CN113541134A - Method for electrical topology identification, controller and power acquisition system - Google Patents
Method for electrical topology identification, controller and power acquisition system Download PDFInfo
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- CN113541134A CN113541134A CN202110830038.1A CN202110830038A CN113541134A CN 113541134 A CN113541134 A CN 113541134A CN 202110830038 A CN202110830038 A CN 202110830038A CN 113541134 A CN113541134 A CN 113541134A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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- H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
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Abstract
The invention discloses a method for electrical topology identification, a controller and an electric power acquisition system. The power acquisition system comprises a transformer, branch nodes and an electric energy meter, and the method comprises the following steps: respectively acquiring parameter values of the transformer, the branch node and the electric energy meter; determining a first correlation between the parameter values of the transformer and the parameter values of the branch nodes; determining a first topological relation between the transformer and the branch node according to the first correlation; determining a terminal branch node in the branch nodes according to the first topological relation; determining a second correlation of the parameter value of the electric energy meter and the parameter value of the tail end branch node; determining a second topological relation between the electric energy meter and the tail end branch node according to the second correlation; and determining the topological relation of the power acquisition system according to the first topological relation and the second topological relation. The invention does not need complex parameters, has less calculation amount and higher precision, thereby leading the efficiency of topology identification to be higher.
Description
Technical Field
The invention relates to the technical field of power distribution networks, in particular to a method, a controller and a power acquisition system for electrical topology identification.
Background
The automation of electric topology recognition of the power distribution network is an effective technical basis for improving the refined management of a power distribution station area and providing digital support for power distribution network planning, construction, operation and inspection and customer service. In the processes of new construction, reconstruction, extension, operation, maintenance and repair of the intelligent substation, the change of distribution equipment and lines in a distribution network can cause the change of the topological relation of a distribution network in a transformer area. Therefore, it is necessary to identify and control the network topology relationship of the whole distribution area network system in real time, improve the fine management level of the distribution area, and further support the work of segment line loss management, distribution area fault study and judgment, leakage condition monitoring and the like. In the prior art, a distribution network area topological relation is usually established through manually maintained files, so that the problems of insufficient refinement degree, inconsistent graph reality, lack of intelligent identification means and the like exist, the refinement and intelligent management requirements of the distribution network area are difficult to meet, and the efficiency of electrical topology identification of the distribution network is low.
Disclosure of Invention
The embodiment of the invention aims to provide a method, a controller and a power acquisition system for electrical topology identification, which are used for solving the problem of low efficiency of electrical topology identification of a power distribution network in the prior art.
In order to achieve the above object, a first aspect of the present invention provides a method for electrical topology identification, which is applied to a power acquisition system, wherein the power acquisition system comprises a transformer, a branch node and an electric energy meter, and the method comprises:
respectively acquiring parameter values of the transformer, the branch node and the electric energy meter;
determining a first correlation between the parameter values of the transformer and the parameter values of the branch nodes;
determining a first topological relation between the transformer and the branch node according to the first correlation;
determining a terminal branch node in the branch nodes according to the first topological relation;
determining a second correlation of the parameter value of the electric energy meter and the parameter value of the tail end branch node;
determining a second topological relation between the electric energy meter and the tail end branch node according to the second correlation;
and determining the topological relation of the power acquisition system according to the first topological relation and the second topological relation.
In an embodiment of the present invention, the obtaining the parameter values of the transformer, the branch node, and the electric energy meter respectively includes:
and respectively acquiring voltage series values of the transformer, the branch node and the electric energy meter within set time.
In an embodiment of the invention, determining the first topological relation of the transformer to the branch node according to the first correlation comprises:
obtaining a first correlation coefficient of the parameter value of each branch node and the parameter value of the transformer;
obtaining a second correlation coefficient between parameter values of the branch nodes;
determining a core branch node in the branch nodes according to the first correlation coefficient and the second correlation coefficient;
distributing the rest branch nodes in the branch nodes to corresponding core branch nodes according to the second correlation coefficient;
and layering the rest branch nodes corresponding to each core branch node according to the second correlation coefficient to obtain a first topological relation.
In an embodiment of the present invention, determining a core branch node among the branch nodes according to the first correlation coefficient and the second correlation coefficient includes:
judging whether a first correlation coefficient of the parameter value of the branch node and the parameter value of the transformer is larger than a first threshold value or not;
determining the branch node as an alternative branch node under the condition that the first correlation coefficient is larger than a first threshold value;
and eliminating the pseudo branch nodes in the alternative branch nodes according to the first correlation coefficient and the second correlation coefficient to obtain the core branch nodes.
In the embodiment of the present invention, the removing the pseudo branch node from the candidate branch nodes according to the first correlation coefficient and the second correlation coefficient to obtain the core branch node includes:
judging whether a second correlation number between parameter values of two alternative branch nodes exists in the alternative branch nodes is larger than a second threshold value;
and under the condition that a second correlation number between the parameter values of the two candidate branch nodes is larger than a second threshold value, the candidate branch nodes with smaller first correlation coefficients with the parameter values of the transformer are removed.
