CN111798163B - Active power distribution network security assessment method - Google Patents
Active power distribution network security assessment method Download PDFInfo
- Publication number
- CN111798163B CN111798163B CN202010736523.8A CN202010736523A CN111798163B CN 111798163 B CN111798163 B CN 111798163B CN 202010736523 A CN202010736523 A CN 202010736523A CN 111798163 B CN111798163 B CN 111798163B
- Authority
- CN
- China
- Prior art keywords
- distribution network
- power distribution
- active power
- node
- probability
- 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.)
- Active
Links
- 238000009826 distribution Methods 0.000 title claims abstract description 140
- 238000000034 method Methods 0.000 title claims abstract description 32
- 238000011156 evaluation Methods 0.000 claims abstract description 19
- 238000004544 sputter deposition Methods 0.000 claims abstract description 7
- 239000011159 matrix material Substances 0.000 claims description 30
- 239000002245 particle Substances 0.000 claims description 29
- 238000000342 Monte Carlo simulation Methods 0.000 claims description 7
- 238000005070 sampling Methods 0.000 claims description 6
- 238000005477 sputtering target Methods 0.000 claims description 3
- 238000005457 optimization Methods 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- Theoretical Computer Science (AREA)
- Mathematical Physics (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Optimization (AREA)
- Computational Mathematics (AREA)
- Economics (AREA)
- Mathematical Analysis (AREA)
- Pure & Applied Mathematics (AREA)
- Strategic Management (AREA)
- Educational Administration (AREA)
- Algebra (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Development Economics (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Entrepreneurship & Innovation (AREA)
- Evolutionary Biology (AREA)
- Public Health (AREA)
- Probability & Statistics with Applications (AREA)
- Quality & Reliability (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Game Theory and Decision Science (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Computing Systems (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The invention discloses a safety evaluation method for an active power distribution network, which comprises the following steps: calculating the instability probability of the active power distribution network; establishing a space-time model of the active power distribution network; based on the instability probability of the active power distribution network, establishing a diffraction index, a focusing index, a sputtering index and a global index through the space-time model, and evaluating the safety of the active power distribution network according to the four indexes; the method can solve the problem of safety evaluation of the active power distribution network under the influence of multiple uncertainties, ensures safe and stable operation of the active power distribution network, is accurate in evaluation, is suitable for safety evaluation of operation of various types of active power distribution networks, and has a good application prospect.
Description
Technical Field
The invention relates to the technical field of power grid evaluation, in particular to a safety evaluation method for an active power distribution network.
Background
Currently, active power distribution networks are the key points of research in various countries as means for realizing the integrated operation of renewable energy sources and loads. Meanwhile, electric automobile charging piles are becoming important components of active power distribution networks gradually. However, the renewable energy is affected by natural conditions such as wind and light, the output of the renewable energy is uncertain, and the random charging behavior of the electric vehicle also brings new challenges to the safe and stable operation of the active power distribution network. Meanwhile, risks also exist between the coupling of the physical system and the information system of the active power distribution network, and the damage to the active power distribution network caused by various network attacks is different.
Disclosure of Invention
The invention aims to provide a safety assessment method for an active power distribution network, which aims to solve the problems in the prior art, realize accurate judgment and early warning on the safety state of the active power distribution network and ensure the safe and stable operation of the active power distribution network.
In order to achieve the purpose, the invention provides the following technical scheme:
the invention provides a safety evaluation method of an active power distribution network, which comprises the following steps:
calculating the instability probability of the active power distribution network;
establishing a space-time model of the active power distribution network;
and establishing a diffraction index, a focusing index, a sputtering index and a global index through the space-time model based on the instability probability of the active power distribution network, and evaluating the safety of the active power distribution network according to the four indexes.
