CN113363987A - Master-slave type fault self-healing control method and system for power distribution network - Google Patents

Master-slave type fault self-healing control method and system for power distribution network Download PDF

Info

Publication number
CN113363987A
CN113363987A CN202110512269.8A CN202110512269A CN113363987A CN 113363987 A CN113363987 A CN 113363987A CN 202110512269 A CN202110512269 A CN 202110512269A CN 113363987 A CN113363987 A CN 113363987A
Authority
CN
China
Prior art keywords
distribution network
power distribution
power
scheme
determining
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202110512269.8A
Other languages
Chinese (zh)
Other versions
CN113363987B (en
Inventor
蒋帅
李仲青
梁英
杨国生
周泽昕
孙天甲
沈冰
药韬
薛志英
朱禹澜
李波
廖凯
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
State Grid Corp of China SGCC
Southwest Jiaotong University
China Electric Power Research Institute Co Ltd CEPRI
State Grid Shanghai Electric Power Co Ltd
Original Assignee
State Grid Corp of China SGCC
Southwest Jiaotong University
China Electric Power Research Institute Co Ltd CEPRI
State Grid Shanghai Electric Power Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by State Grid Corp of China SGCC, Southwest Jiaotong University, China Electric Power Research Institute Co Ltd CEPRI, State Grid Shanghai Electric Power Co Ltd filed Critical State Grid Corp of China SGCC
Priority to CN202110512269.8A priority Critical patent/CN113363987B/en
Priority claimed from CN202110512269.8A external-priority patent/CN113363987B/en
Publication of CN113363987A publication Critical patent/CN113363987A/en
Application granted granted Critical
Publication of CN113363987B publication Critical patent/CN113363987B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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
    • H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
    • H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02H—EMERGENCY PROTECTIVE CIRCUIT ARRANGEMENTS
    • H02H7/00—Emergency protective circuit arrangements specially adapted for specific types of electric machines or apparatus or for sectionalised protection of cable or line systems, and effecting automatic switching in the event of an undesired change from normal working conditions
    • H02H7/26—Sectionalised protection of cable or line systems, e.g. for disconnecting a section on which a short-circuit, earth fault, or arc discharge has occured
    • H02H7/28—Sectionalised protection of cable or line systems, e.g. for disconnecting a section on which a short-circuit, earth fault, or arc discharge has occured for meshed systems
    • 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
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
    • 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
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • 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
    • 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
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • 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
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/20—Systems supporting electrical power generation, transmission or distribution using protection elements, arrangements or systems
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • 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
    • Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
    • Y04S40/12—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment

Abstract

The application discloses a master-slave type fault self-healing control method and system for a power distribution network. Wherein, the method comprises the following steps: determining a master-slave fault self-healing control framework of the power distribution network, controlling the action of an interconnection switch by adopting distributed slave control to complete power supply recovery of a power loss area, solving the optimal combination of the interconnection switch and a section switch of the power distribution network by adopting centralized master control, and adjusting the running state of the power distribution network to recover to an optimal state; according to the measurement data of the power distribution network measurement unit, initializing a power distribution network topological structure and electrical quantity parameters after the fault branch is cut off, wherein the electrical quantity parameters comprise node voltage, branch current and load power; executing a distribution network fault self-healing control slave control scheme, and formulating a distribution network contact switch action scheme to be recovered; and executing a power distribution network fault self-healing control main control scheme, calculating the optimal combination of all section switches and interconnection switches of the network, and optimizing the running state of the power distribution network.

