Harmonic monitoring stationing method, system, equipment and medium

Abstract

The invention provides a harmonic monitoring point distribution method, system and device and a medium, and the method comprises the steps: constructing an initial node observability matrix based on direct observability judgment; taking the observable zero-harmonic injection node as a starting point, and carrying out node indirect observability judgment in an iteration manner until no new observable zero-harmonic injection node exists; carrying out indirect observability judgment on the remaining unobservable zero-harmonic injection nodes, determining a newest node observability matrix, and outputting a final point distribution scheme until all the nodes are observable or reach a set point distribution termination condition; according to the method, on the basis of direct observability judgment, indirect observability judgment is carried out by taking a newly discovered zero-harmonic injection node as a starting point, so that the completeness of an analysis result is ensured, the search efficiency is greatly improved, rapid convergence can be realized, and a decision basis is provided for a subsequent output point distribution scheme; therefore, the harmonic state monitoring of the whole power distribution network covered by the least harmonic measuring devices is finally realized.

Description

A method, system, device and medium for harmonic monitoring point placement. Technical Field

[0001] This invention belongs to the field of power system harmonic monitoring and state estimation technology, specifically relating to a harmonic monitoring point deployment method, system, equipment, and medium. Background Technology

[0002] With the widespread application of nonlinear loads and power electronic equipment in modern power systems, the problem of power grid harmonic pollution is becoming increasingly serious. Harmonic state estimation (HSE) technology, as an important means of harmonic monitoring, relies on collecting voltage and current data from key nodes using a limited number of harmonic measurement devices to estimate the harmonic distribution across the entire network. However, the number and location of measurement points directly determine the accuracy and coverage of HSE estimation.

[0003] In existing technologies, the problem of optimizing the configuration of harmonic measurement points mainly employs mathematical methods and heuristic algorithms. Mathematical methods include exhaustive search, implicit enumeration, and integer programming. While exhaustive search can obtain an exact solution, the computational cost increases exponentially with the number of nodes, making it difficult to apply to large-scale distribution networks. Implicit enumeration narrows the search range through constraints, but remains computationally cumbersome when the number of nodes is large. Integer programming is only applicable to linear models and has poor adaptability.

[0004] Heuristic algorithms, such as genetic algorithms (GA), simulated annealing (SAA), and particle swarm optimization (PSO), can effectively solve combinatorial optimization problems, but they have high computational complexity and lack theoretical guarantees, and may get trapped in local optima.

[0005] Therefore, there is an urgent need for a method to optimize the placement of harmonic monitoring points that balances computational efficiency, global observability, and engineering practicality. Summary of the Invention

[0006] To overcome the shortcomings of the existing technology, this invention proposes a harmonic monitoring point deployment method, comprising: based on the topology connection matrix of each node in the distribution network and the initial deployment scheme of harmonic measurement points, performing direct observability judgment on each node to construct an initial node observability matrix; the initial deployment scheme is determined based on the number of basic harmonic measurement points; starting from the observable zero-harmonic injection node in the initial node observability matrix, performing indirect node observability judgment to update the node observability matrix, and iteratively searching for and judging new observable nodes until there are no new observable zero-harmonic injection nodes; in each round of search and judgment, The newly observable zero-harmonic injection nodes in this round are used as the starting point for the next round of search, and the node observability matrix updated in this round is used as the initial node observability matrix for the next round. After completing the iterative search judgment, the remaining unobservable zero-harmonic injection nodes in each node are indirectly judged to determine the latest node observability matrix. Based on the latest node observability matrix, it is determined whether all nodes are observable. If not, the layout scheme of harmonic measurement points is adjusted, and the observability of each node is re-judged until all nodes are observable or the set layout termination condition is met, and the final layout scheme is output.

[0007] Preferably, the step of determining the indirect observability of nodes, starting from the observable zero-harmonic injection node in the initial node observability matrix, includes: obtaining the starting point connection row vector in the topology connection matrix corresponding to the starting point, using the observable zero-harmonic injection node in the initial node observability matrix as the starting point; calculating the difference between the starting point connection row vector and the initial node observability matrix to obtain the starting point observation state discrimination vector; and determining that the node corresponding to the element with only one element as 1 is indirectly observable when only one element in the starting point observation state discrimination vector is 1.

[0008] Preferably, the calculation process of the starting point observation state discrimination vector satisfies the following formula: ;in, This represents the starting observation state discrimination vector originating from node i. This represents the row vector connecting nodes starting from node i. This represents the transpose of the initial node observability matrix.

