CN113887989A - Power system reliability evaluation method and device, computer equipment and storage medium - Google Patents

Power system reliability evaluation method and device, computer equipment and storage medium Download PDF

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CN113887989A
CN113887989A CN202111204961.0A CN202111204961A CN113887989A CN 113887989 A CN113887989 A CN 113887989A CN 202111204961 A CN202111204961 A CN 202111204961A CN 113887989 A CN113887989 A CN 113887989A
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王荣超
杨绍远
郝志杰
李晓霞
吕习超
石万里
韦德重
黄一钊
胡付有
陈明佳
樊友平
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Liuzhou Bureau of Extra High Voltage Power Transmission Co
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Abstract

The application relates to a method and a device for evaluating reliability of a power system, computer equipment and a storage medium. The method comprises the following steps: acquiring initialization parameters of the power system, wherein the initialization parameters comprise standard values of discrete degrees of load loss probability; generating a plurality of different power system state vectors according to the initialization parameters; performing iterative computation on the system state vector by adopting a cross entropy algorithm to update the reliability index load loss probability; when the discrete degree of the latest reliability index loss load probability is smaller than the standard value of the discrete degree of the loss load probability, the iteration is finished; and performing power system reliability evaluation according to the latest reliability index load loss probability to obtain a reliability evaluation result of the power system. By adopting the method, the reliability evaluation result of the power system can be quickly and accurately obtained.

Description

Power system reliability evaluation method and device, computer equipment and storage medium
Technical Field
The present application relates to the field of power system reliability evaluation technologies, and in particular, to a method and an apparatus for evaluating reliability of a power system, a computer device, and a storage medium.
Background
With the continuous expansion of the scale of a power grid and the increasing complexity of a network structure, uncertain factors and randomness of an electric power system in actual operation bring challenges to reliability evaluation, and the stability of the electric power system is affected by slight change of a wire. Any failure in the system can result in an end user power outage, further complicating maintaining extremely high reliability in high capacity power systems. Therefore, in order to ensure the safety and reliability of the power system, and improve the transmission efficiency and the quality of electric energy, it is necessary to evaluate the reliability of the power system.
In the prior art, the optimal unavailability of a generator in a power system needs to be calculated by using a cross entropy important sampling method, and then another sampling method is used for generating a generator state sequence and a corresponding likelihood ratio sequence, so that the reliability index load loss probability of the power system is calculated. According to the technical scheme, two different algorithms are needed to be used for sequentially calculating and processing the generated system state, and the process is complicated; meanwhile, only the state of the generator in the power system is considered, and the influence of the states of other elements in the power system on the state of the whole power system is not considered, so that the accuracy of an evaluation result is influenced.
Therefore, the above method has a problem that reliability evaluation is inefficient and inaccurate.
Disclosure of Invention
In view of the above, it is necessary to provide a method, an apparatus, a computer device and a storage medium for efficient and accurate reliability evaluation of a power system.
A power system reliability assessment method includes:
acquiring initialization parameters of the power system, wherein the initialization parameters comprise standard values of discrete degrees of load loss probability;
generating a plurality of different power system state vectors according to the initialization parameters;
performing iterative computation on the system state vector by adopting a cross entropy algorithm to update the reliability index load loss probability;
when the discrete degree of the latest reliability index loss load probability is smaller than the standard value of the discrete degree of the loss load probability, the iteration is finished;
and performing power system reliability evaluation according to the latest reliability index load loss probability to obtain a reliability evaluation result of the power system.
In one embodiment, generating a plurality of different power system state vectors according to the initialization parameters comprises:
obtaining a k-1 st iteration unavailable vector value v in initialization parametersk-1；
According to the (k-1) th iteration unavailable vector value vk-1A plurality of different power system state vectors are generated according to a bernoulli mass function.
In one embodiment, the iteratively calculating the system state vector by using a cross entropy algorithm to update the reliability index load loss probability further includes:
carrying out load flow calculation on the system state vectors one by one to obtain the power system performance function P (X) of each system state vectori)；
According to a performance function P (X)i) Calculating an evaluation function H (X) of the system state vectori) Obtaining a state evaluation result of the power system;
obtaining the accumulated downtime of the power system according to the state evaluation result;
and updating the load loss probability of the reliability index according to the accumulated downtime.
In one embodiment, according to a performance function P (X)i) Calculating an evaluation function H (X) of the system state vectori) Obtaining a state evaluation result of the power system includes:
the performance function P (X)i) Sorting according to descending order to obtain a performance function sequence in descending order;
obtaining the (1-rho) quantile P in the performance function sequence according to the grading parameter rho(1-ρ)NA value of (d);
will P(1-ρ)NValue of (d) and load maximum value LdComparing to determine a power system load value L of the system state vector;
combining a performance function P (X) according to a load value L of the power systemi) Calculating an evaluation function H (X)i) And obtaining the state evaluation result of the power system.