Description

Master-slave type fault self-healing control method and system for power distribution network
Technical Field
The application relates to the technical field of power systems, in particular to a master-slave type fault self-healing control method and system for a power distribution network.
Background
The distribution network carries the burden of delivering stable electrical energy for production and life. Along with the continuous improvement of urban development, the power supply load density of a power distribution network is obviously increased, and the variety diversity of loads is strong; the requirements on the quality of electric energy of sensitive loads and important loads are increasingly raised, and the safety and the reliability of a power distribution network are particularly important. However, the structure of the distribution network is complex, the reliability of the distribution network is limited by elements, environment and other factors, and faults are difficult to avoid. And the distribution network is usually a radial passive structure, each node only has a unique path for acquiring the transmission power of the generator node, and the fault trip will inevitably cause the loss of power in a part of areas.
At present, the short-time power failure phenomenon of the power distribution network is frequent, the influence is brought to the production and the life depending on the electric power, and certain economic loss is caused, so that the importance of the self-healing function of the power distribution network is self-evident. The fault self-healing control becomes an important characteristic of the current intelligent power distribution network, and an effective self-healing control technology is an important guarantee for improving the power supply safety, reliability and economy of the power distribution network. The fault self-healing control of the power distribution network needs to quickly remove faults, the power-losing load of the power distribution network is automatically transferred, the power failure range is reduced, the power failure time is shortened, and the continuous power supply capacity of the power distribution network is guaranteed to the maximum extent.
Under the normal condition, after a fault occurs, the action of a switch needs to be quickly controlled, the power supply of a power-losing area is recovered, and the power supply reliability of a power distribution network is ensured. However, most of the existing fault self-healing control is based on an intelligent optimization algorithm, and the existing fault self-healing control is limited by numerous constraint conditions due to the characteristics of numerous nodes of a power distribution network, complex network topology structure, and various electrical parameters, and needs to rely on a large amount of iterative calculations, try and error and find an optimal solution, so that the solving speed is low; in addition, the resistance of the power distribution network line cannot be ignored, active power and reactive power are difficult to decouple, the calculation amount of iterative solution is further increased, the calculation time of a power supply recovery scheme is long, and the requirement on rapidity of power distribution network fault self-healing recovery is difficult to meet.
Disclosure of Invention
The embodiment of the disclosure provides a master-slave type fault self-healing control method and system for a power distribution network, and at least solves the technical problem that the power supply reliability of the power distribution network is insufficient due to low power supply recovery speed caused by global optimization solution based on an intelligent optimization algorithm in the existing self-healing control scheme in the prior art.
According to an aspect of the embodiment of the disclosure, a master-slave fault self-healing control method for a power distribution network is provided, which includes: determining a master-slave fault self-healing control framework of the power distribution network, controlling the action of an interconnection switch by adopting distributed slave control to complete power supply recovery of a power loss area, solving the optimal combination of the interconnection switch and a section switch of the power distribution network by adopting centralized master control, and adjusting the running state of the power distribution network to recover to an optimal state; according to the measurement data of the power distribution network measurement unit, initializing a power distribution network topological structure and electrical quantity parameters after the fault branch is cut off, wherein the electrical quantity parameters comprise node voltage, branch current and load power; executing a distribution network fault self-healing control slave control scheme, and formulating a distribution network contact switch action scheme to be recovered; and executing a power distribution network fault self-healing control main control scheme, calculating the optimal combination of all section switches and interconnection switches of the network, and optimizing the running state of the power distribution network.
According to another aspect of the embodiments of the present disclosure, there is also provided a master-slave fault self-healing control system for a power distribution network, including: the control system comprises a determining control framework module, a master-slave fault self-healing control framework module, a distributed slave control module, a centralized master control module, a section switch module and a power distribution network main-slave fault self-healing control framework module, wherein the determining control framework module is used for determining a master-slave fault self-healing control framework of the power distribution network, controlling the action of the contact switch to complete power supply recovery of a power loss area, solving the optimal combination of the contact switch and the section switch of the power distribution network by adopting the centralized master control module, and adjusting the running state of the power distribution network to recover to the optimal state; the initialization module is used for initializing a power distribution network topological structure and electrical quantity parameters after a fault branch is cut off according to power distribution network measurement unit measurement data, wherein the electrical quantity parameters comprise node voltage, branch current and load power; the execution slave control scheme module is used for executing a power distribution network fault self-healing control slave control scheme and formulating a power distribution network connection switch action scheme to be recovered; and the execution main control scheme module is used for executing the distribution network fault self-healing control main control scheme, calculating the optimal combination of all section switches and interconnection switches of the network and optimizing the running state of the distribution network.
The invention provides a master-slave type fault self-healing control method for a power distribution network. The method adopts a double-layer control scheme of distributed slave control and centralized master control, and separates two optimal targets of power supply recovery speed and power supply state: based on the rapid calculation of slave control, a better power supply recovery scheme is determined, the action of an interconnection switch is controlled, and the power supply recovery is rapidly realized; and determining a switch combination state under the optimal operation state of the power distribution network based on the global optimization of the master control, and controlling the actions of the interconnection switch and the section switch. The power supply recovery time can be greatly shortened, and the method has practical value for the power distribution network fault self-healing control. The method solves the contradiction between two goals of power supply recovery time and state optimization after recovery in the existing self-healing control scheme, can quickly recover power supply in a fault power-loss area, and meanwhile, adopts an intelligent optimization algorithm to realize optimal operation of the power distribution network, and can provide reference for fault self-healing recovery of the power distribution network.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the disclosure and together with the description serve to explain the disclosure and not to limit the disclosure. In the drawings:
fig. 1 is a schematic diagram of a master-slave fault self-healing control method for a power distribution network according to an embodiment of the present disclosure;
fig. 2 is a flowchart of an embodiment of master-slave self-healing control for a power distribution network according to the present disclosure;
fig. 3 is a diagram of an IEEE33 node topology according to an embodiment of the present disclosure;
fig. 4 is a schematic numbering diagram of IEEE33 node tie switches according to an embodiment of the present disclosure;
FIG. 5a is a graph of electrical distance relationships between nodes during normal operation according to an embodiment of the present disclosure;