In an embodiment of the invention, assigning remaining ones of the branch nodes to corresponding core branch nodes according to the second correlation coefficient comprises:
acquiring a second correlation coefficient between the parameter value of the target residual branch node and the parameter value of each core branch node;
determining the core branch node with the maximum second correlation number with the parameter values of the target residual branch nodes as a target core branch node;
and distributing the target residual branch node to the target core branch node.
In an embodiment of the invention, determining the second topological relation of the power meter to the end branch node based on the second correlation comprises:
respectively calculating a third correlation coefficient between the parameter value of the target electric energy meter and the parameter value of each tail end branch node;
determining the tail end branch node with the maximum third phase relation number with the parameter value of the target electric energy meter as a target tail end branch node;
and distributing the target electric energy meter to the target tail end branch node.
In an embodiment of the present invention, the first correlation and the second correlation satisfy the following formula:
wherein, Vx，VyA voltage series of values for any two parameters;
is a Vx，VyPearson's correlation coefficient; cov (V)x，Vy) Is a VxAnd VyThe covariance between;
is a VxThe variance of (a);
is a VYThe variance of (c).
A second aspect of the invention provides a controller comprising a method for electrical topology identification as described above.
A third aspect of the present invention provides a power collecting system, comprising:
the transformer is used for acquiring data of the whole transformer area of the power acquisition system;
the branch node is provided with a first low-voltage monitoring unit which is used for acquiring voltage data of the branch node and transmitting the voltage data to the transformer through power line carrier communication;
the electric energy meter is provided with a second low-voltage monitoring unit, and the second low-voltage monitoring unit is used for measuring and collecting voltage data of the electric energy meter and transmitting the voltage data to the branch node;
the controller is connected with the transformer, the branch node and the electric energy meter and used for obtaining parameter values of the transformer, the branch node and the electric energy meter.
According to the technical scheme, the parameter values of the transformer, the branch nodes and the electric energy meter are respectively acquired, the first topological relation between each branch node and the transformer is determined, and then the second topological relation between the electric energy meter and the tail end branch node is determined, so that the electric network topological relation of the whole electric power acquisition system is formed. The invention does not need complex parameters, has less calculation amount and higher precision, thereby leading the efficiency of topology identification to be higher.
Additional features and advantages of embodiments of the invention will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the embodiments of the invention without limiting the embodiments of the invention. In the drawings:
fig. 1 is a schematic flow chart of a method for electrical topology identification according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of a method for determining a first topological relation according to an embodiment of the present invention;
fig. 3 is a flowchart illustrating a method for determining a second topological relation according to an embodiment of the present invention;
FIG. 4 is a block diagram of a controller provided by an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electric power collection system according to an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating embodiments of the invention, are given by way of illustration and explanation only, not limitation.
It should be noted that if directional indications (such as up, down, left, right, front, and back … …) are referred to in the embodiments of the present application, the directional indications are only used to explain the relative positional relationship between the components, the movement situation, and the like in a specific posture (as shown in the drawings), and if the specific posture is changed, the directional indications are changed accordingly.
In addition, if there is a description of "first", "second", etc. in the embodiments of the present application, the description of "first", "second", etc. is for descriptive purposes only and is not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present application.
Fig. 1 is a schematic flowchart of a method for electrical topology identification according to an embodiment of the present invention. Referring to fig. 1, an embodiment of the present invention provides a method for electrical topology identification, which is applied to a power acquisition system including a transformer, a branch node, and an electric energy meter, and the method may include the following steps.
In step S11, parameter values of the transformer, the branch node, and the electric energy meter are acquired, respectively. In the embodiment of the invention, the power supply path of the power acquisition system generally supplies power according to a plurality of topological levels, such as a transformer, a plurality of branch nodes, a plurality of electric energy meters and the like, so that the distribution network electrical topological relation of the power acquisition system can comprise the transformer, the branch nodes and the electric energy meters. Since the power collection system includes a plurality of branch nodes and electric energy meters, it is necessary to identify a topological diagram of the power collection system in order to determine the branch nodes and the electric energy meters of the same line. According to the embodiment of the invention, the correlation among the parameter values is determined by acquiring the parameter values of the transformer, the branch node and the electric energy meter, so that the topology identification is carried out.
In one example, the parameter values may be a voltage series of values. The transformer may include a concentrator, a Central Coordinator (CCO), a high-speed carrier module, and a three-phase voltage series value collecting device, so that the voltage series value of the transformer may be collected by the three-phase voltage series value collecting device. Each branch node end can be provided with a Low-voltage Terminal Unit (LTU) and a high-speed carrier communication module, and the LTU can accurately detect short-circuit faults, grounding faults, power cut and transmission, three-phase voltage, three-phase current, active power, reactive power, zero-sequence voltage, zero-sequence current and the like of a line. Accordingly, a corresponding voltage series value may be collected by the LTU provided at each branch node. The terminal of each electric energy meter has the capability of collecting voltage series values and the capability of information communication, for example, an LTU can be arranged at each branch node. Therefore, the voltage series value can be acquired through each electric energy meter terminal.
