CN114552669A - Distribution network partitioning method of distributed power supply with high permeability considering flexibility - Google Patents

Distribution network partitioning method of distributed power supply with high permeability considering flexibility Download PDF

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CN114552669A
CN114552669A CN202210193972.1A CN202210193972A CN114552669A CN 114552669 A CN114552669 A CN 114552669A CN 202210193972 A CN202210193972 A CN 202210193972A CN 114552669 A CN114552669 A CN 114552669A
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毕锐
朱正轩
王孝淦
袁华凯
吴红斌
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Hefei University of Technology
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Abstract

The invention discloses a distribution network partitioning method considering flexibility and containing a high-permeability distributed power supply, which comprises the following steps: 1. respectively establishing a corresponding cluster flexibility supply model and a cluster flexibility demand model according to the regulation characteristics of the existing flexibility resources in the power distribution network and the fluctuation of the original DGs and loads; 2. providing a net load adaptation rate index describing the flexibility supply matching degree relative to the flexibility requirement in the cluster; 3. providing a branch load margin index for describing the transmission characteristics of the flexible resource output in the cluster on the space; 4. providing a module degree value index for describing the cluster structure characteristics; 5. and endowing the indexes with certain weight coefficients to form a comprehensive index of the network partition. The invention can improve the autonomous characteristic of the cluster and furthest exert the adjusting capability of the flexible resources in the cluster, thereby being beneficial to solving the problem of difficult consumption caused by insufficient flexibility in the later operation of the power distribution network planning.

Description

Distribution network partitioning method of distributed power supply with high permeability considering flexibility
Technical Field
The invention relates to the field of planning of access of a high-permeability distributed power supply to a power distribution network, in particular to a high-permeability distributed power supply-containing power distribution network partitioning method considering flexibility.
Background
The large penetration of intermittent distributed power sources such as wind power and photovoltaic power, and the increase of novel loads with uncertain altitude such as electric vehicles pose great challenges to the operation of a power distribution network, and problems such as voltage fluctuation out-of-limit, tide reverse transmission, system loss increase, DG (distributed generation) consumption level reduction, power imbalance among feeders and the like are caused. Meanwhile, a large number of distributed power supplies are connected, the complexity of the power grid is greatly increased due to the characteristics of small single-machine capacity, large number and scattered geographic positions, so that the traditional centralized management structure of the power distribution network cannot meet the requirement of controlling time scale in the operation stage, and the power distribution network has the problem of serious and insufficient flexibility in operation; on the other hand, the power supply planning problem and the operation control problem of the power distribution network affect each other, so that it is necessary to adopt a partition mode to perform power distribution network operation management after the large-scale distributed power supply is accessed.
The network partitioning of the power distribution network is carried out by taking a cluster as a basic unit, and in the power system, the cluster has the advantages of coupling and cooperation of nodes in the cluster and loose and separated work among the clusters. The application of the cluster in the power system mainly comprises two fields of dispatching control and power grid planning, and most of the current work is concentrated on dispatching control, including the fields of reactive voltage control, power grid zoning, active power control and the like. In particular to the following partitioning method: taking the space electrical distance as an index, and performing reactive voltage control partitioning on the power distribution network system by adopting an immune-central point clustering algorithm; guiding the division of the power distribution network based on the cluster modularity performance indexes of the electrical distance and the regional voltage regulation capability; cluster division is carried out based on the modularity index of the electrical distance so as to facilitate reasonable calling of energy storage adjusting resources, and therefore the voltage of the power distribution network is controlled in a partitioning mode; and constructing comprehensive performance indexes based on the electrical distance, the reactive power balance degree and the active power balance degree, and carrying out network partition by taking the power distribution network planning as an application scene.