[0009] Preferably, the indirect observability determination of the remaining unobservable zero-harmonic injection nodes in each node includes: taking the remaining unobservable zero-harmonic injection nodes in each node as determination points, obtaining the determination point connection row vector in the topological connection matrix corresponding to the determination point; calculating the difference between the determination point connection row vector and the node observability matrix updated after completing the iterative search determination, to obtain the determination point observation state discrimination vector; when only one element in the determination point observation state discrimination vector is 1, and the node corresponding to the element with 1 is the determination point, the determination point is indirectly observable.

[0010] Preferably, the method of directly determining the observability of each node based on the topology connection matrix of each node in the distribution network and the initial layout scheme of harmonic measurement points to construct an initial node observability matrix includes: determining the measurement point attributes of each node in the distribution network based on the initial layout scheme of harmonic measurement points and constructing a measurement point matrix; calculating the product of the topology connection matrix of each node in the distribution network and the measurement point matrix to obtain a node observability frequency matrix; extracting the observability of each node based on the node observability frequency matrix, and constructing an initial node observability matrix based on the observability.

[0011] Preferably, the initial node observability matrix satisfies the following formula: ; ; ; ; ; ; ;in, Let represent the initial node observability matrix. Indicate the observability of node i. =1,...,n, where n is the total number of nodes; , indicating that node i is observable; , indicating that node i is not observable; Represents the observable order matrix of nodes. Represents a node A considerable number of times; Represents the measurement point matrix. =1 indicates that node i is a measurement point. This represents the topological connectivity matrix.

[0012] Preferably, the method for adjusting the layout of harmonic measurement points includes: using a heuristic search algorithm to adjust the layout of harmonic measurement points, wherein the heuristic search algorithm includes at least one of genetic algorithm, particle swarm optimization algorithm, and simulated annealing algorithm.

[0013] Based on the same inventive concept, this invention also provides a harmonic monitoring point deployment system, comprising: a direct judgment module, used to perform direct observability judgment on each node based on the topology connection matrix of each node in the distribution network and the initial layout scheme of harmonic measurement points, to construct an initial node observability matrix; the initial layout scheme is determined based on the number of basic harmonic measurement points; and an indirect judgment module, used to perform indirect node observability judgment starting from observable zero-harmonic injection nodes in the initial node observability matrix, to update the node observability matrix, and iteratively search for and judge new observable nodes until no new observable zero-harmonic injection nodes are found; in each round of search and judgment, The newly observable zero-harmonic injection nodes in this round serve as the starting point for the next round of search, and the node observability matrix updated in this round is used as the initial node observability matrix for the next round. The supplementary judgment module is used to perform indirect observability judgment on the remaining unobservable zero-harmonic injection nodes among the nodes after completing the iterative search judgment, and determine the latest node observability matrix. The scheme determination module is used to determine whether all nodes are observable based on the latest node observability matrix. If not, the layout scheme of harmonic measurement points is adjusted, and the observability of each node is re-judged until all nodes are observable or the set layout termination condition is met, and the final layout scheme is output.

[0014] Preferably, the indirect judgment module is specifically used for: taking the observable zero-harmonic injection node in the initial node observability matrix as the starting point, obtaining the starting point connection row vector in the topology connection matrix corresponding to the starting point; calculating the difference between the starting point connection row vector and the initial node observability matrix to obtain the starting point observation state discrimination vector; when only one element in the starting point observation state discrimination vector is 1, the node corresponding to the element with the value of 1 is indirectly observable.

[0015] Preferably, the calculation process of the starting point observation state discrimination vector satisfies the following formula: ;in, This represents the starting observation state discrimination vector originating from node i. This represents the row vector connecting nodes starting from node i. This represents the transpose of the initial node observability matrix.

[0016] Preferably, the supplementary judgment module is specifically used to: take the remaining unobservable zero-harmonic injection nodes in each node as judgment points, obtain the judgment point connection row vector corresponding to the judgment point in the topological connection matrix; calculate the difference between the judgment point connection row vector and the node observability matrix updated after completing the iterative search judgment, and obtain the judgment point observation state discrimination vector; when there is only one element of the judgment point observation state discrimination vector that is 1, and the node corresponding to the element that is 1 is the judgment point, the judgment point is indirectly observable.

[0017] Preferably, the direct judgment module is specifically used for: determining the measurement point attributes of each node in the distribution network based on the initial layout scheme of harmonic measurement points, and constructing a measurement point matrix; calculating the product of the topology connection matrix of each node in the distribution network and the measurement point matrix to obtain the node observability matrix; extracting the observability of each node based on the node observability matrix, and constructing an initial node observability matrix based on the observability.