In the embodiment of the invention, the data acquisition synchronization of the transformer, the branch node and the electric energy meter is required to be ensured in the parameter value acquisition process, so that the time synchronization among parameter value acquisition places can be realized by utilizing the self time synchronization function of the high-speed carrier communication module. The acquisition period of the parameter values may be determined according to the data communication capabilities and storage capabilities of the acquisition points, e.g. 5, 10, 15, 30, 60 minutes, etc. may be selected as acquisition periods.
In step S12, a first correlation between the parameter values of the transformer and the parameter values of the branch nodes is determined. Embodiments of the invention may comprise a plurality of branch nodes, and the first correlation may comprise a correlation of a parameter value of the transformer and a parameter value of the branch node and a correlation of the branch nodes with each other. In one example, the correlation between each parameter value may be determined by a correlation coefficient. The correlation coefficient is a quantity for researching the degree of linear relation between variables, and various calculation modes of the correlation coefficient can be adopted according to different research objects. For example, embodiments of the present invention may employ Pearson correlation coefficients to measure the correlation between each parameter value. The pearson correlation coefficient is between-1 and +1, which is one of the methods to measure the correlation between two parameter values. The correlation coefficient of the parameter value of the transformer and the parameter value of each branch node and the correlation coefficient between the parameter values of every two branch nodes can be respectively calculated by adopting the Pearson correlation coefficient.
In step S13, a first topological relationship of the transformer to the branch node is determined according to the first correlation. In the embodiment of the present invention, by determining the first correlation between the parameter values of the transformer and the branch nodes and the parameter values of the branch nodes, the topological relationship between the transformer and each branch node, that is, the first topological relationship, may be obtained. Specifically, the core branch node of the first layer may be determined according to the correlation between the parameter value of the transformer and the parameter value of each branch node. Further, according to the first correlation between the remaining branch nodes and each core branch node, the core branch nodes corresponding to the remaining branch nodes are determined. Thus, clustering processing can be performed according to the first correlation, and the core branch nodes and the remaining branch nodes corresponding to each core branch node are determined. The remaining branch nodes are branch nodes other than the core branch node. Meanwhile, the hierarchy of the topological relation can be determined according to the network hierarchy of the power acquisition system. For example, if the branch node is two layers, the first layer is a core branch node (first layer branch node), and the second layer is a remaining branch node (second layer branch node); if the branch node is three layers, the first layer is a core branch node (first layer branch node), the second layer is a second layer branch node, the third layer is a third layer branch node, and the second layer branch node and the third layer branch node are the rest branch nodes. In the case of including three and more levels of branch nodes, the determination of the second level branch node may refer to the determination method of the core branch node.
In one example, the power harvesting system includes 1 transformer and 100 branch nodes, which need to be divided into two layers. Therefore, the correlation between the parameter values of the 100 branch nodes and the parameter values of the transformer can be calculated to determine the core branch node. For example, a branch node having a first correlation greater than a first threshold is determined to be a core branch node. Assuming that the first layer includes 10 core branch nodes, the number of the remaining branch nodes is 90, the 90 remaining branch nodes are respectively correlated with the 10 core branch nodes, and the core branch node having the maximum correlation with the target remaining branch node is determined as the corresponding target core branch node. Thereby distributing the remaining branch nodes to the corresponding core branch nodes, and forming 10 different branch nodes.
In another example, the power harvesting system includes 1 transformer and 100 branch nodes, which need to be divided into three layers. Therefore, the correlation between the parameter values of the 100 branch nodes and the parameter values of the transformer can be calculated to determine the core branch node. For example, a branch node having a first correlation greater than a first set value is determined as a core branch node. Assuming that the first layer includes 10 core branch nodes, the number of the remaining branch nodes is 90, the 90 remaining branch nodes are respectively correlated with the 10 core branch nodes, and the core branch node having the maximum correlation with the target remaining branch node is determined as the corresponding target core branch node. Thereby distributing the remaining branch nodes to the corresponding core branch nodes, and forming 10 different branch nodes. Further, for each cluster of branch nodes, the remaining branch nodes of the branch nodes having the first correlation with the parameter of the target core branch node larger than the second set value are determined as second-layer branch nodes, and the remaining branch nodes are determined as third-layer branch nodes, that is, end branch nodes.
In the embodiment of the invention, the branch nodes can be divided into a plurality of layers in a mode of clustering first and then layering, so that the first topological relation comprising the transformer and the branch nodes is obtained.
In step S14, an end branch node among the branch nodes is determined according to the first topological relation. In an embodiment of the present invention, a last layer of branch nodes of the branch nodes in the first topological relation is determined as an end branch node, so as to establish a second topological relation with the electric energy meter. Thus, the calculation amount can be reduced, and the calculation efficiency can be improved.
