CN114021350A - Cascading failure probability calculation method and system for power system - Google Patents

Cascading failure probability calculation method and system for power system Download PDF

Info

Publication number
CN114021350A
CN114021350A CN202111308246.1A CN202111308246A CN114021350A CN 114021350 A CN114021350 A CN 114021350A CN 202111308246 A CN202111308246 A CN 202111308246A CN 114021350 A CN114021350 A CN 114021350A
Authority
CN
China
Prior art keywords
probability
failure
fault
voltage
line
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.)
Pending
Application number
CN202111308246.1A
Other languages
Chinese (zh)
Inventor
余浩
邹小兵
彭穗
陈武晖
段瑶
左郑敏
陈鸿琳
金吴清
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.)
Guangdong Power Grid Co Ltd
Original Assignee
Guangdong Power Grid 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 Guangdong Power Grid Co Ltd filed Critical Guangdong Power Grid Co Ltd
Priority to CN202111308246.1A priority Critical patent/CN114021350A/en
Publication of CN114021350A publication Critical patent/CN114021350A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/08—Probabilistic or stochastic CAD
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/02—Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computer Hardware Design (AREA)
  • Evolutionary Computation (AREA)
  • Geometry (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The invention provides a method and a system for calculating cascading failure probability of a power system, wherein the method comprises the following steps: acquiring current power system operation data, and judging whether the first equipment has a fault according to the current power system operation data; if so, calculating the probability of the low-voltage fault of the bus according to the voltage change value of the bus, and calculating the probability of the overload outage fault of the line according to the power change value of the line; calculating the probability of the second equipment failing after the first equipment fails according to the probability of the bus low-voltage failure and the probability of the line overload outage failure; and calculating the probability of the cascading failure of the power system according to the probability of the failure of the first equipment and the probability of the failure of the second equipment after the failure of the first equipment. The invention deduces the calculation of the single conditional probability of the cascading failure in the power system by using the Bayesian theory, carries out quantitative analysis on the mutual influence between two mutually independent failures in the power system, and improves the accuracy of failure calculation.