FIG. 5b is a graph illustrating electrical distance relationships between nodes after a 5-6 branch fault is removed according to an embodiment of the disclosure;
FIG. 5c is a graph of the electrical distance relationship between nodes after the tie switches 8-21 are closed according to an embodiment of the present disclosure;
fig. 5d is a graph of the electrical distance relationship between the closed nodes of the tie switches 12-22 according to an embodiment of the present disclosure;
fig. 5e is a graph of the electrical distance relationship between the closed nodes of the tie switches 25-29 according to an embodiment of the disclosure;
FIG. 6 is a graph of node electrical distance similarity dynamics, according to an embodiment of the present disclosure;
FIG. 7 is a graph of a topology result of a power distribution network after power is restored from slave control according to an embodiment of the present disclosure;
fig. 8 is a topology structure diagram of a distribution network after a master control optimization operation according to an embodiment of the present disclosure;
fig. 9 is a schematic diagram of a master-slave fault self-healing control system for a power distribution network according to an embodiment of the present disclosure.
Detailed Description
The exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, however, the present invention may be embodied in many different forms and is not limited to the embodiments described herein, which are provided for complete and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments illustrated in the accompanying drawings is not intended to be limiting of the invention. In the drawings, the same units/elements are denoted by the same reference numerals.
Unless otherwise defined, terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Further, it will be understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense.
According to a first aspect of the present application, a master-slave fault self-healing control method 100 for a power distribution network is provided. Referring to fig. 1, the method includes:
s102, determining a master-slave fault self-healing control framework of the power distribution network, controlling the action of an interconnection switch by adopting distributed slave control to complete power supply recovery of a power loss area, solving the optimal combination of the interconnection switch and a section switch of the power distribution network by adopting centralized master control, and adjusting the running state of the power distribution network to recover to an optimal state;
s104, initializing a power distribution network topological structure and electrical quantity parameters after the fault branch is cut off according to the power distribution network measurement data, wherein the electrical quantity parameters comprise node voltage, branch current and load power;
s106, executing a power distribution network fault self-healing control slave control scheme, and formulating a power distribution network connection switch action scheme to be recovered;
and S108, executing a power distribution network fault self-healing control main control scheme, calculating the optimal combination of all section switches and interconnection switches of the network, and optimizing the running state of the power distribution network.
Specifically, a master-slave self-healing control flow of the power distribution network is shown in fig. 2. Referring to fig. 3, taking IEEE33 node as an example, the calculation is performed by the method of the present invention:
the first step is as follows: and determining a master-slave type fault self-healing control framework of the power distribution network. The slave control adopts distributed calculation, the action of the interconnection switch is rapidly controlled, and the power supply recovery of the power-off area is rapidly completed; the main control adopts centralized control, solves the optimal combination of the interconnection switch and the section switch of the power distribution network, and adjusts the running state of the power distribution network to recover to approximate optimization.
The second step is that: according to the measurement data of the power distribution network measurement unit, initializing a power distribution network topological structure after the fault branch is cut off, and electrical quantity parameters such as node voltage, branch current, load power and the like;
the branch impedance and node load data for the IEEE33 node are as follows:
TABLE 1 IEEE33 node parameters
Figure BDA0003060826840000041
Figure BDA0003060826840000051
The third step: the method comprises the following steps of executing a power distribution network fault self-healing control slave control scheme, formulating a power distribution network contact switch action scheme to be recovered, and carrying out the following specific processes:
a: according to the topological structure of the power distribution network to be recovered, calculating a tie switch combination scheme, and determining a feasible alternative power supply recovery scheme:
(1) determining a tie switch combination scheme:
the IEEE33 node distribution network has 5 tie switch branches in total, and when the power supply is recovered from the slave control, no more than 5 tie switches can be closed, and the combination of the tie switches has p-25-1-31 types in total.
(2) Checking the topological structure of the power distribution network:
the number of the interconnection switches is as shown in fig. 4, whether the power loss area of the power distribution network can recover power supply and keep radial operation under each interconnection switch combination scheme is verified, and the verification result is as follows:
table 2 verification of power distribution network interconnection switch combination scheme
Figure BDA0003060826840000052
Figure BDA0003060826840000061
After passing the verification, there are 3 alternative power restoration schemes that satisfy the condition:
scheme 1: communication switch 8-21 is closed
Scheme 2: tie switches 12-22 are closed
Scheme 3: tie switch 25-29 is closed
B: under a polar coordinate system, calculating a distribution network tide Jacobian block matrix when different power supply recovery schemes are adopted respectively:
Figure BDA0003060826840000062
in the formula:
Figure BDA0003060826840000063
the block matrix of the Seattle is obtained;
Figure BDA0003060826840000064
is Δ P to δTPartial derivatives of (a);
Figure BDA0003060826840000065
is DeltaP to UTPartial derivatives of (a);
Figure BDA0003060826840000066
is Δ Q to δTPartial derivatives of (a);
Figure BDA0003060826840000067
is Δ Q to δTPartial derivatives of (a);
c: neglecting the influence of active power disturbance on voltage, namely setting delta P as 0, calculating a reactive-voltage sensitivity matrix by using a power flow Jacobian block matrix:
ΔQ＝(L-MH-1N)ΔU
in the formula: s ═ L-MH-1N)-1Namely a reactive-voltage sensitivity matrix;
d: performing per unit on the reactive-voltage sensitivity matrix, and calculating the coupling relation between nodes by using an Euclidean distance formula, namely the electrical distance:
(1) standard deviation transformation:
and (3) carrying out standard deviation transformation on elements in the reactive-voltage sensitivity matrix S:
Figure BDA0003060826840000071
in the formula: i. j corresponds to a node i and a node j, i, j in the power distribution network and belongs to [0,1 ]]N is the number of nodes of the power distribution network;
Figure BDA0003060826840000072
is the average value of the jth row element of the matrix S;
Figure BDA0003060826840000073
is the standard deviation of the jth column element;
(2) range conversion:
and (3) performing range transformation on the matrix alpha after S standardization:
Figure BDA0003060826840000074
in the formula: x is the number ofijFor the per unit value, x, of the voltage influence capability of node j on node i due to reactive changeij∈[0,1]；
(3) Euclidean electrical distance:
and (3) defining the electrical distance between the nodes by using the per-unit reactive-voltage matrix x based on the Euclidean method:
Figure BDA0003060826840000075
in the formula: ED (electronic device)ijRepresenting the electrical distance, ED, between node i and node jij∈[0,1]，EDijThe larger the electrical connection between node i and node j is;
the calculation results of the electrical distance relationship between the nodes under each operating condition are shown in fig. 5 (fig. 5a, 5b, 5c, 5d, 5 e).
E: calculating the similarity of the electrical distance matrixes based on the electrical distance matrixes under each power supply recovery scheme, determining the power supply recovery scheme, and controlling the action of an interconnection switch:
(1) calculating the cosine similarity of each electrical distance matrix and the electrical distance matrix in normal operation:
Figure BDA0003060826840000076
in the formula: a. theijEach component of the electrical distance matrix in normal operation; b isijCalculating an electrical distance matrix with similarity to the A, wherein the electrical distance matrix comprises an electrical distance matrix in normal operation and electrical distance matrices under various power supply recovery schemes;
the calculation result of the total change of the electrical distance similarity of each node under each operating condition is shown in fig. 6.
(2) Calculating the average value of the cosine similarity of the electrical distance:
respectively calculating cosine similarity average values under each scene:
Figure BDA0003060826840000081
TABLE 3 mean values of similarity of electrical distance matrices
Figure BDA0003060826840000082
(3) Determining a slave control power supply recovery scheme, controlling the action of an interconnection switch, and recovering power supply of a power loss area:
the power supply recovery scheme corresponding to the similarity average value closest to the normal operation is used as a slave control power supply recovery scheme, namely the contact switches 25-29 are closed to recover the power supply of the power-off area, and the topology of the recovered power distribution network is shown in FIG. 7;
the fourth step: executing a power distribution network fault self-healing control main control scheme, calculating the optimal combination of all section switches and interconnection switches of the network, and optimizing the running state of the power distribution network, wherein the specific process comprises the following steps:
a: determining an optimal operation objective function of the power distribution network:
(1) the method aims at minimizing the active loss of the power distribution network:
Figure BDA0003060826840000083
in the formula: l is the total number of branches of the power distribution network; k is a radical ofiIs the state of the ith branch, kiBranch off when 0, k i1, namely the branch is closed; riThe resistance value of the ith branch is; u shapeiRepresenting the voltage amplitude of the terminal node of the ith branch; pi、QiRespectively representing active power and reactive power injected by the tail end node of the ith branch;
(2) the minimum voltage deviation of the nodes of the power distribution network is taken as a target:
Figure BDA0003060826840000091
in the formula: u shapeiIs the reality of node iA voltage; u shapeiNRepresents the nominal voltage of node i;
(3) constructing a comprehensive objective function:
min f＝w1f1+w2f2
w1+w2＝1
0≤w1≤1
0≤w2≤1
in the formula: w is a1，w2The weight coefficients of active network loss and voltage deviation are respectively;
b: determining network operation constraint conditions:
(1) power constraint conditions of each power flow of the power distribution network are as follows:
Figure BDA0003060826840000092
in the formula: pi、QiRespectively injecting active power and reactive power into the node i; u shapei、UjThe amplitudes of the voltages of the nodes i and j are respectively; gij、BijIs the conductance and susceptance between nodes i, j; deltaijIs the voltage phase difference of nodes i, j;
(2) voltage constraint conditions of each node of the power distribution network are as follows:
Uimin≤Ui≤Uimax
in the formula: u shapeiIs the voltage amplitude of node i; u shapeimax、UiminRespectively a maximum voltage amplitude and a minimum voltage amplitude of the node i;
(3) current constraint conditions of each branch of the power distribution network are as follows:
Ik≤Ikmax
in the formula: i isk、IkmaxThe current magnitude of the branch k and the maximum allowed current are respectively;
(4) capacity constraint conditions of each branch of the power distribution network are as follows:
Sk≤Skmax
in the formula: sk、SkmaxRespectively transmitting the size of power and the maximum allowable transmission power for the branch k;
(5) constraint conditions of a network topology structure of the power distribution network:
maintaining the power distribution network in a radial topology;
c: and (3) iterative solution is carried out by adopting a genetic algorithm, the optimal switch combination of the power distribution network meeting the constraint conditions is calculated, the actions of the interconnection switch and the section switch are controlled, and the running state of the power distribution network is adjusted to be approximately optimal.
The optimal switch combination scheme of the power distribution network is calculated as follows:
Figure BDA0003060826840000101
by this optimal combination, the optimized topology of the distribution network is as shown in fig. 8, and the distribution network is in an optimal operation state.
Therefore, a master-slave type fault self-healing control method for the power distribution network is provided. The method adopts a double-layer control scheme of distributed slave control and centralized master control, and separates two optimal targets of power supply recovery speed and power supply state: based on the rapid calculation of slave control, a better power supply recovery scheme is determined, the action of an interconnection switch is controlled, and the power supply recovery is rapidly realized; and determining a switch combination state under the optimal operation state of the power distribution network based on the global optimization of the master control, and controlling the actions of the interconnection switch and the section switch. The power supply recovery time can be greatly shortened, and the method has practical value for the power distribution network fault self-healing control. The method solves the contradiction between two goals of power supply recovery time and state optimization after recovery in the existing self-healing control scheme, can quickly recover power supply in a fault power-loss area, and meanwhile, adopts an intelligent optimization algorithm to realize optimal operation of the power distribution network, and can provide reference for fault self-healing recovery of the power distribution network.
Optionally, carry out distribution network fault self-healing control slave control scheme, formulate the distribution network contact switch action scheme of treating recovering, include: determining an interconnection switch combination scheme and a feasible alternative power supply recovery scheme according to a topological structure of the power distribution network to be recovered; under a polar coordinate system, respectively calculating a Jacobian block matrix of the power flow of the power distribution network when different power supply recovery schemes are adopted; neglecting the influence of active power disturbance on voltage, and calculating a reactive-voltage sensitivity matrix by using the Jacobian tide block matrix; performing per unit on the reactive-voltage sensitivity matrix, calculating the coupling relation between nodes by using an Euclidean distance formula, and determining an Euclidean electrical distance; and calculating the similarity of an electrical distance matrix based on the Euclidean electrical distance under each power supply recovery scheme, determining a power supply recovery scheme, and controlling the action of the interconnection switch.
Optionally, determining a tie switch combination scheme according to a topology structure of the power distribution network to be restored, and determining a feasible alternative power supply restoration scheme, including: determining a tie switch combination scheme: the power grid is equipped with r and liaison switch branches, and when the follow accuse recovered the power supply, can be closed and do not exceed r liaison switches, the total p kinds of combination of liaison switch:
Figure BDA0003060826840000111
checking the topological structure of the power distribution network: and checking the p-type combination scheme of the contact switches, and screening a scheme which can enable the power-loss area of the power distribution network to recover power supply and the power distribution network to keep radial topology to serve as a slave control power supply recovery alternative scheme.
Optionally, in a polar coordinate system, respectively calculating a jacobian block matrix of a power flow of the power distribution network when different power restoration schemes are adopted, including: respectively calculating the Jacobian block matrixes of the power flow of the power distribution network when different power supply recovery schemes are adopted according to the following formula:
Figure BDA0003060826840000112
wherein
Figure BDA0003060826840000113
The block matrix of the Seattle is obtained;
Figure BDA0003060826840000114
is ΔPartial derivatives of P to delta T;
Figure BDA0003060826840000115
is DeltaP to UTPartial derivatives of (a);
Figure BDA0003060826840000116
is Δ Q to δTPartial derivatives of (a);
Figure BDA0003060826840000117
is Δ Q to δTThe partial derivatives of (1).
Optionally, the step of calculating a reactive-voltage sensitivity matrix by using the jacobian block matrix of the power flow, ignoring the influence of active power disturbance on the voltage, includes:
ΔQ＝(L-MH-1N)ΔU
wherein, S ═ L-MH-1N)-1And is a reactive-voltage sensitivity matrix.
Optionally, performing per unit on the reactive-voltage sensitivity matrix, calculating a coupling relationship between nodes by using a euclidean distance formula, and determining a euclidean electrical distance, including: and (3) carrying out standard deviation transformation on elements in the reactive-voltage sensitivity matrix S:
Figure BDA0003060826840000121