[0018] Preferably, the initial node observability matrix satisfies the following formula: ; ; ; ; ; ; ;in, Let represent the initial node observability matrix. Let i represent the observability of node i, where i = 1, ..., n, and n is the total number of nodes. , indicating that node i is observable; , indicating that node i is not observable; Represents the observable order matrix of nodes. Represents a node A considerable number of times; Represents the measurement point matrix. =1 indicates that node i is a measurement point. This represents the topological connectivity matrix.

[0019] Preferably, the scheme determination module is specifically used to: adjust the layout scheme of harmonic measurement points using a heuristic search algorithm, wherein the heuristic search algorithm includes at least one of genetic algorithm, particle swarm optimization algorithm, and simulated annealing algorithm.

[0020] Based on the same inventive concept, the present invention also provides a computer device, comprising: one or more processors; a memory for storing one or more programs; and when the one or more programs are executed by the one or more processors, implementing the harmonic monitoring point placement method as described above.

[0021] Based on the same inventive concept, the present invention also provides a readable storage medium having a computer program stored thereon, which, when executed, implements a harmonic monitoring point placement method as described above.

[0022] Compared with the closest existing technology, the present invention has the following beneficial effects: The present invention provides a method, system, device, and medium for harmonic monitoring point deployment. The method includes: based on the topology connection matrix of each node in the distribution network and the initial deployment scheme of harmonic measurement points, performing direct observability judgment on each node to construct an initial node observability matrix; the initial deployment scheme is determined based on the number of basic harmonic measurement points; starting from the observable zero-harmonic injection node in the initial node observability matrix, performing indirect node observability judgment to update the node observability matrix, and iteratively searching for and judging new observable nodes until there are no new observable zero-harmonic injection nodes; in each round of search judgment, the new observable zero-harmonic injection node of this round is used as the starting point of the next round of search, and the node observability matrix updated in this round is used as the initial node observability matrix of the next round; after completing the iterative search judgment, the method further includes: The remaining unobservable zero-harmonic injection nodes in each node are indirectly observable to determine the latest node observability matrix. Based on the latest node observability matrix, it is determined whether all nodes are observable. If not, the layout of harmonic measurement points is adjusted, and the observability of each node is reassessed until all nodes are observable or the set layout termination condition is met, and the final layout scheme is output. This method is based on direct observability judgment and uses each newly discovered zero-harmonic injection node as the starting point for the next round of search, so that the indirect observability judgment propagates automatically like waves. This not only ensures the completeness of the analysis results but also greatly improves the search efficiency and can converge quickly. It provides a direct decision basis for subsequent adjustment of the layout of harmonic measurement points and the realization of full network monitoring with the fewest harmonic measurement devices, thereby ultimately achieving full distribution network harmonic status monitoring with the fewest harmonic measurement devices. Attached Figure Description

[0023] Figure 1 is a schematic flowchart of a harmonic monitoring point placement method provided by the present invention; Figure 2 is a schematic flowchart of the overall harmonic monitoring point placement method provided by the present invention; Figure 3 is a schematic diagram of a harmonic monitoring point placement system provided by the present invention; Figure 4 is a schematic diagram of an electronic device provided by the present invention. Detailed Implementation

[0024] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0025] Example 1: The present invention provides a harmonic monitoring point deployment method, as shown in Figure 1, comprising: S1, based on the topology connection matrix of each node in the distribution network and the initial deployment scheme of harmonic measurement points, performing direct observability judgment on each node to construct an initial node observability matrix; the initial deployment scheme is determined based on the number of basic harmonic measurement points; S2, starting from the observable zero-harmonic injection node in the initial node observability matrix, performing indirect observability judgment on nodes to update the node observability matrix, and iteratively searching for and judging new observable nodes until there are no new observable zero-harmonic injection nodes; in each round of search and judgment, The newly observable zero-harmonic injection nodes in this round are used as the starting point for the next round of search, and the node observability matrix updated in this round is used as the initial node observability matrix for the next round; S3, after completing the iterative search judgment, the remaining unobservable zero-harmonic injection nodes in each node are indirectly judged to determine the latest node observability matrix; S4, based on the latest node observability matrix, it is determined whether all nodes are observable. If not, the layout scheme of harmonic measurement points is adjusted, and the observability of each node is re-judged until all nodes are observable or the set layout termination condition is reached, and the final layout scheme is output.

[0026] Given that existing studies often neglect the characteristics of zero-harmonic current injection nodes, leading to redundant or insufficient coverage of measurement points, this invention, based on direct observability judgment, uses each newly discovered zero-harmonic injection node as the starting point for the next round of searching. This allows indirect observability judgments to propagate automatically like waves, ensuring not only the completeness of the analysis results but also significantly improving search efficiency and enabling rapid convergence. This provides a direct decision-making basis for subsequent adjustments to the harmonic measurement point layout scheme and for achieving full-network monitoring with minimal harmonic measurement devices, ultimately realizing harmonic status monitoring of the entire distribution network with minimal harmonic measurement devices.