The traditional network partition comprehensive index facing to cluster planning generally takes structure and function as principles, namely structurally satisfies the conditions that the connection in clusters is tight and the connection among the clusters is sparse, so as to be beneficial to power exchange in the clusters; functionally, intra-cluster should have source-to-source complementarity to reduce inter-cluster power exchange and promote intra-cluster consumption of DG; the network partitioning by using the indexes determined by the structural and functional principles is beneficial to solving the power balance under the static condition, but along with the superposition of high-permeability DG grid connection and multi-type loads, the operating environment of the cluster has more uncertainty and volatility, so that higher requirements are provided for the dynamic power balance capability of the cluster, namely the cluster needs to have stronger flexibility. At present, relevant researches provide corresponding flexibility supply and demand balance indexes from the perspective of climbing flexibility shortage when network partitioning is carried out, the capacity of real-time power balance in a cluster is improved to a certain extent, but the consideration is not carried out from the perspective of network side flexibility, namely the flexibility of response of flexibility resources in the cluster to net load demands on space is ignored, and the method has certain limitation.
In summary, how to solve the problems of mismatch between supply and demand and power imbalance between feeders in each cluster by considering the combination between each flexible resource node and a payload node in the coordination system and the combination between different lines, and set the flexibility index from different angles, so as to fully exert the adjusting capability of the flexible resource to improve the autonomous characteristics of the cluster are problems to be solved by those skilled in the art.
Disclosure of Invention
The invention can overcome the defects of the existing network partitioning method, and provides the distribution network partitioning method of the distributed power supply with high permeability, which considers the flexibility, so that the distribution network can be reasonably partitioned, the regulation capability of the flexibility resources in each cluster can be exerted to the maximum extent, and the problem of insufficient operation flexibility in the later period of the distribution network planning under the background of high permeability DG grid connection and various types of loads can be solved.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention relates to a distribution network partitioning method considering flexibility and containing high-permeability distributed power supplies, which is characterized by comprising the following steps of:
a: establishing a corresponding cluster flexibility supply model and a cluster flexibility demand model;
a1: suppose an adjustable unit G at the ith nodeiAnd an energy storage element ESiAt time t, the output and the charge-discharge power are respectively
Figure BDA0003526204880000021
Then the total flexibility up-regulation capability of all the flexibility resources in the c-th cluster at the moment t is obtained by using the formulas (1-1) and (1-2)
Figure BDA0003526204880000022
And down regulation ability
Figure BDA0003526204880000023
Figure BDA0003526204880000024
Figure BDA0003526204880000025
In the formulae (1-1) and (1-2),
Figure BDA0003526204880000026
respectively representing adjustable units G at ith nodeiThe active maximum and minimum output and the upper and lower climbing speed limit values;
Figure BDA0003526204880000027
representing a node set which is connected into an adjustable unit G in the c cluster; τ represents a response time scale;
Figure BDA0003526204880000028
respectively representing the maximum charging and discharging power of the stored energy at the ith node;
Figure BDA0003526204880000029
representing a node set of an access energy storage element ES in the c-th cluster;
Figure BDA00035262048800000210
when positive, the energy storage element ES of the i-th node is showniDischarging, when negative, the energy storage element ES of the i-th nodeiCharging; wherein,
Figure BDA00035262048800000211
energy storage element ES as the ith nodeiMaximum capacity of installation;
a2: respectively obtaining quantitative indexes of net loads in the c-th cluster at the t moment by using the formulas (1-3) and (1-4)
Figure BDA00035262048800000212
And quantitative indicators of flexibility requirements
Figure BDA00035262048800000213
Figure BDA00035262048800000214
Figure BDA00035262048800000215
In the formulae (1-3) and (1-4),