Description

Cascading failure probability calculation method and system for power system
Technical Field
The invention relates to the technical field of power system fault diagnosis, in particular to a method and a system for calculating cascading fault probability of a power system.
Background
The power system faults can be divided into single faults and multiple faults, wherein the single faults refer to single element faults; multiple failures refer to failures of a plurality of elements, and can be divided into common mode failures and sequential failures according to the occurrence time of the failures of the elements. The common mode fault refers to an event that multiple faults occur simultaneously due to the same external cause, although the multiple faults occur simultaneously, the faults have no mutual cause-effect relationship, for example, simultaneous outage of double-circuit transmission lines on the same tower due to tower failure or lightning stroke is a typical common mode fault. Each fault in successive faults often occurs in sequence, which can be divided into cascading faults and independent successive faults according to the existence or non-existence of correlation between the faults. There is no correlation between each fault in the independent successive faults. Cascading failure refers to the condition that one or more element failures of the system spread to other parts of the system, new failures are induced, updated failures are caused to occur in a cascading mode, and cascading and correlation characteristics exist among the failures. The scale of the power system is gradually enlarged, the power supply reliability and the economic benefit are improved, and meanwhile, the risk of a large power failure accident is increased. In recent years, a large number of blackout accidents occur worldwide, and researches show that the large blackout accidents are mostly caused by a series of cascading failures.
The existing cascading failure analysis method mainly comprises the following steps: the method comprises a pattern search method, a research method based on a complex system theory and a research method based on a complex network. The probability calculation of the cascading failures is mainly based on statistical data of conditional probability and power system element failure probability, the statistical data of the power system element failure probability is mostly used in the vulnerability assessment based on risks of the power system cascading failures, and the probability calculation of the accident chain, namely the cascading failures, mostly uses the conditional probability. Since a cascading failure is a set of several system states with a time sequence, and the former system state affects the occurrence probability of the latter system state, the cascading failure probability is essentially a conditional probability. For the calculation of cascading failures of a power system, generally, a single failure has more historical statistical data, and the occurrence probability of the single failure can be directly calculated, however, the existing power system conditional probability formula is mainly used for solving the occurrence probability of an accident chain, and the correlation or the mutual influence between two power system failures cannot be analyzed in detail.
Disclosure of Invention
In order to solve the above problems in the prior art, the present invention provides a method and a system for calculating the cascading failure probability of an electrical power system, which analyze the correlation between two electrical power system failures or the mutual influence thereof.
The invention provides a power system cascading failure probability calculation method in a first aspect, which comprises the following steps:
acquiring current power system operation data, and judging whether the first equipment has a fault according to the current power system operation data;
if so, calculating the probability of the low-voltage fault of the bus according to the voltage change value of the bus, and calculating the probability of the overload outage fault of the line according to the power change value of the line;
calculating the probability of the second equipment failing after the first equipment fails according to the probability of the bus low-voltage failure and the probability of the line overload outage failure;
and calculating the probability of the cascading failure of the power system according to the probability of the failure of the first equipment and the probability of the failure of the second equipment after the failure of the first equipment.
Further, the probability that the second device fails after the first device fails is calculated according to the probability of the bus low-voltage fault and the probability of the line overload outage fault, and the calculation is performed according to the following formula:
P(T2|T1)＝a*Pv+b*Pp；
wherein, T1For the first device to fail, T2For the second device to fail, P (T)2|T1) Is the probability, P, of a failure of a second device after a failure of a first devicevIs the probability of bus low voltage fault, a is the weight of the probability of bus low voltage fault, PpB is the weight of the probability of the line overload outage fault.
Further, the probability of the cascading failure of the power system is calculated according to the probability of the failure of the first device and the probability of the failure of the second device after the failure of the first device, and is calculated according to the following formula:
P(Ci)＝P(T1)P(T2|T1)；
wherein, CiFor cascading failures of the power system, P (C)i) As the probability of cascading failure of the power system, T1For the first device to fail, T2For the second device to fail, P (T)1) Is the probability of failure of the first device, P (T)2|T1) Is the probability that the second device fails after the first device fails.
Further, the probability of the bus low-voltage fault is calculated according to the bus voltage change value, and is calculated by the following formula:
Pv＝Pv0，x>1；
Figure BDA0003340906900000031
Pv＝1，x<α；
wherein，PvProbability of bus low-voltage fault, Pv0The probability of the bus low-voltage fault when the line voltage is normal is shown, x is the current bus voltage value, and alpha is the preset bus voltage value.
Further, the probability of the line overload outage fault is calculated according to the line power change value, and is calculated by the following formula:
Pp＝PP0，PlPl Rated；
Figure BDA0003340906900000032
Pp＝1，Pl≥Pl Max；
wherein, PpFor the probability of line overload outage failure, PP0Probability of line overload outage fault occurring when line tide is normal, PlFor the current line power value, Pl RatedRated power of the line, Pl MaxLimit power values are transmitted for the lines.
A second aspect of the present invention provides a power system cascading failure probability calculating system, including: the device comprises a judgment module, a first calculation module, a second calculation module and a third calculation module; wherein:
the judging module is used for acquiring current power system operation data and judging whether the first equipment has a fault according to the current power system operation data;
the first calculation module is used for calculating the probability of the low-voltage fault of the bus according to the voltage change value of the bus and calculating the probability of the overload outage fault of the line according to the power change value of the line when the judgment module judges that the first equipment has the fault;
the second calculation module is used for calculating the probability of the second equipment failing after the first equipment fails according to the probability of the bus low-voltage fault and the probability of the line overload outage fault;
and the third calculation module is used for calculating the probability of the cascading failure of the power system according to the probability of the failure of the first equipment and the probability of the failure of the second equipment after the failure of the first equipment.
Further, the probability that the second device fails after the first device fails is calculated according to the probability of the bus low-voltage fault and the probability of the line overload outage fault, and the calculation is performed according to the following formula:
P(T2|T1)＝a*Pv+b*Pp；
wherein, T1For the first device to fail, T2For the second device to fail, P (T)2|T1) Is the probability, P, of a failure of a second device after a failure of a first devicevIs the probability of bus low voltage fault, a is the weight of the probability of bus low voltage fault, PpB is the weight of the probability of the line overload outage fault.
Further, the probability of the cascading failure of the power system is calculated according to the probability of the failure of the first device and the probability of the failure of the second device after the failure of the first device, and is calculated according to the following formula:
P(Ci)＝P(T1)P(T2|T1)；
wherein, CiFor cascading failures of the power system, P (C)i) As the probability of cascading failure of the power system, T1For the first device to fail, T2For the second device to fail, P (T)1) Is the probability of failure of the first device, P (T)2|T1) Is the probability that the second device fails after the first device fails.
Further, the probability of the bus low-voltage fault is calculated according to the bus voltage change value, and is calculated by the following formula:
Pv＝Pv0，x>1；
Figure BDA0003340906900000051
Pv＝1，x<α；
wherein, PvProbability of bus low-voltage fault, Pv0The probability of the bus low-voltage fault when the line voltage is normal is shown, x is the current bus voltage value, and alpha is the preset bus voltage value.
Further, the probability of the line overload outage fault is calculated according to the line power change value, and is calculated by the following formula:
Pp＝PP0，PlPl Rated；
Figure BDA0003340906900000052
Pp＝1，Pl≥Pl Max；
wherein, PpFor the probability of line overload outage failure, PP0Probability of line overload outage fault occurring when line tide is normal, PlFor the current line power value, Pl RatedRated power of the line, Pl MaxLimit power values are transmitted for the lines.
Compared with the prior art, the embodiment of the invention has the beneficial effects that:
the invention provides a method and a system for calculating cascading failure probability of a power system, wherein the method comprises the following steps: acquiring current power system operation data, and judging whether the first equipment has a fault according to the current power system operation data; if so, calculating the probability of the low-voltage fault of the bus according to the voltage change value of the bus, and calculating the probability of the overload outage fault of the line according to the power change value of the line; calculating the probability of the second equipment failing after the first equipment fails according to the probability of the bus low-voltage failure and the probability of the line overload outage failure; and calculating the probability of the cascading failure of the power system according to the probability of the failure of the first equipment and the probability of the failure of the second equipment after the failure of the first equipment. The invention utilizes the quantitative risk assessment method, avoids the complexity and complication of obtaining the conditional probability by a large amount of experimental and statistical data in the calculation of the single conditional probability of the cascading failure, deduces the calculation of the single conditional probability of the cascading failure in the power system by using the Bayesian theory, and can also carry out quantitative analysis on the mutual influence between two mutually independent failures in the power system by using the theory, thereby improving the accuracy of the failure calculation.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a method for calculating a cascading failure probability of a power system according to an embodiment of the present invention;
FIG. 2 is a graphical illustration of a probability function of low voltage evidence provided by an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating a probability function relationship of line overload outage evidence provided by an embodiment of the present invention;
fig. 4 is a device diagram of a power system cascading failure probability calculation system according to an embodiment of the present invention;
fig. 5 is a block diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be understood that the step numbers used herein are for convenience of description only and are not intended as limitations on the order in which the steps are performed.
It is to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The terms "comprises" and "comprising" indicate the presence of the described features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The term "and/or" refers to and includes any and all possible combinations of one or more of the associated listed items.
A first aspect.
Referring to fig. 1, an embodiment of the invention provides a method for calculating a cascading failure probability of a power system, including:
and S10, acquiring current power system operation data, and judging whether the first equipment has a fault according to the current power system operation data.
And S20, if yes, calculating the probability of the bus low-voltage fault according to the bus voltage change value, and calculating the probability of the line overload outage fault according to the line power change value.
Preferably, the probability of the bus low-voltage fault is calculated according to the bus voltage variation value by the following formula:
Pv＝Pv0，x>1；
Figure BDA0003340906900000081
Pv＝1，x<α；
wherein, PvProbability of bus low-voltage fault, Pv0The probability of the bus low-voltage fault when the line voltage is normal is shown, x is the current bus voltage value, and alpha is the preset bus voltage value.
The probability of the line overload outage fault is calculated according to the line power change value, and is calculated through the following formula:
Pp＝PP0，PlPl Rated；
Figure BDA0003340906900000082
Pp＝1，Pl≥Pl Max；
wherein, PpFor the probability of line overload outage failure, PP0Probability of line overload outage fault occurring when line tide is normal, PlFor the current line power value, Pl RatedRated power of the line, Pl MaxLimit power values are transmitted for the lines.
And S30, calculating the probability of the second equipment failing after the first equipment fails according to the probability of the bus low-voltage failure and the probability of the line overload outage failure.
Preferably, the probability that the second device fails after the first device fails is calculated according to the probability of the bus low-voltage fault and the probability of the line overload outage fault, and the calculation is performed according to the following formula:
P(T2|T1)＝a*Pv+b*Pp；
wherein, T1For the first device to fail, T2For the second device to fail, P (T)2|T1) Is the probability, P, of a failure of a second device after a failure of a first devicevIs the probability of bus low voltage fault, a is the weight of the probability of bus low voltage fault, PpB is the weight of the probability of the line overload outage fault.
And S40, calculating the probability of the cascading failure of the power system according to the probability of the failure of the first equipment and the probability of the failure of the second equipment after the failure of the first equipment.
Preferably, the probability of the line overload outage fault is calculated according to the line power variation value, and is calculated by the following formula:
Pp＝PP0，PlPl Rated；
Figure BDA0003340906900000091
Pp＝1，Pl≥Pl Max；
wherein, PpFor the probability of line overload outage failure, PP0Probability of line overload outage fault occurring when line tide is normal, PlFor the current line power value, Pl RatedRated power of the line, Pl MaxLimit power values are transmitted for the lines.
In a specific implementation manner of the embodiment of the present invention, the applying of the bayesian theory to the cascading failure inference of the power system includes:
(1) suppose there are two faults, T, in the power system1Fault and T2The occurrence of the two faults respectively corresponds to T in Bayesian theory2Event and T1An event. First, the hazard source, i.e., the previously occurring T with an evoked potential, is identified and described1And establishing a fault evidence observation index according to the possible induced faults of the electrical equipment in the power system to determine T2The extent of damage and the vulnerability of consequences of an event to electrical equipment that may be induced to malfunction. The probability of different scenarios is quantified based on all the existing relevant evidence obtained as a result of the running model and their corresponding damage levels, before the cascading failure probability P (T) can be deduced2|T1) Obtaining P (T)1|T2). For cascading failures of power system, the relevant evidence refers to T2The damage degree refers to the damage of overvoltage and tidal current overload to the system and the evidence probability relation function value pair T of quantitative damage2The depth of the effect of the occurrence of a fault.The scenario is combined according to the injury level, the probability of the system fault state is quantified, and the result is then converted into an appropriate fault probability curve and priority.