Further, a specific method for calculating the instability probability of the active power distribution network includes:
under the influence of multiple uncertainties, if the inertia of all nodes of the active power distribution network is in
Within the range, the active power distribution network is stable, and the inertia of each node of the active power distribution network is within
The probability in the range is that the frequency change rate of the node is within
Probability within range, then probability P of active distribution network stabilityMIComprises the following steps:
wherein,
the upper bound for the rate of change of frequency of the active distribution network,R f,systhe lower bound of the frequency change rate of the original power distribution network, p (f) the probability density of the frequency change of the active power distribution network,
is an upper bound on the inertia of the active distribution network,H systhe lower bound of the inertia of the active distribution network;
sampling to obtain P by Markov Monte Carlo simulation methodMI；
The instability probability P of the active power distribution network is as follows: p is 1-PMI。
Further, under the influence of multiple uncertainties, the inertia formula of the active power distribution network is as follows:
wherein HsysIs the inertia of the active distribution network, f0Rated power, R, of an active distribution networkf,sysThe frequency change rate of the active power distribution network, and the delta P is the power change amount of the active power distribution network under the influence of multiple uncertainties.
Further, the specific method for establishing the space-time model of the active power distribution network comprises the following steps:
the probability matrix A, namely a space-time model, of mutual influence of all nodes of the active power distribution network in different air is as follows:
wherein the framed element Ai,jIs a matrix of zero values, and is,
if the active power distribution network contains n nodes, then:
Ai,j＝[P1|i,j P2|i,j … Pn|i,j]，Pk|i,j＝[pk,1|i,j pk,2|i,j … pk,n|i,j]T,k＝1,2…n，
wherein p isl,m|i,j,l,m＝1,2…n∈{Pk|i,jK is 1,2 … n, i, j is 1,2 … T, a is the probability that the j-th time node m will affect the i-th time node l under the influence of multiple uncertainties, and ai,jThe probability that the node at the ith moment is influenced by the node at the jth moment in the whole time T is shown;
each pl,m|i,jAre all independent of each other and obey different probability distributions;
when node m is not coupled to node l, pl,m|i,j0, and P | |k|i,j||∞≤1,k＝1,2…n；
When the state change of the j-th time node m to the i-th time node l is larger than the threshold value under the influence of multiple uncertainties, p isl,m|i,jNot equal to 0, and
wherein x ism|j→xm|iThe change of the state of the node l at the ith time under the influence of multiple uncertainties received by the node m at the jth time,
is a threshold value for the state of the node m,
sampling to obtain p by Markov Monte Carlo simulation methodl,m|i,j；
The threshold formula for the state of a node is:
min H(x)
s.t.x∈Φ
H(x)-R f,sys≥0，
wherein, H (x) is the relation between the node state and the frequency change rate, and x ∈ Φ is the conditional formula of the node state.
Further, a specific method for obtaining a threshold value of each node of the active power distribution network includes:
s1: initializing a population of particles, including a population size N, a location x of each particleiAnd velocity vi；
S2: calculating a fitness value H (x) for each particlei)；
S3: using the fitness value H (x) of each particlei) And individual extremum pbest(i) By comparison, if H (x)i)＞pbest(i) Then H (x)i) In place of pbest(i)；
S4: using the fitness value H (x) of each particlei) And global extreme gbest(i) By comparison, if H (x)i)＞gbest(i) Then H (x)i) In place of gbest(i)；
S5: updating the position x of the particle according toiAnd velocity vi：
Wherein,
for the t-th iteration particle i airspeed vector,
is the position vector of the t-th iteration particle i, c1And c2Is a learning factor, r1And r2Is [0,1 ]]Uniform random number in the range, w is the inertial weight, pbestAnd gbestThe best positions that the particle and population have experienced, respectively;
s6: if H (x) ═R f,sysOr the number of cycles reaches the maximum number of cycles Nc, the process returns to S2.