Figure BDA0003526204880000031
and
Figure BDA0003526204880000032
respectively representing photovoltaic, wind power original output and load active data of the ith node at the time t;
Figure BDA0003526204880000033
the net load of the c-th cluster at the time t and the time t +1 respectively;
Figure BDA0003526204880000034
the number of load nodes in the c cluster;
b: constructing a net load adaptability index, a branch load margin index and a module value index, and giving a certain weight coefficient to form a comprehensive index of a network partition;
b1: constructing a net load adaptability index of the c-th cluster in the t period by using the formula (1-5)
Figure BDA0003526204880000035
Figure BDA0003526204880000036
In the formula (1-5); sigma represents the upper limit of the ratio of the total flexible resource adjustment capacity in the cluster relative to the net load demand;
Figure BDA0003526204880000037
represents the comprehensive adjusting capacity of the c-th cluster in the t period corresponding to the actual change direction of the flexibility requirement, and is represented by the following formulas (1-6):
Figure BDA0003526204880000038
in the formula (1-6), NcDividing the number of clusters;
within the planning period T, the net load adaptation rate index is subjected to by using the formula (1-7)
Figure BDA0003526204880000039
Performing per unit valuation to obtain the comprehensive net load adaptability index L of the whole distribution networkAR：
Figure BDA00035262048800000310
B2: the branch load margin index of the c-th cluster at the time t is constructed by using the formula (1-8)
Figure BDA00035262048800000311
Figure BDA00035262048800000312
In the formula (1-8), ImaxFor the branch carrying the maximum value of the current, Iij,tThe transmission current of a line between the ith node and the jth node at the time t;
Figure BDA00035262048800000313
the number of branches in the c cluster;
in a planning period T, the branch load margin index is indicated by using the formula (1-7)
Figure BDA00035262048800000314
Performing per unit value to obtain a comprehensive branch load margin index H of the whole distribution networkBM：
Figure BDA00035262048800000315
B3: the modularity index ρ is constructed by using the formula (1-10):
Figure BDA00035262048800000316
in the formula (1-10), Ai,jIs the weight of the edge between the ith node and the jth node and is represented by the formula (1-11)) Obtaining; n is a node set in the power distribution network; k is a radical ofi＝∑j∈NAi,jIs the sum of the weights of all edges connected with the ith node; k is a radical ofj＝∑i∈NAi,jIs the sum of the weights of all edges connected to the jth node; m ═ sigma (∑)i∈N∑j∈NAi,j) The/2 represents the sum of the weights of all edges connected with the nodes in the power distribution network; sigma (i, j) is an optimization variable of the partitioning problem, if sigma (i, j) is 1, the ith node and the jth node are located in the same region, otherwise, the ith node and the jth node are not located in the same region;
Ai,j＝1-Lij/max(L) (1-11)
in the formula (1-11), dijThe ratio of the voltage change value of the jth node to the voltage change value of the ith node after unit reactive power is injected into the jth node is represented; l isijThe spatial electrical distance between the ith node and the jth node, which is considered to be influenced by all the nodes, is obtained by the formula (1-12); max (L) represents the maximum value of the elements in the electrical distance matrix L;
Figure BDA0003526204880000041
b4: and (3) constructing a comprehensive index gamma of the network partition by using the formula (1-13):
max γ＝λ1ρ+λ2LAR+λ3HBM (1-13)
in the formula (1-13), λ1、λ2、λ3A module degree value index rho and a net load adaptability index L which respectively correspond to the network partitionsARAnd branch load margin index HBMThe weight of (c);
c: taking the comprehensive division index gamma as an optimization target of the improved FN algorithm and calculating to obtain an optimal division result;
c1: initializing network partitions, regarding each node in a power distribution network to be partitioned as an independent cluster, and calculating an initial value rho of a modularity index0Let the real-time value of the modularity of the distribution network be rhonewAnd initializes rhonew＝ρ0(ii) a The real-time value of the comprehensive index of the distribution network partition is gammanewAnd initializing gammanew＝0；
C2: according to the cluster division condition in the current power distribution network, calculating a modularity increment matrix delta rho 'under various cluster combination conditions before each combination to obtain a corresponding modularity value matrix rho' ═ rhonew+Δρ'；