The selection of the fault evidence observation index is mainly considered from two aspects of line voltage and line current, because the two indexes are easier to observe in the power system and have obvious influence on the fault occurrence of the power system. If the actual operating voltage is higher or lower than its rated voltage, the operating performance and efficiency will be reduced and may affect the service life or even cause damage to the equipment. Therefore, when the voltage of the power system deviates from its rated value, i.e., a voltage offset is generated, it will have a bad influence on the user and even the power system; and to circuit trend overload, produce the fault effect more easily, easily observe the evidence index, it can lead to the wire jumper position of wire and fastener to generate heat seriously, then begin to melt, the wire strand break leads to the wire broken string at last. Therefore, the two electrical quantities are selected as the fault-related evidence observation indexes.
(2) For electric machinery, when the voltage is reduced by more than l 0%, the current of the motor is too high, the temperature of the coil is too high, and the motor can stop running or cannot start without moving machinery (such as a fan, a water pump and the like) in serious conditions, and even the motor is burnt out. In this case, alpha can be accurately selected to be 0.85; in the hub substation and the power receiving area, when the voltage of the hub substation and the power receiving area is reduced to about 70% of the rated voltage, voltage collapse accidents may occur, that is, the load of the power transmission line is slightly increased, the voltage of the power receiving area is reduced, and the load of the line is further increased. Thus, a vicious circle is formed, a large-area power failure accident is caused, and alpha can be accurately selected to be 0.65; the effect of the low voltage is not significant enough for e.g. faults occurring on the line, and a may be chosen to be a value between 0.25 and 0.45.
(3) Will T1The event is regarded as a single-phase grounding short-circuit fault at a certain position of a line, the fault can cause the current of a non-grounding phase line to be reduced to 0, the phase current of the grounding phase to be increased, various voltages to be obviously changed and the like, T1Events can also be considered single phase line breaks or other types of short circuit faults, etc., while T2The event canSo that other short-circuit faults, disconnection faults, asymmetric faults and the like occur at different places of the power system at the same time, and in the power system, T is assumed at the moment1The event is a short-circuit fault and occurs already, the system voltage can be obviously reduced due to the short circuit of the system, the converter is used for alternating current-direct current conversion in the system, the voltage reduction causes the converter commutation failure, the commutation failure is a common fault in a high-voltage direct-current power transmission system, and multiple continuous and discontinuous commutation failures can be accompanied, so that the direct-current of the system is increased sharply, the service life of a converter valve is shortened, the direct-current power transmission power is reduced, and the voltage of an alternating-current system on the inversion side is unstable.
(4) For different induced T2The fault, low voltage evidence indicator and overload evidence indicator have different degrees of influence. When T is2When the fault is a disconnection fault, the possibility caused by tidal current overload is obviously higher, the weight index occupied by the overload index is larger according to direct evidence, and the low-voltage evidence index does not completely have influence on the disconnection fault, for example, for the existing new energy accessed to a power grid, such as wind power and photovoltaic power generation accessed to the power grid, the existing new energy accessed to the power grid needs to have low-voltage ride through capability, when the voltage of a grid-connected point of a wind power plant fails to recover to 90% of rated voltage within 2s after the voltage drop, a wind turbine in the wind power plant is cut out from the power grid, and at the moment, the system generates tidal current transfer, or when a line transmits certain electric energy, the voltage is reduced, the current is correspondingly increased, and the line loss is increased, and the line is heated. Some line overload situations may occur, in other words, the low voltage indicator may serve as an indirect induction factor of the disconnection fault, i.e. indirect evidence, and the low voltage indicator may occupy a small weight point due to its indirection. For example, the voltage of a power system is reduced to cause the commutation failure of a converter, the commutation failure is a common fault in a high-voltage direct-current transmission system, and the commutation failure can be accompanied by multiple continuous and discontinuous commutation failures, so that the direct current of the system is increased sharply, and the wire is heated to generate a wire breaking fault due to the sharp increase of the direct current; when T is2When the fault is asymmetric fault occurring at different places of the power system at the same time, the T occurs first1The low voltage impact of a fault, i.e. a short-circuit fault, is more likely than a tidal current overload to cause an asymmetric fault to occur simultaneously at different locations of the power system, i.e. the low voltage evidence indicator should be weighted more heavily than the overload evidence indicator in such a case. In summary, for different induced T2And the fault is assigned with different weight ratios according to actual conditions.
(5) Under the condition that no fault occurs, recording related data according to the generated waveform; after the occurrence of the fault, the relevant data is recorded based on the generated waveform. The two types of data recorded here can be used as a judgment for the difference between the two types of data, and the influence of the occurrence probability of another fault in the power system when one or both of the faults occur in the system can be observed by comparing the two types of data.
(6) The Bayesian theorem is applied to the inference analysis of the cascading failure probability, and then the occurrence of two failures of the system is respectively regarded as T2Event and T1And (3) analyzing the mutual influence of the occurrence probability of the two events by applying Bayes theorem. Due to T1Fault represented by event and T2The faults represented by the events can affect each other in the same system, and cannot be two completely independent events, and the Bayesian formula is applied to know that if the event T is1And event T2Are two mutually independent events, P (T)1|T2)/P(T1) Not likely to equal 1, T in the system2The probability of occurrence of the fault represented by the event will also vary significantly. When multiple fault events are involved and multiple faults occur in the system, T is still set2The event representing the object to be investigated, condition T1Representing the probability of other multiple events occurring, simply calculating the condition T1It should be noted that the events in "all other events occur" are not independent of each other.
The Bayes theory is that under the condition of knowing conditional probability density parameter expression and prior probability, or when prior distribution is unknown, historical samples can be used for estimating prior distribution, and the prior probability is converted into the posterior probability through Bayes formula, and mostAnd then decision judgment is carried out according to the posterior probability. Bayes' theorem establishes the link between conditional probability and its inverse. For fault T2And T1Known as P (T)1)≠0，P(T2) Is a fault T2A priori of P (T)2|T1) Is to give a fault T1Rear fault T2A posteriori probability of P (T)1|T2)/P(T1) Is a fault T2Occurrence of pair fault T1Degree of support or attenuation of, fault T2Occurrence of pair fault T1Whether to support or attenuate depends on P (T)1|T2)/P(T1) Is greater than 1 or less than 1, i.e. the likelihood function. So that the fault T can be known by Bayesian theorem1Whether the occurrence of the fault T is increased or decreased2The probability of occurrence, and the degree of increase/decrease thereof can be quantified in terms of the degree of support/attenuation.