wherein i and j correspond to a node i and a node j in the power distribution network, and the i and the j belong to [0,1 ]]N is the number of nodes of the power distribution network;
Figure BDA0003060826840000122
is the average value of the jth row element of the matrix S;
Figure BDA0003060826840000123
is the standard deviation of the jth column element;
and (3) performing range transformation on the matrix alpha after S standardization:
Figure BDA0003060826840000124
wherein x isijFor the per unit value, x, of the voltage influence capability of node j on node i due to reactive changeij∈[0,1](ii) a And (3) defining the Euclidean electrical distance between the nodes based on the Euclidean method by utilizing the per-unit reactive-voltage matrix x:
Figure BDA0003060826840000125
wherein EDijRepresenting the Euclidean electrical distance, ED, between node i and node jij∈[0,1]。
Optionally, calculating an electrical distance matrix similarity based on the euclidean electrical distance under each power supply restoration scheme, determining a restoration power supply scheme, and controlling an interconnection switch action, including: calculating the cosine similarity of each electrical distance matrix and the electrical distance matrix in normal operation:
Figure BDA0003060826840000126
wherein A isijEach component of the electrical distance matrix in normal operation; b isijCalculating an electrical distance matrix with similarity to the A, wherein the electrical distance matrix comprises an electrical distance matrix in normal operation and electrical distance matrices under various power supply recovery schemes; calculating the average value of the cosine similarity of the electrical distance: respectively calculating cosine similarity average values under each scene:
Figure BDA0003060826840000127
and determining a slave control power supply recovery scheme, controlling the action of the interconnection switch, and recovering the power supply of the power-off area.
Optionally, executing a power distribution network fault self-healing control master control scheme, calculating an optimal combination of all section switches and interconnection switches of the network, and optimizing the running state of the power distribution network, including: determining an optimal operation objective function of the power distribution network; determining a network operation constraint condition; and (3) iterative solution is carried out by adopting a genetic algorithm, the optimal switch combination of the power distribution network meeting the network operation constraint condition is calculated according to the optimal operation objective function of the power distribution network, the actions of the contact switch and the section switch are controlled, and the operation state of the power distribution network is adjusted to be optimal.
Optionally, determining an optimal operation objective function of the power distribution network includes: the method aims at minimizing the active loss of the power distribution network:
Figure BDA0003060826840000131
wherein l is the total branch number of the power distribution network; k is a radical ofiIs the state of the ith branch, kiBranch off when 0, k i1, the branch is closed; riThe resistance value of the ith branch is; u shapeiRepresenting the voltage amplitude of the terminal node of the ith branch; pi、QiRespectively representing active power and reactive power injected by the tail end node of the ith branch;
the minimum voltage deviation of the nodes of the power distribution network is taken as a target:
Figure BDA0003060826840000132
wherein, UiIs the actual voltage at node i; u shapeiNRepresents the nominal voltage of node i;
constructing a comprehensive objective function:
minf＝w1f1+w2f2
w1+w2＝1
0≤w1≤1
0≤w2≤1
wherein, w1，w2The weighting coefficients of the active network loss and the voltage deviation are respectively.
Optionally, determining network operation constraints comprises:
determining power constraint conditions of each power flow of the power distribution network:
Figure BDA0003060826840000133
wherein, Pi、QiRespectively injecting active power and reactive power into the node i; ui and Uj are the amplitude values of the voltages of the nodes i and j respectively; gij and Bij are conductance and susceptance between nodes i and j; δ ij is the voltage phase difference of nodes i, j;
determining a voltage constraint condition of each node of the power distribution network:
Uimin≤Ui≤Uimax
wherein, UiIs the voltage amplitude of node i; u shapeimax、UiminRespectively a maximum voltage amplitude and a minimum voltage amplitude of the node i;
determining current constraint conditions of each branch of the power distribution network:
Ik≤Ikmax
wherein, Ik、IkmaxThe current magnitude of the branch k and the maximum allowed current are respectively;
determining the capacity constraint conditions of each branch of the power distribution network:
Sk≤Skmax
wherein S isk、SkmaxRespectively transmitting the size of power and the maximum allowable transmission power for the branch k;
and determining constraint conditions of a network topology structure of the power distribution network, and keeping the power distribution network in a radial topology.
Therefore, a master-slave type fault self-healing control method for the power distribution network is provided. The method adopts a double-layer control scheme of distributed slave control and centralized master control, and separates two optimal targets of power supply recovery speed and power supply state: based on the rapid calculation of slave control, a better power supply recovery scheme is determined, the action of an interconnection switch is controlled, and the power supply recovery is rapidly realized; and determining a switch combination state under the optimal operation state of the power distribution network based on the global optimization of the master control, and controlling the actions of the interconnection switch and the section switch. The power supply recovery time can be greatly shortened, and the method has practical value for the power distribution network fault self-healing control. The method solves the contradiction between two goals of power supply recovery time and state optimization after recovery in the existing self-healing control scheme, can quickly recover power supply in a fault power-loss area, and meanwhile, adopts an intelligent optimization algorithm to realize optimal operation of the power distribution network, and can provide reference for fault self-healing recovery of the power distribution network.
According to another aspect of the present application, a master-slave fault self-healing control system 900 for a power distribution network is also provided. Referring to fig. 9, the system 900 includes: the determining control architecture module 910 is configured to determine a master-slave fault self-healing control architecture of the power distribution network, control the contact switch to operate by adopting distributed slave control, complete power restoration in a power loss area, solve an optimal combination of the contact switch and the section switch of the power distribution network by adopting centralized master control, and adjust the running state of the power distribution network to restore to an optimal state; the initialization module 920 is configured to initialize a topology structure of the power distribution network and electrical quantity parameters after the fault branch is removed according to the measurement data of the power distribution network measurement unit, where the electrical quantity parameters include node voltage, branch current, and load power; the slave control scheme execution module 930 is used for executing a distribution network fault self-healing control slave control scheme and formulating a distribution network connection switch action scheme to be recovered; and the main control scheme execution module 940 is used for executing the power distribution network fault self-healing control main control scheme, calculating the optimal combination of all section switches and interconnection switches of the network, and optimizing the running state of the power distribution network.
Optionally, the slave solution module 930 is executed, including: the alternative power supply recovery scheme determining submodule is used for determining an interconnection switch combination scheme according to a topological structure of the power distribution network to be recovered and determining a feasible alternative power supply recovery scheme; the calculation load flow Jacobian block matrix submodule is used for respectively calculating load flow Jacobian block matrices of the power distribution network when different power supply recovery schemes are adopted under a polar coordinate system; the reactive-voltage sensitivity matrix calculation submodule is used for neglecting the influence of active power disturbance on voltage and calculating a reactive-voltage sensitivity matrix by utilizing the flow Jacobian block matrix; the Euclidean electrical distance determining submodule is used for conducting per-unit treatment on the reactive-voltage sensitivity matrix, calculating the coupling relation between nodes by using an Euclidean distance formula, and determining the Euclidean electrical distance; and the contact switch action control submodule is used for calculating the similarity of an electrical distance matrix based on the Euclidean electrical distance under each power supply recovery scheme, determining the power supply recovery scheme and controlling the contact switch action.
Optionally, the determining an alternative power restoration scheme sub-module includes: a tie switch combination scheme determining unit for determining a tie switch combination scheme: the power grid is equipped with r and liaison switch branches, and when the follow accuse recovered the power supply, can be closed and do not exceed r liaison switches, the total p kinds of combination of liaison switch:
Figure BDA0003060826840000151
the verification distribution network topological structure unit is used for verifying a distribution network topological structure: and checking the p-type combination scheme of the contact switches, and screening a scheme which can enable the power-loss area of the power distribution network to recover power supply and the power distribution network to keep radial topology to serve as a slave control power supply recovery alternative scheme.
Optionally, the calculating a power flow jacobian block matrix submodule includes: and the unit for calculating the block matrix of the power flow Jacobian is used for respectively calculating the block matrix of the power flow Jacobian of the power distribution network when different power supply recovery schemes are adopted according to the following formula:
Figure BDA0003060826840000152
wherein
Figure BDA0003060826840000153
The block matrix of the Seattle is obtained;
Figure BDA0003060826840000154
is the partial derivative of Δ P to δ T;
Figure BDA0003060826840000155
is DeltaP to UTPartial derivatives of (a);
Figure BDA0003060826840000156
is Δ Q to δTPartial derivatives of (a);
Figure BDA0003060826840000157
is Δ Q to δTThe partial derivatives of (1).
Optionally, the calculate reactive-voltage sensitivity matrix submodule includes: and the reactive-voltage sensitivity matrix calculating unit is used for calculating a reactive-voltage sensitivity matrix by using the Seattle tidal current block matrix according to the following formula:
ΔQ＝(L-MH-1N)ΔU
wherein, S ═ L-MH-1N)-1And is a reactive-voltage sensitivity matrix.
Optionally, the determine euclidean electrical distance sub-module comprises: a standard deviation transformation unit, configured to perform standard deviation transformation on elements in the reactive-voltage sensitivity matrix S:
Figure BDA0003060826840000161
wherein i and j correspond to a node i and a node j in the power distribution network, and the i and the j belong to [0,1 ]]N is the number of nodes of the power distribution network;
Figure BDA0003060826840000162
is the average value of the jth row element of the matrix S;
Figure BDA0003060826840000163
is the standard deviation of the jth column element;
a range transformation unit for performing range transformation on the matrix α after S normalization:
Figure BDA0003060826840000164
wherein x isijFor the per unit value, x, of the voltage influence capability of node j on node i due to reactive changeij∈[0,1]；
And defining a Euclidean electrical distance unit, which is used for defining the Euclidean electrical distance between the nodes based on the Euclidean method by utilizing the per-unit reactive-voltage matrix x:
Figure BDA0003060826840000165
wherein EDijRepresenting the Euclidean electrical distance, ED, between node i and node jij∈[0,1]。
Optionally, the control interconnection switch action sub-module comprises: and the unit for calculating the cosine similarity of the electrical distance matrix is used for calculating the cosine similarity of each electrical distance matrix and the electrical distance matrix in normal operation:
Figure BDA0003060826840000166
wherein A isijEach component of the electrical distance matrix in normal operation; b isijCalculating an electrical distance matrix with similarity to the A, wherein the electrical distance matrix comprises an electrical distance matrix in normal operation and electrical distance matrices under various power supply recovery schemes;
and the cosine similarity average value calculating unit is used for calculating the electrical distance cosine similarity average value: respectively calculating cosine similarity average values under each scene:
Figure BDA0003060826840000167
and the control interconnection switch action unit is used for determining a slave control power supply recovery scheme, controlling the interconnection switch to act and recovering power supply of the power-off area.
Optionally, the module 940 for executing the master control scheme includes: the objective function determining submodule is used for determining an optimal operation objective function of the power distribution network; a constraint condition determining submodule for determining a network operation constraint condition; and the sub-module for adjusting the running state of the power distribution network is used for adopting a genetic algorithm to carry out iterative solution, calculating the optimal switch combination of the power distribution network meeting the network running constraint condition according to the optimal running objective function of the power distribution network, controlling the actions of the contact switch and the section switch and adjusting the running state of the power distribution network to be optimal.
Optionally, determining an objective function submodule includes: determining a minimum active loss target unit for targeting the minimum active loss of the power distribution network:
Figure BDA0003060826840000171
wherein l is the total branch number of the power distribution network; k is a radical ofiIs the state of the ith branch, kiBranch off when 0, k i1, the branch is closed; riThe resistance value of the ith branch is; u shapeiRepresenting the voltage amplitude of the terminal node of the ith branch; pi、QiRespectively representing active power and reactive power injected by the tail end node of the ith branch;
determining a target unit with minimum voltage deviation, and using the minimum voltage deviation of the nodes of the power distribution network as a target:
Figure BDA0003060826840000172
wherein, UiIs the actual voltage at node i; u shapeiNRepresents the nominal voltage of node i;
the comprehensive objective function constructing unit is used for constructing a comprehensive objective function:
minf＝w1f1+w2f2
w1+w2＝1
0≤w1≤1
0≤w2≤1
wherein, w1，w2The weighting coefficients of the active network loss and the voltage deviation are respectively.
Optionally, the determining a constraint condition submodule includes:
and the power constraint condition determining unit is used for determining the power constraint conditions of each power flow of the power distribution network:
Figure BDA0003060826840000173
wherein, Pi、QiRespectively injecting active power and reactive power into the node i; ui and Uj are the amplitude values of the voltages of the nodes i and j respectively; gij and Bij are conductance and susceptance between nodes i and j; δ ij is the voltage phase difference of nodes i, j;
and the voltage constraint condition determining unit is used for determining the voltage constraint conditions of each node of the power distribution network:
Uimin≤Ui≤Uimax
wherein, UiIs the voltage amplitude of node i; u shapeimax、UiminRespectively a maximum voltage amplitude and a minimum voltage amplitude of the node i;
determining each branch current constraint condition unit, which is used for determining each branch current constraint condition of the power distribution network:
Ik≤Ikmax
wherein, Ik、IkmaxThe current magnitude of the branch k and the maximum allowed current are respectively;
determining a capacity constraint condition unit of each branch, which is used for determining the capacity constraint condition of each branch of the power distribution network:
Sk≤Skmax
wherein S isk、SkmaxRespectively transmitting the size of power and the maximum allowable transmission power for the branch k;
and the network topology structure constraint condition determining unit is used for determining the network topology structure constraint conditions of the power distribution network and keeping the power distribution network in a radial topology.
The electro-optical homology-based frame dispersion receiving and tracing system 500 according to the embodiment of the present invention corresponds to the electro-optical homology-based frame dispersion receiving and tracing method 100 according to another embodiment of the present invention, and is not described herein again.
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. The scheme in the embodiment of the application can be implemented by adopting various computer languages, such as object-oriented programming language Java and transliterated scripting language JavaScript.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may 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 the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
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 the flowchart flow or flows and/or block diagram block or blocks.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.