In one embodiment, before obtaining the accumulated downtime of the power system according to the state evaluation result, the method further includes:
obtaining a k-1 st iteration unavailable vector value v in initialization parametersk-1；
According to the (k-1) th iteration unavailable vector value vk-1And calculating to obtain a likelihood ratio function value W of the k-1 iteration of the system state vectork-1；
Likelihood ratio function value W according to the k-1 th iterationk-1Combining the state evaluation result to obtain an unavailable vector value v of the kth iteration of the system state vectork；
Value of unavailable vector v according to k-th iterationkTo obtain the likelihood ratio function value W of the kth iterationk；
In one embodiment, the likelihood ratio function value W of the k-th iteration is combined according to the state evaluation resultkObtaining the cumulative down time of the power system includes:
simulating the system state vectors according to the state evaluation result to obtain the sampling time T of each system state vectori；
According to the sampling time TiCombining the values of the likelihood ratio functions W of the k-th iterationkAnd obtaining the accumulated downtime of the power system.
In one embodiment, when the degree of dispersion of the probability of losing load of the reliability index is greater than or equal to the standard value of the degree of dispersion of the probability of losing load, starting a new round of iterative computation comprises:
obtaining an unavailable vector value v for the kth iterationk；
The value v of the unavailable vector of the k iterationkAs the latest (k-1) th iteration unavailable vector value vk-1And generating a new power system state vector and carrying out a new round of iterative calculation.
An electric power system reliability evaluation device, the device comprising:
the system comprises a first module, a second module and a third module, wherein the first module is used for acquiring initialization parameters of the power system;
a second module for generating a plurality of different power system states according to the initialization parameters;
the third module is used for performing iterative computation on the system state vector by adopting a cross entropy algorithm so as to update the reliability index load loss probability; when the discrete degree of the latest reliability index loss load probability is smaller than the standard value of the discrete degree of the loss load probability, the iteration is finished; and performing power system reliability evaluation according to the latest reliability index load loss probability to obtain a reliability evaluation result of the power system.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring initialization parameters of the power system, wherein the initialization parameters comprise standard values of discrete degrees of load loss probability;
generating a plurality of different power system state vectors according to the initialization parameters;
performing iterative computation on the system state vector by adopting a cross entropy algorithm to update the reliability index load loss probability;
when the discrete degree of the latest reliability index loss load probability is smaller than the standard value of the discrete degree of the loss load probability, the iteration is finished;
and performing power system reliability evaluation according to the latest reliability index load loss probability to obtain a reliability evaluation result of the power system.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring initialization parameters of the power system, wherein the initialization parameters comprise standard values of discrete degrees of load loss probability;
generating a plurality of different power system state vectors according to the initialization parameters;
performing iterative computation on the system state vector by adopting a cross entropy algorithm to update the reliability index load loss probability;
when the discrete degree of the latest reliability index loss load probability is smaller than the standard value of the discrete degree of the loss load probability, the iteration is finished;
and performing power system reliability evaluation according to the latest reliability index load loss probability to obtain a reliability evaluation result of the power system.
The method, the device, the computer equipment and the storage medium for evaluating the reliability of the power system acquire the initialization parameters of the power system, wherein the initialization parameters comprise standard values of discrete degree of loss load probability; generating a plurality of different power system state vectors according to the initialization parameters; performing iterative computation on the system state vector by adopting a cross entropy algorithm to update the reliability index load loss probability; when the discrete degree of the latest reliability index loss load probability is smaller than the standard value of the discrete degree of the loss load probability, the iteration is finished; and performing power system reliability evaluation according to the latest reliability index load loss probability to obtain a reliability evaluation result of the power system. In the whole process, a plurality of power system state vectors are generated and analyzed, so that the contingency of reliability evaluation results can be reduced, more accurate power system reliability evaluation results can be obtained, moreover, iterative computation is performed by adopting a cross entropy algorithm, the reliability evaluation results can be quickly obtained only through a self-adaptive iterative process, and meanwhile, the accuracy of the reliability evaluation results is further ensured. In general, by the method, the reliability evaluation result of the power system can be quickly and accurately obtained.
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FIG. 1 is a schematic flow chart diagram of a method for evaluating reliability of a power system according to an embodiment;
FIG. 2 is a schematic flow chart illustrating an embodiment of using a cross entropy algorithm to perform iterative computation on a system state vector to update a reliability indicator loss probability;
FIG. 3 is a schematic flow chart of obtaining cumulative down time of a power system in another embodiment;
FIG. 4 is a schematic diagram of a process of processing iterative calculation data in a method for evaluating reliability of a power system in a real-time embodiment;
FIG. 5 is a block diagram of an embodiment of a reliability evaluation apparatus for a power system;
FIG. 6 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
In one embodiment, as shown in fig. 1, a method for evaluating reliability of a power system is provided, which is described by taking the method as an example of being applied to a server, it is to be understood that the method may also be applied to a terminal, and may also be applied to a system including a terminal and a server, and is implemented through interaction between the terminal and the server.
In this embodiment, the method includes the steps of:
s100, acquiring initialization parameters of the power system, wherein the initialization parameters comprise standard values of discrete degrees of the load loss probability.
The load loss probability refers to the probability that the available capacity of the generator of the power system is smaller than or equal to a certain constant load demand, and if the value of the load loss probability is too large, the reliability of the whole power system is affected. Specifically, the standard value β of the degree of dispersion of the loss of load probability in the initialization parameter of the power system is set in advancemaxThe method is used for comparing the discrete degree value of the reliability index load loss probability obtained in the follow-up process with the discrete degree value of the reliability index load loss probability obtained in the follow-up process, and the discrete degree value is used as a basis for judging whether iteration is finished or not; in addition, the initialization parameters include a grading parameter ρ, an iteration counter k, and a load maximum LdValue of unavailable vector v for the k-1 st iterationk-1Where ρ, LdIs also preset and is not updated along with the change of the iteration process, and the iteration counter k and the unavailable vector value v of the k-1 th iterationk-1It is continuously updated with the iterative calculation until the iterative process is finished.
S200, generating a plurality of different power system state vectors according to the initialization parameters;
specifically, in order to obtain a more accurate evaluation result of the power system, a plurality of different power system states need to be analyzed, so that the contingency of the evaluation result is reduced. Unavailable vector v for k-1 iteration in initialization parametersk-1And performing analysis processing to generate a plurality of different power system state vectors.
S300, performing iterative computation on the system state vector by adopting a cross entropy algorithm to update the reliability index load loss probability;
wherein, the cross entropy algorithm is a method for making the obtained probability density function and the theoretically optimal probability density functionThe cross entropy of (a) is gradually reduced; iterative computation means that a new value is recurred by continuously using an old value of a variable until a preset condition is reached, an iterative computation process is completed, and an obtained result is more accurate along with the increase of iteration times. Specifically, the value v of the unavailable vector is an important parameter of the probability density function, and a new value v of the unavailable vector is generated every time an iteration is performed, i.e., at the k-th iteration, the value v of the unavailable vector of the k-th iteration is generatedkValue of unavailable vector v according to k-th iterationkAnd updating the reliability index load loss probability to obtain the latest reliability index load loss probability.
S400, when the discrete degree of the loss load probability of the latest reliability index is smaller than the discrete degree standard value of the loss load probability, the iteration is finished;
specifically, a discrete degree value of the latest reliability index load loss probability is calculated, the obtained discrete degree value is compared with a preset load loss probability discrete degree standard value in the initialization parameter to serve as a criterion for ending iteration, if the obtained discrete degree value is smaller than the standard value, the iteration process is ended, the current reliability index load loss probability is output, and the final reliability index load loss probability is obtained.
S500, performing reliability evaluation on the power system according to the latest reliability index load loss probability to obtain a reliability evaluation result of the power system;
specifically, the reliability index load loss probability reflects the reliability of the power system, and when the reliability index load loss probability is larger, the power system is less reliable, otherwise, the more stable the power system is, the higher the reliability is. When the value of the final reliability index load loss probability exceeds a certain value or interval range, the reliability of the power system at the moment is low.
The method for evaluating the reliability of the power system obtains the initialization parameters of the power system, wherein the initialization parameters comprise the standard values of the discrete degree of the load loss probability; generating a plurality of different power system state vectors according to the initialization parameters; performing iterative computation on the system state vector by adopting a cross entropy algorithm to update the reliability index load loss probability; when the discrete degree of the latest reliability index loss load probability is smaller than the standard value of the discrete degree of the loss load probability, the iteration is finished; and performing power system reliability evaluation according to the latest reliability index load loss probability to obtain a reliability evaluation result of the power system. In the whole process, a plurality of power system state vectors are generated and analyzed, so that the contingency of reliability evaluation results can be reduced, more accurate power system reliability evaluation results can be obtained, moreover, iterative computation is performed by adopting a cross entropy algorithm, the reliability evaluation results can be quickly obtained only through a self-adaptive iterative process, and meanwhile, the accuracy of the reliability evaluation results is further ensured. In general, by the method, the reliability evaluation result of the power system can be quickly and accurately obtained.
In one embodiment, S200 includes:
s220, obtaining a k-1 iteration unavailable vector value v in the initialization parametersk-1；
S240, according to the k-1 iteration unavailable vector value vk-1Generating a plurality of different power system state vectors X according to a Bernoulli mass function1，X2，X3...Xi(ii) a The unavailable vector value v is composed of unavailable vectors of a generator and a transmission line of the power system and represents the fault unavailable probability of the power system; specifically, the first time the power system state vector is generated, since no iterative calculation has been performed, it is based on the original unavailable vector u ═ u in the power systemG，uL]Generated according to a Bernoulli mass function, where uGAnd uLRepresenting the original unavailability vectors, u, of the generator and transmission line, respectivelyGAnd uLThe values of (c) are obtained from a known power system unavailability parameter table. As the iteration calculation proceeds, each iteration calculation produces a new value of the scalar quantity of unavailability vkBefore the iterative computation is finished, the value v of the unavailable vector generated by each iteration is used as a new (k-1) th iteration unavailable vector vk-1And then according to the new k-1 iteration unavailable vector vk-1Generating a new plurality of different power system state vectors X according to a Bernoulli mass functioniThe power system state vector XiIncluding generator state XGTransmission line state XLAnd a load state XLOADI.e. Xi＝[XG，XL，XLOAD]Wherein X isG＝[xG1，xG2，...，xGN]And XL＝[xL1，xL2，...，xLN]Can be calculated by the following formula, GN is the total number of system generators, LN is the total number of system transmission lines, and XLOADIs randomly generated from a known load curve:
Figure BDA0003306477100000071
Figure BDA0003306477100000072
in the present embodiment, the non-vector value v is obtained by the k-1 th iteration according to the power system initialization parameterk-1And generating a plurality of different power system state vectors, so that the generated power system state vectors can be conveniently subjected to iterative computation subsequently, and a final reliability evaluation result is obtained. The generated power system state vector is composed of a generator state vector value, a transmission line vector value and a load state value, the state of a generator in the power system, the influence of the state of a transmission line and the load state on the state of the whole power system are comprehensively considered, and the accuracy of the reliability evaluation result is further improved.
In one embodiment, as shown in fig. 2, S300 includes:
s320, carrying out load flow calculation on the system state vectors one by one to obtain a power system performance function P (X) of each system state vectori)；
Wherein, the power flow calculation refers to the calculation of determining the steady-state operation state parameters of each part of the power system according to the given power grid structure and parameters and the operation conditions of elements such as a generator, a load and the like; the performance function is used for reflecting the degree of the current operation state of the power system, and if the value is positive and larger, the power system is indicated to have stronger load bearing capacity and safer system, otherwise, the system is indicated to need load reduction and be in a fault state. Specifically, a power system carries out load flow calculation on generated system states, and the sum of the capacities of all generators in each system state is recorded as P (X)i) I.e. a performance function.
S340, according to the performance function P (X)i) Calculating an evaluation function H (X) of the system state vectori) Obtaining a state evaluation result of the power system;
wherein the evaluation function is a function for evaluating whether the power system is in a normal state or a fault state; specifically, the obtained performance functions are sorted in descending order, and a performance function sequence P ═ P in descending order is obtained1，P2，...，PN]According to the grading parameter rho, acquiring the (1-rho) quantile P in the performance function sequence(1-ρ)NA value of (A), P to be obtained(1-ρ)NAnd the maximum value L of the load in the initialization parametersdComparing to determine the power system load value L of the power system state vector, comparing the obtained load value with the obtained performance function value to judge whether the power system is in a fault state or a normal state, and obtaining the state evaluation result of the power system, namely when P (X) is obtainedi) When < L, H (X)i) When the power system is in failure state, H (X) is turned offi) The power system is in a normal state 1.
S360, obtaining the accumulated downtime of the power system according to the state evaluation result;
and S380, updating the load loss probability of the reliability index according to the accumulated downtime.
The accumulated downtime refers to the sum of the downtime of all generators in all system states; specifically, the result is evaluated according to the state of the power systemSimulating the generated state vector of the power system, and recording the sampling time T of each stateiAnd obtaining the accumulated downtime T _ down of the system state according to the recorded sampling time. After the accumulated downtime T _ down is calculated, the reliability index load loss probability LOLP of the kth iteration can be obtained by using the following formulakAs the iterative computation progresses, the loppkContinuously updating:
Figure BDA0003306477100000091
in this embodiment, each time iterative computation is performed, an evaluation function value of a system state vector is obtained according to a power system performance function of each system state vector, and after the power system is judged to be in a fault state or a normal state, an operation condition of the power system is simulated, so that the obtained reliability index load loss probability is more consistent with an actual condition of the actual power system, and the latest reliability index load loss probability can be quickly obtained through iterative computation, so that the efficiency and the accuracy of a reliability evaluation result are improved.
In one embodiment, S340 includes:
s342, a performance function P (X)i) Sorting according to descending order to obtain a performance function sequence in descending order;
s344, according to the grading parameter rho, the (1-rho) quantile P in the performance function sequence is obtained(1-ρ)NA value of (d);
s346, adding P(1-ρ)NValue of (d) and load maximum value LdComparing and determining a power system load value L of the power system vector in the system state;
s348, combining the performance function P (X) according to the load value L of the power systemi) Calculating an evaluation function H (X)i) And obtaining the state evaluation result of the power system.
Specifically, the obtained performance functions are arranged in descending order, and a performance function sequence in descending order is obtained, namely, P ═ P1，P2，...，PN]In which P is1＞P2＞，...，＞PNCalculating the (1-rho) th quantile P of the performance function by using the preset grading parameter rho of the initialization parameter as 0.1(1-ρ)NA value of (A) P(1-ρ)NIs equal to a predetermined maximum load value LdComparing with 7612MW to obtain the load value L of the power system, i.e. P(1-ρ)N＜Ld，L＝LdOtherwise L ═ P(1-ρ)N(ii) a Comparing the obtained load value L with the performance function value, if P (X)i)＜L，H(Xi) 0, otherwise H (X)i) When H (X) is equal to 1i) When the power system is in the fault state, H (X) is turned oni) And (1) the power system is in a normal state, and a state evaluation result of the power system is obtained.
In one embodiment, before obtaining the accumulated downtime of the power system according to the state evaluation result, the method further comprises:
s400, obtaining a k-1 iteration unavailable vector value v in the initialization parametersk-1；
S420, according to the k-1 iteration unavailable vector value vk-1And calculating to obtain a likelihood ratio function value W of the k-1 iteration of the system state vectork-1；
Wherein, the likelihood ratio is an index reflecting the authenticity of the result; specifically, the value of the (k-1) th iteration unavailable vector in the initialization parameter is obtained, and the value W of the likelihood ratio function of the (k-1) th iteration of the system state can be obtained through the following formulak-1：
Figure BDA0003306477100000101
Wherein N iscNumber of elements, x, of the systemi，tGenerated system state vector X of representationiEach element of (1), utIs an element in the original unavailability vector u of the power system, vk-1，tIs an unavailable degree vector v after k-1 iterationsk-1Of (1).
S440, according to the likelihood ratio function value W of the k-1 iterationk-1Combining the state evaluation result to obtain an unavailable vector value v of the kth iteration of the system state vectork；
In particular, the value W of the likelihood ratio function for the k-1 th iteration is obtainedk-1And the determined evaluation function H (X)i) The value of (a), namely the power system state evaluation result, is calculated by the following formula to obtain an unavailable vector value v of the kth iteration of the system statek：
Figure BDA0003306477100000102
S460, according to the unavailable vector value v of the k iterationkTo obtain the likelihood ratio function value W of the kth iterationk。
In particular, the value v of the unavailability vector of the k-th iteration to be foundkAccording to the calculation formula of the likelihood ratio function, the likelihood ratio function value W of the kth iteration can be obtainedk：
Figure BDA0003306477100000103
In this embodiment, the k-th iteration is iterated by calculating the unavailable vector vkTo find the likelihood ratio function value W of the k-th iterationkThen based on the obtained likelihood ratio function value WkThe reliability index load loss probability is obtained, the obtained reliability index load loss probability value can be ensured to have unbiased property, namely, the accuracy of the reliability index load loss probability value can be ensured, and therefore the accuracy of the reliability evaluation result is improved.
In one embodiment, as shown in FIG. 3, the likelihood ratio function value W of the k-th iteration is combined according to the state evaluation resultkObtaining a cumulative down time for the power system, comprising:
s500, simulating the system state vector according to the state evaluation result to obtain the sampling time T of each system statei；
S520, according to the sampling time TiCombining the values of the likelihood ratio functions W of the k-th iterationkAnd obtaining the accumulated downtime of the power system.
Specifically, the system state is simulated according to the obtained state evaluation result, and the sampling time T of each state is recordediSo that
Figure BDA0003306477100000111
Combining the calculated likelihood ratio function value W of the k-th iterationkAnd calculating the accumulated downtime T _ down by the following formula:
Figure BDA0003306477100000112
in one embodiment, when the degree of dispersion of the reliability index loss load probability is greater than or equal to the loss load probability dispersion degree standard value, starting a new round of iterative calculation includes:
s600, obtaining an unavailable vector value v of the kth iterationk；
S620, the unavailable vector value v of the k iterationkAs the latest (k-1) th iteration unavailable vector value vk-1And generating a new power system state vector and carrying out a new round of iterative calculation.
Specifically, the discrete degree value COV of the reliability index load loss probability is calculated according to the following formula:
Figure BDA0003306477100000113
the obtained reliability index loss load probability discrete degree value and the loss load probability discrete degree standard value beta in the initialization parametermaxAnd comparing the values with 5 percent, if the obtained discrete degree value COV is greater than or equal to 5 percent, acquiring an unavailable vector of the kth iteration, taking the unavailable vector as an unavailable vector value of the kth-1 iteration in the initialization parameters during the next iteration calculation, generating a new power system state, and performing a new round of iteration calculation.
In this embodiment, when the discrete degree of the reliability index loss load probability is greater than or equal to the loss load probability discrete degree standard value, the iterative computation is continued, the reliability index loss load probability can be continuously updated until the discrete degree of the reliability index loss load probability is less than the loss load probability discrete degree standard value, the iterative computation is completed, the final reliability index loss load probability is obtained, and the reliability evaluation efficiency is favorably improved.
Fig. 4 is a schematic diagram of an iterative calculation data processing procedure in the power system reliability evaluation method, and it should be understood that, although the steps in the flowcharts of fig. 1 to 4 are shown in sequence as indicated by arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 1-4 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least some of the other steps.
In one embodiment, as shown in fig. 5, there is provided a power system reliability evaluation device including: a first module 100, a second module 200, and a third module 300, wherein:
the method includes a first module 100 for obtaining initialization parameters of the power system.
A second module 200 is configured to generate a plurality of different power system state vectors according to the initialization parameter.
A third module 300, configured to perform iterative computation on the system state vector by using a cross entropy algorithm to update the reliability index loss probability; when the discrete degree of the latest reliability index loss load probability is smaller than the standard value of the discrete degree of the loss load probability, the iteration is finished; and performing power system reliability evaluation according to the latest reliability index load loss probability to obtain a reliability evaluation result of the power system.
In one embodiment, the second module 200 is further configured to obtain a k-1 st iteration unavailable vector value v in the initialization parametersk-1(ii) a According to the (k-1) th iteration unavailable vector value vk-1A plurality of different power system state vectors are generated according to a bernoulli mass function.
In one embodiment, the third module 300 is further configured to perform load flow calculation on the system state vectors one by one to obtain a power system performance function P (X) of each system state vectori) (ii) a According to a performance function P (X)i) Calculating an evaluation function H (X) of the system state vectori) Obtaining a state evaluation result of the power system; obtaining the accumulated downtime of the power system according to the state evaluation result; and updating the load loss probability of the reliability index according to the accumulated downtime.
In one embodiment, the third module 300 is further configured to apply a performance function P (X)i) Sorting according to descending order to obtain a performance function sequence in descending order; obtaining the (1-rho) quantile P in the performance function sequence according to the grading parameter rho(1-ρ)NA value of (d); will P(1-ρ)NValue of (d) and load maximum value LdComparing to determine a power system load value L of the system state vector; combining a performance function P (X) according to a load value L of the power systemi) Calculating an evaluation function H (X)i) And obtaining the state evaluation result of the power system.
In one embodiment, the third module 300 is further configured to obtain a k-1 st iteration unavailable vector value v in the initialization parametersk-1(ii) a According to the (k-1) th iteration unavailable vector value vk-1And calculating to obtain a likelihood ratio function value W of the k-1 iteration of the system state vectork-1(ii) a Likelihood ratio function value W according to the k-1 th iterationk-1Combining the state evaluation result to obtain an unavailable vector value v of the kth iteration of the system state vectork(ii) a Value of unavailable vector v according to k-th iterationkTo obtain the likelihood ratio function value W of the kth iterationk。
In one embodiment, the third module 300 is further configured to evaluate based on the stateSimulating the system state vector to obtain the sampling time T of each system statei(ii) a According to the sampling time TiCombining the values of the likelihood ratio functions W of the k-th iterationkAnd obtaining the accumulated downtime of the power system.
In one embodiment, the third module 300 is further configured to obtain the value v of the unavailable vector for the k-th iteration when the degree of dispersion of the probability of losing load of the reliability indicator is greater than or equal to the standard value of the degree of dispersion of the probability of losing loadk(ii) a The value v of the unavailable vector of the k iterationkAs the latest (k-1) th iteration unavailable vector value vk-1And generating a new power system state vector and carrying out a new round of iterative calculation.