The method starts from the Bayes theory, introduces the Bayes theorem first, and tells us that a new event T is used1When it occurs, event T2How the probability of occurrence varies. Then, theoretical derivation of formula is carried out to prove why T is1After the occurrence of the fault represented by the event, T2The probability of occurrence of the fault represented by the event also changes significantly; then establishing evidence observation index for observing T1Occurrence of failure to T2And (3) observing the influence of the change of the electrical quantity value of the indexes by the two fault-related evidences at the fault, and establishing an evidentiary probability relation function for quantifying the possibility of the cascading faults. Then, a power system model is built through time domain simulation, after the model can run a normal steady-state result, a plurality of power system faults are set to simulate multiple faults, after the faults are set, the built time domain model is run, and T is observed1T after fault2Relevant evidence indicators at the fault; according to the observation result, namely the actual operated graph and data result, the probability of cascading failure is quantified by using an evidence probability relation function, and then the probability of multiple cascading failure is deduced to obtain P (T) based on Bayes theory2|T1) Then, the P (T) is obtained according to the formula1|T2) And finallyAnd analyzing the correlation between two faults in the power system or the mutual influence of the two faults on the basis of a Bayesian formula.
Referring to fig. 2, fig. 2 is a flow chart illustrating a specific implementation step method of bayesian inference in power system cascading failure probability inference, taking a double failure as an example;
step 1: in a target power system, a fault T that may occur in a certain device A is selected1And a possible failure T of another device B2Calculating the fault T according to historical statistical data1Probability of occurrence P (T)1) And a fault T2Probability of occurrence P (T)2)。
Step 2: failure T of device a1Under the condition of (1), establishing two evidence observation indexes of voltage and power flow of the equipment B and the fault T of the equipment B2The probability quantization function of (2) is specifically as follows:
the first evidence observation index is: line low voltage evidence. In combination with the reality, for the sake of simplicity, the influence of overvoltage on the system is not considered here, a low-voltage evidence probability relation function of the bus is defined in the fault possibility evaluation due to low voltage, and the voltage amplitude of each bus determines the value of the low-voltage evidence probability relation function of the bus, so that the damage degree of different accidents on the system is reflected. In fig. 1: for each bus, when the bus voltage is α pu (0)<α<1) The value of the low voltage evidence probability relation function of the bus is 1.0; and alpha is selected according to the fault T2The voltage level of the corresponding device B depends on the actual situation. When the bus voltage is 1.0pu, the value of the low-voltage evidence probability relation function of the bus is Pv0，Pv0Namely, the average probability of the fault occurrence according to historical statistical data when the line voltage is normal; the value of the low voltage evidence probability relation function of the bus is in linear relation with the amplitude of the bus voltage. The influence of overvoltage on the system is not considered, so that when the bus voltage is greater than 1.0pu, the value of the low-voltage evidence probability relation function of the bus is still Pv0. The piecewise linear curve relationship in FIG. 3 is as follows.
Pv＝Pv0，x>1；
Figure BDA0003340906900000141
Pv＝1，x<α；
The second evidence observation index is: line overload evidence. An overload evidence probability relation function of the line is defined in the overload obstacle-causing possibility evaluation, and the active power flow of each line determines the value of the overload evidence probability relation function of the line. According to the operation reliability theory, the outage probability P of the power transmission line is closely related to the power on the line, and a line outage probability curve changing along with the power flow is usually fitted in a linear segmentation mode. In fig. 4: plIs the power on line L; pl RatedRated power for the line; pl MaxLimit power is transmitted for the line. When P is presentlPl RatedThe line fault probability is slightly influenced by the power flow, and the fault probability can be taken as a statistical average value PP0，PP0Namely, the average probability of the fault occurrence according to historical statistical data when the line power flow is normal; when P is presentl≥Pl MaxWhen the circuit is disconnected, the protection device acts to cut off the circuit, and the fault probability is 1; when P is presentl Rated≤Pl≤Pl MaxThe line fault probability increases linearly as shown in the following equation.
Pp＝PP0，PlPl Rated；
Figure BDA0003340906900000142
Pp＝1，Pl≥Pl Max；
After the failure probability curve and the priority are obtained from the evidence probability relation function for quantifying the failure probability, the cascading failure probability can be deduced according to the failure probability curve and the priority because the probability is based on the assumed credibility of all available related evidenceRate P (T)2|T1) And the subsequent analysis is convenient.
And step 3: and carrying out weight assignment on the low-voltage and overload evidence probability relation functions.
The weights of the low-voltage and overload evidence probability relation function values are represented by a and b (a + b is equal to 1), and are used for different T2The faults a, b should also be given different values, but still satisfy a + b of 1. When overload and low voltage are applied to fault T2When the occurrence of (a) is the same, a ═ b ═ 0.5; when overload and low voltage are applied to fault T2The assignment of a and b should also have a significant difference when there is a large difference in the contribution of occurrence of (a) and (b). The specific assignment should be based on T in the actual situation, respectively2The impact size of the contributing factor of the fault.
And 4, step 4: and (4) according to the observation result, substituting the obtained data into the step (2) to obtain an evidence index and a probability relation function value, and solving the conditional probability.
And (4) carrying out probability inference based on Bayesian theory according to a quantitative fault possibility curve or priority obtained by the evidence probability relation function. From a methodological perspective, computing the likelihood or probability is a core problem in "quantifying" the degree of confidence that a fault may occur.
PvRendering T for low voltage evidence2Probability of fault occurrence, i.e. value of the low voltage evidence probability relation function, PpRendering T for overload evidence2The probability of the fault occurrence, i.e. the value of the overload evidence probability relationship function, a and b (a + b is 1) represent the weight of the low voltage and overload evidence probability relationship function value, respectively, so that:
P(T2|T1)＝a*Pv+b*Pp；
P(T2|T1) Is shown at T1T after fault occurrence2Probability of occurrence of failure, at T1After the fault occurs, T is added2Substituting the electric quantity values of two related evidence observation indexes at the fault into an evidence probability relation function for quantifying the possibility of the cascading faults to obtain a low-voltage and overload evidence probability relation function value,then substituting two function values into the above-mentioned calculated conditional probability P (T)2|T1) To obtain a conditional probability P (T)1|T2) Then based on the aforementioned Bayesian equation, P (T) is calculated1|T2). And then carrying out multiple fault probability inference analysis on the correlation between the faults of the two power systems or the mutual influence of the faults of the two power systems based on Bayesian theory.
And 5: building a power system model by time domain simulation, and selecting equipment A to set T1Failure, selection of device B, observation and recording of T1The evidence observation indexes of the voltage and the current of the B equipment after the fault occurs; calculating the conditional probability P (T) according to the step 2 and the step 41|T2)。
The PSCAD is used for building a power system model, so that the power system model can run well when no fault is set, and correct steady-state waveforms can be simulated. In the simulation, T on device A1The fault is a power system fault set to occur at a specific moment and lasting for a period of time, T2Setting the fault as a specific fault on the equipment B which is possibly influenced by fault transient in the system, operating the model, observing and verifying the change of the observed index, and comparing the normal state with the normal state1The difference in the failure occurrence state is recorded as T1Normal state when failure does not occur and preset T after failure occurs2And (4) observing a steady-state result waveform and load flow data corresponding to the relevant evidence observation indexes operated at the fault.