C3: before any ith independent cluster and jth independent cluster in the power distribution network are combined, whether a node between the ith independent cluster and the jth independent cluster forms a branch is judged, if yes, the ith independent cluster and the jth independent cluster are combined, and the net load adaptability index after combination is calculated
Figure BDA0003526204880000042
And branch load margin index
Figure BDA0003526204880000043
Otherwise, combining the ith independent cluster and the jth independent cluster to obtain the net load adaptability index
Figure BDA0003526204880000044
And branch load margin index
Figure BDA0003526204880000045
Recording as zero, thereby completing the combination judgment and calculation of all clusters, and obtaining the comprehensive index value judgment matrix gamma' ═ lambda after all combination conditions are considered1ρ'+λ2LAR'+λ3HBM'(ii) a Wherein L isAR’、HBM'Respectively representing a matrix formed by each net load adaptability index and a matrix formed by each branch load margin index under the condition that all nodes in the power distribution network are combined;
c4: selecting two clusters corresponding to the maximum value in the comprehensive index value judgment matrix gamma' in the step C3 to merge, and calculating the net load adaptability index of the merged clusters
Figure BDA0003526204880000051
Branch load margin index
Figure BDA0003526204880000052
And modularity index value rho'maxTo obtain a total index γ 'of the merged clusters'max；
C5: prepared from rho'maxIs assigned to rhonewPrepared from gamma'maxAssigned to gammanewThen, the sequence returns to the step C2 to be executed until gammanewNo longer increased, and thus an optimal partitioning result is obtained.
Compared with the prior art, the invention has the following advantages:
1. the invention establishes a network partition comprehensive index considering flexibility and structural characteristics, on one hand, improves the matching degree of the flexibility resource adjustment margin in a cluster relative to the flexibility requirement, on the other hand, provides spatial flexibility for the flexibility resource to respond to the net load fluctuation output, furthest exerts the adjustment capability of the flexibility resource in the cluster, improves the autonomous characteristic of the cluster, and is beneficial to solving the problem of difficult consumption caused by insufficient operation flexibility in the later period of power distribution network planning under the complex background of high-permeability DG grid connection and multi-type loads.
2. The invention provides branch load margin indexes for the space dimension of flexibility, provides flexible transmission channels for the flexible resource response net load output, ensures the balance of the distribution of the flexible resource power in the cluster among all the feeders, and further solves the problem of insufficient operation flexibility in the later period of cluster planning.
3. Aiming at the defects of the traditional FN algorithm, the improved FN algorithm is provided, and the judgment module of the connectivity condition of the nodes among the clusters to be merged is added into the algorithm, so that the unnecessary combination calculation process is reduced, the searching efficiency of the algorithm in optimization searching is improved, and the accurate and efficient partition process is ensured when the comprehensive division index of the method is used as the optimization target of the improved FN algorithm.
Drawings
Fig. 1 is a flow chart of the steps of a method for partitioning a distribution network including high-permeability distributed power sources in accordance with the present invention, which allows for flexibility.
Fig. 2 is a flow chart of the present invention for partitioning a power distribution network using the modified FN algorithm.
Detailed Description
The invention is further illustrated by the following figures and examples, which are not to be construed as limiting the invention.
Example (b): the method for partitioning the power distribution network with the high permeability considering the flexibility is based on the source side and the network side, sets related flexibility indexes, and combines the coupling characteristics inside the cluster to realize reasonable partitioning of the power distribution network, specifically, as shown in fig. 1, and is performed according to the following steps:
a: and respectively establishing a corresponding cluster flexibility supply model and a cluster flexibility demand model according to the regulation characteristics of the existing flexibility resources in the network and the fluctuation of the original DGs and loads.