Further, based on the instability probability of the active power distribution network, a diffraction index, a focusing index, a sputtering index and a global index are established through the space-time model, and the specific method for evaluating the safety of the active power distribution network according to the four indexes comprises the following steps:
matrix R of diffraction indices0Comprises the following steps:
wherein the elements of the added frame are zero matrixes,
wherein,
is an index p of instability of the active power distribution network at the ith moment caused by the influence of multiple uncertainties on the node l at the jth momentl,l|i,jWhere l is 1,2 … n, i, j is 1, and 2 … T is the probability that the jth time node l will be affected by multiple uncertainties, pm,l|i,jI, m is 1,2 … n, i, j is 1,2 … T is the probability that the j-th time node l is influenced by multiple uncertainties on the i-th time node m, pl(f) And pm(f) Probability densities of system frequency changes caused by state changes of the node l and the node m respectively;
matrix R of sputtering targets1Comprises the following steps:
wherein the elements of the added frame are zero matrixes,
wherein,
node l is subject to multiple uncertainties for time jUnder the influence, the other nodes except the node l at the ith moment cause the instability index of the active power distribution network;
matrix R of focus indices2Comprises the following steps:
wherein the elements of the added frame are zero matrixes,
wherein,
the index of instability of the active power distribution network caused by the node l at the ith moment under the influence of multiple uncertainties on all the nodes at the jth moment;
matrix R of global index3Comprises the following steps:
wherein the elements of the added frame are zero matrixes,
and comprehensively evaluating the safe and stable running state of the active power distribution network under the influence of multiple uncertainties through the four indexes.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a safety evaluation method for an active power distribution network, which comprises the steps of firstly calculating the instability probability of the active power distribution network; then establishing a space-time model of the active power distribution network; finally, based on the instability probability of the active power distribution network, establishing a diffraction index, a focusing index, a sputtering index and a global index through the space-time model, and evaluating the safety of the active power distribution network according to the four indexes; the method can solve the problem of safety evaluation of the active power distribution network under the influence of multiple uncertainties, ensures safe and stable operation of the active power distribution network, is accurate in evaluation, is suitable for safety evaluation of operation of various types of active power distribution networks, and has a good application prospect.
Drawings
Fig. 1 is a flowchart of a method for evaluating the security of an active power distribution network according to an embodiment of the present invention;
fig. 2 is a flowchart of a particle swarm optimization algorithm for solving thresholds of each node in the active power distribution network security evaluation method provided by the embodiment of the 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.
The embodiment of the invention provides a safety evaluation method for an active power distribution network, which comprises the following steps:
calculating the instability probability of the active power distribution network;
establishing a space-time model of the active power distribution network;
and establishing a diffraction index, a focusing index, a sputtering index and a global index through the space-time model based on the instability probability of the active power distribution network, and evaluating the safety of the active power distribution network according to the four indexes.
The specific method for calculating the instability probability of the active power distribution network comprises the following steps:
the inertia formula of the generator set can deduce that the frequency change rate formula of the active power distribution network is as follows:
the inertia formula of the active power distribution network can be deduced by the frequency change rate formula of the active power distribution network as follows:
wherein HsysIs inertia of the active power distribution network, delta P is power variation of the active power distribution network under the influence of multiple uncertainties, the delta P has different values in different scenes, and f is determined according to the situation0Rated frequency, R, of active distribution networkf,sysThe frequency change rate of the active power distribution network;
at steady state, the inertia of the active distribution network is within a range, i.e.
Wherein,
being an upper bound on the inertia of the active distribution network,H sysfor the moment of inertia of the active distribution network,
the upper bound for the rate of change of frequency of the active distribution network,R f,systhe lower bound of the frequency change rate of the active power distribution network;
when the active distribution network is under the influence of multiple uncertainties and the Δ P is determined, the inertia of all nodes of the active distribution network must be kept at
Within the range, the active power distribution network can be stabilized, and at the moment, the inertia of each node of the active power distribution network is kept at
The probability in the range is that the frequency change rate of the node is within
A probability within a range;
under the influence of multiple uncertainties, the probability formula for the stability of the active power distribution network is as follows:
wherein, PMIThe probability of the stability of the active power distribution network, and p (f) the probability density of the frequency change of the active power distribution network under the influence of multiple uncertainties;
sampling to obtain P by adopting Markov Monte Carlo simulation methodMI；
Under the influence of multiple uncertainties, the probability formula of instability of the active power distribution network is as follows:
P＝1-PMI
wherein P is the instability probability of the active power distribution network.