Substituting the data obtained by observation and recording into the evidence probability relation function in step 2 and the probability inference formula in step 4 to obtain P (T)2|T1) Then P (T) is added2|T1)、P(T2) And P (T)1) Substituting into Bayesian formula to obtain P (T)1|T2) Finally, Bayesian theory is used for analyzing the correlation between the faults of the two power systems or the mutual influence of the faults of the two power systems.
Step 6: finally, according to the step 1 and the step 5, calculating the double faults T1And T2The probability of a cascading failure occurring;
according to the P (T) obtained in step 11) Or P (T)2) And P (T) obtained in step 52|T1) Or P (T)1|T2) Substituting the probability calculation formula of the accident chain to obtain the probability of the double cascading failures as follows:
P(Ci)＝P(T1)P(T2|T1)；
when multiple fault events are involved, i.e. multiple faults occur in the system, T is still set2The event representing the object to be investigated, condition T1Representing the probability that other events have occurred, and calculating the condition T1It is noted that the various events in "all other various events occur" are not independent of one another. At this time, the probability of multiple cascading failures obtained by popularization is as follows:
P(Ci)＝P(T1)P(T2|T1)＝P(T1T2,...,Tr-1)·P(Tr|T1T2,...,Tr-1)；
the existing power system conditional probability formula is mainly used for solving the occurrence probability of an accident chain, and the conditional probability p (T) is not available2|T1) The method for solving the conditional probability needs a large amount of statistical data in probability statistics, the probability calculation of the cascading failure accident chain only relates to the probability calculation of the cascading failure accident chain in the conventional cascading failure probability calculation, the calculation of a single conditional probability in the accident chain is not researched too much, on the basis of a total architecture using a quantitative risk assessment method, Bayesian theorem for solving the conditional probability is applied to the calculation of the single conditional probability of the cascading failure accident chain in a power system, the change of the electric quantity used as an evidence observation index in the power system after the occurrence of the previous failure is taken as an evidence of Bayesian inference, and the failure possibility of the cascading failure is quantified according to an evidence probability relation function of the evidence observation index. The method utilizes the Quantitative Risk Assessment (QRA) technology to avoid the complexity and complication of obtaining the conditional probability by a large amount of experimental and statistical data in the calculation of the single conditional probability of the cascading failure, deduces the calculation of the single conditional probability of the cascading failure in the power system by using the Bayesian theory, and can also use the theory to calculate the two mutually independent failures in the power systemThe interaction between the two was quantitatively analyzed.
A second aspect.
Referring to fig. 5, an embodiment of the invention provides a power system cascading failure probability calculating system, including: the device comprises a judgment module 10, a first calculation module 20, a second calculation module 30 and a third calculation module 40.
Wherein: the determining module 10 is configured to obtain current power system operation data, and determine whether the first device fails according to the current power system operation data.
The first calculating module 20 is configured to calculate a probability of a bus low-voltage fault according to the bus voltage variation value and calculate a probability of a line overload outage fault according to the line power variation value when the determining module determines that the first device has a fault.
Preferably, the probability of the bus low-voltage fault is calculated according to the bus voltage variation value by the following formula:
Pv＝Pv0，x>1；
Figure BDA0003340906900000181
Pv＝1，x<α；
wherein, PvProbability of bus low-voltage fault, Pv0The probability of the bus low-voltage fault when the line voltage is normal is shown, x is the current bus voltage value, and alpha is the preset bus voltage value.
The probability of the line overload outage fault is calculated according to the line power change value, and is calculated through the following formula:
Pp＝PP0，PlPl Rated；
Figure BDA0003340906900000182
Pp＝1，Pl≥Pl Max；
wherein, PpFor the probability of line overload outage failure, PP0Probability of line overload outage fault occurring when line tide is normal, PlFor the current line power value, Pl RatedRated power of the line, Pl MaxLimit power values are transmitted for the lines.
And the second calculating module 30 is configured to calculate, according to the probability of the bus low-voltage fault and the probability of the line overload outage fault, a probability that the second device fails after the first device fails.
Preferably, the probability that the second device fails after the first device fails is calculated according to the probability of the bus low-voltage fault and the probability of the line overload outage fault, and the calculation is performed according to the following formula:
P(T2|T2)＝a*Pv+b*Pp；
wherein, T1For the first device to fail, T2For the second device to fail, P (T)2|T1) Is the probability, P, of a failure of a second device after a failure of a first devicevIs the probability of bus low voltage fault, a is the weight of the probability of bus low voltage fault, PpB is the weight of the probability of the line overload outage fault.
And the third calculating module 40 is configured to calculate the probability of the cascading failure of the power system according to the probability of the failure of the first device and the probability of the failure of the second device after the failure of the first device.
Preferably, the probability of the line overload outage fault is calculated according to the line power variation value, and is calculated by the following formula:
Pp＝PP0，PlPl Rated；
Figure BDA0003340906900000191
Pp＝1，Pl≥Pl Max；
wherein, PpFor the probability of line overload outage failure, PP0Probability of line overload outage fault occurring when line tide is normal, PlFor the current line power value, Pl RatedRated power of the line, Pl MaxLimit power values are transmitted for the lines.
In a third aspect.
The present invention provides an electronic device, including:
a processor, a memory, and a bus;
the bus is used for connecting the processor and the memory;
the memory is used for storing operation instructions;
the processor is configured to call the operation instruction, and the executable instruction causes the processor to perform an operation corresponding to the power system cascading failure probability calculation method according to the first aspect of the present invention.
In an alternative embodiment, an electronic device is provided, as shown in fig. 5, the electronic device 5000 shown in fig. 5 includes: a processor 5001 and a memory 5003. The processor 5001 and the memory 5003 are coupled, such as via a bus 5002. Optionally, the electronic device 5000 may also include a transceiver 5004. It should be noted that the transceiver 5004 is not limited to one in practical application, and the structure of the electronic device 5000 is not limited to the embodiment of the present invention.
The processor 5001 may be a CPU, general purpose processor, DSP, ASIC, FPGA or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 5001 may also be a combination of processors implementing computing functionality, e.g., a combination comprising one or more microprocessors, a combination of DSPs and microprocessors, or the like.
Bus 5002 can include a path that conveys information between the aforementioned components. The bus 5002 may be a PCI bus or EISA bus, etc. The bus 5002 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 5, but this is not intended to represent only one bus or type of bus.
The memory 5003 may be, but is not limited to, a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an EEPROM, a CD-ROM or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
The memory 5003 is used to store application program code that implements aspects of the present invention and is controlled in execution by the processor 5001. The processor 5001 is configured to execute application program code stored in the memory 5003 to implement the teachings of any of the foregoing method embodiments.
Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like.
A fourth aspect.
The present invention provides a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements a method for calculating a cascading failure probability of a power system according to the first aspect of the present invention.
A further embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, which, when run on a computer, enables the computer to perform the respective content of the aforementioned method embodiments.