[0027] In harmonic monitoring of cable networks, a node is considered observable because, given a configuration of measuring devices and network topology, its harmonic state variables can be uniquely and deterministically calculated or derived from other known measurements through direct measurement or based on circuit constraints such as Kirchhoff's laws. The node's state is known and unambiguous. Conversely, a node is considered unobservable because, under existing conditions, sufficient information cannot be obtained to uniquely determine its harmonic state. Its state variables may have infinitely many solutions, which cannot be derived from known measurements and network relationships. The node's state is unknown and uncertain.

[0028] This scheme performs node observability analysis based on the network topology matrix (i.e., the topology connection matrix), including direct and indirect node observability assessment. The main idea is to use newly added observable nodes as starting points to continue searching for observable nodes. Direct observability assessment identifies nodes observable through self-measurement or branch current measurement; while indirect observability assessment identifies nodes observable through existing measurements and zero-harmonic current injection measurements.

[0029] The rules for determining the direct observability of a node include: Rule 1: If a node is equipped with a harmonic measurement device, then the state of that node is observable, which is called self-measurement; Rule 2: If a node on one side of a branch is equipped with a harmonic measurement device, the branch current measurement can make the state of the node on the opposite side observable; The rules for determining the indirect observability of a node include: Rule 3: When the voltages of two nodes on opposite sides of the same branch are observable, the current of that branch is observable; Rule 4: If a node injected with a non-harmonic current has only one unobservable branch, Kirchhoff's current law can be used to solve for the current of that unobservable branch, making the node on the opposite side of that branch observable; Rule 5: If all nodes associated with a node injected with a non-harmonic current are observable, Kirchhoff's voltage law can be used to make that node observable.

[0030] Based on the above five observability judgment rules, observable nodes can be searched starting from the measurement points. The observability of the nodes can be judged directly or indirectly through harmonic voltage measurement and current measurement.

[0031] To implement the above rules for determining the observability of nodes, S1 is achieved through a topology connection matrix and the construction of an initial node observability matrix. In this embodiment, S1 may include: determining the measurement point attributes of each node in the distribution network based on the initial layout scheme of harmonic measurement points, and constructing a measurement point matrix; calculating the product of the topology connection matrix and the measurement point matrix of each node in the distribution network to obtain a node observability frequency matrix; extracting the observability of each node based on the node observability frequency matrix, and constructing an initial node observability matrix based on the observability.

[0032] It should be noted that, based on the initial node observability matrix, we can obtain the newly added directly observable nodes determined by rule 2 above under the current initial node layout scheme.

[0033] In this embodiment, the initial node observability matrix satisfies the following formula: ; ; ; ; ; ; ;in, Let represent the initial node observability matrix. Indicate the observability of node i. =1,...,n, where n is the total number of nodes; , indicating that node i is observable; , indicating that node i is not observable; Represents the observable order matrix of nodes. Represents a node A considerable number of times; Represents the measurement point matrix. =1 indicates that node i is a measurement point, also known as the initial directly observable node; This represents the topological connectivity matrix.

[0034] In practical power distribution networks, buses are equivalent to nodes, and distribution lines are equivalent to edges. Therefore, the topology of a power distribution network can be represented by a topology connectivity matrix. Specifically, for an undirected, unweighted network... V is the set of network nodes, and E is the set of edges in the network, represented by the network topology connection matrix A.

[0035] ; ; where each element a in the topological connectivity matrix A ij This represents the connection state between node i and node j. =1,...,n, where i=j indicates that the node itself is connected; if i≠j and {i,j} is an edge of network G, it means that there is a direct edge connection between node i and j; if i≠j and {i,j} is not an edge of network G, it means that there is no direct edge connection between node i and j.

[0036] In this embodiment, the layout scheme can be represented by a measurement point matrix M, including the number of harmonic measurement points, i.e., the number of detection devices, and the measurement point locations, i.e., the installation locations of the detection devices. Considering the overall feasibility of the technical solution, the number of basic harmonic measurement points is set to a very small value (e.g., 1 unit), starting from the theoretically possible minimum configuration, aiming to find the limit solution of "minimum detection devices". Based on this, in the actual determination process of the initial layout scheme, one of the following strategies can be referenced: (1) Random generation: In the node set, a node equal to the number of basic harmonic measurement points is randomly selected as the initial measurement point, and different starting areas can be explored in multiple independent runs.

[0037] (2) Degree priority: Prioritize the node with the highest network connectivity (i.e., the number of adjacent nodes) because it may observe more branches.