The specific method for establishing the space-time model of the active power distribution network comprises the following steps:
the probability matrix A, namely a space-time model, of mutual influence of each node of the active power distribution network in different air is as follows:
wherein, because of the time irreversibility, the framed element Ai,jIs a zero matrix;
if the active power distribution network contains n nodes, then
Ai,j＝[P1|i,j P2|i,j … Pn|i,j]，Pk|i,j＝[pk,1|i,j pk,2|i,j … pk,n|i,j]T,k＝1,2…n，
Wherein p isl,m|i,j,l,m＝1,2…n∈{Pk|i,jK is 1,2 … n, i, j is 1,2 … T, a is the probability that the j-th time node m will affect the i-th time node l under the influence of multiple uncertainties, and ai,jThe probability that the node at the ith moment is influenced by the node at the jth moment in the whole time T is shown;
each pl,m|i,jAre all independent of each other and obey different probability distributions;
when node m is not coupled to node l, pl,m|i,j0, and P | |ki,j||∞≤1,k＝1,2…n
When the state change of the j-th time node m to the i-th time node l is larger than the threshold value under the influence of multiple uncertainties, p isl,m|i,jNot equal to 0, and
wherein x ism|j→xm|iThe change of the state of the node l at the ith moment under the influence of multiple uncertainties received by the node m at the jth moment is related to the structure of the active power distribution network,
is a threshold value for the state of the node m,
sampling to obtain p by adopting Markov Monte Carlo simulation methodl,m|i,j；
The threshold formula for the state of a node is:
min H(x)
s.t.x∈Φ
H(x)-R f,sys≥0，
wherein, H (x) is the relation between the node state and the frequency change rate, and x ∈ Φ is the conditional formula of the node state.
The specific method for obtaining the threshold value of each node of the active power distribution network by adopting the particle swarm optimization algorithm comprises the following steps:
s1: initializing a population of particles, including a population size N, a location x of each particleiAnd velocity vi；
S2: calculating a fitness value H (x) for each particlei)；
S3: using the fitness value H (x) of each particlei) And individual extremum pbest(i) By comparison, if H (x)i)＞pbest(i) Then H (x)i) In place of pbest(i)；
S4: using the fitness value H (x) of each particlei) And global extreme gbest(i) By comparison, if H (x)i)＞gbest(i) Then H (x)i) In place of gbest(i)；
S5: updating the position x of the particle according toiAnd velocity vi：
Wherein,
for the t-th iteration particle i airspeed vector,
is the position vector of the t-th iteration particle i, c1And c2Is a learning factor, also called acceleration constant, r1And r2Is [0,1 ]]Uniform random number within the range, w is the inertial weight, non-negative number, adjusts the search range for the solution space, pbestAnd gbestThe best positions that the particle and population have experienced, respectively;
s6: if H (x) ═R f,sysOr the number of cycles reaches the maximum number of cycles Nc, the process returns to S2.
Based on the instability probability of the active power distribution network, establishing a diffraction index, a focusing index, a sputtering index and a global index through the space-time model, and evaluating the safety of the active power distribution network according to the four indexes, wherein the specific method comprises the following steps:
matrix R of diffraction indices0Comprises the following steps:
wherein, the matrix R0Like the a matrix, the boxed elements are the zero matrix,
wherein,
is an index p of instability of the active power distribution network at the ith moment caused by the influence of multiple uncertainties on the node l at the jth momentl,l|i,jWhere l is 1,2 … n, i, j is 1, and 2 … T is the probability that the jth time node l will be affected by multiple uncertainties, pm,l|i,jI, m is 1,2 … n, i, j is 1,2 … T is the probability that the j-th time node l is influenced by multiple uncertainties on the i-th time node m, pl(f) And pm(f) Probability densities of system frequency changes caused by state changes of the node l and the node m respectively;
matrix R of sputtering targets1Comprises the following steps:
wherein, the matrix R1Like the a matrix, the boxed elements are the zero matrix,
wherein,
node l is receiving at time jUnder the influence of multiple uncertainties, other nodes except the node l at the ith moment cause the instability index of the active power distribution network;
matrix R of focus indices2Comprises the following steps:
wherein, the matrix R2Like the a matrix, the boxed elements are the zero matrix,
wherein,
the index of instability of the active power distribution network caused by the node l at the ith moment under the influence of multiple uncertainties on all the nodes at the jth moment;
matrix R of global index3Comprises the following steps:
wherein, the matrix R3Like the a matrix, the boxed elements are the zero matrix,
and comprehensively evaluating the safe and stable running state of the active power distribution network under the influence of multiple uncertainties through the four indexes.