Claims (10)

1. A power system cascading failure probability calculation method is characterized by comprising the following steps:
acquiring current power system operation data, and judging whether the first equipment has a fault according to the current power system operation data;
if so, calculating the probability of the low-voltage fault of the bus according to the voltage change value of the bus, and calculating the probability of the overload outage fault of the line according to the power change value of the line;
calculating the probability of the second equipment failing after the first equipment fails according to the probability of the bus low-voltage failure and the probability of the line overload outage failure;
and calculating the probability of the cascading failure of the power system according to the probability of the failure of the first equipment and the probability of the failure of the second equipment after the failure of the first equipment.
2. The method according to claim 1, wherein the calculating of the probability of the cascading failure of the power system is performed according to the probability of the low-voltage failure of the bus and the probability of the overload shutdown failure of the line, and the probability of the failure of the second device after the failure of the first device is calculated according to the following formula:
P(T2|T1)＝a*Pv+b*Pp；
wherein, T1For the first device to fail, T2For the second device to fail, P (T)2|T1) Is the probability, P, of a failure of a second device after a failure of a first devicevIs the probability of bus low voltage fault, a is the weight of the probability of bus low voltage fault, PpB is the weight of the probability of the line overload outage fault.
3. The method according to claim 2, wherein the calculating of the power system cascading failure probability according to the probability of the first device failing and the probability of the second device failing after the first device failing is calculated by the following formula:
P(Ci)＝P(T1)P(T2|T1)；
wherein, CiFor cascading failures of the power system, P (C)i) As the probability of cascading failure of the power system, T1For the first device to fail, T2For the second device to fail, P (T)1) Is the probability of failure of the first device, P (T)2|T1) Is the probability that the second device fails after the first device fails.
4. The method for calculating the cascading failure probability of the power system according to claim 1, wherein the probability of the bus low-voltage failure is calculated according to the bus voltage change value by the following formula:
Pv＝Pv0，x＞1；
Figure FDA0003340906890000021
Pv＝1，x＜α；
wherein, PvProbability of bus low-voltage fault, Pv0The probability of the bus low-voltage fault when the line voltage is normal is shown, x is the current bus voltage value, and alpha is the preset bus voltage value.
5. The method according to claim 1, wherein the calculating of the line overload outage fault probability according to the line power variation value is performed by using the following formula:
Pp＝PP0，Pl≤Pl Rated；
Figure FDA0003340906890000022
Pp＝1，Pl≥Pl Max；
wherein, PpFor line overload shutdownProbability of the barrier, PP0Probability of line overload outage fault occurring when line tide is normal, PlFor the current line power value, Pl RatedRated power of the line, Pl MaxLimit power values are transmitted for the lines.
6. A power system cascading failure probability calculation system, comprising: the device comprises a judgment module, a first calculation module, a second calculation module and a third calculation module; wherein:
the judging module is used for acquiring current power system operation data and judging whether the first equipment has a fault according to the current power system operation data;
the first calculation module is used for calculating the probability of the low-voltage fault of the bus according to the voltage change value of the bus and calculating the probability of the overload outage fault of the line according to the power change value of the line when the judgment module judges that the first equipment has the fault;
the second calculation module is used for calculating the probability of the second equipment failing after the first equipment fails according to the probability of the bus low-voltage fault and the probability of the line overload outage fault;
and the third calculation module is used for calculating the probability of the cascading failure of the power system according to the probability of the failure of the first equipment and the probability of the failure of the second equipment after the failure of the first equipment.
7. The power system cascading failure probability calculating system of claim 6, wherein the probability that the second equipment fails after the first equipment fails is calculated according to the probability of the bus low-voltage failure and the probability of the line overload shutdown failure, and is calculated by the following formula:
P(T2|T1)＝a*Pv+b*Pp；
wherein, T1For the first device to fail, T2For the second device to fail, P (T)2|T1) Is the probability of a second device failing after a first device fails,Pvis the probability of bus low voltage fault, a is the weight of the probability of bus low voltage fault, PpB is the weight of the probability of the line overload outage fault.
8. The system according to claim 7, wherein the power system cascading failure probability calculating system is configured to calculate the power system cascading failure probability according to the probability of the first device failing and the probability of the second device failing after the first device failing, and is calculated by the following formula:
P(Ci)＝P(T1)P(T2|T1)；
wherein, CiFor cascading failures of the power system, P (C)i) As the probability of cascading failure of the power system, T1For the first device to fail, T2For the second device to fail, P (T)1) Is the probability of failure of the first device, P (T)2|T1) Is the probability that the second device fails after the first device fails.
9. The power system cascading failure probability calculating system as claimed in claim 6, wherein the probability of the bus low-voltage failure is calculated according to the bus voltage variation value by the following formula:
Pv＝Pv0，x＞1；
Figure FDA0003340906890000041
Pv＝1，x＜α；
wherein, PvProbability of bus low-voltage fault, Pv0The probability of the bus low-voltage fault when the line voltage is normal is shown, x is the current bus voltage value, and alpha is the preset bus voltage value.
10. The power system cascading failure probability calculating system as claimed in claim 6, wherein the probability of the line overload outage failure is calculated according to the line power variation value by the following formula:
Pp＝PP0，Pl≤Pl Rated；
Figure FDA0003340906890000042
Pp＝1，Pl≥Pl Max；
wherein, PpFor the probability of line overload outage failure, PP0Probability of line overload outage fault occurring when line tide is normal, PlFor the current line power value, Pl RatedRated power of the line, Pl MaxLimit power values are transmitted for the lines.
CN202111308246.1A 2021-11-05 2021-11-05 Cascading failure probability calculation method and system for power system Pending CN114021350A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111308246.1A CN114021350A (en) 2021-11-05 2021-11-05 Cascading failure probability calculation method and system for power system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111308246.1A CN114021350A (en) 2021-11-05 2021-11-05 Cascading failure probability calculation method and system for power system