[0038] (3) Rule generation: Directly apply simple observability rules. For example, to ensure that there is at least one starting point, the first initial point can be set to be a zero-harmonic injection node or a specific key node in the network.

[0039] To ensure the implementation of the aforementioned rules for determining the indirect observability of nodes (rules 3 and 4), in S2 above, the relationship between the starting point connection row vector and the node observability matrix is ​​used for judgment. In this embodiment, when determining the indirect observability of nodes in S2 above, it may include: taking the observable zero-harmonic injection node in the initial node observability matrix as the starting point, obtaining the starting point connection row vector corresponding to the starting point in the topological connection matrix; calculating the difference between the starting point connection row vector and the initial node observability matrix to obtain the starting point observation state discrimination vector; when only one element in the starting point observation state discrimination vector is 1, the node corresponding to the element with the value of 1 is indirectly observable.

[0040] In this embodiment, let The harmonic injection point matrix L indicates whether each node in the network is a suspected harmonic current injection node. ; Elements in L The harmonic injection state of node i is represented by the following equation: For the considerable number of nodes added in S1 and during the iteration process in S2. ,if Then, the starting observation state discrimination vector is calculated for that node.

[0041] In this embodiment, the calculation process of the starting point observation state discrimination vector satisfies the following formula: ;in, This represents the starting observation state discrimination vector originating from node i. This represents the row vector connecting nodes starting from node i. This represents the transpose of the initial node observability matrix.

[0042] Specifically, if If there is only one element that is 1, then the column containing that element is... corresponding nodes Observable. That is, when the node Inject zero harmonics into the node, and with the node If all connected nodes also satisfy the observability requirement, then the node For newly added indirectly observable nodes, update the elements of the corresponding column v in the node observability matrix. The value is 1. Buses in a distribution network that are not directly carrying loads can be considered as zero-harmonic injection nodes. In addition, for a given bus with a linear load, since its harmonic impedance is usually large, it can also be considered as a zero-harmonic injection node. Because there is no harmonic current injection at a zero-harmonic injection node, the state of other nodes can be inferred using Kirchhoff's Current Law (KCL).

[0043] To avoid situations where the topology is complex, zero-harmonic injection nodes form closed loops, and branch extensions cannot directly reach the boundary, rule 5 is added to S3 above to further determine indirect observability.

[0044] In this embodiment, the indirect observability determination in S3 above may include: taking the remaining unobservable zero-harmonic injection nodes in each node as determination points, obtaining the determination point connection row vector in the topological connection matrix corresponding to the determination point; calculating the difference between the determination point connection row vector and the node observability matrix updated after completing the iterative search determination, to obtain the determination point observation state discrimination vector; when only one element in the determination point observation state discrimination vector is 1, and the node corresponding to the element with 1 is the determination point, the determination point is indirectly observable.

[0045] Specifically, if node Inject zero harmonics into nodes and with nodes If all connected nodes are observable, then according to rule 5, the node... These are indirectly observable nodes. For all remaining unobservable nodes... Execute step S3 and update the node observability matrix and node observability index matrix. Based on the node observability matrix, the observability of each node in the network can be determined. Step S3 serves as a fallback step to protect the algorithm's completeness and robustness across all possible network topologies.

[0046] In this embodiment, when adjusting the layout scheme of harmonic measurement points in S4 above, it may include: using a heuristic search algorithm to adjust the layout scheme of harmonic measurement points, wherein the heuristic search algorithm includes at least one of genetic algorithm, particle swarm optimization algorithm, and simulated annealing algorithm.

[0047] In this embodiment, the termination condition set in S4 includes reaching the maximum number of measurement points.

[0048] The above node layout adjustment process is more suitable for situations with a large number of nodes and complex topological connections.

[0049] Taking a genetic algorithm as an example, a complete node placement scheme is encoded as a binary chromosome, the length of which is equal to the number of network nodes N. A gene bit of 1 indicates that the corresponding node has a measurement device installed, while 0 indicates that it is not installed. Based on a preset population size, an initial set of chromosomes is randomly generated or generated based on a certain heuristic rule (such as prioritizing placement on nodes with high height), forming the first generation population. Its fitness is calculated based on two main objectives: the primary objective is to maximize the number of observable nodes (or determine whether the entire network is observable), and the secondary objective is to minimize the number of devices (i.e., the number of 1s in the chromosome). A feasible fitness function design is to prioritize the scheme to satisfy the observability of the entire network, and then pursue the minimum number of devices under this condition. Subsequently, selection, crossover, and mutation are performed. When the preset number of iterations is reached, or the optimal solution no longer improves after several consecutive generations, the algorithm terminates and outputs the optimal node placement scheme in each generation as the adjustment result of step S4.