In step S15, a second correlation of the parameter values of the power meter with the parameter values of the end branch node is determined. In an embodiment of the invention, the second correlation is a correlation of a parameter value of the power meter with a parameter value of the end branch node. In one example, the correlation between each parameter value may be determined by a correlation coefficient. The correlation coefficient is a quantity for researching the degree of linear relation between variables, and various calculation modes of the correlation coefficient can be adopted according to different research objects. For example, embodiments of the present invention may employ Pearson correlation coefficients to measure the correlation between each parameter value. The pearson correlation coefficient is between-1 and +1, which is one of the methods to measure the correlation between two parameter values. The correlation coefficient between the parameter value of the electric energy meter and the parameter value of the tail branch node can be respectively calculated by adopting the Pearson correlation coefficient.
In step S16, a second topological relationship of the power meter to the end branch node is determined based on the second correlation.
In an embodiment of the invention, the electrical energy meter is electrically connected to an end one of the branch nodes, and thus a second topological relationship comprising the electrical energy meter and the end branch node may be determined by a second correlation of the parameter values of the electrical energy meter and the parameter values of the end branch node. In one example, a third correlation coefficient between the parameter value of the target electric energy meter and the parameter value of each end branch node is calculated respectively, and the end branch node with the largest third phase relation number with the parameter value of the target electric energy meter is determined as the target end branch node, that is, the end branch node with the largest correlation with the target electric energy meter is selected. And then distributing the target electric energy meter to the corresponding target tail end branch node. Thus, the electric energy meter can be corresponding to the tail end branch node, and a second topological relation is formed.
In step S17, a topological relation of the power collection system is determined according to the first topological relation and the second topological relation. In the embodiment of the invention, the first topological relation comprises the topological relation between the transformer and the branch node, the second topological relation comprises the topological relation between the tail end branch node and the electric energy meter, and the complete topological relation of the power acquisition system can be obtained by combining the first topological relation and the second topological relation.
According to the technical scheme, the parameter values of the transformer, the branch nodes and the electric energy meter are respectively acquired, the first topological relation between each branch node and the transformer is determined, and then the second topological relation between the electric energy meter and the tail end branch node is determined, so that the electric network topological relation of the whole electric power acquisition system is formed. The invention does not need complex parameters, has less calculation amount and higher precision, thereby leading the efficiency of topology identification to be higher.
In an embodiment of the present invention, the step S11 of respectively obtaining the parameter values of the transformer, the branch node and the electric energy meter may include:
and respectively acquiring voltage series values of the transformer, the branch node and the electric energy meter within set time.
In particular, the parameter values of the embodiment of the present invention may be voltage series values. Therefore, the embodiment of the invention can respectively collect the voltage series values of the transformer, the branch node and the electric energy meter in the set time, and determine the correlation among the voltage series values of each parameter, thereby carrying out topology identification.
In one example, the parameter values may be a voltage series of values, assuming there are N sampling points employed. The transformer can include concentrator, CCO, high-speed carrier module and three-phase voltage serial value collection equipment, can gather the voltage serial value of transformer like this through three-phase voltage serial value collection equipment. For example, the series of values of the voltage picked up at the transformer is VTX＝[VTX，1，VTX，2，...，VTX，N]To indicate (voltage phase A, B, C information is omitted here for ease of expression). Each branch node end can be provided with an LTU and a high-speed carrier communication module, and the corresponding voltage series value can be acquired through the LTU arranged at each branch node. For example, the series of voltage values collected at the ith branch node is represented by VPC，i＝[VPC，i，1，VPC，i，2，...，VPC，i，N]And (4) showing. The terminal of each electric energy meter has the capacity of collecting the voltage series value and the capacity of information communication, so that the voltage series value can be acquired through each electric energy meter terminal. For example, the voltage series collected at the jth electric energy meter is represented by VM，j＝[VM，j，1，VM，j，2，...，VM，j，N]And (4) showing.
In the embodiment of the invention, the data acquisition synchronization of the transformer, the branch node and the electric energy meter is required to be ensured in the parameter value acquisition process, so that the time synchronization among parameter value acquisition places can be realized by utilizing the self time synchronization function of the high-speed carrier communication module. The acquisition period of the parameter values may be determined according to the data communication capabilities and storage capabilities of the acquisition points, e.g. 5, 10, 15, 30, 60 minutes, etc. may be selected as acquisition periods.
Fig. 2 is a flowchart illustrating a method for determining a first topological relation according to an embodiment of the present invention. Referring to fig. 2, in the embodiment of the present invention, the step S13 of determining the first topological relationship between the transformer and the branch node according to the first correlation may include:
step S21, obtaining a first correlation coefficient of the parameter value of each branch node and the parameter value of the transformer;
step S22, obtaining a second correlation coefficient between the parameter values of the branch nodes;
step S23, determining a core branch node in the branch nodes according to the first correlation coefficient and the second correlation coefficient;
step S24, distributing the rest branch nodes in the branch nodes to corresponding core branch nodes according to the second correlation coefficient;
and step S25, layering the remaining branch nodes corresponding to each core branch node according to the second correlation coefficient to obtain the first topological relation.