For specific limitations of the power system reliability evaluation device, reference may be made to the above limitations of the power system reliability evaluation method, which is not described herein again. The modules in the power system reliability evaluation device can be wholly or partially implemented by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 6. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The computer program is executed by a processor to implement a power system reliability assessment method. Those skilled in the art will appreciate that the architecture shown in fig. 6 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
acquiring initialization parameters of the power system, wherein the initialization parameters comprise standard values of discrete degrees of load loss probability; generating a plurality of different power system state vectors according to the initialization parameters; performing iterative computation on the system state vector by adopting a cross entropy algorithm to update the reliability index load loss probability; when the discrete degree of the latest reliability index loss load probability is smaller than the standard value of the discrete degree of the loss load probability, the iteration is finished; and performing power system reliability evaluation according to the latest reliability index load loss probability to obtain a reliability evaluation result of the power system.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
obtaining a k-1 st iteration unavailable vector value v in initialization parametersk-1(ii) a According to the (k-1) th iteration unavailable vector value vk-1A plurality of different power system state vectors are generated according to a bernoulli mass function.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
carrying out load flow calculation on the system state vectors one by one to obtain the power system performance function P (X) of each system state vectori) (ii) a According to a performance function P (X)i) Calculating an evaluation function H (X) of the system state vectori) Obtaining a state evaluation result of the power system; obtaining the accumulated downtime of the power system according to the state evaluation result; and updating the load loss probability of the reliability index according to the accumulated downtime.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
the performance function P (X)i) In descending orderSorting to obtain a performance function sequence in descending order; obtaining the (1-rho) quantile P in the performance function sequence according to the grading parameter rho(1-ρ)NA value of (d); will P(1-ρ)NValue of (d) and load maximum value LdComparing to determine a power system load value L of the system state vector; combining a performance function P (X) according to a load value L of the power systemi) Calculating an evaluation function H (X)i) And obtaining the state evaluation result of the power system.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
obtaining a k-1 st iteration unavailable vector value v in initialization parametersk-1(ii) a According to the (k-1) th iteration unavailable vector value vk-1And calculating to obtain a likelihood ratio function value W of the k-1 iteration of the system state vectork-1(ii) a Likelihood ratio function value W according to the k-1 th iterationk-1Combining the state evaluation result to obtain an unavailable vector value v of the kth iteration of the system state vectork(ii) a Value of unavailable vector v according to k-th iterationkTo obtain the likelihood ratio function value W of the kth iterationk。
In one embodiment, the processor, when executing the computer program, further performs the steps of:
simulating the system state vector according to the state evaluation result to obtain the sampling time T of each system statei(ii) a According to the sampling time TiCombining the values of the likelihood ratio functions W of the k-th iterationkAnd obtaining the accumulated downtime of the power system.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
when the discrete degree of the loss load probability of the reliability index is greater than or equal to the discrete degree standard value of the loss load probability, acquiring an unavailable vector value v of the kth iterationk(ii) a The value v of the unavailable vector of the k iterationkAs the latest (k-1) th iteration unavailable vector value vk-1And generating a new power system state vector and carrying out a new round of iterative calculation.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring initialization parameters of the power system, wherein the initialization parameters comprise standard values of discrete degrees of load loss probability; generating a plurality of different power system state vectors according to the initialization parameters; performing iterative computation on the system state vector by adopting a cross entropy algorithm to update the reliability index load loss probability; when the discrete degree of the latest reliability index loss load probability is smaller than the standard value of the discrete degree of the loss load probability, the iteration is finished; and performing power system reliability evaluation according to the latest reliability index load loss probability to obtain a reliability evaluation result of the power system.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
obtaining a k-1 st iteration unavailable vector value v in initialization parametersk-1(ii) a According to the (k-1) th iteration unavailable vector value vk-1Generating a plurality of different power system state vectors according to a Bernoulli mass function; in one embodiment, the processor, when executing the computer program, further performs the steps of: carrying out load flow calculation on the system state vectors one by one to obtain the power system performance function P (X) of each system state vectori) (ii) a According to a performance function P (X)i) Calculating an evaluation function H (X) of the system state vectori) Obtaining a state evaluation result of the power system; obtaining the accumulated downtime of the power system according to the state evaluation result; and updating the load loss probability of the reliability index according to the accumulated downtime.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
the performance function P (X)i) Sorting according to descending order to obtain a performance function sequence in descending order; obtaining the (1-rho) quantile P in the performance function sequence according to the grading parameter rho(1-ρ)NA value of (d); will P(1-ρ)NValue of (d) and load maximum value LdComparing to determine a power system load value L of the system state vector; according to the load value L of the power system, combining performance functionsNumber P (X)i) Calculating an evaluation function H (X)i) And obtaining the state evaluation result of the power system.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
obtaining a k-1 st iteration unavailable vector value v in initialization parametersk-1(ii) a According to the (k-1) th iteration unavailable vector value vk-1And calculating to obtain a likelihood ratio function value W of the k-1 iteration of the system state vectork-1(ii) a Likelihood ratio function value W according to the k-1 th iterationk-1Combining the state evaluation result to obtain an unavailable vector value v of the kth iteration of the system state vectork(ii) a Value of unavailable vector v according to k-th iterationkTo obtain the likelihood ratio function value W of the kth iterationk。
In one embodiment, the processor, when executing the computer program, further performs the steps of:
simulating the system state vector according to the state evaluation result to obtain the sampling time T of each system statei(ii) a According to the sampling time TiCombining the values of the likelihood ratio functions W of the k-th iterationkAnd obtaining the accumulated downtime of the power system.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
when the discrete degree of the loss load probability of the reliability index is greater than or equal to the discrete degree standard value of the loss load probability, acquiring an unavailable vector value v of the kth iterationk(ii) a The value v of the unavailable vector of the k iterationkAs the latest (k-1) th iteration unavailable vector value vk-1And generating a new power system state vector and carrying out a new round of iterative calculation.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware related to instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (10)

1. A method for evaluating reliability of a power system, the method comprising:
acquiring initialization parameters of the power system, wherein the initialization parameters comprise standard values of discrete degrees of load loss probability;
generating a plurality of different power system state vectors according to the initialization parameters;
performing iterative computation on the system state vector by adopting a cross entropy algorithm to update the reliability index load loss probability;
when the dispersion degree of the latest reliability index load loss probability is smaller than the standard value of the dispersion degree of the load loss probability, finishing the iteration;
and evaluating the reliability of the power system according to the latest reliability index load loss probability to obtain a reliability evaluation result of the power system.
2. The method of claim 1, wherein the initialization parameters further comprise an iteration counter k and an unavailable vector value v for a k-1 th iterationk-1；
The generating a plurality of different power system state vectors according to the initialization parameters comprises:
obtaining a k-1 th iteration unavailable vector value v in the initialization parametersk-1；
According to the k-1 iteration unavailable vector value vk-1A plurality of different power system state vectors are generated according to a bernoulli mass function.
3. The method of claim 1, wherein iteratively calculating the system state vector using a cross-entropy algorithm to update a reliability indicator load loss probability comprises:
carrying out load flow calculation on the system state vectors one by one to obtain a power system performance function P (X) of each system state vectori)；
According to the performance function P (X)i) Calculating an evaluation function H (X) of the system state vectori) Obtaining a state evaluation result of the power system;
obtaining the accumulated downtime of the power system according to the state evaluation result;
and updating the load loss probability of the reliability index according to the accumulated downtime.
4. The method of claim 3, wherein the initialization parameters further comprise a classification parameter and a load maximum Ld；
According to the performance function P (X)i) Calculating an estimate of the system state vectorFunction H (X)i) Obtaining the state evaluation result of the power system comprises:
applying the performance function P (X)i) Sorting according to descending order to obtain a performance function sequence in descending order;
according to the grading parameter rho, obtaining the (1-rho) quantile P in the performance function sequence(1-ρ}NA value of (d);
the P is added(1-ρ)NThe value of (d) and the load maximum value LdComparing to determine a power system load value L of the system state vector;
combining said performance function P (X) according to said power system load value Li) Calculating an evaluation function H (X)i) Obtaining a state evaluation result of the power system.
5. The method of claim 3, wherein the initialization parameters further comprise a k-1 iteration unavailable vector value vk-1；
Before obtaining the accumulated downtime of the power system according to the state evaluation result, the method further comprises:
obtaining a k-1 th iteration unavailable vector value v in the initialization parametersk-1；
According to the k-1 iteration unavailable vector value vk-1Calculating to obtain a likelihood ratio function value W of k-1 iteration of the system state vectork-1；
Likelihood ratio function value W according to the k-1 iterationk-1Combining the state evaluation result to obtain an unavailable vector value v of the kth iteration of the system state vectork；
According to the unavailable vector value v of the k iterationkTo obtain the likelihood ratio function value W of the kth iterationk；
The obtaining of the accumulated downtime of the power system according to the state evaluation result includes:
combining the likelihood ratio function value W of the k-th iteration according to the state evaluation resultkTo obtain said electricityCumulative down time of the force system.
6. The method according to claim 5, wherein the likelihood ratio function value W of the k-th iteration is combined according to the state evaluation resultkObtaining the cumulative down time of the power system comprises:
simulating the system state vector according to the state evaluation result to obtain the sampling time T of each system statei；
According to the sampling time TiCombining the values of the likelihood ratio functions W of the k-th iterationkAnd obtaining the accumulated downtime of the power system.
7. The method of claim 1, further comprising:
when the discrete degree of the reliability index load loss probability is larger than or equal to the discrete degree standard value of the load loss probability, starting a new round of iterative calculation;
the starting of a new round of iterative computation comprises:
obtaining an unavailable vector value v of the kth iterationk；
The value v of the unavailable vector of the k-th iterationkAs the latest (k-1) th iteration unavailable vector value vk-1And generating a new power system state vector and carrying out a new round of iterative calculation.
8. An apparatus for evaluating reliability of an electric power system, the apparatus comprising:
the system comprises a first module, a second module and a third module, wherein the first module is used for acquiring initialization parameters of the power system;
a second module for generating a plurality of different power system state vectors according to the initialization parameters;
the third module is used for performing iterative computation on the system state vector by adopting a cross entropy algorithm so as to update the reliability index load loss probability; when the discrete degree of the latest reliability index loss load probability is smaller than the standard value of the discrete degree of the loss load probability, the iteration is finished; and performing power system reliability evaluation according to the latest reliability index load loss probability to obtain a reliability evaluation result of the power system.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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