[0050] In another alternative implementation, for networks with a small number of nodes and a relatively simple topology, a more direct and gradual adjustment strategy can be adopted to reduce computational complexity. As shown in Figure 2, the core process is as follows: First, based on the current node deployment scheme that does not meet the requirement of network-wide observability, the total number of measurement points is increased by a preset fixed step size (e.g., adding 1 measurement point each time). Next, based on the updated total number of measurement points and combined with a predetermined node generation strategy (e.g., random generation, node degree-based priority), multiple candidate node deployment schemes are systematically enumerated or generated. Subsequently, a complete observability analysis is performed on these schemes in sequence. If none of the schemes tried at this scale can achieve network-wide observability, the total number of measurement points is increased again, and the above process is repeated until a scheme that meets the requirement of network-wide observability is found. This method, by gradually increasing the number of devices and systematically enumerating, avoids the additional overhead that heuristic search algorithms may generate in simple problems. It is suitable for scenarios with limited solution space and where exhaustive search can be performed in a finite number of steps, improving computational efficiency while ensuring optimal results.

[0051] Example 2: Based on the same inventive concept, this invention also provides a harmonic monitoring point deployment system, as shown in Figure 3, including: a direct judgment module, used to perform direct observability judgment on each node based on the topology connection matrix of each node in the distribution network and the initial layout scheme of harmonic measurement points, so as to construct an initial node observability matrix; the initial layout scheme is determined based on the number of basic harmonic measurement points; an indirect judgment module, used to perform indirect node observability judgment starting from observable zero-harmonic injection nodes in the initial node observability matrix, so as to update the node observability matrix, and iteratively search for and judge new observable nodes until there are no new observable zero-harmonic injection nodes; in each round of search... In the search judgment, the newly observable zero-harmonic injection nodes in this round are used as the starting point for the next round of search, and the node observability matrix updated in this round is used as the initial node observability matrix for the next round. The supplementary judgment module is used to perform indirect observability judgment on the remaining unobservable zero-harmonic injection nodes among the nodes after the iterative search judgment is completed, and determine the latest node observability matrix. The scheme determination module is used to determine whether all the nodes are observable based on the latest node observability matrix. If not, the layout scheme of harmonic measurement points is adjusted, and the observability of each node is re-judged until all nodes are observable or the set layout termination condition is met, and the final layout scheme is output.

[0052] In this embodiment, the indirect judgment module is specifically used to: take the observable zero-harmonic injection node in the initial node observability matrix as the starting point, obtain the starting point connection row vector in the topology connection matrix corresponding to the starting point; calculate the difference between the starting point connection row vector and the initial node observability matrix to obtain the starting point observation state discrimination vector; when only one element in the starting point observation state discrimination vector is 1, the node corresponding to the element with the value of 1 is indirectly observable.

[0053] In this embodiment, the calculation process of the starting point observation state discrimination vector satisfies the following formula: ;in, This represents the starting observation state discrimination vector originating from node i. This represents the row vector connecting nodes starting from node i. This represents the transpose of the initial node observability matrix.

[0054] In this embodiment, the supplementary judgment module is specifically used to: take the remaining unobservable zero-harmonic injection nodes in each node as judgment points, obtain the judgment point connection row vector corresponding to the judgment point in the topological connection matrix; calculate the difference between the judgment point connection row vector and the node observability matrix updated after completing the iterative search judgment, and obtain the judgment point observation state discrimination vector; when there is only one element of the judgment point observation state discrimination vector that is 1, and the node corresponding to the element that is 1 is the judgment point, the judgment point is indirectly observable.

[0055] In this embodiment, the direct judgment module is specifically used to: determine the measurement point attributes of each node in the distribution network based on the initial layout scheme of harmonic measurement points, and construct a measurement point matrix; calculate the product of the topology connection matrix of each node in the distribution network and the measurement point matrix to obtain the node observability matrix; extract the observability of each node based on the node observability matrix, and construct an initial node observability matrix based on the observability.

[0056] In this embodiment, the initial node observability matrix satisfies the following formula: ; ; ; ; ; ; ;in, Let represent the initial node observability matrix. Let i represent the observability of node i, where i = 1, ..., n, and n is the total number of nodes. , indicating that node i is observable; , indicating that node i is not observable; Represents the observable order matrix of nodes. Represents a node A considerable number of times; Represents the measurement point matrix. =1 indicates that node i is a measurement point. This represents the topological connectivity matrix.

[0057] In this embodiment, the scheme determination module is specifically used to: adjust the layout scheme of harmonic measurement points using a heuristic search algorithm, wherein the heuristic search algorithm includes at least one of genetic algorithm, particle swarm optimization algorithm, and simulated annealing algorithm.

[0058] As shown in Figure 4, Embodiment 3 of the present invention also provides an electronic device, which may be a computer device, a microcontroller device, a smart mobile device, etc. The electronic device in this embodiment may include a processor, a memory, a transceiver component, etc. The memory, processor, and transceiver component are connected via a bus; the memory can be used to store executable programs, and an exemplary executable program may include instructions; the processor is used to execute the instructions stored in the memory. The memory can also be used to store data, which can be accessed and / or modified when instructions are executed.

[0059] The processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, and it is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the storage medium to implement the corresponding method flow or corresponding function, so as to implement the steps of the harmonic monitoring point placement method in the above embodiments.

[0060] Example 4, based on the same inventive concept, also provides a readable storage medium, specifically an electronic device readable storage medium (Memory). This readable storage medium is a memory device within an electronic device used to store programs and data. It is understood that the storage medium here can include both built-in storage media within the electronic device and extended storage media supported by the electronic device. The storage medium provides storage space, which stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more executable programs (including program code). It should be noted that the storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. Loading and executing one or more instructions stored in the storage medium by the processor can implement the steps of the harmonic monitoring point placement method described in the above embodiments.

[0061] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0062] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more blocks of the flowchart illustrations and / or one or more blocks of the block diagrams.

[0063] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams.

[0064] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0065] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit its scope of protection. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that after reading the present invention, they can still make various changes, modifications or equivalent substitutions to the specific implementation methods of the application, but these changes, modifications or equivalent substitutions are all within the scope of protection of the claims of the present invention.

Claims

1. A method for harmonic monitoring point placement, characterized in that, include: Based on the topology connection matrix of each node in the distribution network and the initial layout scheme of harmonic measurement points, the observability of each node is directly judged to construct an initial node observability matrix. The initial node placement scheme is determined based on the number of basic harmonic measurement points. Starting with the observable zero-harmonic injection nodes in the initial node observability matrix, node indirect observability is judged to update the node observability matrix. The search for new observable nodes is iteratively performed until there are no new observable zero-harmonic injection nodes. In each round of search and judgment, the new observable zero-harmonic injection nodes in this round are used as the starting point for the next round of search, and the node observability matrix updated in this round is used as the initial node observability matrix for the next round. After completing the iterative search judgment, the indirect observability judgment is performed on the remaining unobservable zero harmonic injection nodes in each node to determine the latest node observability matrix. Based on the latest node observability matrix, determine whether all nodes are observable. If not, adjust the layout of harmonic measurement points and re-determine the observability of each node until all nodes are observable or the set layout termination condition is met, and output the final layout scheme.

2. The method as described in claim 1, characterized in that, The step of determining the indirect observability of nodes, starting from the observable zero-harmonic injection node in the initial node observability matrix, includes: obtaining the starting point connection row vector in the topology connection matrix corresponding to the starting point, using the observable zero-harmonic injection node in the initial node observability matrix as the starting point; calculating the difference between the starting point connection row vector and the initial node observability matrix to obtain the starting point observation state discrimination vector; and determining the node indirect observability corresponding to the element that is 1 when only one element in the starting point observation state discrimination vector is 1.

3. The method as described in claim 2, characterized in that, The calculation process of the starting observation state discrimination vector satisfies the following formula: ;in, This represents the starting observation state discrimination vector originating from node i. This represents a row vector starting from node i. This represents the transpose of the initial node observability matrix.

4. The method according to any one of claims 1-3, characterized in that, The indirect observability determination of the remaining unobservable zero-harmonic injection nodes in each node includes: taking the remaining unobservable zero-harmonic injection nodes in each node as determination points, obtaining the determination point connection row vector in the topological connection matrix corresponding to the determination point; calculating the difference between the determination point connection row vector and the node observability matrix updated after completing the iterative search determination, to obtain the determination point observation state discrimination vector; when only one element in the determination point observation state discrimination vector is 1, and the node corresponding to the element with 1 is the determination point, the determination point is indirectly observable.

5. The method according to any one of claims 1-3, characterized in that, The method based on the topology connection matrix of each node in the distribution network and the initial layout scheme of harmonic measurement points, and performing direct observability judgment on each node to construct an initial node observability matrix, includes: determining the measurement point attributes of each node in the distribution network based on the initial layout scheme of harmonic measurement points, and constructing a measurement point matrix; calculating the product of the topology connection matrix of each node in the distribution network and the measurement point matrix to obtain a node observability frequency matrix; extracting the observability of each node based on the node observability frequency matrix, and constructing an initial node observability matrix based on the observability.

