coupling degree between nodes, and its meaning is that the number of edges passed from node i to node j is the distance from node i to node j. If there is a power transmission relationship between node i and node j, it is considered that a branch is formed between the two nodes, called a generalized branch. The impedance z i of this generalized branch can characterize the power loss caused by the power transmitted from node i to node j, and is called the equivalent transfer impedance. When there is a power transmission relationship between nodes, the transfer impedance is a finite value; if there is no transmission relationship, the transfer impedance is infinite. Take the modulus |z i | of the transfer impedance as the electrical distance between nodes. The terminal 102 can also use the similarity weight to weight the edges and nodes in the network to establish a weighted network model of the system. Among them, the first weight w i of the edge is the ratio of the capacity S ij of the electric energy transmitted by this edge to the rated capacity S N defined for the entire power grid, and S ijThe absolute value of the sum of the rated capacities of all connecting edges between nodes i and j minus the dissipated energy, which is positive when the power transmission direction is from i to j and negative otherwise. The second weight s of a node i is defined as the capacity S currently transmitted by this node i and the defined rated capacity S of the entire power grid N The ratio; S i is the sum of all positive S ij values.

[0084] After obtaining the above first weight and second weight, the terminal 102 can obtain the harmonic oscillation risk value W based on the above harmonic oscillation risk value calculation formula. And the terminal 102 can also calculate the harmonic oscillation risk value W under different network structures and preset component parameters, such as the network structures under different working conditions such as N-1, N2, etc., and transform the parameters, so as to obtain multiple Ws, sort the multiple Ws, conduct simulation verification, and obtain the high-risk network structure and preset component parameters, as well as the low-risk network structure and preset component parameters. Thus, relevant personnel can set the power system based on the above low-risk network structure and low-risk component parameters to reduce the harmonic oscillation risk of the power system. In addition, when the terminal determines that the result of the simulation verification does not match the actual situation after the simulation verification, it can also re-determine the network structure coefficient and component parameter coefficient, and obtain the harmonic oscillation risk value based on the re-determined coefficients.

[0085] Through this embodiment, the terminal 102 constructs the network structure of the power system and determines the harmonic oscillation risk based on the weights and electrical distances of each node and connecting edge in the network structure, improving the applicability of detecting the harmonic oscillation risk.

[0086] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are sequentially shown according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0087] Based on the same inventive concept, an embodiment of the present application further provides a detection device for power system harmonic oscillation for implementing the detection method of power system harmonic oscillation involved above. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the detection device for power system harmonic oscillation provided below can refer to the limitations on the detection method of power system harmonic oscillation in the foregoing, and will not be elaborated herein.

[0088] In one embodiment, as Figure 4 shown, a detection device for power system harmonic oscillation is provided, including: an acquisition module 500, a first determination module 502, a second determination module 504, and a detection module 506, where:

[0089] The acquisition module 500 is configured to acquire the network structure of the power system to be detected; the network structure includes a plurality of power devices included in the power system and the connection relationships between the power devices.

[0090] The first determination module 502 is configured to determine the connection edges included in each connection relationship according to the connection relationships of the power devices, and determine the electrical distances between the power devices according to the voltage values of the power devices with existing connection relationships and the energy loss values corresponding to the connection edges.

[0091] The second determination module 504 is configured to determine the first weight corresponding to the connection edge according to the power transmission capacity corresponding to the connection edge and the rated capacity of the power system to be detected, and determine the second weight corresponding to each power device based on the power transmission capacity corresponding to each power device and the rated capacity of the power system to be detected.

[0092] The detection module 506 is configured to determine the harmonic oscillation risk value of the power system to be detected according to the first weight corresponding to the connection edge, the second weights corresponding to the power devices, the network structure coefficient corresponding to the network structure, the power parameter offset between the power devices, the electrical distances between the power devices, and the preset element parameter coefficient.

[0093] In one embodiment, the above acquisition module 500 is specifically configured to acquire a plurality of power devices included in the power system with DC feeding into AC and the connection relationships between the power devices to obtain the network structure of the power system to be detected.

[0094] In one embodiment, the above-mentioned first determination module 502 is specifically configured to obtain multiple groups of power equipment with connection relationships in each power equipment; for each group of power equipment, obtain the number of connection edges corresponding to the group of power equipment, determine the voltage transmission loss value and power transmission loss value between the group of power equipment according to the number of connection edges, and obtain the electrical distance between each power equipment in the group of power equipment according to the ratio of the square of the voltage transmission loss value to the power transmission loss value.

[0095] In one embodiment, the above-mentioned second determination module 504 is specifically configured to obtain the rated capacity corresponding to the connection edge and the power transmission loss value between each power equipment connected by the connection edge; obtain the power transmission capacity corresponding to the connection edge according to the difference between the sum of the rated capacities of each connection edge included between each power equipment and the absolute value of the power transmission loss value; determine the first weight corresponding to the connection edge according to the ratio of the power transmission capacity to the rated capacity of the power system to be detected.