The invention provides a safety evaluation method for an active power distribution network, which combines the safety of the active power distribution network with the inertia of each node in the active power distribution network, then links the inertia with the frequency change rate of the node to convert the evaluation into a probability problem, solves the unstable probability of the active power distribution network by a Markov Monte Carlo simulation method, establishes a model of the active power distribution network, judges the probability of mutual influence among the nodes under different time-space conditions, finally defines each risk index of the active power distribution network, and comprehensively evaluates the safety of the active power distribution network by utilizing the risk indexes; the method can solve the problem of safety evaluation of the active power distribution network under the influence of multiple uncertainties, ensures safe and stable operation of the active power distribution network, is accurate in evaluation, is suitable for safety evaluation of operation of various types of active power distribution networks, and has a good application prospect.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (3)
1. A safety assessment method for an active power distribution network is characterized by comprising the following steps:
the method for calculating the instability probability of the active power distribution network comprises the following steps:
under the influence of multiple uncertainties, if the inertia of all nodes of the active power distribution network is in
Within the range, the active power distribution network is stable, and the inertia of each node of the active power distribution network is within
The probability in the range is that the frequency change rate of the node is within
Probability within range, then probability P of active distribution network stabilityMIComprises the following steps:
wherein,
the upper bound for the rate of change of frequency of the active distribution network,R f,systhe lower bound of the frequency change rate of the active distribution network, p (f) the probability density of the frequency change of the active distribution network,
is an upper bound on the inertia of the active distribution network,H systhe lower bound of the inertia of the active distribution network;
sampling to obtain P by Markov Monte Carlo simulation methodMI；
The instability probability P of the active power distribution network is as follows: p is 1-PMI；
The method for establishing the space-time model of the active power distribution network comprises the following steps:
the probability matrix A, namely a space-time model, of mutual influence of all nodes of the active power distribution network in different air is as follows:
wherein the elements of the frame
Is a matrix of zero values, and is,
if the active power distribution network contains n nodes, then:
Ai,j＝[P1|i,j P2|i,j…Pn|i,j]，Pk|i,j＝[pk,1|i,j pk,2|i,j…pk,n|i,j]T,k＝1,2…n，
wherein p isl,m|i,jIs the probability that the j-th time node m will affect the i-th time node l under the influence of multiple uncertaintiesIn, pl,m|i,j∈{Pk|i,j}，l,m＝1,2…n，k＝1,2…n，i,j＝1,2…T，Ai,jThe probability that the node at the ith moment is influenced by the node at the jth moment in the whole time T is shown;
each pl,m|i,jAre all independent of each other and obey different probability distributions;
when node m is not coupled to node l, pl,m|i,j0, and P | |k|i,j||∞≤1,k＝1,2…n；
When the state change of the j-th time node m to the i-th time node l is larger than the threshold value under the influence of multiple uncertainties, p isl,m|i,jNot equal to 0, and
wherein x ism|j→xm|iThe change of the state of the node l at the ith time under the influence of multiple uncertainties of the node m at the jth time,
is a threshold value for the state of the node m,
sampling to obtain p by Markov Monte Carlo simulation methodl,m|i,j；
The threshold formula for the state of a node is:
minH(x)
s.t.x∈Φ
H(x)-R f,sys≥0，
wherein, H (x) is the relationship between the node state and the frequency change rate, and x belongs to the conditional formula of the node state;
based on the instability probability of the active power distribution network, establishing a diffraction index, a focusing index, a sputtering index and a global index through the space-time model, and evaluating the safety of the active power distribution network according to the four indexes, wherein the specific method comprises the following steps:
matrix R of diffraction indices0Comprises the following steps:
wherein the elements of the added frame are zero matrixes,
wherein,
is an index p of instability of the active power distribution network at the ith moment caused by the influence of multiple uncertainties on the node l at the jth momentl,l|i,jIs the probability that the j-th time node l is influenced by multiple uncertainties, pm,l|i,jIs the probability that the j-th time node l will affect the i-th time node m under the influence of multiple uncertainties, wherein l, m is 1,2 … n, i, j is 1,2 … T, pl(f) And pm(f) Probability densities of system frequency changes caused by state changes of the node l and the node m respectively;
matrix R of sputtering targets1Comprises the following steps:
wherein the elements of the added frame are zero matrixes,
wherein,
the method is an index of instability of the active power distribution network caused by other nodes except the node l at the ith moment under the influence of multiple uncertainties on the node l at the jth moment;
matrix R of focus indices2Comprises the following steps:
wherein the elements of the added frame are zero matrixes,
wherein,
the index of instability of the active power distribution network caused by the node l at the ith moment under the influence of multiple uncertainties on all the nodes at the jth moment;
matrix R of global index3Comprises the following steps:
wherein the elements of the added frame are zero matrixes,
and comprehensively evaluating the safe and stable running state of the active power distribution network under the influence of multiple uncertainties through the four indexes.
2. The active power distribution network safety assessment method according to claim 1, wherein under the influence of multiple uncertainties, the inertia formula of the active power distribution network is as follows:
wherein HsysIs the inertia of the active distribution network, f0Rated power, R, of an active distribution networkf,sysThe frequency change rate of the active power distribution network, and the delta P is the power change amount of the active power distribution network under the influence of multiple uncertainties.
3. The active power distribution network security evaluation method according to claim 1, wherein the specific method for obtaining the threshold value of each node of the active power distribution network comprises:
s1: initializing a population of particles, including a population size N, a location x of each particleiAnd velocity vi；
S2: calculating a fitness value H (x) for each particlei)；
S3: using the fitness value H (x) of each particlei) And individual extremum pbest(i) By comparison, if H (x)i)＞pbest(i) Then H (x)i) In place of pbest(i)；
S4: using the fitness value H (x) of each particlei) And global extreme gbest(i) By comparison, if H (x)i)＞gbest(i) Then H (x)i) In place of gbest(i)；
S5: updating the position x of the particle according toiAnd velocity vi：
Wherein,
for the t-th iteration particle i airspeed vector,
is the position vector of the t-th iteration particle i, c1And c2Is a learning factor, r1And r2Is [0,1 ]]Uniform random number in the range, w is the inertial weight, pbestAnd gbestThe best positions that the particle and population have experienced, respectively;
s6: if H (x) ═R f,sysOr the number of cycles reaches the maximum number of cycles Nc, the process returns to S2, where h (x) is a relationship between the node state and the frequency change rate.
Priority Applications (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010736523.8A CN111798163B (en) | 2020-07-28 | 2020-07-28 | Active power distribution network security assessment method |
| JP2022505619A JP7319739B2 (en) | 2020-07-28 | 2021-07-19 | Safety evaluation methods for active distribution networks |
| PCT/CN2021/106988 WO2022022307A1 (en) | 2020-07-28 | 2021-07-19 | Safety evaluation method for active power distribution network |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010736523.8A CN111798163B (en) | 2020-07-28 | 2020-07-28 | Active power distribution network security assessment method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111798163A CN111798163A (en) | 2020-10-20 |
| CN111798163B true CN111798163B (en) | 2021-03-05 |
Family
ID=72827824
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010736523.8A Active CN111798163B (en) | 2020-07-28 | 2020-07-28 | Active power distribution network security assessment method |
Country Status (3)
| Country | Link |
|---|---|
| JP (1) | JP7319739B2 (en) |
| CN (1) | CN111798163B (en) |
| WO (1) | WO2022022307A1 (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111798163B (en) * | 2020-07-28 | 2021-03-05 | 南京邮电大学 | Active power distribution network security assessment method |
| CN117970036B (en) * | 2024-03-29 | 2024-07-09 | 杭州欣美成套电器制造有限公司 | Power distribution network cable equipment state evaluation method and system |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105140913A (en) * | 2015-08-14 | 2015-12-09 | 中国电力科学研究院 | Uncertainty based reconstruction method for active power distribution grid |
| CN106532688A (en) * | 2016-11-22 | 2017-03-22 | 国电南瑞科技股份有限公司 | Method and system for evaluating operation reliability of micro-grid |
| CN106972481A (en) * | 2017-02-28 | 2017-07-21 | 国网江苏省电力公司常州供电公司 | Scale electrically-charging equipment accesses the security quantitative estimation method of active power distribution network |
| CN107220775A (en) * | 2017-06-01 | 2017-09-29 | 东北大学 | A kind of active power distribution network various visual angles collaboration vulnerability assessment method for considering information system effect |
| CN108510162A (en) * | 2018-03-13 | 2018-09-07 | 南京邮电大学 | A kind of active power distribution network security effectiveness appraisal procedure |
| CN109559019A (en) * | 2018-11-01 | 2019-04-02 | 三峡大学 | A kind of Electrical Power System Dynamic safety evaluation method based on risk index |
| CN111044846A (en) * | 2019-12-30 | 2020-04-21 | 河南工程学院 | Probability evaluation method for fault tolerance online fault location of complex active power distribution network |
Family Cites Families (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH07123593A (en) * | 1993-10-21 | 1995-05-12 | Chubu Electric Power Co Inc | Supervisory system of operation stability of power system |
| JP2004064941A (en) | 2002-07-31 | 2004-02-26 | Hitachi Ltd | Distributed power supply analysis system |
| US8996185B2 (en) | 2011-06-03 | 2015-03-31 | Mitsubishi Electric Research Laboratories, Inc. | Method for scheduling power generators based on optimal configurations and approximate dynamic programming |
| US10211638B2 (en) * | 2013-09-30 | 2019-02-19 | Board Of Regents, The University Of Texas System | Power quality of service optimization for microgrids |
| JPWO2015079554A1 (en) | 2013-11-29 | 2017-03-16 | 株式会社日立製作所 | Power system state estimation device, state estimation method thereof, and power system control system |
| US10512094B2 (en) * | 2017-12-28 | 2019-12-17 | Intel Corporation | Assessment and mitigation of radio frequency interference of networked devices |
| CN109004679B (en) * | 2018-09-06 | 2021-08-20 | 国网安徽省电力有限公司芜湖供电公司 | Renewable energy source accessed power grid safety and stability monitoring method |
| CN110518568A (en) * | 2019-03-20 | 2019-11-29 | 华北电力大学 | A kind of distribution network voltage quality evaluation index considering voltage security and stability |
| CN110807172A (en) | 2019-10-12 | 2020-02-18 | 许昌许继软件技术有限公司 | Risk prediction method and device for relay protection of power system |
| CN111798163B (en) * | 2020-07-28 | 2021-03-05 | 南京邮电大学 | Active power distribution network security assessment method |
-
2020
- 2020-07-28 CN CN202010736523.8A patent/CN111798163B/en active Active
-
2021
- 2021-07-19 WO PCT/CN2021/106988 patent/WO2022022307A1/en active Application Filing
- 2021-07-19 JP JP2022505619A patent/JP7319739B2/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105140913A (en) * | 2015-08-14 | 2015-12-09 | 中国电力科学研究院 | Uncertainty based reconstruction method for active power distribution grid |
| CN106532688A (en) * | 2016-11-22 | 2017-03-22 | 国电南瑞科技股份有限公司 | Method and system for evaluating operation reliability of micro-grid |
| CN106972481A (en) * | 2017-02-28 | 2017-07-21 | 国网江苏省电力公司常州供电公司 | Scale electrically-charging equipment accesses the security quantitative estimation method of active power distribution network |
| CN107220775A (en) * | 2017-06-01 | 2017-09-29 | 东北大学 | A kind of active power distribution network various visual angles collaboration vulnerability assessment method for considering information system effect |
| CN108510162A (en) * | 2018-03-13 | 2018-09-07 | 南京邮电大学 | A kind of active power distribution network security effectiveness appraisal procedure |
| CN109559019A (en) * | 2018-11-01 | 2019-04-02 | 三峡大学 | A kind of Electrical Power System Dynamic safety evaluation method based on risk index |
| CN111044846A (en) * | 2019-12-30 | 2020-04-21 | 河南工程学院 | Probability evaluation method for fault tolerance online fault location of complex active power distribution network |
Non-Patent Citations (2)
| Title |
|---|
| Advanced control architectures for intellengent microgrids--Part I:Decentralized and hierarchical control;Guerrero J M;《IEEE Transactions on Industrial Electronics》;20131231;第60卷(第4期);第1254-1262页 * |
| 有源配电网关键运行特性的评价理论与优化提升研究;叶琳浩;《中国博士学位论文全文数据库工程科技Ⅱ辑》;20190515(第5期);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| JP2022545769A (en) | 2022-10-31 |
| JP7319739B2 (en) | 2023-08-02 |
| CN111798163A (en) | 2020-10-20 |
| WO2022022307A1 (en) | 2022-02-03 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106532778B (en) | Method for calculating maximum access capacity of distributed photovoltaic grid connection | |
| CN111798163B (en) | Active power distribution network security assessment method | |
| Moshksar et al. | Adaptive estimation approach for parameter identification of photovoltaic modules | |
| Philip et al. | An evolutionary computation based approach for reduced order modelling of linear systems | |
| CN108649605B (en) | DRE grid-connected access capacity planning method based on double-layer scene interval power flow | |
| CN112785027B (en) | Wind-solar-storage combined power generation system confidence capacity evaluation method and system | |
| CN112310980B (en) | Safety and stability evaluation method and system for direct-current blocking frequency of alternating-current and direct-current series-parallel power grid | |
| CN110189061A (en) | A kind of extensive dispersion photovoltaic access planing method based on risk assessment | |
| Chen et al. | Distributional analysis for model predictive deferrable load control | |
| CN107834540B (en) | Method for determining distributed photovoltaic access capacity based on probability constraint | |
| CN104915788B (en) | A method of considering the Electrical Power System Dynamic economic load dispatching of windy field correlation | |
| CN109066651A (en) | The calculation method of wind-powered electricity generation-load scenarios limit transmitted power | |
| Wang et al. | Research on electricity consumption behavior of users based on deep learning | |
| CN113902343A (en) | Vulnerable line and vulnerable load node identification method for gas-electricity interconnection system | |
| CN117318018A (en) | Short-term prediction method and system for wind power output | |
| CN117039894A (en) | Photovoltaic power short-term prediction method and system based on improved dung beetle optimization algorithm | |
| CN116031957A (en) | Large-scale wind farm voltage and frequency recovery control method | |
| CN115800260A (en) | Power system frequency response modeling method containing high-proportion new energy | |
| CN115660433A (en) | Photovoltaic power station planning method based on winged insect light-searching movement principle | |
| CN112819278B (en) | Segmented affine method for solving two-stage robust optimization unit combination model | |
| CN113239547A (en) | Core backbone network frame construction method based on TLBO algorithm | |
| CN113837485A (en) | Light storage micro-grid system source-load characteristic prediction method, system, device and storage medium | |
| Wang et al. | Calculation of maximum permitted capacity of photovoltaic based on flower pollination algorithm combined with genetic algorithm (GA-FPA) in distribution network | |
| CN113591224A (en) | Urban power grid cascading failure risk assessment method and system | |
| Chen et al. | SOC Estimation of Lithium-ion Batteries at Different Temperatures |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |