CN114595543A - Power distribution network topology identification method based on voltage correlation coefficient - Google Patents

Power distribution network topology identification method based on voltage correlation coefficient Download PDF

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CN114595543A
CN114595543A CN202210244671.7A CN202210244671A CN114595543A CN 114595543 A CN114595543 A CN 114595543A CN 202210244671 A CN202210244671 A CN 202210244671A CN 114595543 A CN114595543 A CN 114595543A
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power distribution
distribution network
model
voltage
correlation coefficient
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王一清
高海龙
肖学权
周钰山
张潇
任孝峰
吴冲
苏岭东
周峰
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State Grid Xuzhou Power Supply Co
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F30/00—Computer-aided design [CAD]
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    • G06F30/18—Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling
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    • G06F30/20—Design optimisation, verification or simulation
    • 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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    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
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Abstract

The invention discloses a power distribution network topology identification method based on voltage correlation coefficients, which comprises the steps of removing redundant electrical equipment from a power distribution network model and simplifying the topology model of a power distribution network; constructing the simplified power distribution network topology model into an abstract model, determining a voltage correlation coefficient based on the voltage of a substation bus and a distribution transformer load point, and generating a voltage correlation coefficient matrix; obtaining a relation set of voltage correlation coefficients and switch states by adopting a graph search algorithm, constructing a power distribution network topology model into a probability network model, reasoning parameters of the probability network model, obtaining states of all switches in the model, and further determining the operation state topology condition of the power distribution network; the method improves the practicability and reliability of the identification technology, provides a solid foundation for efficient and reasonable planning design and operation control of the power distribution network, and effectively improves the scientificity and rationality of scheduling decision.

Description

Power distribution network topology identification method based on voltage correlation coefficient
Technical Field
The invention relates to the technical field of power distribution network topology identification, in particular to a power distribution network topology identification method based on voltage correlation coefficients.
Background
The power distribution network is an important component of a power distribution system, is a complex network comprising a plurality of devices, and the safe and reliable operation of the complex network is an important guarantee for production and life. In the actual operation process, due to uncertain factors such as equipment maintenance and faults, the network topology can be irregularly changed.
At present, the topology maintenance of the related power distribution network is often influenced by human subjectivity and analysis means, the situation of topology maintenance errors is easy to occur, and the related requirements of the actual operation analysis service of the power distribution network are difficult to meet. The traditional distribution network topology identification method is based on state estimation and parameter estimation of a power system and adopts a corresponding algorithm for research and calculation. When the scale of the power distribution network is large, huge calculation amount is needed for traversing the connection relation between the nodes of the power distribution network by using the connection criterion, and the traditional identification method is difficult to support. Therefore, the topology of the power distribution network is scientifically and effectively identified, and the method is very important for ensuring the stable operation of the power distribution network.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a power distribution network topology identification method based on a voltage correlation coefficient, which can scientifically and effectively identify the topology of a power distribution network and ensure the stable operation of the power distribution network.
The technical scheme adopted by the invention is as follows: a power distribution network topology identification method based on voltage correlation coefficients comprises the following steps:
s1: redundant electrical equipment is removed from the power distribution network model, and the topology model of the power distribution network is simplified;
s2: constructing the simplified power distribution network topology model into an abstract model, determining a voltage correlation coefficient based on the voltage of a substation bus and a distribution transformer load point, and generating a voltage correlation coefficient matrix;
s3: obtaining a relation set of voltage correlation coefficients and switch states by adopting a graph search algorithm, constructing a power distribution network topology model into a probability network model, reasoning parameters of the probability network model, obtaining states of all switches in the model, and further determining the operation state topology condition of the power distribution network.
Preferably, step S1 specifically includes:
s11: devices that contribute to topology identification are retained: the method comprises the following steps of (1) deleting other redundant equipment from a substation bus, a switch and a feeder line;
s12: a plurality of feeder lines between distribution transformers and between substation buses and distribution transformers in a power distribution network topological structure are combined into one feeder line, and a union set of switch states is reserved in the combined feeder line.
Preferably, the step S2 specifically includes:
s21: the simplified power distribution network topology model is abstracted into a point-line model, solid dots are used for representing voltage variables in the point-line model respectively, hollow dots represent switch state variables, a letter P represents a substation bus, a letter L represents distribution transformation, and a letter B represents a coupling node between a branch and a main feeder;
s22: calculating voltage correlation coefficient T through voltages of each substation bus and distribution transformer load pointVPVLThe following were used:
Figure BDA0003542548440000021
in the formula of UPAnd ULVoltages of the substation busbar and distribution load point, respectively, are indicated cov (U)P,UL) Is UPAnd ULCovariance between, σ (U)P) And σ (U)L) Represents UPAnd ULStandard deviation of the data;
further generating a voltage correlation coefficient matrix TfThe following:
Figure BDA0003542548440000022
wherein, the element T in the matrixPjLiIndicating the bus voltage U of the substationPj(j-1, 2, …, M) and distribution voltage ULiAnd (i is 1,2, …, N), wherein M is the number of substations and N is the number of distribution transformers.
Preferably, step S3 is specifically:
s31: searching lines between power distribution buses and transformer substation buses and between power distribution buses and power distribution buses by adopting a graph searching algorithm, and determining the relation between the switching state quantity and the voltage correlation coefficient;
s32: obtaining the relation between the switch state quantity and the voltage correlation coefficient according to a graph search algorithm to form a directed edge relation graph, wherein the directed edge direction points to the switch state node from the voltage correlation node, and the topological structure is converted into a probability model;
s33: the state quantities of the switch state nodes in the probability model are divided into 0 and 1, wherein 0 represents that the switch is opened or the voltage association degree is smaller than a set standard, and 1 represents that the switch is closed or the voltage association degree is larger than the set standard; performing parameter learning on the existing data to obtain initial probability and conditional probability parameters to obtain parameters of a probability model;
s34: collecting the transformer substation bus and the distribution node voltage in the distribution network node model, determining the required observed quantity of all the switch states, and simplifying the difficulty of deducing the switch states;
s35: and deducing the state of the hidden content through part of the observed quantity to obtain the states of all switches in the network, and obtaining the topological structure of the power distribution network by using the obtained information of all switches to realize the topological identification of the power distribution network.
The invention has the beneficial effects that: the invention provides a topology identification technology considering a voltage correlation coefficient, which generally considers that the state of a switch has direct relation with the voltage fluctuation relation between corresponding nodes, namely the closer the electrical distance between the nodes, the higher the correlation coefficient of a voltage sequence is. The method improves the practicability and reliability of the identification technology, provides a solid foundation for efficient and reasonable planning design and operation control of the power distribution network, and effectively improves the scientificity and rationality of scheduling decisions.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a schematic view of a topology model of a simplified power distribution network according to the present invention;
FIG. 3 is a schematic diagram of a power distribution network topology model abstracted as a dotted line model according to the present invention;
FIG. 4 is a flow chart of a method in an embodiment of the invention;
fig. 5 is a schematic diagram of the state identification of the topology switch of the power distribution network.
Detailed Description
To further illustrate the details of the technical solution of the present invention, an embodiment is given and described with reference to the accompanying drawings.
As shown in fig. 1, a method for identifying a power distribution network topology based on a voltage correlation coefficient includes the following steps:
s1: redundant electrical equipment is removed from the power distribution network model, and the topology model of the power distribution network is simplified;
s2: constructing the simplified power distribution network topology model into an abstract model, determining a voltage correlation coefficient based on the voltage of a substation bus and a distribution transformer load point, and generating a voltage correlation coefficient matrix;
s3: obtaining a relation set of voltage correlation coefficients and switch states by adopting a graph search algorithm, constructing a power distribution network topology model into a probability network model, reasoning parameters of the probability network model, obtaining states of all switches in the model, and further determining the operation state topology condition of the power distribution network.
In this embodiment, as shown in fig. 2, step S1 specifically includes:
s11: devices that contribute to topology identification are retained: the method comprises the following steps of (1) deleting other redundant equipment from a substation bus, a switch and a feeder line;
s12: combining a plurality of feeder lines between distribution transformers and between a substation bus and the distribution transformers in a power distribution network topological structure into one feeder line, and keeping a union set of switch states in the combined feeder line.
As shown in fig. 3, step S2 specifically includes:
s21: the simplified power distribution network topology model is abstracted into a point-line model, solid dots are used for representing voltage variables in the point-line model respectively, hollow dots represent switch state variables, a letter P represents a substation bus, a letter L represents distribution transformation, and a letter B represents a coupling node between a branch and a main feeder;
s22: calculating voltage correlation coefficient T through voltages of each substation bus and distribution transformer load pointVPVLThe following were used:
Figure BDA0003542548440000041
in the formula of UPAnd ULVoltages of the substation busbar and distribution load point, respectively, are indicated cov (U)P,UL) Is UPAnd ULCovariance between, σ (U)P) And σ (U)L) Represents UPAnd ULStandard deviation of the data;
further generating a voltage correlation coefficient matrix TfThe following:
Figure BDA0003542548440000042
wherein, the element T in the matrixPjLiRepresenting the bus voltage U of the substationPj(j ═ 1,2, …, M) and distribution voltage ULiAnd (i is 1,2, …, N), wherein M is the number of substations and N is the number of distribution transformers.
Preferably, the step S3 specifically includes:
s31: searching lines between power distribution buses and transformer substation buses and between power distribution buses and power distribution buses by adopting a graph searching algorithm, and determining the relation between the switching state quantity and the voltage correlation coefficient;
s32: obtaining the relation between the switch state quantity and the voltage correlation coefficient according to a graph search algorithm to form a directed edge relation graph, wherein the directed edge direction points to the switch state node from the voltage correlation node, and the topological structure is converted into a probability model;
s33: the state quantities of the switch state nodes in the probability model are divided into 0 and 1, wherein 0 represents that the switch is opened or the voltage association degree is smaller than a set standard, and 1 represents that the switch is closed or the voltage association degree is larger than the set standard; performing parameter learning on the existing data to obtain initial probability and conditional probability parameters to obtain parameters of a probability model;
s34: collecting the transformer substation bus and the distribution node voltage in the distribution network node model, determining the required observed quantity of all the switch states, and simplifying the difficulty of deducing the switch states; the technical scheme that any one of the prior art can achieve the function can be adopted for collecting the substation bus and the distribution node voltage in the distribution network node model, and an active track technology is adopted in the embodiment.
Active trajectory techniques: the track relations between the switch states and the correlation coefficient variables in the search model comprise track relations between voltage correlation coefficients, between switch closed state quantities, between voltage correlation coefficients and switch state quantities, the active track can determine the relation of reasoning the state of another variable from one variable, determine a collection of required observed quantities, remove redundant observed quantities, filter to obtain simplified node data, and can reason the states of all switches in the network only by the required voltage state quantities determined in advance. As shown in FIG. 5, the desired observed quantity is T thereinP1L1，TP1L3，TP2L1。
S35: through part of the observed quantities, the states of the hidden contents are deduced to obtain the states of all switches in the network, the obtained information of all the switches is utilized to obtain the topological structure of the power distribution network, and the topological identification of the power distribution network is realized, as shown in fig. 5. The hidden content state is inferred through part of the observed quantity, any algorithm capable of achieving the function in the prior art can be adopted, and a belief propagation inference algorithm is adopted in the embodiment.
Belief propagation reasoning algorithm: the complexity of topology identification can be reduced by an inference algorithm for iteratively updating the state of the probability model by transmitting information among parallelized nodes. And reasoning propagation reasoning, namely reasoning the required amount of marginal probability quantity, wherein the information transmitted by the nodes is the result of multiplying all adjacent node information, the marginal probability quantity is the information of the nodes without adjacent nodes, and the required switching state quantity is finally obtained after the whole model is propagated and is iterated next round until convergence is met.
The observed quantity required is TP1L1，TP1L3，TP2L1，TL1L3All switches S can be obtained by belief propagation reasoning algorithm1，S2，S3The inference results are shown in the table below, for example.
Table 1 example table of power distribution network topology state identification result based on voltage correlation coefficient
Figure BDA0003542548440000051

Claims (4)

1. A power distribution network topology identification method based on voltage correlation coefficients is characterized by comprising the following steps:
s1: redundant electrical equipment is removed from the power distribution network model, and the topology model of the power distribution network is simplified;
s2: constructing the simplified power distribution network topology model into an abstract model, determining a voltage correlation coefficient based on the voltage of a substation bus and a distribution transformer load point, and generating a voltage correlation coefficient matrix;
s3: obtaining a relation set of voltage correlation coefficients and switch states by adopting a graph search algorithm, constructing a power distribution network topology model into a probability network model, reasoning parameters of the probability network model, obtaining states of all switches in the model, and further determining the operation state topology condition of the power distribution network.
2. The method for identifying the power distribution network topology based on the voltage correlation coefficient according to claim 1, characterized in that: step S1 specifically includes:
s11: devices that contribute to topology identification are retained: the method comprises the following steps of (1) deleting other redundant equipment from a substation bus, a switch and a feeder line;
s12: combining a plurality of feeder lines between distribution transformers and between a substation bus and the distribution transformers in a power distribution network topological structure into one feeder line, and keeping a union set of switch states in the combined feeder line.
3. The method for identifying the power distribution network topology based on the voltage correlation coefficient as claimed in claim 1, wherein: the step S2 specifically includes:
s21: the simplified power distribution network topology model is abstracted into a point-line model, voltage variables are represented by solid dots in the point-line model, hollow dots represent switch state variables, a letter P represents a substation bus, a letter L represents distribution transformation, and a letter B represents a coupling node between a branch and a main feeder;
s22: calculating voltage correlation coefficient T through voltages of each substation bus and distribution transformer load pointVPVLThe following were used:
Figure FDA0003542548430000011
in the formula of UPAnd ULVoltages of the substation busbar and distribution load point, respectively, are indicated cov (U)P,UL) Is UPAnd ULCovariance between, σ (U)P) And σ (U)L) Represents UPAnd ULStandard deviation of the data;
further generating a voltage correlation coefficient matrix TfThe following were used:
Figure FDA0003542548430000021
wherein, the element T in the matrixPjLiIndicating the bus voltage U of the substationPj(j ═ 1,2, …, M) and distribution voltage ULiAnd (i is 1,2, …, N), wherein M is the number of substations and N is the number of distribution transformers.
4. The method for identifying the power distribution network topology based on the voltage correlation coefficient as claimed in claim 1, wherein: the step S3 specifically includes:
s31: searching lines between power distribution buses and transformer substation buses and between power distribution buses and power distribution buses by adopting a graph searching algorithm, and determining the relation between the switching state quantity and the voltage correlation coefficient;
s32: obtaining the relation between the switch state quantity and the voltage correlation coefficient according to a graph search algorithm to form a directed edge relation graph, wherein the directed edge direction points to the switch state node from the voltage correlation node, and the topological structure is converted into a probability model;
s33: the state quantities of the switch state nodes in the probability model are divided into 0 and 1, wherein 0 represents that the switch is opened or the voltage association degree is smaller than a set standard, and 1 represents that the switch is closed or the voltage association degree is larger than the set standard; performing parameter learning on the existing data to obtain initial probability and conditional probability parameters to obtain parameters of a probability model;
s34: collecting the transformer substation bus and the distribution node voltage in the distribution network node model, determining the required observed quantity of all the switch states, and simplifying the difficulty of deducing the switch states;
s35: and deducing the state of the hidden content through part of the observed quantity to obtain the states of all switches in the network, and obtaining the topological structure of the power distribution network by using the obtained information of all switches to realize the topological identification of the power distribution network.
CN202210244671.7A 2022-03-11 2022-03-11 Power distribution network topology identification method based on voltage correlation coefficient Pending CN114595543A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115144679A (en) * 2022-08-31 2022-10-04 武汉格蓝若智能技术有限公司 Method and system for identifying real-time topological relation of collected voltage on line

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115144679A (en) * 2022-08-31 2022-10-04 武汉格蓝若智能技术有限公司 Method and system for identifying real-time topological relation of collected voltage on line
CN115144679B (en) * 2022-08-31 2022-11-29 武汉格蓝若智能技术有限公司 Method and system for identifying real-time topological relation of collected voltage on line

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