The cluster flexibility supply and demand model is as follows:
a1: according to the existing research on the supply characteristics of various flexible resources, and the consideration of main flexible resources in the network before planning, the main flexible resources are adjustable conventional units and energy storage elements. Suppose an adjustable unit G at the ith nodeiAnd an energy storage element ESiAt time t, the output and the charge-discharge power are respectively
Figure BDA0003526204880000061
Then the total flexibility up-regulation capability of all the flexibility resources in the c-th cluster at the moment t is obtained by using the formulas (1-1) and (1-2)
Figure BDA0003526204880000062
And down regulation ability
Figure BDA0003526204880000063
Figure BDA0003526204880000064
Figure BDA0003526204880000065
In the formulae (1-1) and (1-2),
Figure BDA0003526204880000066
respectively representing adjustable units G at ith nodeiThe active maximum and minimum output and the upper and lower climbing speed limit values;
Figure BDA0003526204880000067
representing a node set which is connected into an adjustable unit G in the c cluster; τ represents a response time scale;
Figure BDA0003526204880000068
respectively representing the maximum charging and discharging power of the stored energy at the ith node;
Figure BDA0003526204880000069
representing a node set of an access energy storage element ES in the c-th cluster;
Figure BDA00035262048800000610
when positive, the energy storage element ES of the i-th node is showniDischarging, when negative, the energy storage element ES of the ith node is showniCharging; wherein,
Figure BDA00035262048800000611
energy storage element ES as the ith nodeiMaximum capacity of installation;
a2: flexibility requirements within the cluster. The cluster flexibility requirement comes from the fluctuation and randomness of the original DG and the load, and the quantized indexes of the net load in the c-th cluster at the t moment are respectively obtained by using the formulas (1-3) and (1-4)
Figure BDA00035262048800000612
And quantitative indicators of flexibility requirements
Figure BDA00035262048800000613
Figure BDA00035262048800000614
Figure BDA00035262048800000615
In the formulae (1-3) and (1-4),
Figure BDA00035262048800000616
and
Figure BDA00035262048800000617
respectively representing photovoltaic, wind power original output and load active data of the ith node at the time t;
Figure BDA00035262048800000618
the net load of the c-th cluster at the time t and the time t +1 respectively;
Figure BDA00035262048800000619
the number of load nodes in the c cluster;
b: based on two aspects of source side flexibility and network side flexibility, a net load adaptability index for describing flexibility supply matching degree relative to flexibility requirement in a cluster, a branch load margin index for describing transmission characteristics of flexibility resource output in the cluster on space, and a module value index for describing cluster structure characteristics are provided, and a certain weight coefficient is given to form a comprehensive index of network partitions.
B1: constructing a net load adaptability index of the c-th cluster in the t period by using the formula (1-5)
Figure BDA00035262048800000620
Figure BDA00035262048800000621
In the formula (1-5), sigma represents the upper limit of the ratio of the total flexible resource adjusting capacity in the cluster relative to the net load demand;
Figure BDA0003526204880000071
represents the comprehensive adjusting capacity of the c-th cluster in the t period corresponding to the actual change direction of the flexibility requirement, and is represented by the following formulas (1-6):
Figure BDA0003526204880000072
in the formula (1-6), NcDividing the number of clusters;
within the planning period T, the net load adaptation rate index is obtained by using the formula (1-7)
Figure BDA0003526204880000073
Performing per unit valuation to obtain the comprehensive net load adaptability index L of the whole distribution networkAR：
Figure BDA0003526204880000074
In the formula (1-7), LARThe net load adaptation rate index of the whole system is obtained; t is a planning period;
Figure BDA0003526204880000075
representing the maximum value of the payload adaptation rate in all clusters during the whole period.
B2: the branch load margin index of the c-th cluster at the time t is constructed by using the formula (1-8)
Figure BDA0003526204880000076
Figure BDA0003526204880000077
In the formula (1-8), ImaxFor the branch carrying the maximum value of the current, Iij,tThe transmission current of a line between the ith node and the jth node at the time t;
Figure BDA0003526204880000078
the number of branches in the c cluster;
in a planning period T, the branch load margin index is indicated by using the formula (1-9)
Figure BDA0003526204880000079
Performing per unit value to obtain a comprehensive branch load margin index H of the whole distribution networkBM：
Figure BDA00035262048800000710
B3: the modularity index ρ is constructed by using the formula (1-10):
Figure BDA00035262048800000711
in the formula (1-10), Ai,jThe weight of the edge between the ith node and the jth node is obtained by the formula (1-11); n is a node set in the power distribution network; k is a radical ofi＝∑j∈NAi,jIs the sum of the weights of all edges connected with the ith node; k is a radical ofj＝∑i∈NAi,jIs the sum of the weights of all edges connected to the jth node; m ═ Σi∈N∑j∈NAi,j) The/2 represents the sum of the weights of all edges connected with the nodes in the power distribution network; sigma (i, j) is an optimization variable of the partitioning problem, if sigma (i, j) is 1, the ith node and the jth node are in the same region, otherwise, the ith node and the jth node are not in the same region;
Ai,j＝1-Lij/max(L) (1-11)
network edge weight Ai,jSpace-based electrical distance representationThe spatial electrical distance is used for measuring the closeness degree of electrical connection between two nodes influenced by other nodes in an n-dimensional space, and is generally obtained by a reactive sensitivity relationship, wherein the expression is as follows:
ΔV＝SQV*ΔQ (1-12)
in the formulae (1-12): sQVTo take into account the reactive sensitivity matrix of the line active effects, Δ V, Δ Q represent the voltage and reactive values, respectively.
In the formula (1-11), dijThe ratio of the voltage change value of the jth node to the voltage change value of the ith node after unit reactive power is injected into the jth node is expressed and obtained by the formula (1-14); l isijThe spatial electrical distance between the ith node and the jth node, which is considered to be influenced by all the nodes, is obtained by the formula (1-13); max (L) represents the maximum value of the elements in the electrical distance matrix L;
Figure BDA0003526204880000081
Figure BDA0003526204880000082
b4: and (3) constructing a comprehensive index gamma of the network partition by using the formula (1-15):
max γ＝λ1ρ+λ2LAR+λ3HBM (1-15)
in the formula (1-15), lambda1、λ2、λ3A module degree value index rho and a net load adaptability index L which respectively correspond to the network partitionsARAnd branch load margin index HBMThe weight of (c);
c: an improved FN algorithm is provided, a judgment module for judging the connectivity condition of nodes between clusters to be merged is added, the comprehensive division index is used as an optimization target of the algorithm, and an optimal partition result is obtained through calculation, specifically, as shown in FIG. 2, the method comprises the following steps:
c1: initializing network partition and distributing network to be partitionedEach node in the network is regarded as an independent cluster, and the initial value rho of the modularity index is calculated0Let the real-time value of the modularity of the distribution network be rhonewAnd initializes rhonew＝ρ0(ii) a The real-time value of the comprehensive index of the distribution network partition is gammanewAnd initializing gammanew＝0；
C2: according to the cluster division condition in the current power distribution network, calculating a modularity increment matrix delta rho 'under various cluster combination conditions before each combination to obtain a corresponding modularity value matrix rho' ═ rhonew+Δρ'；
C3: before any ith independent cluster and jth independent cluster in the power distribution network are combined, whether a node between the ith independent cluster and the jth independent cluster forms a branch is judged, if yes, the ith independent cluster and the jth independent cluster are combined, and the net load adaptability index after combination is calculated
Figure BDA0003526204880000083
And branch load margin index
Figure BDA0003526204880000084
Otherwise, combining the ith independent cluster and the jth independent cluster to obtain the net load adaptability index
Figure BDA0003526204880000085
And branch load margin index
Figure BDA0003526204880000086
Recording as zero, thereby completing the combination judgment and calculation of all clusters, and obtaining the comprehensive index value judgment matrix gamma' ═ lambda after all combination conditions are considered1ρ'+λ2LAR'+λ3HBM'(ii) a Wherein L isAR’、HBM'Respectively representing matrixes formed by each net load adaptation rate index value and each branch load margin index value under the condition that all nodes in the power distribution network are combined;
c4: the maximum value in the comprehensive index value judgment matrix gamma' in the selection step C3Merging the two clusters corresponding to the value, and calculating the net load adaptability index of the merged cluster
Figure BDA0003526204880000091
Branch load margin index
Figure BDA0003526204880000092
And modularity index value rho'maxTo obtain a total index γ 'of the merged clusters'max；
C5: prepared from rho'maxIs assigned to rhonewPrepared from gamma'maxAssigned to gammanewThen, the sequence returns to the step C2 to be executed until gammanewNo longer increasing, thus obtaining the optimal partitioning result.