In the embodiment of the present invention, the core branch node of the first layer may be determined according to the correlation between the parameter value of the transformer and the parameter value of each branch node. Further, according to the first correlation between the remaining branch nodes and each core branch node, the core branch nodes corresponding to the remaining branch nodes are determined. In an embodiment of the present invention, the correlation between each parameter value may be determined by a correlation coefficient. The correlation coefficient of the embodiment of the invention comprises a first correlation coefficient and a second correlation coefficient, wherein the first correlation coefficient is a correlation coefficient between the parameter value of each branch node and the parameter value of the transformer, and the second correlation coefficient is a correlation coefficient between the parameter values of the branch nodes. And performing clustering processing according to the first correlation coefficient and the second correlation coefficient to determine the core branch node. Further, the rest branch nodes in the branch nodes are distributed to the corresponding core branch nodes according to the second correlation coefficient. The remaining branch nodes are branch nodes other than the core branch node. Meanwhile, the hierarchy of the topological relation can be determined according to the network hierarchy of the power acquisition system. For example, if the branch node is two layers, the first layer is a core branch node (first layer branch node), and the second layer is a remaining branch node (second layer branch node); if the branch node is three layers, the first layer is a core branch node (first layer branch node), the second layer is a second layer branch node, the third layer is a third layer branch node, and the second layer branch node and the third layer branch node are the rest branch nodes. In the case of including three and more levels of branch nodes, the determination of the second level branch node may refer to the determination method of the core branch node. That is to say, in the embodiment of the present invention, the branch nodes may be divided into multiple layers in a manner of clustering first and then layering, so as to obtain the first topological relationship including the transformer and the branch nodes.
In an embodiment of the present invention, the step S23 of determining a core branch node among the branch nodes according to the first correlation coefficient and the second correlation coefficient may include:
judging whether a first correlation coefficient of the parameter value of the branch node and the parameter value of the transformer is larger than a first threshold value or not;
determining the branch node as an alternative branch node under the condition that the first correlation coefficient is larger than a first threshold value;
and eliminating the pseudo branch nodes in the alternative branch nodes according to the first correlation coefficient and the second correlation coefficient to obtain the core branch nodes.
Specifically, the core branch node, i.e., the first-layer branch node, first calculates a first correlation coefficient between the parameter values of all the branch nodes and the parameter values of the transformer by using the pearson correlation coefficient. And judging whether a first correlation coefficient between the parameter value of the branch node and the parameter value of the transformer is larger than a first threshold value, wherein the first threshold value can be an empirical value calculated according to the measurement of an actual application scene. And if the first correlation coefficient of the parameter value of the branch node and the parameter value of the transformer is larger than the first threshold value, the correlation between the branch node and the transformer is larger. However, there may be two branch nodes with larger correlation, and the first correlation coefficient of the transformer is larger than the first threshold, and at this time, only one branch node is a core branch node, and the other branch node is a dummy branch node. Therefore, the branch node with the first correlation coefficient larger than the first threshold value can be determined as the candidate branch node, and then the pseudo branch node in the candidate branch node is proposed to obtain the final core branch node. In this way, the accuracy of topology identification can be made higher.
In an embodiment of the present invention, culling the pseudo branch nodes in the candidate branch nodes according to the first correlation coefficient and the second correlation coefficient to obtain the core branch node may include:
judging whether a second correlation number between parameter values of two alternative branch nodes exists in the alternative branch nodes is larger than a second threshold value;
and under the condition that a second correlation number between the parameter values of the two candidate branch nodes is larger than a second threshold value, the candidate branch nodes with smaller first correlation coefficients with the parameter values of the transformer are removed.
Specifically, there may be two candidate branch nodes in the candidate branch nodes whose correlation between the parameter values is large, that is, the second correlation number is greater than the second threshold value. Therefore, one of the two branch nodes with larger correlation is necessarily a dummy branch node. The second threshold value can be obtained according to actual numerical measurement and experimental verification. And determining the candidate branch node with a smaller first correlation coefficient with the parameter value of the transformer as a pseudo branch node of a first layer, removing the pseudo branch node, and determining the candidate branch node with a larger first correlation coefficient with the parameter value of the transformer as a core branch node. This can improve the accuracy of topology identification.
In an embodiment of the present invention, the step S24 of allocating the remaining ones of the branch nodes to the corresponding core branch nodes according to the second correlation coefficients may include:
acquiring a second correlation coefficient between the parameter value of the target residual branch node and the parameter value of each core branch node;
determining the core branch node with the maximum second correlation number with the parameter values of the target residual branch nodes as a target core branch node;
and distributing the target residual branch node to the target core branch node.