Claims (11)

1. A master-slave type fault self-healing control method for a power distribution network is characterized by comprising the following steps:
determining a master-slave fault self-healing control framework of the power distribution network, controlling the action of an interconnection switch by adopting distributed slave control to complete power supply recovery of a power loss area, solving the optimal combination of the interconnection switch and a section switch of the power distribution network by adopting centralized master control, and adjusting the running state of the power distribution network to recover to an optimal state;
according to the measurement data of the power distribution network measurement unit, initializing a power distribution network topological structure and electrical quantity parameters after the fault branch is cut off, wherein the electrical quantity parameters comprise node voltage, branch current and load power;
executing a distribution network fault self-healing control slave control scheme, and formulating a distribution network contact switch action scheme to be recovered;
and executing a power distribution network fault self-healing control main control scheme, calculating the optimal combination of all section switches and interconnection switches of the network, and optimizing the running state of the power distribution network.
2. The method according to claim 1, wherein a distribution network fault self-healing control slave control scheme is executed, and a distribution network interconnection switch action scheme to be recovered is formulated, and the method comprises the following steps:
determining an interconnection switch combination scheme and a feasible alternative power supply recovery scheme according to a topological structure of the power distribution network to be recovered;
under a polar coordinate system, respectively calculating a Jacobian block matrix of the power flow of the power distribution network when different power supply recovery schemes are adopted;
neglecting the influence of active power disturbance on voltage, and calculating a reactive-voltage sensitivity matrix by using the Jacobian tide block matrix;
performing per unit on the reactive-voltage sensitivity matrix, calculating the coupling relation between nodes by using an Euclidean distance formula, and determining an Euclidean electrical distance;
and calculating the similarity of an electrical distance matrix based on the Euclidean electrical distance under each power supply recovery scheme, determining a power supply recovery scheme, and controlling the action of the interconnection switch.
3. The method of claim 2, wherein determining a tie switch combination scheme and determining a feasible alternative power restoration scheme according to the topology of the power distribution network to be restored comprises:
determining a tie switch combination scheme: the power grid is equipped with r and liaison switch branches, and when the follow accuse recovered the power supply, can be closed and do not exceed r liaison switches, the total p kinds of combination of liaison switch:
Figure FDA0003060826830000021
checking the topological structure of the power distribution network: and checking the p-type combination scheme of the contact switches, and screening a scheme which can enable the power-loss area of the power distribution network to recover power supply and the power distribution network to keep radial topology to serve as a slave control power supply recovery alternative scheme.
4. The method of claim 2, wherein calculating the Jacobian block matrix of the power flow of the power distribution network when different power recovery schemes are adopted under a polar coordinate system respectively comprises:
respectively calculating the Jacobian block matrixes of the power flow of the power distribution network when different power supply recovery schemes are adopted according to the following formula:
Figure FDA0003060826830000022
wherein
Figure FDA0003060826830000023
The block matrix of the Seattle is obtained;
Figure FDA0003060826830000024
is the partial derivative of Δ P to δ T;
Figure FDA0003060826830000025
is DeltaP to UTPartial derivatives of (a);
Figure FDA0003060826830000026
is Δ Q to δTPartial derivatives of (a);
Figure FDA0003060826830000027
is Δ Q to δTThe partial derivatives of (1).
5. The method of claim 2, wherein computing a reactive-voltage sensitivity matrix using the tidal Jacobian block matrix, ignoring the effect of active power disturbances on voltage, comprises:
calculating a reactive-voltage sensitivity matrix using the Seatty-to-tidal block matrix according to the following formula:
ΔQ＝(L-MH-1N)ΔU
wherein, S ═ L-MH-1N)-1And is a reactive-voltage sensitivity matrix.
6. The method according to claim 2, wherein the per-unit treatment of the reactive-voltage sensitivity matrix, the calculation of the coupling relation between the nodes by using a Euclidean distance formula and the determination of the Euclidean electrical distance comprise:
and (3) carrying out standard deviation transformation on elements in the reactive-voltage sensitivity matrix S:
Figure FDA0003060826830000028
wherein i and j correspond to a node i and a node j in the power distribution network, and the i and the j belong to [0,1 ]]N is the number of nodes of the power distribution network;
Figure FDA0003060826830000029
is the average value of the jth row element of the matrix S;
Figure FDA00030608268300000210
is the standard deviation of the jth column element;
and (3) performing range transformation on the matrix alpha after S standardization:
Figure FDA0003060826830000031
wherein x isijFor the per unit value, x, of the voltage influence capability of node j on node i due to reactive changeij∈[0,1]；
And (3) defining the Euclidean electrical distance between the nodes based on the Euclidean method by utilizing the per-unit reactive-voltage matrix x:
Figure FDA0003060826830000032
wherein EDijRepresenting the Euclidean electrical distance, ED, between node i and node jij∈[0,1]。
7. The method of claim 2, wherein calculating electrical distance matrix similarity based on the euclidean electrical distances under each power restoration scheme, determining a restoration power scheme, and controlling tie switch action comprises:
calculating the cosine similarity of each electrical distance matrix and the electrical distance matrix in normal operation:
Figure FDA0003060826830000033
wherein A isijEach component of the electrical distance matrix in normal operation; b isijCalculating an electrical distance matrix with similarity to the A, wherein the electrical distance matrix comprises an electrical distance matrix in normal operation and electrical distance matrices under various power supply recovery schemes;
calculating the average value of the cosine similarity of the electrical distance: respectively calculating cosine similarity average values under each scene:
Figure FDA0003060826830000034
and determining a slave control power supply recovery scheme, controlling the action of the interconnection switch, and recovering the power supply of the power-off area.
8. The method of claim 1, wherein: executing a power distribution network fault self-healing control main control scheme, calculating the optimal combination of all section switches and interconnection switches of the network, and optimizing the running state of the power distribution network, wherein the method comprises the following steps:
determining an optimal operation objective function of the power distribution network;
determining a network operation constraint condition;
and (3) iterative solution is carried out by adopting a genetic algorithm, the optimal switch combination of the power distribution network meeting the network operation constraint condition is calculated according to the optimal operation objective function of the power distribution network, the actions of the contact switch and the section switch are controlled, and the operation state of the power distribution network is adjusted to be optimal.
9. The method of claim 8, wherein determining the optimal operational objective function for the power distribution network comprises:
the method aims at minimizing the active loss of the power distribution network:
Figure FDA0003060826830000041
wherein l is the total branch number of the power distribution network; k is a radical ofiIs the state of the ith branch, kiBranch off when 0, ki1, the branch is closed; riThe resistance value of the ith branch is; u shapeiRepresenting the voltage amplitude of the terminal node of the ith branch; pi、QiRespectively representing active power and reactive power injected by the tail end node of the ith branch;
the minimum voltage deviation of the nodes of the power distribution network is taken as a target:
Figure FDA0003060826830000042
wherein, UiIs the actual voltage at node i; u shapeiNRepresents the nominal voltage of node i;
constructing a comprehensive objective function:
minf＝w1f1+w2f2
w1+w2＝1
0≤w1≤1
0≤w2≤1
wherein, w1，w2The weighting coefficients of the active network loss and the voltage deviation are respectively.
10. The method of claim 8, wherein determining network operating constraints comprises:
determining power constraint conditions of each power flow of the power distribution network:
Figure FDA0003060826830000043
wherein, Pi、QiAre respectively nodesi, injecting the active power and the reactive power; ui and Uj are the amplitude values of the voltages of the nodes i and j respectively; gij and Bij are conductance and susceptance between nodes i and j; δ ij is the voltage phase difference of nodes i, j;
determining a voltage constraint condition of each node of the power distribution network:
Uimin≤Ui≤Uimax
wherein, UiIs the voltage amplitude of node i; u shapeimax、UiminRespectively a maximum voltage amplitude and a minimum voltage amplitude of the node i;
determining current constraint conditions of each branch of the power distribution network:
Ik≤Ikmax
wherein, Ik、IkmaxThe current magnitude of the branch k and the maximum allowed current are respectively;
determining the capacity constraint conditions of each branch of the power distribution network:
Sk≤Skmax
wherein S isk、SkmaxRespectively transmitting the size of power and the maximum allowable transmission power for the branch k;
and determining constraint conditions of a network topology structure of the power distribution network, and keeping the power distribution network in a radial topology.
11. The utility model provides a distribution network master-slave mode fault self-healing control system which characterized in that includes:
the control system comprises a determining control framework module, a master-slave fault self-healing control framework module, a distributed slave control module, a centralized master control module, a section switch module and a power distribution network main-slave fault self-healing control framework module, wherein the determining control framework module is used for determining a master-slave fault self-healing control framework of the power distribution network, controlling the action of the contact switch to complete power supply recovery of a power loss area, solving the optimal combination of the contact switch and the section switch of the power distribution network by adopting the centralized master control module, and adjusting the running state of the power distribution network to recover to the optimal state;
the initialization module is used for initializing a power distribution network topological structure and electrical quantity parameters after a fault branch is cut off according to power distribution network measurement unit measurement data, wherein the electrical quantity parameters comprise node voltage, branch current and load power;
the execution slave control scheme module is used for executing a power distribution network fault self-healing control slave control scheme and formulating a power distribution network connection switch action scheme to be recovered;
and the execution main control scheme module is used for executing the distribution network fault self-healing control main control scheme, calculating the optimal combination of all section switches and interconnection switches of the network and optimizing the running state of the distribution network.
CN202110512269.8A 2021-05-11 Master-slave fault self-healing control method and system for power distribution network Active CN113363987B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110512269.8A CN113363987B (en) 2021-05-11 Master-slave fault self-healing control method and system for power distribution network

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110512269.8A CN113363987B (en) 2021-05-11 Master-slave fault self-healing control method and system for power distribution network

Publications (2)

Publication Number Publication Date
CN113363987A true CN113363987A (en) 2021-09-07
CN113363987B CN113363987B (en) 2024-05-03

Family

ID=

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110029148A1 (en) * 2007-12-12 2011-02-03 Fang Yang Load restoration for feeder automation in electric power distribution systems
CN104701831A (en) * 2015-03-30 2015-06-10 国家电网公司 Power distribution network self-healing control method
CN111476423A (en) * 2020-04-13 2020-07-31 国网河北省电力有限公司电力科学研究院 Energy interconnected distribution network fault recovery method

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110029148A1 (en) * 2007-12-12 2011-02-03 Fang Yang Load restoration for feeder automation in electric power distribution systems
CN104701831A (en) * 2015-03-30 2015-06-10 国家电网公司 Power distribution network self-healing control method
CN111476423A (en) * 2020-04-13 2020-07-31 国网河北省电力有限公司电力科学研究院 Energy interconnected distribution network fault recovery method

Non-Patent Citations (6)

* Cited by examiner, † Cited by third party
Title
M. -T. KUO: "Application of the Artificial Bee Colony Algorithm to Scheduling Strategies for Energy-Storage Systems of a Microgrid With Self-Healing Functions", IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS *
娄铖伟;张筱慧;丛鹏伟;张博;唐巍;张璐;: "含柔性软开关的有源配电网故障恢复策略", 电力系统自动化, no. 01 *
战一鸣: "分布式馈线自动化故障恢复技术研究", 中国硕士论文全文数据库工程科技Ⅱ辑 *
管霖等: "面向暂态电压控制的大电网区域划分方法", 电网技术 *
马天祥;贾伯岩;卢志刚;程肖;王代远;: "基于主从博弈理论的能源互联配电网多能互补协调故障恢复方法", 电力自动化设备, no. 05 *
马秀达等: "多端柔性直流配电网的分层控制策略设计", 西安交通大学学报 *

Similar Documents

Publication Publication Date Title
Shayeghi et al. Multi-machine power system stabilizers design using chaotic optimization algorithm
CN109378815B (en) Power distribution network closed loop switching power supply control method, device and equipment
CN110661265B (en) Safety constraint optimal power flow calculation method based on branch circuit breaking distribution factor
CN110932281B (en) Multi-section cooperative correction method and system based on quasi-steady-state sensitivity of power grid
CN108270248B (en) Active safety correction control method based on quasi-steady-state sensitivity analysis
CN109635331B (en) Economic short-circuit current limiter optimal configuration method
Tanti et al. Optimal placement of custom power devices in power system network to mitigate voltage sag under faults
CN102403720A (en) Hyper-real-time setting method for superposed time sequences based on transient voltage safety margin
CN114665479B (en) Power distribution network power supply recovery method and system considering network reconfiguration
CN114336674B (en) Distributed toughness frequency control method for alternating-current micro-grid
CN112989597A (en) Short-circuit current calculation method and system
CN109377020B (en) Power transmission network planning method considering load transfer capacity of power distribution network
CN115021249A (en) Distribution network transient characteristic equivalence method and system considering distributed photovoltaic
CN104617575A (en) Method for using static security analysis to assess flow insolubility of anticipated faults
WO2022064073A1 (en) Distribution power system fault control apparatus and method
CN113363987A (en) Master-slave type fault self-healing control method and system for power distribution network
Lee et al. Modelling and locating unified power‐flow controllers for static voltage stability enhancements
CN113363987B (en) Master-slave fault self-healing control method and system for power distribution network
CN110544960A (en) distributed control method for improving reactive power sharing capability of island microgrid
CN111786382B (en) Power distribution network load recovery amount calculation method considering weighted power flow entropy
CN115940120A (en) Master-slave self-healing control method and system based on power distribution network state evaluation
Li et al. Explicit linear model of bus impedance with unknown branch status
CN111082414B (en) Transient voltage calculation method and system
CN110120669A (en) Limit rack method of adjustment, device and the terminal device of grid short circuit electric current
CN112198454B (en) Method for carrying out local iteration of short-circuit current in network containing new energy power supply

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant