CN116316887A - Distribution line distributed photovoltaic bearing capacity assessment method based on N-1 safety criterion - Google Patents

Distribution line distributed photovoltaic bearing capacity assessment method based on N-1 safety criterion Download PDF

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CN116316887A
CN116316887A CN202310285711.7A CN202310285711A CN116316887A CN 116316887 A CN116316887 A CN 116316887A CN 202310285711 A CN202310285711 A CN 202310285711A CN 116316887 A CN116316887 A CN 116316887A
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distribution line
scene
node
moment
distributed photovoltaic
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岳宝强
李彪
陈涛
冯德品
李静鹏
张利
张恒
胡伟才
吕贵龙
滕立凯
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Linyi Power Supply Co of State Grid Shandong Electric Power Co Ltd
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Linyi Power Supply Co of State Grid Shandong Electric Power Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/48—Controlling the sharing of the in-phase component
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/50—Controlling the sharing of the out-of-phase component
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/22—The renewable source being solar energy
    • H02J2300/24—The renewable source being solar energy of photovoltaic origin

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Abstract

The invention provides a distribution line distributed photovoltaic bearing capacity assessment method based on an N-1 safety criterion, which relates to the technical field of distribution line bearing capacity assessment and specifically comprises the following steps: collecting data of the distributed photovoltaic historical output data, and obtaining a typical output scene through a K-means clustering algorithm; and combining uncertainty characteristics of source load, and taking the acceptance capacity of the distributed photovoltaic power supply in a fault scene into consideration to establish a distribution line bearing capacity evaluation model based on an N-1 safety criterion. Based on a decoupling strategy, performing decoupling dimension reduction calculation on a feasible domain considering an N-1 fault scene; the feasible region considering the N-1 security constraint can be characterized as the intersection of the feasible regions in all fault scenes, and the evaluation result of the distributed photovoltaic power supply carrying capacity of the distribution line in the scene is obtained. And checking whether all the typical output scenes obtained through the K-means algorithm are traversed. The method provided by the invention is beneficial to providing reference for reasonable configuration of distribution lines and distributed photovoltaic power sources.

Description

Distribution line distributed photovoltaic bearing capacity assessment method based on N-1 safety criterion
Technical Field
The patent belongs to the technical field of distribution line bearing capacity assessment and relates to a distribution line distributed photovoltaic bearing capacity assessment method based on N-1 safety criteria.
Background
In order to reduce carbon emission, the generation proportion of new energy is greatly increased in recent years, and particularly, distributed generation is applied in a large scale. The capacity and permeability of a distributed power source represented by photovoltaic and wind power on a power source side in a power system are continuously increased, and the fluctuation and uncertainty of the output of the distributed power source provide challenges for the running stability and reliability of a power grid to the safe running of a distribution line. Therefore, the assessment of the bearing capacity of the distribution line has important significance for the safe operation of the distribution line.
The existing distributed photovoltaic access capacity is evaluated under the condition of safe operation of a distribution line, and in actual conditions, when the distribution line faces to faults or overhauls and the like, in order to ensure that a terminal user does not have the power failure and the like, the reliability of the distribution line is ensured, and the load rate of the distribution line is required to meet N-1 safety standards. Therefore, there is a need to propose a distribution line distributed photovoltaic load capacity assessment method based on N-1 safety guidelines.
Disclosure of Invention
In order to solve the defects and the shortcomings in the prior art, the patent adopts a distributed photovoltaic bearing capacity evaluation method of the distribution line based on the N-1 safety criterion, and the bearing capacity of the distribution line is evaluated under the condition of considering the receiving capacity of the distributed photovoltaic power supply under the fault scene.
Specifically, the power distribution line distributed photovoltaic bearing capacity evaluation method based on the N-1 safety rule is characterized by comprising the following steps of:
step 1: combining uncertainty characteristics of source load, and considering acceptance capacity of a distributed photovoltaic power supply in a fault scene to establish a distribution line bearing capacity assessment method based on an N-1 safety criterion;
step 2: and carrying out decoupling dimension reduction calculation on the feasible domain in the N-1 safety criterion fault scene based on a decoupling strategy.
In the step 1, based on the N-1 safety criterion, the installation capacity of the distributed photovoltaic power supply is taken as an objective function, and the line capacity, the node voltage, the tide and the short-circuit current are taken as constraint conditions:
the objective function is that the distributed photovoltaic power supply of the line has the largest installation capacity, and the expression is as follows:
Figure BDA0004139763680000021
wherein:
Figure BDA0004139763680000022
capacity is installed for the distributed power supply at node i under scenario s.
Moreover, before the occurrence of the fault scene, the constraint condition of the distributed photovoltaic power supply bearing capacity evaluation model is as follows:
1) Line capacity constraints
Figure BDA0004139763680000023
Wherein:
Figure BDA0004139763680000024
the active power flowing through the ij branch t of the distribution line at the moment of the scene s is obtained; />
Figure BDA0004139763680000025
The reactive power flowing through the ij branch t of the distribution line at the moment of the scene s is obtained; />
Figure BDA0004139763680000026
Line capacity for ij branch of distribution line;
2) Tidal current constraint
Figure BDA0004139763680000027
Figure BDA0004139763680000028
V s,j,t ＝V s,i,t -(r ij P s,ij,t +x ij Q s,ij,t )
Wherein: p (P) s,ij,t The active power flowing through the branch ij at the moment t of the distribution line under the scene s is obtained; q (Q) s,ij,t The reactive power flowing through the branch ij at the moment t of the distribution line in the scene s is obtained; p (P) s,jk,t Active power flowing out of the node j and flowing to the node k at the moment of the distribution line t in the scene s; q (Q) s,jk,t The reactive power flows out of the node j and flows to the node k at the moment of the distribution line t in the scene s;
Figure BDA0004139763680000031
the active power is the load active power of a node j at the moment t of the distribution line under the scene s; />
Figure BDA0004139763680000032
The reactive power is the load reactive power of a node j at the moment t of the distribution line under the scene s; />
Figure BDA0004139763680000033
DG power of a node j at t moment of a distribution line in a scene s; />
Figure BDA0004139763680000034
The energy storage and charging power of a node j at the moment t of the distribution line in the scene s; />
Figure BDA0004139763680000035
The energy storage and discharge power of a node j at the moment t of the distribution line in the scene s is obtained; r is (r) ij The resistance of branch ij; x is x ij Is the reactance of branch ij.
Moreover, after the fault scene occurs, the constraint conditions of the distributed photovoltaic power supply bearing capacity evaluation model are as follows:
1) Line capacity constraints
For the transmission line, after a fault occurs or an overhaul scene is met, the condition that the N-1 check is met means that: when one power transmission line fails or overhauls and stops running, the load of the power transmission line can be transferred to other power transmission lines which normally run, and the short-time allowable overload capacity of the normal running line is not more than the rated capacity of a single line, and the power transmission line is based on the N-1 safety constraint as shown in the formula:
|P(t)≤(N-1)S|
wherein: n is the number of transmission lines; s is the rated capacity of a single power transmission line; p (t) is the net load of the transmission line at the moment t;
2) Tidal current constraint
Figure BDA0004139763680000036
V f,j,t ＝V f,i,t -(r ij P f,ij,t +x ij Q f,ij,t )
Wherein: p (P) f,ij,t The active power flowing through the branch ij at the moment t of the distribution line in the fault scene f; q (Q) f,ij,t Reactive power flowing through a branch ij at the moment t of the distribution line in the fault scene f; p (P) f,jk,t Active power flowing out of the node j and flowing to the node k at the moment of the distribution line t in the fault scene f; q (Q) f,jk,t The reactive power flows out of the node j and flows to the node k at the moment of the distribution line t in the fault scene f;
Figure BDA0004139763680000041
the active power is the load active power of a node j at the moment t of the distribution line under the fault scene f; />
Figure BDA0004139763680000042
The reactive power is the load reactive power of a node j at the moment t of the distribution line in the fault scene f; />
Figure BDA0004139763680000043
The DG power of a node j at the moment t of the distribution line in the fault scene f; />
Figure BDA0004139763680000044
The energy storage and charging power of a node j at the moment t of the distribution line in the fault scene f; />
Figure BDA0004139763680000045
The energy storage and discharge power of a node j at the moment t of the distribution line in the fault scene f; r is (r) ij The resistance of branch ij; x is x ij Is the reactance of branch ij.
And in the step 2, the feasible domains meeting the constraint in the ith line fault scene and the constraint in the non-fault scene are obtained in parallel, the feasible domain considering the N-1 security constraint can be characterized as the intersection of the feasible domains in all fault scenes, and the specific flow is as follows:
(1) According to the maximum value and the minimum value in each dimension, constructing an initialized distributed photovoltaic access capacity feasible domain;
the minimum solution problem for the ith dimension:
Figure BDA0004139763680000046
S.t.
maximum solving problem for the i-th dimension:
Figure BDA0004139763680000047
S.t.
the obtained information under the non-fault scene and the fault scene
Figure BDA0004139763680000048
Is used as vertex V to construct a feasible domain omega c ；
(2) New vertex search: by shifting out the feasible region omega c Searching for new vertices; let the inequality expression of the kth boundary plane be
Figure BDA0004139763680000049
Obtaining a new vertex by solving the following linear programming problem:
Figure BDA0004139763680000051
wherein: v (V) p Is the feasible domain omega c Any point in the above;
the optimal solution of the linear programming is the top point of the constraint. Therefore, the optimal solution is the new vertex, and after all sides are translated, all the vertices are marked as V new ；
(3) Algorithm termination condition checking: calculating the difference between the feasible region volumes before and after the new vertex in the consideration (2) to be DeltaV; the smaller the delta V change, the smaller the feasible region change before and after adding the new vertex, thus, when delta V is smaller than the given threshold, the algorithm is terminated and the feasible region omega under the c-th line fault is recorded c To construct a feasible region Ω from the new vertices otherwise c Then return to (2);
when obtaining the feasible region Ω in all fault conditions c The feasible region Ω taking into account the N-1 security constraints is characterized as the feasible region Ω under all fault conditions c And (3) obtaining the carrying capacity evaluation result of the distributed photovoltaic power distribution line.
And step 2, the confidence degrees are ranked from large to small, the confidence degrees are opposite to the obtained bearing capacity ranking order, and the corresponding bearing capacity of the distributed photovoltaic power distribution line is determined after the confidence degrees are selected.
The application has the advantages and positive effects that:
the method for evaluating the distributed photovoltaic bearing capacity of the distribution line based on the N-1 safety criterion is based on the N-1 safety criterion, aims at the maximum bearing capacity of the distribution line, comprehensively considers the admittance capacity of the distributed photovoltaic power supply under a fault scene, and is favorable for providing references for reasonable configuration of the distribution line and the distributed photovoltaic power supply.
Drawings
FIG. 1 is a graph of historical output of a distributed photovoltaic power source.
Fig. 2 is a graph of typical output curves of clustered distributed photovoltaic power supplies.
Fig. 3 is a diagram of the structure of the line a.
Fig. 4 is a load time sequence characteristic curve.
Fig. 5 is a flow chart of the method.
Detailed Description
The present application is further described in detail below with reference to the attached drawings by way of specific examples, which are intended to be illustrative, not limiting, and not to limit the scope of the present application.
The distribution line distributed photovoltaic bearing capacity assessment method based on the N-1 safety rule comprises the following steps of:
step 1: and combining uncertainty characteristics of source load, and taking the acceptance capacity of the distributed photovoltaic power supply in a fault scene into consideration to establish a distribution line bearing capacity assessment method based on an N-1 safety criterion.
Step 2: and carrying out decoupling dimension reduction calculation on the feasible domain considering the N-1 fault scene based on a decoupling strategy.
In the step 1, a K-means clustering algorithm is adopted to obtain a distributed photovoltaic typical output scene, and the specific flow is as follows:
(1) Normalizing the collected historical distributed photovoltaic power output data;
(2) Randomly selecting K points from the normalized data to serve as mass centers;
(3) Respectively calculating the distance from the remaining data points to each centroid;
(4) Classifying the non-centroid points into clusters represented by centroids with shortest distances to the non-centroid points to form K clusters;
(5) According to the classified clusters, re-calculating mass centers in each cluster, and determining actual mass centers in the group;
(6) Repeating the operation of the step (3) until the iteration times or errors are smaller than the specified value, and obtaining the typical output scene of the distributed photovoltaic.
The specific calculation process is as follows:
note that sample dataset d= { X 1 ,X 2 ,...,X n N represents the number of samples, sample X of the ith i ＝{x i1 ,x i2 ,...,x ip P represents the attribute number or index category of the sample, and K represents the number of clusters. In K-means clustering, any two samples X i And X is f The euclidean distance between them is in the form:
Figure BDA0004139763680000071
wherein: d (x) i ,x f ) Is the distance between element i and the initial centroid f.
At the beginning of clustering, K samples are randomly selected as initial clustering centers, and then non-clustering center samples are classified into a category C represented by a clustering center h with the shortest distance to the non-clustering center samples according to the above formula h Is a kind of medium.
The cluster center is then updated by:
Figure BDA0004139763680000072
wherein: phi (X) i ) Represents the h th class C h Sample contained in (C) h I represents the h th category C h The number of samples contained in the sample, m h Represents the hClass C h Mean of the samples.
The goal of K-means clustering is a minimized square error criterion function, of the form:
Figure BDA0004139763680000073
the clustering center m is continuously updated through the formula h Samples phi (X) i ) Until the square error criterion function value no longer changes or the set number of iterations is reached.
After iteration is finished, the clustering center m at the moment is read h I.e. the typical sample we need, phi (X i ) I.e., the class to which each representative sample corresponds.
Based on the N-1 safety criterion, the step 1 is to use the maximum installation capacity of the distributed photovoltaic power supply of the distribution line as an objective function, and use the line capacity, the node voltage, the tide, the short-circuit current and the harmonic voltage distortion rate as constraint condition processes, and provides a distributed photovoltaic distribution line bearing capacity assessment method based on the N-1 criterion, which comprises the following steps:
the objective function is to maximize the distribution line distributed photovoltaic power installation capacity, expressed as follows:
Figure BDA0004139763680000081
wherein:
Figure BDA0004139763680000082
capacity is installed for the distributed power supply at node i under scenario s.
Before a fault scene occurs, the constraint conditions of the distributed photovoltaic power supply bearing capacity assessment model are as follows:
1) Node voltage constraint
V i,min ≤V s,i,t ≤V i,max
Wherein: v (V) i,min A lower voltage limit for safe operation of the distribution line node i;V i,max the upper voltage limit for safe operation of the distribution line node i; v (V) s,i,t The voltage of the distribution line node i at the moment t under the scene s.
2) Line capacity constraints
Figure BDA0004139763680000083
Wherein:
Figure BDA0004139763680000084
the active power flowing through the ij branch t of the 10kV medium-voltage distribution line at the moment of the scene s; />
Figure BDA0004139763680000085
The reactive power flowing through the ij branch t of the 10kV medium-voltage distribution line at the moment of the scene s; />
Figure BDA0004139763680000086
The line capacity of the ij branch of the 10kV medium voltage distribution line.
3) Tidal current constraint
Figure BDA0004139763680000087
Figure BDA0004139763680000088
V s,j,t ＝V s,i,t -(r ij P s,ij,t +x ij Q s,ij,t )
Wherein: p (P) s,ij,t The active power flowing through the branch ij at the moment t of the distribution line under the scene s is obtained; q (Q) s,ij,t The reactive power flowing through the branch ij at the moment t of the distribution line in the scene s is obtained; p (P) s,jk,t Active power flowing out of the node j and flowing to the node k at the moment of the distribution line t in the scene s; q (Q) s,jk,t The reactive power flows out of the node j and flows to the node k at the moment of the distribution line t in the scene s;
Figure BDA0004139763680000091
the active power is the load active power of a node j at the moment t of the distribution line under the scene s; />
Figure BDA0004139763680000092
The reactive power is the load reactive power of a node j at the moment t of the distribution line under the scene s; />
Figure BDA0004139763680000093
DG power of a node j at t moment of a distribution line in a scene s; />
Figure BDA0004139763680000094
The energy storage and charging power of a node j at the moment t of the distribution line in the scene s; />
Figure BDA0004139763680000095
The energy storage and discharge power of a node j at the moment t of the distribution line in the scene s is obtained; r is (r) ij The resistance of branch ij; x is x ij Is the reactance of branch ij.
4) Harmonic voltage distortion rate constraint
The limitation of harmonic voltage distortion rate specified by national standards is expressed as follows:
THD V ≤THD V,max
Figure BDA0004139763680000096
Figure BDA0004139763680000097
wherein: THD (total heat transfer) V Is harmonic voltage distortion rate; THD (total heat transfer) V,max Maximum harmonic voltage distortion rate allowed for ensuring safe operation of the network; u (U) h-spectrum Is the harmonic voltage amplitude of the h-th typical spectrum; u (U) h The harmonic voltage amplitude of the h harmonic source; u (U) 1 Is the grid-connected point fundamental voltage.
5) Short circuit current restraint
Figure BDA0004139763680000098
Wherein:
Figure BDA0004139763680000099
short-circuit current contributing to the original power supply; />
Figure BDA00041397636800000910
Short-circuit current contributing to DG; i sc,max The maximum short-circuit current allowed to ensure safe operation of the network.
After the fault scene occurs, the constraint conditions of the distributed photovoltaic power supply bearing capacity evaluation model are as follows:
1) Node voltage constraint
V i,min ≤V s,i,t ≤V i,max
Wherein: v (V) i,min A lower voltage limit for safe operation of the distribution line node i; v (V) i,max The upper voltage limit for safe operation of the distribution line node i; v (V) s,i,t The voltage of the distribution line node i at the moment t under the scene s.
2) Line capacity constraints
For the transmission line, after a fault occurs or an overhaul scene is met, the condition that the N-1 check is met means that: when one transmission line fails or overhauls and stops running, the load of the transmission line can be transferred to other transmission lines which normally run, and the overload capacity of the normal running line is allowed to be smaller than the rated capacity of a single line. The N-1 based security constraint is shown in the formula.
|P 1 (t)≤(N-1)S|
Wherein: n is the number of transmission lines; s is the rated capacity of a single power transmission line; p (P) l And (t) is the net load of the transmission line at the moment t.
3) Tidal current constraint
Figure BDA0004139763680000101
Figure BDA0004139763680000102
V f,j,t ＝V f,i,t -(r ij P f,ij,t +x ij Q f,ij,t )
Wherein: p (P) f,ij,t The active power flowing through the branch ij at the moment t of the distribution line in the fault scene f; q (Q) f,ij,t Reactive power flowing through a branch ij at the moment t of the distribution line in the fault scene f; p (P) f,jk,t Active power flowing out of the node j and flowing to the node k at the moment of the distribution line t in the fault scene f; q (Q) f,jk,t The reactive power flows out of the node j and flows to the node k at the moment of the distribution line t in the fault scene f;
Figure BDA0004139763680000103
the active power is the load active power of a node j at the moment t of the distribution line under the fault scene f; />
Figure BDA0004139763680000104
The reactive power is the load reactive power of a node j at the moment t of the distribution line in the fault scene f; />
Figure BDA0004139763680000111
The DG power of a node j at the moment t of the distribution line in the fault scene f; />
Figure BDA0004139763680000112
The energy storage and charging power of a node j at the moment t of the distribution line in the fault scene f; />
Figure BDA0004139763680000113
The energy storage and discharge power of a node j at the moment t of the distribution line in the fault scene f; r is (r) ij The resistance of branch ij; x is x ij Is the reactance of branch ij.
4) Harmonic voltage distortion rate constraint
The limitation of harmonic voltage distortion rate specified by national standards is expressed as follows:
THD V ≤THD V,max
Figure BDA0004139763680000114
Figure BDA0004139763680000115
wherein: THD (total heat transfer) V Is harmonic voltage distortion rate; THD (total heat transfer) V,max Maximum harmonic voltage distortion rate allowed for ensuring safe operation of the network; u (U) f,h-spectrum Is the harmonic voltage amplitude of the h-th typical frequency spectrum after the fault; u (U) f,h The harmonic voltage amplitude of the h harmonic source after the fault; u (U) 1 Is the grid-connected point fundamental voltage.
5) Short circuit current restraint
Figure BDA0004139763680000116
Wherein:
Figure BDA0004139763680000117
short-circuit current contributing to the original power supply after failure; />
Figure BDA0004139763680000118
Short-circuit current contributing to DG after failure; i sc,max The maximum short-circuit current allowed to ensure safe operation of the network.
Further, in step 2, the algorithm is initialized
(1) According to the maximum value and the minimum value in each dimension, constructing an initialized distributed photovoltaic access capacity feasible domain;
the minimum solution problem for the ith dimension:
Figure BDA0004139763680000119
S.t.
maximum solving problem for the i-th dimension:
Figure BDA0004139763680000121
S.t.
the obtained information under the non-fault scene and the fault scene
Figure BDA0004139763680000122
Is used as vertex V to construct a feasible domain omega c 。
(2) New vertex search: by shifting out the feasible region omega c Searching for new vertices; let the inequality expression of the kth boundary plane be
Figure BDA0004139763680000123
Obtaining a new vertex by solving the following linear programming problem:
Figure BDA0004139763680000124
wherein: v (V) p Is the feasible domain omega c Any point in the above;
the optimal solution of the linear programming is the top point of the constraint. Therefore, the optimal solution is the new vertex, and after all sides are translated, all the vertices are marked as V new ；
(3) Algorithm termination condition checking: calculating the difference between the feasible region volumes before and after the new vertex in the consideration (2) to be DeltaV; the smaller the delta V change, the smaller the feasible region change before and after adding the new vertex, thus, when delta V is smaller than the given threshold, the algorithm is terminated and the feasible region omega under the c-th line fault is recorded c To construct a feasible region Ω from the new vertices otherwise c Then return to (2);
when obtaining the feasible region Ω in all fault conditions c The feasible region Ω taking into account the N-1 security constraints is characterized as the feasible region Ω under all fault conditions c Is a complex of the two. By solving forAnd solving the optimization model to obtain a distributed photovoltaic power distribution line bearing capacity evaluation result based on an N-1 criterion.
Further, when the bearing capacity is smaller, the condition of line capacity out-of-limit cannot occur in different output scenes, so that the more the number of scenes for bearing capacity adaptation is, the higher the confidence is. And according to the confidence coefficient from large to small, namely the obtained bearing capacity is from small to large, the smaller the bearing capacity is, namely the larger the confidence coefficient is, and after the confidence coefficient is selected, the corresponding distributed photovoltaic power bearing capacity of the distribution line can be determined.
In the embodiment, six distribution lines in a certain area are selected, the numbers of the six distribution lines are a, b, c, d, e, f respectively, when the bearing capacity of the distribution lines is evaluated, K-means clustering is adopted to cut down a large number of distribution photovoltaic power output scenes obtained by the collection so as to obtain typical scenes and probability thereof, and the bearing capacity evaluation of the distribution lines of the distributed photovoltaic power is continuously carried out based on the obtained typical scenes.
(1) Historical scene of distributed photovoltaic power output
Drawing a large number of distributed photovoltaic power output curves according to the funding data, wherein the result is shown in the following graph:
the k-means clustering is adopted to cut down a large number of scenes, in the example, all scenes are divided into 10 types, the clustering center of each type is used as a cut-down scene, and the obtained cut-down typical output curve is shown in the following graph:
the probability of the scene data within each class and the various typical curves derived therefrom are shown in the following table:
TABLE 1 typical scenario and probability thereof
Category(s) Number of scenes in class Probability of occurrence Output coefficient at peak time
1 40 0.11 0.67
2 47 0.13 0.42
3 19 0.05 0.21
4 20 0.05 0.82
5 46 0.13 0.68
6 67 0.18 0.56
7 44 0.12 0.07
8 12 0.04 0.55
9 43 0.12 0.43
10 27 0.07 0.39
(2) Bearing capacity assessment of distributed photovoltaic power distribution circuit
Taking a line a as an example to explain the carrying capacity evaluation process of the distributed photovoltaic power distribution line, the structure of the line a is shown in fig. 3, the load information of each node is shown in table 3, and the time sequence characteristic curve of the load is shown in fig. 4.
The following table shows impedance information of the line.
Figure BDA0004139763680000141
The following table shows the load information of each node of the line.
Table 3 load table for each node of line a
Node numbering Maximum active power (kW) Maximum reactive power (kVar)
1 18 9
2 0 0
3 375 182
4 480 465
5 500 242
6 0 0
The lower graph shows the timing characteristics of the load.
And accessing the distributed photovoltaic power supply into a No. 3 node to obtain bearing capacity evaluation results under different confidence degrees, wherein the results are shown in the following table.
Table 4 results of bearing capacity at different confidence levels
Confidence (%) 100％ 95％ 82％ 70％
Bearing capacity (MW) 10.395 12.385 12.847 16.084
It can be seen that the higher the confidence, the less load bearing. This is because, when the load bearing capacity is small, no voltage out-of-limit or line capacity out-of-limit occurs in different output scenarios, and the number of scenarios to which the load bearing capacity is adapted is large, and the confidence is high.
In this embodiment, the confidence level was chosen to be 95% and thus the load bearing capacity was 12.385MW.

Claims (6)

1. A method for evaluating distributed photovoltaic carrying capacity of a distribution line based on N-1 safety criteria, the method comprising the steps of:
step 1: combining uncertainty characteristics of source load, and considering acceptance capacity of a distributed photovoltaic power supply in a fault scene to establish a distribution line bearing capacity assessment method based on an N-1 safety criterion;
step 2: and carrying out decoupling dimension reduction calculation on the feasible domain in the N-1 safety criterion fault scene based on a decoupling strategy.
2. The method for evaluating the distributed photovoltaic carrying capacity of the distribution line based on the N-1 safety criterion according to claim 1, wherein in the step 1, the installation capacity of the distributed photovoltaic power supply is taken as an objective function, and the line capacity, the node voltage, the tide and the short-circuit current are taken as constraint conditions:
the objective function is that the distributed photovoltaic power supply of the line has the largest installation capacity, and the expression is as follows:
Figure FDA0004139763670000011
wherein:
Figure FDA0004139763670000012
capacity is installed for the distributed power supply at node i under scenario s.
3. The method for evaluating the distributed photovoltaic load-bearing capacity of the distribution line based on the N-1 safety criterion according to claim 2, wherein the constraint condition of the distributed photovoltaic power load-bearing capacity evaluation model is as follows before a fault scene occurs:
1) Line capacity constraints
Figure FDA0004139763670000013
Wherein:
Figure FDA0004139763670000014
the active power flowing through the ij branch t of the distribution line at the moment of the scene s is obtained; />
Figure FDA0004139763670000015
The reactive power flowing through the ij branch t of the distribution line at the moment of the scene s is obtained; />
Figure FDA0004139763670000016
Line capacity for ij branch of distribution line;
2) Tidal current constraint
Figure FDA0004139763670000021
Figure FDA0004139763670000022
V s,j,t ＝V s,i,t -(r ij P s,ij,t +x ij Q s,ij,t )
Wherein: p (P) s,ij,t The active power flowing through the branch ij at the moment t of the distribution line under the scene s is obtained; q (Q) s,ij,t The reactive power flowing through the branch ij at the moment t of the distribution line in the scene s is obtained; p (P) s,jk,t Active power flowing out of the node j and flowing to the node k at the moment of the distribution line t in the scene s; q (Q) s,jk,t The reactive power flows out of the node j and flows to the node k at the moment of the distribution line t in the scene s;
Figure FDA0004139763670000023
the active power is the load active power of a node j at the moment t of the distribution line under the scene s; />
Figure FDA0004139763670000024
The reactive power is the load reactive power of a node j at the moment t of the distribution line under the scene s; />
Figure FDA0004139763670000025
DG power of a node j at t moment of a distribution line in a scene s; />
Figure FDA0004139763670000026
The energy storage and charging power of a node j at the moment t of the distribution line in the scene s; />
Figure FDA0004139763670000027
The energy storage and discharge power of a node j at the moment t of the distribution line in the scene s is obtained; r is (r) ij The resistance of branch ij; x is x ij Is the reactance of branch ij.
4. The method for evaluating the distributed photovoltaic load-bearing capacity of the distribution line based on the N-1 safety criterion according to claim 2, wherein after a fault scene occurs, the constraint condition of the distributed photovoltaic power load-bearing capacity evaluation model is as follows:
1) Line capacity constraints
For the transmission line, after a fault occurs or an overhaul scene is met, the condition that the N-1 check is met means that: when one power transmission line fails or overhauls and stops running, the load of the power transmission line can be transferred to other power transmission lines which normally run, and the short-time allowable overload capacity of the normal running line is not more than the rated capacity of a single line, and the power transmission line is based on the N-1 safety constraint as shown in the formula:
|P(t)≤(N-1)S|
wherein: n is the number of transmission lines; s is the rated capacity of a single power transmission line; p (t) is the net load of the transmission line at the moment t;
2) Tidal current constraint
Figure FDA0004139763670000031
V f,j,t ＝V f,i,t -(r ij P f,ij,t +x ij Q f,ij,t )
Wherein: p (P) f,ij,t The active power flowing through the branch ij at the moment t of the distribution line in the fault scene f; q (Q) f,ij,t Reactive power flowing through a branch ij at the moment t of the distribution line in the fault scene f; p (P) f,jk,t Active power flowing out of the node j and flowing to the node k at the moment of the distribution line t in the fault scene f; q (Q) f,jk,t The reactive power flows out of the node j and flows to the node k at the moment of the distribution line t in the fault scene f;
Figure FDA0004139763670000032
the active power is the load active power of a node j at the moment t of the distribution line under the fault scene f; />
Figure FDA0004139763670000033
The reactive power is the load reactive power of a node j at the moment t of the distribution line in the fault scene f; />
Figure FDA0004139763670000034
The DG power of a node j at the moment t of the distribution line in the fault scene f; />
Figure FDA0004139763670000035
The energy storage and charging power of a node j at the moment t of the distribution line in the fault scene f; />
Figure FDA0004139763670000036
The energy storage and discharge power of a node j at the moment t of the distribution line in the fault scene f; r is (r) ij The resistance of branch ij; x is x ij Is the reactance of branch ij.
5. The method for evaluating the distributed photovoltaic bearing capacity of the distribution line based on the N-1 safety criterion according to claim 1, wherein in the step 2, the feasible regions meeting the constraint in the ith line fault scene and the constraint in the non-fault scene are obtained in parallel, and the feasible regions considering the N-1 safety constraint can be characterized as the intersection of the feasible regions in all fault scenes, and the specific flow is as follows:
(1) According to the maximum value and the minimum value in each dimension, constructing an initialized distributed photovoltaic access capacity feasible domain;
the minimum solution problem for the ith dimension:
Figure FDA0004139763670000037
S.t.
maximum solving problem for the i-th dimension:
Figure FDA0004139763670000041
S.t.
the obtained information under the non-fault scene and the fault scene
Figure FDA0004139763670000042
Is used as vertex V to construct a feasible domain omega c ；
(2) New vertex search: by shifting out the feasible region omega c Searching for new vertices; let the inequality expression of the kth boundary plane be
Figure FDA0004139763670000043
Obtaining a new vertex by solving the following linear programming problem:
Figure FDA0004139763670000044
wherein: v (V) p Is the feasible domain omega c Any point in the above;
the optimal solution of the linear programming is the top point of the constraint. Therefore, the optimal solution is the new vertex, and after all sides are translated, all the vertices are marked as V new ；
(3) Algorithm termination condition checking: calculating the difference between the feasible region volumes before and after the new vertex in the consideration (2) to be DeltaV; the smaller the delta V change, the smaller the feasible region change before and after adding the new vertex, thus, when delta V is smaller than the given threshold, the algorithm is terminated and the feasible region omega under the c-th line fault is recorded c To construct a feasible region Ω from the new vertices otherwise c Then return to (2);
when obtaining the feasible region Ω in all fault conditions c The feasible region Ω taking into account the N-1 security constraints is characterized as the feasible region Ω under all fault conditions c And (3) obtaining the carrying capacity evaluation result of the distributed photovoltaic power distribution line.
6. The method for evaluating distributed photovoltaic load-bearing capacity of power distribution lines based on N-1 safety criteria according to claim 5, wherein in step 2, confidence levels are sorted from large to small, the confidence levels are opposite to the obtained load-bearing capacity arrangement order, and after the confidence levels are selected, the corresponding distributed photovoltaic power distribution line load-bearing capacity is determined.
CN202310285711.7A 2023-03-22 2023-03-22 Distribution line distributed photovoltaic bearing capacity assessment method based on N-1 safety criterion Pending CN116316887A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118074240A (en) * 2024-04-22 2024-05-24 国网浙江省电力有限公司宁波供电公司 Maximum admittance capacity assessment method and equipment for distributed power supply
CN118157219A (en) * 2024-01-31 2024-06-07 广东电网有限责任公司 Photovoltaic access method considering feeder line absorption space and carbon reduction benefits

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118157219A (en) * 2024-01-31 2024-06-07 广东电网有限责任公司 Photovoltaic access method considering feeder line absorption space and carbon reduction benefits
CN118074240A (en) * 2024-04-22 2024-05-24 国网浙江省电力有限公司宁波供电公司 Maximum admittance capacity assessment method and equipment for distributed power supply

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