Claims (1)

1. A distribution network partitioning method considering flexibility and comprising high-permeability distributed power supplies is characterized by comprising the following steps:
a: establishing a corresponding cluster flexibility supply model and a cluster flexibility demand model;
a1: suppose an adjustable unit G at the ith nodeiAnd an energy storage element ESiAt time t, the output and the charge-discharge power are respectively
Figure FDA0003526204870000011
Then the total flexibility up-regulation capability of all the flexibility resources in the c-th cluster at the moment t is obtained by using the formulas (1-1) and (1-2)
Figure FDA0003526204870000012
And down regulation ability
Figure FDA0003526204870000013
Figure FDA0003526204870000014
Figure FDA0003526204870000015
In the formulae (1-1) and (1-2),
Figure FDA0003526204870000016
respectively representing adjustable units G at ith nodeiThe active maximum and minimum output and the upper and lower climbing speed limit values;
Figure FDA0003526204870000017
representing a node set which is connected into an adjustable unit G in the c cluster; τ represents a response time scale;
Figure FDA0003526204870000018
respectively representing the maximum charging and discharging power of the stored energy at the ith node;
Figure FDA0003526204870000019
representing a node set of an access energy storage element ES in the c-th cluster;
Figure FDA00035262048700000110
when positive, the energy storage element ES of the i-th node is showniDischarging, when negative, the energy storage element ES of the i-th nodeiCharging; wherein,
Figure FDA00035262048700000111
Figure FDA00035262048700000112
energy storage element ES as the ith nodeiMaximum capacity of installation;
a2: respectively obtaining quantitative indexes of net loads in the c-th cluster at the t moment by using the formulas (1-3) and (1-4)
Figure FDA00035262048700000113
And quantitative indicators of flexibility requirements
Figure FDA00035262048700000114
Figure FDA00035262048700000115
Figure FDA00035262048700000116
In the formulae (1-3) and (1-4),
Figure FDA00035262048700000117
and
Figure FDA00035262048700000118
respectively representing photovoltaic, wind power original output and load active data of the ith node at the time t;
Figure FDA00035262048700000119
the net load of the c-th cluster at the time t and the time t +1 respectively;
Figure FDA00035262048700000120
the number of load nodes in the c cluster is counted;
b: constructing a net load adaptability index, a branch load margin index and a module value index, and giving a certain weight coefficient to form a comprehensive index of a network partition;
b1: constructing a net load adaptability index of the c-th cluster in the t period by using the formula (1-5)
Figure FDA00035262048700000121
Figure FDA0003526204870000021
In the formula (1-5); sigma represents the upper limit of the ratio of the total flexible resource adjustment capacity in the cluster relative to the net load demand;
Figure FDA0003526204870000022
represents the comprehensive adjusting capacity of the c-th cluster in the t period corresponding to the actual change direction of the flexibility requirement, and is represented by the following formulas (1-6):
Figure FDA0003526204870000023
in the formula (1-6), NcDividing the number of clusters;
within the planning period T, the net load adaptation rate index is subjected to by using the formula (1-7)
Figure FDA0003526204870000024
Performing per unit value to obtain a comprehensive net load adaptability index L of the whole distribution networkAR：
Figure FDA0003526204870000025
B2: the branch load margin index of the c-th cluster at the time t is constructed by using the formula (1-8)
Figure FDA0003526204870000026
Figure FDA0003526204870000027
In the formula (1-8), ImaxFor the branch carrying the maximum value of the current, Iij,tThe transmission current of a line between the ith node and the jth node at the time t;
Figure FDA0003526204870000028
the number of branches in the c cluster;
in a planning period T, the indexes of branch load margins are measured by using the formulas (1-7)
Figure FDA0003526204870000029
Performing per unit valuation to obtain a comprehensive branch load margin index H of the whole distribution networkBM：
Figure FDA00035262048700000210