Specifically, after the core branch nodes are determined, the remaining branch nodes need to be clustered, that is, the remaining branch nodes in the branch nodes are allocated to the corresponding core branch nodes according to the second correlation coefficient. The remaining branch nodes are branch nodes other than the core branch node. And acquiring a second correlation coefficient between the parameter of the target residual branch node and the parameter value of each core branch node, and selecting the core branch node with the largest second correlation number as the target core branch node, namely selecting the core branch node with the largest correlation as the target core branch node, so that the target residual branch node is distributed to the target core branch node. This ensures that each remaining branch node is in a cluster with the core branch node having the greatest correlation.
Fig. 3 is a flowchart illustrating a method for determining a second topological relation according to an embodiment of the present invention. Referring to fig. 3, the step S16 of determining the second topological relation between the electric energy meter and the end branch node according to the second correlation may include:
step S31, respectively calculating a third correlation coefficient between the parameter value of the target electric energy meter and the parameter value of each tail end branch node;
step S32, determining the tail end branch node with the maximum third phase relation number with the parameter value of the target electric energy meter as a target tail end branch node;
and step S33, distributing the target electric energy meter to the target tail end branch node.
In an embodiment of the invention, the electrical energy meter is electrically connected to an end one of the branch nodes, and thus a second topological relationship comprising the electrical energy meter and the end branch node may be determined by a second correlation of the parameter values of the electrical energy meter and the parameter values of the end branch node. In one example, a third correlation coefficient between the parameter value of the target electric energy meter and the parameter value of each end branch node is calculated respectively, and the end branch node with the largest third phase relation number with the parameter value of the target electric energy meter is determined as the target end branch node, that is, the end branch node with the largest correlation with the target electric energy meter is selected. And then distributing the target electric energy meter to the corresponding target tail end branch node. Thus, the electric energy meter can be corresponding to the tail end branch node, and a second topological relation is formed.
In an embodiment of the present invention, the first correlation and the second correlation may satisfy the following formulas:
wherein, Vx，VyA voltage series of values for any two parameters;
is a Vx，VyPearson's correlation coefficient; cov (V)x，Vy) Is a VxAnd VyThe covariance between;
is a VxThe variance of (a);
is a VYThe variance of (c).
In particular, embodiments of the present invention may utilize pearson correlation coefficients to measure the correlation between each parameter value. The pearson correlation coefficient is between-1 and +1, which is one of the methods to measure the correlation between two parameter values. The correlation coefficient between each two parameter values can be calculated separately using the pearson correlation coefficient. VxAnd VyMay be a voltage series of values of at least one parameter of the transformer, the branch node and the electric energy meter, and the pearson correlation coefficient between the two parameter values is a quotient of a covariance and a standard deviation between the two parameter values. Wherein, cov (V)x，Vy)＝E[(Vx-E(Vx))·(VY-E(VY))]Is denoted by VxAnd VyThe covariance between;
and
respectively represent variable VxAnd VYThe variance of (c).
Fig. 4 is a block diagram of a controller provided by an embodiment of the present invention. Referring to fig. 4, the present invention provides a controller applied to a power acquisition system, including the above method for electrical topology identification. In an embodiment of the present invention, the power harvesting system includes a transformer, a branch node, and an electrical energy meter, and the controller may include a processor 410 and a memory 420. The memory 420 may store instructions that, when executed by the processor 410, may cause the processor 410 to perform the methods for electrical topology identification described in the previous embodiments.
Specifically, in an embodiment of the present invention, the processor 410 is configured to:
respectively acquiring parameter values of the transformer, the branch node and the electric energy meter;
determining a first correlation between the parameter values of the transformer and the parameter values of the branch nodes;
determining a first topological relation between the transformer and the branch node according to the first correlation;
determining a terminal branch node in the branch nodes according to the first topological relation;
determining a second correlation of the parameter value of the electric energy meter and the parameter value of the tail end branch node;
determining a second topological relation between the electric energy meter and the tail end branch node according to the second correlation;
and determining the topological relation of the power acquisition system according to the first topological relation and the second topological relation.
Further, the processor 410 is further configured to:
respectively obtaining parameter values of the transformer, the branch node and the electric energy meter comprises the following steps:
and respectively acquiring voltage series values of the transformer, the branch node and the electric energy meter within set time.
Further, the processor 410 is further configured to:
determining a first topological relationship of the transformer to the branch node according to the first correlation includes:
obtaining a first correlation coefficient of the parameter value of each branch node and the parameter value of the transformer;
obtaining a second correlation coefficient between parameter values of the branch nodes;
determining a core branch node in the branch nodes according to the first correlation coefficient and the second correlation coefficient;
distributing the rest branch nodes in the branch nodes to corresponding core branch nodes according to the second correlation coefficient;
and layering the rest branch nodes corresponding to each core branch node according to the second correlation coefficient to obtain a first topological relation.
Further, the processor 410 is further configured to:
determining a core branch node among the branch nodes according to the first correlation coefficient and the second correlation coefficient includes:
judging whether a first correlation coefficient of the parameter value of the branch node and the parameter value of the transformer is larger than a first threshold value or not;
determining the branch node as an alternative branch node under the condition that the first correlation coefficient is larger than a first threshold value;
and eliminating the pseudo branch nodes in the alternative branch nodes according to the first correlation coefficient and the second correlation coefficient to obtain the core branch nodes.
Further, the processor 410 is further configured to:
removing the pseudo branch nodes in the alternative branch nodes according to the first correlation coefficient and the second correlation coefficient to obtain the core branch node, wherein the removing comprises:
judging whether a second correlation number between parameter values of two alternative branch nodes exists in the alternative branch nodes is larger than a second threshold value;
and under the condition that a second correlation number between the parameter values of the two candidate branch nodes is larger than a second threshold value, the candidate branch nodes with smaller first correlation coefficients with the parameter values of the transformer are removed.
Further, the processor 410 is further configured to:
assigning remaining ones of the branch nodes to corresponding core branch nodes based on the second correlation coefficient comprises:
acquiring a second correlation coefficient between the parameter value of the target residual branch node and the parameter value of each core branch node;
determining the core branch node with the maximum second correlation number with the parameter values of the target residual branch nodes as a target core branch node;
and distributing the target residual branch node to the target core branch node.
Further, the processor 410 is further configured to:
determining a second topological relationship of the electric energy meter to the end branch node according to the second correlation includes:
respectively calculating a third correlation coefficient between the parameter value of the target electric energy meter and the parameter value of each tail end branch node;
determining the tail end branch node with the maximum third phase relation number with the parameter value of the target electric energy meter as a target tail end branch node;
and distributing the target electric energy meter to the target tail end branch node.
In an embodiment of the present invention, the first correlation and the second correlation satisfy the following formula:
wherein, Vx，VyA voltage series of values for any two parameters;
is a Vx，VyPearson's correlation coefficient; cov (V)x，Vy) Is a VxAnd VyThe covariance between;
is a VxThe variance of (a);
is a VYThe variance of (c).
According to the technical scheme, the parameter values of the transformer, the branch nodes and the electric energy meter are respectively acquired, the first topological relation between each branch node and the transformer is determined, and then the second topological relation between the electric energy meter and the tail end branch node is determined, so that the electric network topological relation of the whole electric power acquisition system is formed. The invention does not need complex parameters, has less calculation amount and higher precision, thereby leading the efficiency of topology identification to be higher.
Examples of processor 410 may include, but are not limited to, a general purpose processor, a special purpose processor, a conventional processor, a Digital Signal Processor (DSP), a plurality of microprocessors, one or more microprocessors in association with a DSP core, a controller, a microcontroller, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) circuits, any other type of Integrated Circuit (IC), a state machine, and the like. The processor may perform signal encoding, data processing, power control, input/output processing.
Examples of memory 420 may include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that may be used to store information that may be accessed by a processor.
Fig. 5 is a schematic structural diagram of an electric power collection system according to an embodiment of the present invention. Referring to fig. 5, the present invention provides a power harvesting system, which may include:
the transformer 51 is used for acquiring data of the whole transformer area of the power acquisition system;
a branch node 52 provided with a first low-voltage monitoring unit for collecting voltage data of the branch node 52 and transmitting the voltage data to the transformer 51 by power line carrier communication;
the electric energy meter 53 is provided with a second low-voltage monitoring unit which is used for measuring and collecting voltage data of the electric energy meter 53 and transmitting the voltage data to the branch node 52;
the controller 54 is connected to the transformer 51, the branch node 52 and the electric energy meter 53, and is configured to obtain parameter values of the transformer 51, the branch node 52 and the electric energy meter 53.
In the embodiment of the invention, the power supply path of the power acquisition system generally supplies power according to a plurality of topological levels, such as a transformer, a plurality of branch nodes, a plurality of electric energy meters, and the like, so that the electrical distribution network topological relation of the power acquisition system can include 'transformer 51, branch node 52 and electric energy meter 53'. According to the embodiment of the invention, the correlation among the parameter values is determined by acquiring the parameter values of the transformer 51, the branch node 52 and the electric energy meter 53, so that the topology identification is carried out.
In one example, the parameter values may be a voltage series of values. The transformer 51 may include a concentrator, a Central Coordinator (CCO), a high-speed carrier module, and a three-phase voltage series value collecting device, so that the voltage series value of the transformer may be collected by the three-phase voltage series value collecting device. Each branch node 52 end may be provided with a Low-voltage Terminal Unit (LTU) and a high-speed carrier communication module, and the LTU may accurately detect a short-circuit fault, a ground fault, a power outage and transmission, a three-phase voltage, a three-phase current, an active power, a reactive power, a zero-sequence voltage, a zero-sequence current, and the like of a line. Accordingly, a corresponding series of voltage values may be collected by the LTU provided at each branch node 52. The terminal of each electric energy meter 53 has the capability of collecting the voltage series values and the capability of communicating information, for example, a second low voltage monitoring unit may be provided at each branch node. Therefore, the voltage series value can be acquired through each electric energy meter terminal.