6. The method as described in claim 5, characterized in that, The initial node observability matrix satisfies the following formula: ； ； ； ； ； ； ;in, Let represent the initial node observability matrix. Indicate the observability of node i. =1,...,n, where n is the total number of nodes; , indicating that node i is observable; , indicating that node i is not observable; Represents the matrix of observable times of nodes. Represents a node A considerable number of times; Represents the measurement point matrix. =1 indicates that node i is a measurement point. This represents the topological connectivity matrix.

7. The method according to any one of claims 1-3, characterized in that, The method for adjusting the layout of harmonic measurement points includes: using a heuristic search algorithm to adjust the layout of harmonic measurement points, wherein the heuristic search algorithm includes at least one of genetic algorithm, particle swarm optimization algorithm, and simulated annealing algorithm.

8. A harmonic monitoring point deployment system, characterized in that, include: The direct judgment module is used to make a direct observability judgment on each node based on the topology connection matrix of each node in the distribution network and the initial layout scheme of harmonic measurement points, so as to construct an initial node observability matrix; the initial layout scheme is determined based on the number of basic harmonic measurement points. The indirect judgment module is used to perform indirect observability judgment of nodes, starting from observable zero-harmonic injection nodes in the initial node observability matrix, to update the node observability matrix, and iteratively search for and judge new observable nodes until there are no new observable zero-harmonic injection nodes; in each round of search and judgment, the new observable zero-harmonic injection nodes in this round are used as the starting point of the next round of search, and the node observability matrix updated in this round is used as the initial node observability matrix for the next round; The supplementary judgment module is used to perform indirect observability judgment on the remaining unobservable zero harmonic injection nodes in each node after the iterative search judgment is completed, and to determine the latest node observability matrix. The scheme determination module is used to determine whether all nodes are observable based on the latest node observability matrix. If not, the layout scheme of harmonic measurement points is adjusted, and the observability of each node is re-evaluated until all nodes are observable or the set layout termination condition is met, and the final layout scheme is output.

9. The system as described in claim 8, characterized in that, The indirect judgment module is specifically used to: take the observable zero harmonic injection node in the initial node observability matrix as the starting point, and obtain the starting point connection row vector in the topology connection matrix corresponding to the starting point; Calculate the difference between the starting point connecting row vector and the initial node observability matrix to obtain the starting point observation state discrimination vector; when only one element in the starting point observation state discrimination vector is 1, the node corresponding to the element with the value of 1 is indirectly observable.

10. The system as described in claim 9, characterized in that, The calculation process of the starting observation state discrimination vector satisfies the following formula: ;in, This represents the starting observation state discrimination vector originating from node i. This represents a row vector starting from node i. This represents the transpose of the initial node observability matrix.

11. The system according to any one of claims 8-10, characterized in that, The supplementary judgment module is specifically used to: take the remaining unobservable zero-harmonic injection nodes in each node as judgment points, obtain the judgment point connection row vector corresponding to the judgment point in the topological connection matrix; calculate the difference between the judgment point connection row vector and the node observability matrix updated after completing the iterative search judgment, and obtain the judgment point observation state discrimination vector; when there is only one element of the judgment point observation state discrimination vector that is 1, and the node corresponding to the element that is 1 is the judgment point, the judgment point is indirectly observable.

12. The system according to any one of claims 8-10, characterized in that, The direct judgment module is specifically used for: determining the measurement point attributes of each node in the distribution network based on the initial layout scheme of harmonic measurement points, and constructing a measurement point matrix; calculating the product of the topology connection matrix of each node in the distribution network and the measurement point matrix to obtain the node observability matrix; extracting the observability of each node based on the node observability matrix, and constructing an initial node observability matrix based on the observability.

13. The system as described in claim 12, characterized in that, The initial node observability matrix satisfies the following formula: ； ； ； ； ； ； ;in, Let represent the initial node observability matrix. Indicate the observability of node i. =1,...,n, where n is the total number of nodes; , indicating that node i is observable; , indicating that node i is not observable; Represents the matrix of observable times of nodes. Represents a node A considerable number of times; Represents the measurement point matrix. =1 indicates that node i is a measurement point. This represents the topological connectivity matrix.

14. The system according to any one of claims 8-10, characterized in that, The scheme determination module is specifically used to: adjust the layout scheme of harmonic measurement points using a heuristic search algorithm, wherein the heuristic search algorithm includes at least one of genetic algorithm, particle swarm optimization algorithm, and simulated annealing algorithm.

15. An electronic device, characterized in that, include: At least one processor and memory; The memory and processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, a harmonic monitoring point placement method as described in any one of claims 1 to 7 is implemented.

16. A readable storage medium, characterized in that, It contains an execution program, which, when executed, implements a harmonic monitoring point placement method as described in any one of claims 1 to 7.

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