Publications (1)

Publication Number Publication Date
CN114021350A true CN114021350A (en) 2022-02-08

Family

ID=80062111

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111308246.1A Pending CN114021350A (en) 2021-11-05 2021-11-05 Cascading failure probability calculation method and system for power system

Country Status (1)

Country Link
CN (1) CN114021350A (en)

Similar Documents

Publication Publication Date Title
CN101425686B (en) Electrical power system on-line safety and stability evaluation forecast failure collection adaptive selection method
Wei et al. Complex network-based cascading faults graph for the analysis of transmission network vulnerability
CN113203909B (en) Wind power plant continuous fault ride-through test method, system, computer equipment and medium
CN111368449A (en) Cascading failure evolution path online identification method considering alternating current and direct current influences
CN113675878B (en) Offshore wind farm grid-connected performance testing method and system, computer equipment and medium
Kazmi et al. Cost optimized dynamic design of offshore windfarm transformers with reliability and contingency considerations
Liu et al. Reinforcement learning for cyber-physical security assessment of power systems
Vergara et al. Probabilistic model of wind power parks for reliability assessment
CN114021350A (en) Cascading failure probability calculation method and system for power system
CN111884178A (en) Active power distribution network single-phase line break fault protection method and system
Polymeneas et al. Margin-based framework for online contingency selection in unbalanced networks
Song et al. Control strategies against voltage collapse considering undesired relay operations
Smater et al. A unified framework for reliability assessment of wind energy conversion systems
Al-Sarray et al. A risk-based reliability method for N-1-1 contingency analysis
Xu et al. Fault propagation analysis of IGBT fault in CRH5 traction system based on signed directed graph
CN117996724B (en) Risk assessment method for receiving end power grid under condition of multi-direct-current commutation failure
Rossmaier et al. Further development of the overload risk index, an indicator of system vulnerability
CN112018741B (en) Method and device for designing superconducting alternating current limiter based on reclosing
CN112018740B (en) Method and device for designing superconducting direct current limiter based on reclosing
CN114240111A (en) Power system risk operation assessment method and device and computer equipment
CN116780471B (en) Direct-current voltage-based symmetric loss-of-excitation protection method for variable-speed pumping and storage unit network side
Preece et al. Assessing the risk of small disturbance instability in mixed AC/DC networks
CN108493982A (en) Voltage control method and device for flexible direct current transmission system
Verayiah et al. Under voltage load shedding (UVLS) study for 746 test bus system
CN112217220B (en) Safety and stability defense method and device for new energy source sending multi-terminal flexible direct current power grid

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