The embodiment of the invention respectively collects the parameter values of the transformer 51, the branch nodes 52 and the electric energy meter 53, firstly determines the first topological relation between each branch node 52 and the transformer 51, and then determines the second topological relation between the electric energy meter 53 and the tail end branch node, thereby forming the electric network topological relation of the whole electric power collection system. The invention does not need complex parameters, has less calculation amount and higher precision, thereby leading the efficiency of topology identification to be higher.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may 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, and the like) having computer-usable program code embodied therein.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method for electrical topology identification, applied to a power harvesting system, wherein the power harvesting system comprises a transformer, a branch node and an electric energy meter, the method comprising:
respectively acquiring parameter values of the transformer, the branch node and the electric energy meter;
determining a first correlation between the parameter values of the transformer and the branch nodes;
determining a first topological relation between the transformer and the branch node according to the first correlation;
determining a terminal branch node in the branch nodes according to the first topological relation;
determining a second correlation of the parameter values of the electric energy meter with the parameter values of the end branch nodes;
determining a second topological relation between the electric energy meter and the tail end branch node according to the second correlation;
and determining the topological relation of the power acquisition system according to the first topological relation and the second topological relation.
2. The method of claim 1, wherein said obtaining parameter values for said transformer, said branch node, and said power meter, respectively, comprises:
and respectively collecting voltage series values of the transformer, the branch node and the electric energy meter within set time.
3. The method of claim 1, wherein the determining the first topological relationship of the transformer to the branch node according to the first correlation comprises:
obtaining a first correlation coefficient of the parameter value of each branch node and the parameter value of the transformer;
obtaining a second correlation coefficient between parameter values of the branch nodes;
determining a core branch node in the branch nodes according to the first correlation coefficient and the second correlation coefficient;
distributing the rest of the branch nodes to corresponding core branch nodes according to the second correlation coefficient;
and layering the rest branch nodes corresponding to each core branch node according to the second correlation coefficient to obtain the first topological relation.
4. The method of claim 3, wherein determining a core branch node of the branch nodes according to the first correlation coefficient and the second correlation coefficient comprises:
judging whether a first correlation coefficient of the parameter value of the branch node and the parameter value of the transformer is larger than a first threshold value or not;
determining the branch node as an alternative branch node if the first correlation coefficient is greater than a first threshold;
and eliminating the pseudo branch nodes in the alternative branch nodes according to the first correlation coefficient and the second correlation coefficient to obtain the core branch nodes.
5. The method according to claim 4, wherein said culling the pseudo branch nodes from the candidate branch nodes according to the first correlation coefficient and the second correlation coefficient to obtain core branch nodes comprises:
judging whether a second correlation number between parameter values of two alternative branch nodes exists in the alternative branch nodes is larger than a second threshold value;
and under the condition that a second correlation number between the parameter values of two candidate branch nodes is larger than a second threshold value, the candidate branch nodes with smaller first correlation coefficients with the parameter values of the transformer are removed.
6. The method of claim 3, wherein said assigning remaining ones of said branch nodes to corresponding core branch nodes according to said second correlation coefficients comprises:
acquiring a second correlation coefficient between the parameter value of the target residual branch node and the parameter value of each core branch node;
determining the core branch node with the maximum second correlation number with the parameter values of the target residual branch nodes as a target core branch node;
and distributing the target residual branch node to the target core branch node.
7. The method of claim 1, wherein said determining a second topological relationship of the power meter to the end branch node based on the second correlation comprises:
respectively calculating a third correlation coefficient between the parameter value of the target electric energy meter and the parameter value of each tail end branch node;
determining the tail end branch node with the maximum third phase relation number with the parameter value of the target electric energy meter as a target tail end branch node;
and distributing the target electric energy meter to the target tail end branch node.
8. The method of claim 1, wherein the first correlation and the second correlation satisfy the following equations:
wherein, Vx，VyA voltage series of values for any two parameters; rho Vx，vyIs a Vx，VyPearson's correlation coefficient; cov (V)x，Vy) Is a VxAnd VyThe covariance between; svxIs a VxThe variance of (a); SVYIs a VYThe variance of (c).
9. A controller characterized by comprising a method for electrical topology identification according to any of claims 1 to 8.
10. An electrical power harvesting system, comprising:
the transformer is used for acquiring data of the whole transformer area of the power acquisition system;
the branch node is provided with a first low-voltage monitoring unit which is used for collecting voltage data of the branch node and transmitting the voltage data to the transformer through power line carrier communication;
the electric energy meter is provided with a second low-voltage monitoring unit, and the second low-voltage monitoring unit is used for measuring and collecting voltage data of the electric energy meter and transmitting the voltage data to the branch node;
the controller of claim 9, coupled to the transformer, the branch node, and the power meter, for obtaining parameter values of the transformer, the branch node, and the power meter.
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