B3: the modularity index ρ is constructed by using the formula (1-10):
Figure FDA00035262048700000211
in the formula (1-10), Ai,jThe weight of the edge between the ith node and the jth node is obtained by the formula (1-11); n is a node set in the power distribution network; k is a radical ofi＝∑j∈NAi，jIs the sum of the weights of all edges connected with the ith node; k is a radical ofj＝∑i∈NAi，jIs the sum of the weights of all edges connected to the jth node; m ═ Σi∈N∑j∈NAi，j) The/2 represents the sum of the weights of all edges connected with the nodes in the power distribution network; sigma (i, j) is an optimization variable of the partitioning problem, if sigma (i, j) is 1, the ith node and the jth node are located in the same region, otherwise, the ith node and the jth node are not located in the same region;
Ai，j＝l-Lij/max(L) (1-11)
in the formula (1-11), dijThe ratio of the voltage change value of the jth node to the voltage change value of the ith node after unit reactive power is injected into the jth node is represented; l isijThe spatial electrical distance between the ith node and the jth node for considering the influence of all the nodes is obtained by the formula (1-12)(ii) a max (L) represents the maximum value of the elements in the electrical distance matrix L;
Figure FDA0003526204870000031
b4: and (3) constructing a comprehensive index gamma of the network partition by using the formula (1-13):
max γ＝λ1ρ+λ2LAR+λ3HBM (1-13)
in the formula (1-13), lambda1、λ2、λ3The modularity value index rho and the net load adaptability index L respectively correspond to the network partitionsARAnd branch load margin index HBMThe weight of (c);
c: taking the comprehensive division index gamma as an optimization target of the improved FN algorithm and calculating to obtain an optimal division result;
c1: initializing network partitions, regarding each node in a power distribution network to be partitioned as an independent cluster, and calculating an initial value rho of a modularity index0Let the real-time value of the modularity of the distribution network be rhonewAnd initializing rhonew＝ρ0(ii) a The real-time value of the comprehensive index of the distribution network partition is gammanewAnd initializing gammanew＝0；
C2: according to the cluster division condition in the current power distribution network, calculating a modularity increment matrix delta rho 'under various cluster combination conditions before each combination to obtain a corresponding modularity value matrix rho' ═ rhonew+△ρ′；
C3: before any ith independent cluster and jth independent cluster in the power distribution network are combined, whether a node between the ith independent cluster and the jth independent cluster forms a branch is judged, if yes, the ith independent cluster and the jth independent cluster are combined, and the net load adaptability index after combination is calculated
Figure FDA0003526204870000032
And branch load margin index
Figure FDA0003526204870000033
Otherwise, combining the ith independent cluster and the jth independent cluster to obtain the net load adaptability index
Figure FDA0003526204870000034
And branch load margin index
Figure FDA0003526204870000035
Recording as zero, thereby completing the combination judgment and calculation of all clusters, and obtaining the comprehensive index value judgment matrix gamma' ═ lambda after all combination conditions are considered1ρ′+λ2LAR′+λ3HBM′(ii) a Wherein L isAR′、HBM′Respectively representing a matrix formed by each net load adaptability index and a matrix formed by each branch load margin index under the condition that all nodes in the power distribution network are combined;
c4: selecting two clusters corresponding to the maximum value in the comprehensive index value judgment matrix gamma' in the step C3 to merge, and calculating the net load adaptability index of the merged clusters
Figure FDA0003526204870000036
Branch load margin index
Figure FDA0003526204870000037
And modularity index value rho'maxTo obtain a total index γ 'of the merged clusters'max；
C5: prepared from rho'maxIs assigned to rhonewPrepared from gamma'maxAssigned to gammanewThen, the sequence returns to the step C2 to be executed until gammanewNo longer increasing, thus obtaining the optimal partitioning result.
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