CN108919055A - A kind of photovoltaic Fault Diagnosis Method for Distribution Networks of roof containing high density based on Petri network - Google Patents
A kind of photovoltaic Fault Diagnosis Method for Distribution Networks of roof containing high density based on Petri network Download PDFInfo
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- CN108919055A CN108919055A CN201810754005.1A CN201810754005A CN108919055A CN 108919055 A CN108919055 A CN 108919055A CN 201810754005 A CN201810754005 A CN 201810754005A CN 108919055 A CN108919055 A CN 108919055A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/086—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution networks, i.e. with interconnected conductors
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/088—Aspects of digital computing
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- 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
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
- Y04S10/52—Outage or fault management, e.g. fault detection or location
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- Theoretical Computer Science (AREA)
- Photovoltaic Devices (AREA)
Abstract
A kind of photovoltaic Fault Diagnosis Method for Distribution Networks of roof containing high density based on Petri network of the present invention belongs to Fault Diagnosis of Distribution Network technical field, more particularly to the Fault Diagnosis Method for Distribution Networks of the photovoltaic of roof containing high density.The switching node information uploaded including obtaining terminal device；It provides network positive direction, each switching node is numbered, carry out information configuration；Determine fault section location rule；Petri network fault location model is established according to distribution net work structure；To the assigned initial marking in corresponding library in location model；Calculate the state equation of Petri network；Judge whether igniting is completed, if being completed, according to section library in mark, provide final positioning result, terminate positioning；It is returned if not completing and continues to calculate.The present invention can carry out fast and accurately fault section location to the distribution network system of the photovoltaic of roof containing high density, effectively improve efficiency of fault diagnosis and fault-tolerance.
Description
Technical field
A kind of photovoltaic Fault Diagnosis Method for Distribution Networks of roof containing high density based on Petri network of the present invention belongs to power distribution network event
Hinder diagnostic techniques field, more particularly to the Fault Diagnosis Method for Distribution Networks of the photovoltaic of roof containing high density.
Background technique
In recent years, have many advantages, such as that cleanliness without any pollution, renewable, without transporting distributed photovoltaic power are increasingly becoming biography
Unite the supplement and effectively support of centralized power generation mode, roof photovoltaic power generation system become Future Power System development trend it
One.After distributed photovoltaic power accesses power distribution network, so that traditional simple single supply Radial network becomes complicated mostly electricity
Source network, to change the direction of tide and topological structure of conventional electrical distribution net.When the electric power of the rooftop photovoltaic systems containing high density
When network failure, need quickly and accurately to judge fault zone and isolated fault section, providing for consequent malfunction recovery can
By foundation, guarantee the normal operation in non-faulting region, improves power supply reliability and continuity.
The supervisory control and data aquisition system that electric network failure diagnosis is equipped with according to grid dispatching center（SCADA）And energy pipe
Reason system（EMS）The fault message uploaded is analyzed.But after a large amount of fault diagnosis datas pour in control centre, operator
Member's Artificial Diagnosis fail operation becomes very difficult.Therefore it needs to make traditional fault diagnosis frame in terms of quick and precisely property
Very big promotion.
Mainly there are matrix algorithm and artificial intelligence to the research method of distribution network failure orientation problem（AI）Algorithm.Matrix is calculated
Method has the shortcomings that poor fault tolerance when line feed terminals upload information lacks, it is difficult to ensure that the accuracy of positioning.Relative to other
Intelligent algorithm, the relationship between the various change and variation that may occur in Petri network system emphasis simulation system, for retouching
State the Discrete Dynamic process of system.And the failure process of power grid is a typical Discrete Dynamic process, therefore Petri network is more suitable
It shares to describe the dynamic behaviour in power grid under each element fault state.For the power distribution network of the photovoltaic of roof containing high density, base
In Petri network method for diagnosing faults can lifting system fault section location rapidity, accuracy and fault-tolerance.
Summary of the invention
The purpose of the present invention is to overcome the deficiency in the prior art, provides a kind of light of roof containing high density based on Petri network
Fault Diagnosis Method for Distribution Networks is lied prostrate, this method can quick and precisely positioning failure section, raising positioning fault-tolerance mention for operations staff
For diagnostic tool, manpower, financial resources, time are saved, enhances power supply reliability and continuity.
The present invention is realized using following scheme：
A kind of Fault Diagnosis Method for Distribution Networks for the photovoltaic of roof containing high density based on Petri network, includes the following steps：
1）Obtain the switching node information that terminal device uploads；
2）It provides network positive direction, each switching node is numbered, carry out information configuration；
3）Determine fault section location rule；
4）Petri network fault location model is established according to distribution net work structure；
5）To the assigned initial marking in corresponding library in location model；
6）Calculate the state equation of Petri network；
7）Judge whether igniting is completed, if being completed, enters step 8）；If not completing igniting, return step 6）；
8）According to section library in mark, provide final positioning result, terminate positioning.
Step 1）Described in terminal device upload switching node information include fault current information and switch motion information.
Step 2）Described in network positive direction be system power supply pointing system end direction.
Step 4）Middle to establish Petri network fault location model according to distribution net work structure, step specifically includes：
4-1）Determine each library institute physical meaning；
4-2）Determine each transition ignition condition.
Compared with the existing technology, the beneficial effects of the invention are as follows：
1, conventional fault diagnosis method is directed to single supply Radial network structure mostly, establishes failure according to switching value and electrical quantity
Diagnostic model.But a large amount of distributed photovoltaic access power distribution networks change system load flow direction and topological structure, traditional fault diagnosis
Method is no longer applicable in.The short circuit current direction that the method for diagnosing faults of proposition is uploaded using line feed terminals is more applicable in as foundation
Property, reference can be provided for control centre operations staff, save a large amount of manpower financial capacity's times；
2, when certain switching node line feed terminals upload information lacks, the method for diagnosing faults of proposition can input according to the node,
It exports the fault current information that end node uploads and fault message amendment is carried out to this node, improve diagnosis fault-tolerance and accuracy；
3, the method for diagnosing faults proposed is based on Petri network algorithm.Petri network algorithm has parallel processing relative to other algorithms
Advantage, be greatly improved fault diagnosis speed.And Petri network algorithm can be by visualizing location model, description node event
Hinder the causality of information and fault section；
4, it is based in Petri network algorithm method for diagnosing faults in the past, to prevent each switching node on the ipsilateral route of fault section
The fault current information that terminal uploads is identical and causes to misjudge, and inhibits arc to inhibit non-faulting by addition in diagnostic model mostly
The method of section transition triggering improves diagnostic accuracy, causes diagnostic model excessively complicated, is unfavorable for observing the dynamic row of Tokken
For.The method for diagnosing faults of proposition accordingly changes the triggering rule of all input magazine institute phase "AND" by setting, thus instead of
The function and effect for inhibiting arc greatly reduce and inhibit arc quantity, simplify Petri net model structure, are easy to observe the dynamic row of Tokken
For.And for complicated distribution system, it is easy to model structure topology, is more suitable for the photovoltaic power distribution network system of roof containing high density
System.
Detailed description of the invention
Fig. 1 is that the present invention is based on the calculations of the Fault Diagnosis Method for Distribution Networks for the photovoltaic of roof containing high density of Petri network
Method flow chart；
Fig. 2 is the simple distribution network figure of the photovoltaic containing roof in the present invention；
Fig. 3 is the Petri network fault location model embodiment figure in the present invention.
Specific embodiment
It elaborates in the following with reference to the drawings and specific embodiments to the present invention.