[0096] In one embodiment, the above-mentioned second determination module 504 is specifically configured to obtain the connection edges corresponding to each power equipment with a connection relationship in the power system to be detected; for each power equipment, obtain the power transmission capacity corresponding to the target connection edge with the power equipment as the sender; determine the second weight corresponding to the power equipment according to the ratio of the sum of the power transmission capacities corresponding to multiple target connection edges to the rated capacity of the power system to be detected.

[0097] In one embodiment, the above-mentioned detection module 506 is specifically configured to obtain the node voltage offset corresponding to the power equipment and the branch current offset corresponding to the connection edge as the power parameter offset between the power equipment; obtain the first ratio of the electrical distance between each power equipment to the maximum electrical distance among each electrical distance, and obtain the first weight corresponding to the connection edge included between each power equipment and the branch current offset corresponding to the connection edge included between each power equipment; obtain the sum of the first ratio, the first weight and the first product of the branch current offset corresponding to the connection edge included in each power equipment, obtain the product of the sum of the first product and the preset component parameter coefficient, and obtain the first harmonic oscillation value corresponding to the power system to be detected; obtain the network structure coefficient according to the difference between one and the preset component parameter coefficient; obtain the second weight corresponding to each power equipment, and obtain the sum of the second product of the second ratio of each second weight to the maximum second weight in the power system and the node voltage offset corresponding to each power equipment, obtain the product of the sum of the second product and the network structure coefficient corresponding to the network structure, and obtain the second harmonic oscillation value corresponding to the power system to be detected; determine the harmonic oscillation risk value of the power system to be detected according to the sum of the first harmonic oscillation value and the second harmonic oscillation value.

[0098] In one embodiment, the above device further includes: an output module, configured to obtain the harmonic oscillation risk values respectively corresponding to the power systems to be detected under different network structure coefficients and different preset component parameter coefficients, so as to obtain a plurality of harmonic oscillation risk values; obtain the target network structure coefficient and the target preset component parameter coefficient corresponding to the maximum harmonic oscillation risk value among the plurality of harmonic oscillation risk values, determine the network structure corresponding to the target network structure coefficient as a high-risk network structure, and output the preset component parameters corresponding to the target preset component parameter coefficient as high-risk component parameters.

[0099] Each module in the above device for detecting harmonic oscillation of a power system can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in the processor in the computer device in hardware form or be independent of the processor, or can be stored in the memory in the computer device in software form, so as to facilitate the processor to call and execute the operations corresponding to each of the above modules.

[0100] In one embodiment, a computer device is provided. The computer device can be a terminal, and its internal structure diagram can be as Figure 5 shown. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a method for detecting harmonic oscillation of a power system. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, a touchpad, or a mouse, etc.

[0101] Those skilled in the art can understand that Figure 5 the structure shown in

[0102] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the above-mentioned method for detecting harmonic oscillations in a power system is implemented.

[0103] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned method for detecting harmonic oscillations in a power system is implemented.

[0104] In one embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the above-mentioned method for detecting harmonic oscillations in a power system is implemented.

[0105] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0106] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in this application can be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0107] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0108] The above-described embodiments merely represent several implementation manners of this application. The description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of this application. It should be noted that for those of ordinary skill in the art, without departing from the concept of this application, several modifications and improvements can still be made, and these all belong to the protection scope of this application. Therefore, the protection scope of this application should be subject to the appended claims.

Claims

1. A detection method for harmonic oscillation in a power system, characterized in that, The method includes: Obtaining the network structure of the power system to be detected; the network structure includes multiple power devices included in the power system and the connection relationships between the power devices; Determining the connection edges included in each connection relationship according to the connection relationships of the power devices, and determining the electrical distances between the power devices according to the voltage values of the power devices with connection relationships and the energy loss values corresponding to the connection edges; Determining the first weight corresponding to the connection edge according to the power transmission capacity corresponding to the connection edge and the rated capacity of the power system to be detected, and determining the second weight corresponding to each power device based on the power transmission capacity corresponding to each power device and the rated capacity of the power system to be detected; Determining the harmonic oscillation risk value of the power system to be detected according to the first weight, the second weight, the network structure coefficient corresponding to the network structure, the power parameter offset between the power devices, the electrical distances between the power devices, and the preset component parameter coefficient.

2. The method according to claim 1, characterized in that, The obtaining the network structure of the power system to be detected includes: Obtaining multiple power devices included in the power system to be detected and the connection relationships between the power devices to obtain the network structure of the power system to be detected.

3. The method according to claim 1, characterized in that, The determining the electrical distances between the power devices according to the voltage values of the power devices with connection relationships and the energy loss values corresponding to the connection edges includes: Obtaining multiple groups of power devices with connection relationships among the power devices; For each group of power devices, obtaining the number of connection edges corresponding to the group of power devices, determining the voltage transmission loss value and the power transmission loss value between the power devices in the group according to the number of connection edges, and obtaining the electrical distance between the power devices in the group according to the ratio of the square of the voltage transmission loss value to the power transmission loss value.

4. The method according to claim 3, characterized in that The determining the first weight corresponding to the connection edge according to the power transmission capacity corresponding to the connection edge and the rated capacity of the power system to be detected includes: Obtaining the rated capacity corresponding to the connection edge and the power transmission loss value between the power devices connected by the connection edge; Obtaining the power transmission capacity corresponding to the connection edge according to the difference between the sum of the rated capacities of the connection edges included between the power devices and the absolute value of the power transmission loss value; Determining the first weight corresponding to the connection edge according to the ratio of the power transmission capacity to the rated capacity of the power system to be detected.

5. The method according to claim 1, wherein The determining the second weight corresponding to each power device based on the power transmission capacity corresponding to each power device and the rated capacity of the power system to be detected includes: Obtaining the connection edges corresponding to the power devices with connection relationships in the power system to be detected; For each power device, obtaining the power transmission capacity corresponding to the target connection edge with the power device as the sender; Determining the second weight corresponding to the power device according to the ratio of the sum of the power transmission capacities corresponding to the multiple target connection edges to the rated capacity of the power system to be detected.

6. The method according to claim 1, wherein Determining the harmonic oscillation risk value of the power system to be detected according to the first weight corresponding to the connection edge, the second weight corresponding to each power device, the network structure coefficient corresponding to the network structure, the power parameter offset between each power device, the electrical distance between each power device, and the preset component parameter coefficient includes: Obtaining the node voltage offset corresponding to the power device and the branch current offset corresponding to the connection edge as the power parameter offset between the power devices; Obtaining a first ratio of the electrical distance between each power device to the maximum electrical distance among all electrical distances, and obtaining the first weight corresponding to the connection edge included between each power device and the branch current offset corresponding to the connection edge included between each power device; Obtaining the sum of the first products of the first ratio, the first weight, and the branch current offset corresponding to the connection edge included in each power device, and obtaining the product of the sum of the first products and the preset component parameter coefficient to obtain the first harmonic oscillation value corresponding to the power system to be detected; Obtaining a network structure coefficient according to a difference from the preset component parameter coefficient; the sum of the network structure coefficient and the preset component parameter coefficient is 1; Obtaining the second weight corresponding to each power device, and obtaining the sum of the second products of the second ratio of each second weight to the maximum second weight in the power system and the node voltage offset corresponding to each power device, and obtaining the product of the sum of the second products and the network structure coefficient corresponding to the network structure to obtain the second harmonic oscillation value corresponding to the power system to be detected; Determining the harmonic oscillation risk value of the power system to be detected according to the sum of the first harmonic oscillation value and the second harmonic oscillation value.

7. The method according to any one of claims 1 to 6, characterized in that, After determining the harmonic oscillation risk value of the power system to be detected, it further includes: Obtaining the harmonic oscillation risk values corresponding to the power system to be detected under different network structure coefficients and different preset component parameter coefficients to obtain a plurality of harmonic oscillation risk values; Obtaining the target network structure coefficient and the target preset component parameter coefficient corresponding to the maximum harmonic oscillation risk value among the plurality of harmonic oscillation risk values, determining the network structure corresponding to the target network structure coefficient as the high-risk network structure, and outputting the preset component parameter corresponding to the target preset component parameter coefficient as the high-risk component parameter.

8. A detection device for harmonic oscillation in a power system, characterized in that The device includes: An obtaining module, configured to obtain the network structure of the power system to be detected; the network structure includes a plurality of power devices included in the power system and the connection relationship between each power device; A first determining module, configured to determine the connection edge included in each connection relationship according to the connection relationship between each power device, and determine the electrical distance between each power device according to the voltage value of each power device with a connection relationship and the energy loss value corresponding to the connection edge; A second determination module, configured to determine a first weight corresponding to the connection edge according to the power transmission capacity corresponding to the connection edge and the rated capacity of the power system to be detected, and determine a second weight corresponding to each power device based on the power transmission capacity corresponding to each power device and the rated capacity of the power system to be detected; A detection module, configured to determine a harmonic oscillation risk value of the power system to be detected according to the first weight corresponding to the connection edge, the second weights corresponding to the power devices, the network structure coefficient corresponding to the network structure, the power parameter offset between the power devices, the electrical distance between the power devices, and a preset component parameter coefficient.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 7 are implemented.

11. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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