Shown in Fig. 1, a kind of Fault Diagnosis of Distribution Network side for the photovoltaic of roof containing high density based on Petri network of the present invention
Method includes the following steps：
1）Obtain the switching node information that terminal device uploads；System detection arrives when being occurred using failure fault current information with
Switch motion information establishes fault location model convenient for the later period.
2）It provides network positive direction, each switching node is numbered, carry out information configuration, specific step is as follows：
2-1）Regulation is the positive direction of network by the direction of system power supply pointing system end；
2-2）Switching node each in network is numbered, and defines the incidence relation of each node in network：Such as by the input terminal of node i
Node definition be with network pros round about on adjacent to i node；The output end node definition of node i be with network just
Adjacent to the node of i on the same direction of direction；The T node definition of node i is adjacent with node i and has identical input terminal node
Node；It is the natural number for not being 0 with the i being subsequently noted herein.
2-3）Fault message is corrected, in actual moving process, the fault message that line feed terminals upload is highly prone to ring
Border factor is influenced and is lost.
The method that fault message is modified：If the fault message phase that the input of node i, output end node upload
Together, then the fault message of node i is modified to same type fault message.This step can be improved the fault-tolerance of this method for diagnosing faults with
Accuracy.
Below with reference to Fig. 2, the incidence relation of node each in network is shown in Table 1 below, each Node Switch in corresponding diagram 2.
Table 1
3）Determine fault section location rule
According to the fault current direction that nodal test each under distribution network structure and malfunction arrives, such as to fault location rule
Under：
Rule 1, if all adjacent output end nodes of node i detect positive fault current information, judge node i with
The section that its all output end node surrounds is non-faulting section, is otherwise fault section.
Rule 2, if all adjacent input terminal nodes of node i detect reverse fault current information or node i institute
There is T node to detect positive fault current information, then the section for judging that node i is surrounded with all input nodes and T node is
Otherwise non-faulting section is fault section.
4）According to distribution net work structure and step 3）Identified locating rule establishes Petri network failure as shown in Figure 3
Location model.
Petri network each element is defined as follows,
Library institute：State elements are also known as library institute, and library not only indicates a place, but also indicates to house certain money in the place
Source；
Transition：The consumption of resource uses and generates the variation for causing state elements, also known as T element；
Tokken：Library in resource quantity；
Network identity matrix：Network identity matrixFor indicate Petri network library in Tokken number, including two categories
Know matrix initial marking matrixWith final state identity matrix, initial marking matrixIndicate the Petri network of original state
The Tokken number distribution situation of middle library institute node；Final state identity matrixIndicate entry into library institute node in the Petri network of stable state
Tokken number distribution situation, wherein n is the natural number greater than 0.
Each library institute's element of the Petri net model built in the method for diagnosing faults of proposition and transition physical definition are as follows,
CB1：CB1 tripping.
LCB1：It is faulty in feeder line LCB1.
Ri：Crossover position is without meaning.
Si：It is positive direction that terminal, which uploads short circuit current direction, at Si.
Li：Section Li breaks down.
Inhibit arc：When library in when being identified as sky transition igniting triggering.
In the built Petri net model of the present invention, the physical significance of arc is inhibited to be：
WhenWhen section breaks down, prevent because of terminalEach terminal in front upload simultaneously short circuit current direction be positive direction and
MisjudgementSection breaks down, and wherein n is the natural number greater than 0.
Specific embodiment 1：With section in simple distribution network shown in Fig. 2For breaking down, work as sectionEvent occurs
When barrier, switching node、、The positive fault current information of place's terminal upload, therefore the model of Petri network fault location shown in Fig. 3
Middle library institute、、Include Tokken.And library institute、、Respectively with transition、、To inhibit arc to be connected, that is, change、、It is unable to satisfy trigger condition, Tokken can not be transferred to corresponding library institute、、In, so that it is guaranteed that the standard of fault diagnosis
True property.
For transition、、、、, the ignition condition that it is changed, which is arranged, is：
This changes all input magazine institute phase "AND", i.e., when containing Tokken in all input magazine institutes of transition（When transition with
Input magazine, which passes through, inhibits arc when being connected, input magazine in mark must be sky）, transition can light a fire triggering.This measure
Meaning be：
It is based in Petri network algorithm method for diagnosing faults in the past, to prevent each switching node on the ipsilateral route of fault section whole
It holds the fault current information uploaded identical and causes to misjudge, inhibit arc to inhibit non-faulting area by addition in diagnostic model mostly
The method of Duan Bianqian triggering improves diagnostic accuracy, causes diagnostic model excessively complicated, is unfavorable for observing the dynamic behaviour of Tokken.
The method for diagnosing faults of proposition accordingly changes the triggering rule of all input magazine institute phase "AND" by setting, thus
Instead of inhibiting the function and effect of arc, greatly reduces and inhibit arc quantity, simplify Petri net model structure, be easy to observe the dynamic of Tokken
State behavior.
Specific embodiment 2：With section in simple distribution network shown in Fig. 2For breaking down, work as sectionEvent occurs
When barrier, switching node、、The positive fault current information of place's terminal upload, therefore the model of Petri network fault location shown in Fig. 3
Middle library institute、、Include Tokken, library instituteInterior no Tokken.According to all input magazine institute phase "AND" trigger gauges of the transition of setting
Then, library instituteWith transitionBe connected andIt is interior to be free of Tokken, therefore changeIt is unsatisfactory for trigger condition.Inhibit arc former in conjunction with above
Reason, then change、、、It cannot trigger, changeMeet trigger condition, Tokken is eventually transferred into library instituteIn, i.e. area
SectionIt breaks down, diagnosis is correct.
5）To the assigned initial marking in corresponding library in location model, with section in shown simple distribution networkEvent occurs
For barrier, switching node、、Place has positive fault current to flow through,、、Locate terminal and uploads positive failure electricity
Stream information, Gu Kusuo、、In there are initial marking, obtaining corresponding initial marking vector is：。
6）Calculate the state equation of Petri network.
The state equation is, wherein n is natural number.
Incidence matrix：For describing the topological structure of Petri network, according to library institute in petri netWith transitionPass
Connection relationship, it is known thatIt is oneRowThe matrix of column.
Igniting vector：Igniting vectorActual ignition sequence for the transition node for indicating to meet trigger condition.Igniting
The corresponding vector of transition node in set 1, be otherwise 0.
Petri network state equation：Incidence matrix, network identity matrix, igniting vectorAfter formation, Petri network is utilized
State equation analyzes Petri network change procedure, and state equation describes the dynamic behaviour process of petri net, to make system
Status indicatorIt changes.
7）The incidence matrix determined according to above step, initial marking matrix, igniting vectorAnd state equation, identity matrix is calculated, according to identity matrixWhether meet trigger condition again to judge a little
Whether fire is completed, if being completed, enters step 8）；
If igniting does not complete, according to state equation and obtained identity matrix, then 6 are entered step）Continue calculate until
Igniting is completed.
8）When the transition that Petri network can not trigger, i.e. Petri network reaches stable state, finally obtains stable state
Descend to obtain identity matrix；And according to final identity matrix obtain section library in mark, provide final positioning result, be diagnosed to be therefore
Hinder section, terminates positioning.
From the point of view of the process of specific implementation, the algorithm is practical, can quick and precisely positioning failure section, raising position
Fault-tolerance.
Claims (7)
1. a kind of Fault Diagnosis Method for Distribution Networks for the photovoltaic of roof containing high density based on Petri network, which is characterized in that packet
Include following steps：
1）Obtain the switching node information that terminal device uploads；
2）It provides network positive direction, each switching node is numbered, carry out information configuration；
3）Determine fault section location rule；
4）Petri network fault location model is established according to distribution net work structure；
5）To the assigned initial marking in corresponding library in location model；
6）Calculate the state equation of Petri network；
7）Judge whether igniting is completed, if being completed, enters step 8）；If not completing igniting, return step 6）；
8）According to section library in mark, provide final positioning result, terminate positioning.
2. the Fault Diagnosis of Distribution Network side for the photovoltaic of roof containing high density according to claim 1 based on Petri network
Method, which is characterized in that step 1）Described in the switching node information that uploads of terminal device include that fault current information and switch are dynamic
Make information.
3. the Fault Diagnosis of Distribution Network side for the photovoltaic of roof containing high density according to claim 1 based on Petri network
Method, which is characterized in that step 2）Described in network positive direction be system power supply pointing system end direction.
4. the Fault Diagnosis of Distribution Network side for the photovoltaic of roof containing high density according to claim 1 based on Petri network
Method, which is characterized in that step 4）Middle to establish Petri network fault location model according to distribution net work structure, step specifically includes：
4-1）Determine each library institute physical meaning；
4-2）Determine each transition ignition condition.
5. the Fault Diagnosis of Distribution Network side for the photovoltaic of roof containing high density according to claim 1 based on Petri network
Method, which is characterized in that step 2）Middle regulation network positive direction numbers each switching node, carries out information configuration, specific steps are such as
Under：
2-1）Regulation is the positive direction of network by the direction of system power supply pointing system end；
2-2）Switching node each in network is numbered, and defines the incidence relation of each node in network：By the terminal input section of node i
Point be defined as with network pros round about on adjacent to i node；The output end node definition of node i is and network is square
To on the same direction adjacent to the node of i；The T node definition of node i is adjacent with node i and with identical input terminal node
Node；The i is the natural number for not being 0；
2-3）Fault message is corrected.
6. the Fault Diagnosis of Distribution Network side for the photovoltaic of roof containing high density according to claim 5 based on Petri network
Method, which is characterized in that be if the failure that the input of node i, output end node upload to the method that fault message is modified
Information is identical, then the fault message of node i is modified to same type fault message, and the i is the natural number for not being 0.
7. the Fault Diagnosis of Distribution Network side for the photovoltaic of roof containing high density according to claim 1 based on Petri network
Method, which is characterized in that as follows to fault location rule：
Rule 1, if all adjacent output end nodes of node i detect positive fault current information, judge node i with
The section that its all output end node surrounds is non-faulting section, is otherwise fault section；
Rule 2, if all adjacent input terminal nodes of node i detect reverse fault current information or all T sections of node i
Point detects positive fault current information, then judges section that node i and all input nodes and T node surround for non-faulting
Otherwise section is fault section；The i is the natural number for not being 0.
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| CN109828185A (en) * | 2019-03-05 | 2019-05-31 | 南京理工大学 | For the electrical power distribution network fault location method containing roof photovoltaic power generation system |
| CN110470951A (en) * | 2019-08-18 | 2019-11-19 | 天津大学 | Active power distribution network method for diagnosing faults based on PMU information and Petri network |
| CN113295969A (en) * | 2021-06-30 | 2021-08-24 | 广东电网有限责任公司 | Method, system, terminal and storage medium for rapidly positioning power distribution network fault |
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| CN109828185A (en) * | 2019-03-05 | 2019-05-31 | 南京理工大学 | For the electrical power distribution network fault location method containing roof photovoltaic power generation system |
| CN109828185B (en) * | 2019-03-05 | 2022-02-18 | 南京理工大学 | Power distribution network fault positioning method for roof-containing photovoltaic power generation system |
| CN110470951A (en) * | 2019-08-18 | 2019-11-19 | 天津大学 | Active power distribution network method for diagnosing faults based on PMU information and Petri network |
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| CN113295969A (en) * | 2021-06-30 | 2021-08-24 | 广东电网有限责任公司 | Method, system, terminal and storage medium for rapidly positioning power distribution network fault |
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Application publication date: 20181130 |