CN115146872A - Flexible aggregation method, device, equipment and medium for adjustable resources in power distribution network - Google Patents

Flexible aggregation method, device, equipment and medium for adjustable resources in power distribution network Download PDF

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CN115146872A
CN115146872A CN202210903140.4A CN202210903140A CN115146872A CN 115146872 A CN115146872 A CN 115146872A CN 202210903140 A CN202210903140 A CN 202210903140A CN 115146872 A CN115146872 A CN 115146872A
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胡泽春
文艺林
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Abstract

The application relates to the technical field of flexible resource aggregation, in particular to a flexible aggregation method, a device, equipment and a medium for adjustable resources in a power distribution network, wherein the method comprises the following steps: determining flexible resources on each node in the power distribution network; constructing a feasible region aggregation model of the power distribution network according to preset safety constraint conditions of the power distribution network and flexible resources on each node; and calculating at least one safety constraint parameter of the feasible region aggregation model according to the expected target of the linear power flow constraint, and optimizing the feasible region aggregation model based on the at least one safety constraint parameter so as to perform linear power flow safety constraint on the power distribution network by using the optimized feasible region aggregation model. Therefore, the problems that the aggregation feasible domain of the flexible resources in the distribution network is not comprehensively considered, the flexibility of the flexible resources cannot be utilized to the maximum extent, the economical efficiency and the safety of the operation of the whole network are reduced, and the like in the related technology are solved.

Description

Flexible aggregation method, device, equipment and medium for adjustable resources in power distribution network
Technical Field
The present application relates to the field of flexible resource aggregation technologies, and in particular, to a flexible aggregation method, apparatus, device, and medium for adjustable resources in a power distribution network.
Background
The high proportion infiltration of intermittent renewable energy sources such as wind power, photovoltaic and the like increases the demand on the regulation capacity of the power grid, and under the background, the power grid can not rely on the regulation function of the traditional unit any more, and the regulation capacity of flexible resources on the demand side is brought into play. Some typical demand side flexible resources include distributed power generation, electric vehicles, distributed energy storage, thermal control loads, and the like. The demand side flexible resources participate in power grid regulation and control, safe and stable operation of the power grid can be guaranteed, new energy consumption is promoted, and the power utilization cost of users is reduced. Because parameters of all demand side resources are considered to be too complex during power grid dispatching and are not beneficial to protecting the privacy of power users, the demand side flexible resources need to be aggregated and then participate in power grid regulation and control. In this mode, firstly, the flexible resource aggregator submits the feasible region of the total power to the distribution network operator, and the distribution network operator considers the feasible regions reported by all aggregators in the jurisdiction range of the distribution network operator and the safety constraint of the distribution network, and reports the feasible region of the total power of the distribution network obtained by calculation to the main network operator. After the closeout or scheduling calculation is completed, the total power of each distribution network is determined, and the total power is executed after being distributed to each flexible resource layer by layer. Therefore, it is necessary to accurately construct an aggregate flexibility model of flexible resources in a distribution network to ensure smooth distribution without causing excessive computational complexity.
The current market rules are simple to consider for the flexible resource aggregation feasible domain in the distribution network. For example, the PJM power line market is a top and bottom regulatory boundary that only considers power. In the north China market, power and energy capacity are considered for energy storage and V2G charging piles, and only power regulation capacity is considered for controllable loads such as common charging piles and electric heating. These methods generally describe feasible regions that are far from the actual aggregate feasible region. The existing literature has agreed on the aggregation feasible region of flexible resources in a computational distribution network, that is, the problem of projection of minkowski or minkowski for high-dimensional spatial polyhedron is solved, and no efficient algorithm is generally available. Research in the existing literature often focuses on approximating this feasible domain from inside or outside, and there are no modeling methods and calculation methods that accurately aggregate feasible domains.
Disclosure of Invention
The application provides a flexible aggregation method, a device, equipment and a medium for adjustable resources in a power distribution network, and aims to solve the problems that the current market rules are not comprehensive in consideration of the aggregation feasible region of the flexible resources in the power distribution network, the flexibility of the flexible resources cannot be utilized to the maximum extent, the economy and the safety of the whole network operation are reduced, and the like.
An embodiment of a first aspect of the present application provides a method for flexible aggregation of tunable resources in a power distribution network, including the following steps: determining flexible resources on each node in the power distribution network; constructing a feasible region aggregation model of the power distribution network according to preset safety constraint conditions of the power distribution network and flexible resources on each node; calculating at least one safety constraint parameter of the feasible region aggregation model according to an expected target of linear power flow constraint, and optimizing the feasible region aggregation model based on the at least one safety constraint parameter so as to perform linear power flow safety constraint on the power distribution network by using the optimized feasible region aggregation model.
Optionally, in an embodiment of the present application, the constructing a feasible domain aggregation model of the power distribution network according to preset security constraints of the power distribution network and flexible resources on each node includes: dividing a preset time window into a plurality of time periods according to a preset time interval; constructing an aggregation feasible region of the flexible resources on each node according to the boundary parameters of the flexible resources on each node in each time period; and aggregating the aggregated feasible region of the flexible resources on each node according to a preset distribution network safety constraint and a preset linear distribution network power flow equation to obtain a feasible region aggregation model of the distribution network.
Optionally, in an embodiment of the present application, the expression formula of the feasible domain aggregation model is:
Figure BDA0003771621950000021
wherein X 0 Representing the feasible domain aggregation model, t is a time period index,
Figure BDA0003771621950000022
representing the set of all time periods, T representing the total number of time periods,
Figure BDA0003771621950000023
representing the active power at the root node,
Figure BDA0003771621950000024
is that
Figure BDA0003771621950000025
Any subset of the number of the first and second subsets of,
Figure BDA0003771621950000026
and
Figure BDA0003771621950000027
respectively representing power
Figure BDA0003771621950000028
Set of time periods
Figure BDA0003771621950000029
The upper and lower bounds of the upper integral, the superscript n representing the node power,
Figure BDA00037716219500000210
is represented by
Figure BDA00037716219500000211
And forming a T-dimensional column vector.
Optionally, in one embodiment of the present application, the desired targets of the linear power flow constraint include a first linear power flow constraint target and a second linear power flow constraint target.
Optionally, in an embodiment of the present application, when the desired target of the linear power flow constraint is the first linear power flow constraint target, the calculating at least one safety constraint parameter of the feasible domain aggregation model according to the desired target of the linear power flow constraint, and optimizing the feasible domain aggregation model based on the at least one safety constraint parameter includes:
all the feasible domains of all the variables in the distribution network are converted into
Figure BDA00037716219500000212
Where n is the number of the variable, x n,t Is the value of the nth variable in the power flow equation in the time period t, x n Is represented by x n,t Forming a T-dimensional column vector;
for a target set
Figure BDA00037716219500000213
Is not empty
Figure BDA00037716219500000214
So that
Figure BDA00037716219500000215
Figure BDA00037716219500000216
And (3) satisfying the constraint:
Figure BDA00037716219500000217
and current constraints
Figure BDA00037716219500000218
Where m is the number of the equation, a m,n Is x n,t Coefficients in the m-th equation;
calculating security constraint parameters according to a first optimization formula
Figure BDA00037716219500000219
And
Figure BDA00037716219500000220
the first optimization formula is as follows:
Figure BDA0003771621950000031
wherein,
Figure BDA0003771621950000032
is that
Figure BDA0003771621950000033
The minimum value of (a) is calculated,
Figure BDA0003771621950000034
is that
Figure BDA0003771621950000035
S.t. represents a constraint condition;
according to the safety constraint parameters
Figure BDA0003771621950000036
And
Figure BDA0003771621950000037
optimizing the feasible region aggregation model.
Optionally, in an embodiment of the present application, when the desired target of the linear power flow constraint is the second linear power flow constraint target, the calculating at least one safety constraint parameter of the feasible domain aggregation model according to the desired target of the linear power flow constraint, and optimizing the feasible domain aggregation model based on the at least one safety constraint parameter includes:
calculating the distribution network power flow constraint described by the power flow transfer distribution factor according to the following formula:
Figure BDA0003771621950000038
Figure BDA0003771621950000039
Figure BDA00037716219500000310
Figure BDA00037716219500000311
Figure BDA00037716219500000312
wherein,
Figure BDA00037716219500000313
is the active increment of branch i over time period t,
Figure BDA00037716219500000314
is the active increment of the node i,
Figure BDA00037716219500000315
is the reference power of the branch l,
Figure BDA00037716219500000316
is the reference power of node i, s l,i Is the power flow transfer distribution factor of branch i with respect to node i, meaning that the power of node i is increased by 1 unit so that the power of branch i is increased by an increment,
Figure BDA00037716219500000317
is the set of all nodes in the distribution network,
Figure BDA00037716219500000318
is the set of nodes after the balancing nodes are removed,
Figure BDA00037716219500000319
is a collection of nodes that contains a flexible resource aggregator,
Figure BDA00037716219500000320
is a collection of distribution network branches and,
Figure BDA00037716219500000321
and
Figure BDA00037716219500000322
are respectively composed of
Figure BDA00037716219500000323
And
Figure BDA00037716219500000324
the formed T-dimensional column vector is then,
Figure BDA00037716219500000325
representing a power feasible domain at a flexible resource aggregator node;
according to the distribution network power flow constraint described by the power flow transfer distribution factor, continuously correcting a feasible region from a leaf node along a road to a root node according to the transmission capacity of a branch to obtain a safety constraint parameter, wherein each correction is compared and summed; optimizing the feasible domain aggregation model based on the security constraint parameters.
An embodiment of a second aspect of the present application provides a flexible aggregation device for adjustable resources in a power distribution network, including: the determining module is used for determining flexible resources on each node in the power distribution network; the construction module is used for constructing a feasible region aggregation model of the power distribution network according to preset safety constraint conditions of the power distribution network and flexible resources on each node; and the constraint module is used for calculating at least one safety constraint parameter of the feasible region aggregation model according to an expected target of linear power flow constraint, and optimizing the feasible region aggregation model based on the at least one safety constraint parameter so as to perform linear power flow safety constraint on the power distribution network by using the optimized feasible region aggregation model.
Optionally, in an embodiment of the present application, the constructing module is further configured to divide a preset time window into a plurality of time periods according to a preset time interval, and construct an aggregation feasible region of the flexible resources on each node according to a boundary parameter of the flexible resources on each node in each time period; and aggregating the aggregated feasible region of the flexible resources on each node according to a preset distribution network safety constraint and a preset linear distribution network power flow equation to obtain a feasible region aggregation model of the distribution network.
Optionally, in an embodiment of the present application, the expression formula of the feasible domain aggregation model is:
Figure BDA0003771621950000041
wherein, X 0 Representing the feasible domain aggregation model, t is a time period index,
Figure BDA0003771621950000042
representing the set of all time periods, T representing the total number of time periods,
Figure BDA0003771621950000043
representing the active power at the root node,
Figure BDA0003771621950000044
is that
Figure BDA0003771621950000045
Any subset of the number of the first and second subsets of,
Figure BDA0003771621950000046
and
Figure BDA0003771621950000047
respectively representing power
Figure BDA0003771621950000048
Set of time periods
Figure BDA0003771621950000049
The upper and lower bounds of the upper integral, the superscript n representing the node power,
Figure BDA00037716219500000410
is represented by
Figure BDA00037716219500000411
And forming a T-dimensional column vector.
Optionally, in one embodiment of the present application, the desired targets of the linear power flow constraint include a first linear power flow constraint target and a second linear power flow constraint target.
Optionally, in an embodiment of the present application, when the desired target of the linear power flow constraint is the first linear power flow constraint target, the constraint module further comprisesOne step of converting all the feasible domains of all the variables in the distribution network into
Figure BDA00037716219500000412
Wherein x is n,t Is the value of the nth variable in the power flow equation in the time period t, x n Is represented by x n,t A constructed T-dimensional column vector;
for a target set
Figure BDA00037716219500000413
Is not an empty subset of
Figure BDA00037716219500000414
So that
Figure BDA00037716219500000415
Figure BDA00037716219500000416
And satisfying the constraint:
Figure BDA00037716219500000417
and flow constraints
Figure BDA00037716219500000418
Where m is the number of the equation, a m,n Is x n,t Coefficients in the mth equation;
calculating security constraint parameters according to a first optimization formula
Figure BDA00037716219500000419
And
Figure BDA00037716219500000420
the first optimization formula is as follows:
Figure BDA00037716219500000421
wherein,
Figure BDA00037716219500000422
is that
Figure BDA00037716219500000423
The minimum value of (a) is determined,
Figure BDA00037716219500000424
is that
Figure BDA00037716219500000425
S.t. represents a constraint;
according to the safety constraint parameters
Figure BDA00037716219500000426
And
Figure BDA00037716219500000427
optimizing the feasible domain aggregation model.
Optionally, in an embodiment of the present application, when the desired target of the linear power flow constraint is the second linear power flow constraint target, the constraint module is further configured to calculate a distribution network power flow constraint described by the power flow transfer distribution factor according to the following formula:
Figure BDA0003771621950000051
Figure BDA0003771621950000052
Figure BDA0003771621950000053
Figure BDA0003771621950000054
Figure BDA0003771621950000055
wherein,
Figure BDA0003771621950000056
is the active increment of branch i over time period t,
Figure BDA0003771621950000057
is the active increment of the node i,
Figure BDA0003771621950000058
is the reference power of the branch l,
Figure BDA0003771621950000059
is the reference power of node i, s l,i Is the power flow transfer distribution factor of branch i with respect to node i, meaning that the power at node i increases by 1 unit so that the power of branch i increases by an incremental amount,
Figure BDA00037716219500000510
is the set of all nodes in the distribution network,
Figure BDA00037716219500000511
is the set of nodes after the balancing nodes are removed,
Figure BDA00037716219500000512
is a collection of nodes that contains a flexible resource aggregator,
Figure BDA00037716219500000513
is a collection of distribution network branches and,
Figure BDA00037716219500000514
and
Figure BDA00037716219500000515
are respectively composed of
Figure BDA00037716219500000516
And
Figure BDA00037716219500000517
the formed T-dimensional column vector is processed,
Figure BDA00037716219500000518
representing a power feasible region at a flexible resource aggregator node;
according to the distribution network power flow constraint described by the power flow transfer distribution factor, continuously correcting a feasible region from a leaf node along a road to a root node according to the transmission capacity of a branch to obtain a safety constraint parameter, wherein each correction is compared and summed; optimizing the feasible domain aggregation model based on the security constraint parameters.
An embodiment of a third aspect of the present application provides an electronic device, including: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the method for flexible aggregation of tunable resources in a power distribution network as described in the embodiments above.
A fourth aspect of the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor, and is used to implement the method for flexible aggregation of tunable resources in a power distribution network according to the foregoing embodiments.
Therefore, the application has at least the following beneficial effects:
according to the aggregate feasible region model of the flexible resources on each node, the aggregate feasible region of the flexible resources of the distribution network considering the distribution network tidal current safety constraint is calculated, and the power flexibility of the flexible resources can be utilized to the maximum extent on the premise of ensuring the distribution network tidal current safety and the power distribution feasibility. Therefore, the problems that the aggregation feasible domain of the flexible resources in the distribution network is not comprehensively considered, the flexibility of the flexible resources cannot be utilized to the maximum extent, the economical efficiency and the safety of the operation of the whole network are reduced, and the like in the related technology are solved.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
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The above and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a flowchart of a method for flexible aggregation of tunable resources in a power distribution network according to an embodiment of the present application;
fig. 2 is a schematic block diagram of a flexibility aggregation apparatus for adjustable resources in a power distribution network according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Description of reference numerals: a determination module-100, a construction module-200, a constraint module-300, a memory-301, a processor-302, and a communication interface-303.
Detailed Description
Reference will now be made in detail to the embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
The following describes a flexible aggregation method and apparatus for tunable resources in a power distribution network, an electronic device, and a storage medium according to an embodiment of the present application with reference to the accompanying drawings. In view of the above-mentioned problems in the background art, the present application provides a flexible aggregation method for adjustable resources in a power distribution network, in which flexible resources on each node in the power distribution network are determined; constructing a feasible region aggregation model of the power distribution network according to preset safety constraint conditions of the power distribution network and flexible resources on each node; and calculating at least one safety constraint parameter of the feasible region aggregation model according to the expected target of the linear power flow constraint, and optimizing the feasible region aggregation model based on the at least one safety constraint parameter so as to perform linear power flow safety constraint on the power distribution network by using the optimized feasible region aggregation model. Therefore, the problems that the current market rule is not comprehensive in consideration of the aggregation feasible region of the flexible resources in the distribution network, the flexibility of the flexible resources cannot be utilized to the maximum degree, the economical efficiency and the safety of the operation of the whole network are reduced, and the like are solved.
Specifically, fig. 1 is a schematic flowchart of a method for flexibly aggregating adjustable resources in a power distribution network according to an embodiment of the present disclosure.
As shown in fig. 1, the flexible aggregation method for tunable resources in a power distribution network includes the following steps:
in step S101, flexible resources on individual nodes in the power distribution network are determined.
It can be understood that flexible resources on the demand side participate in the regulation and control of the power grid, so that the safe and stable operation of the power grid can be guaranteed, the consumption of new energy is promoted, and the power consumption cost of a user is reduced. Because the parameters of all demand side resources are considered to be too complex during power grid dispatching, the privacy of power consumers is not protected, and the demand side flexible resources need to be aggregated and then participate in power grid regulation, the flexible resources on each node in the power distribution network need to be determined.
In step S102, a feasible domain aggregation model of the power distribution network is constructed according to preset security constraints of the power distribution network and flexible resources on each node.
According to the method and the device, the feasible region aggregation model of the flexible resources in the distribution network can be calculated by considering the distribution network flow safety constraint on the premise that the feasible region of flexible resource aggregation of a single node in the distribution network is known, and any one power curve in the feasible region can be distributed to each feasible region of the flexible resources without error on the premise that the flow safety constraint is met; the power curve which is not in the accurate feasible region can not be distributed to the feasible region of each flexible resource without error on the premise of meeting the safety constraint of the power flow, a model basis is provided for the decision of the flexible resource participating in the economic dispatching or market clearing of the large power grid, the flexibility of the flexible resource can be utilized to the maximum extent, and the economy and the safety of the whole network operation are improved.
In an embodiment of the present application, a feasible region aggregation model of a power distribution network is constructed according to preset security constraints of the power distribution network and flexible resources on each node, and the method includes: dividing a preset time window into a plurality of time periods according to a preset time interval; constructing an aggregation feasible region of the flexible resources on each node according to the boundary parameters of the flexible resources on each node in each time period; and aggregating the aggregation feasible region of the flexible resources on each node according to the preset distribution network safety constraint and the preset linear distribution network flow equation to obtain a feasible region aggregation model of the distribution network.
Specifically, the method for constructing the flexible resource feasible domain aggregation model considering the distribution network security constraint can comprise the following steps:
1) Discretizing time, dividing the time window considered by optimization into T time segments according to the time interval of delta T, and collecting all the time segments
Figure BDA0003771621950000071
To indicate.
2) The flexible resource accurate aggregation feasible domains on each node in the distribution network are uniformly expressed as follows:
Figure BDA0003771621950000072
wherein X A Representing precisely aggregated feasible domains of flexible resources on a single node, P t A Representing the total power, P, of the flexible resources at a single node over time period t A Is formed by all P t A T-dimensional column vectors (from T =1 to T = T), the bold letters shown later in this application are all T-dimensional column vectors consisting of the corresponding variables,
Figure BDA0003771621950000073
is that
Figure BDA0003771621950000074
Any subset of the number of the first and second subsets of,
Figure BDA0003771621950000075
and
Figure BDA0003771621950000076
is and
Figure BDA0003771621950000077
the associated boundary parameter.
By x t By referring to all variables, the form can be expressed as X A Defining the following set:
Figure BDA0003771621950000078
let all possible fields that can be defined in the above-described manner constitute a set
Figure BDA0003771621950000079
3) The feasible domains determined by the transformation of the distribution network safety constraint and the linear distribution network power flow equation, the transmission capacity constraint and the voltage upper and lower limit constraint in the safety constraint and the like can be uniformly written as follows:
Figure BDA00037716219500000710
this form of feasible domain belongs to
Figure BDA00037716219500000711
Because of the fact that
Figure BDA00037716219500000712
Figure BDA00037716219500000713
The feasible domains determined by the fixed load constraints and the balanced node voltage phase angle constraints in the safety constraints can be uniformly written as:
Figure BDA0003771621950000081
this form of feasible domain also belongs to
Figure BDA0003771621950000082
Because of the fact that
Figure BDA0003771621950000083
Each equation of the linear distribution network power flow equation can be uniformly expressed as:
Figure BDA0003771621950000084
wherein x n,t Is the value of the nth variable in the power flow equation in a time period t, m is the number of the equation, a m,n Is x n,t The coefficients in the mth equation, independent of t, can be equivalently written as:
Figure BDA0003771621950000085
4) Considering a general radial distribution network, an accurate aggregation model of a distribution network flexible resource feasible region is an active power feasible region of a distribution network balance node (i.e., a root node). Let the active power at the root node be variable
Figure BDA0003771621950000086
Then after considering the feasible domain of the flexible resources in the distribution network and the feasible domain determined by the tidal current security constraint,
Figure BDA0003771621950000087
the feasible region accurate model of (a) can be expressed as:
Figure BDA0003771621950000088
wherein the parameters
Figure BDA0003771621950000089
And
Figure BDA00037716219500000810
the calculation method of (2) is given in the subsequent steps of (2) and (3) in combination with the specific power flow equation. X 0 Representing the feasible domain aggregation model, t is timeThe segment subscripts are such that,
Figure BDA00037716219500000811
representing the set of all time periods, T representing the total number of time periods,
Figure BDA00037716219500000812
representing the active power at the root node,
Figure BDA00037716219500000813
is that
Figure BDA00037716219500000814
Any subset of the number of the first and second subsets of,
Figure BDA00037716219500000815
and
Figure BDA00037716219500000816
respectively representing power
Figure BDA00037716219500000817
Set of time periods
Figure BDA00037716219500000818
The upper and lower bounds of the upper integral, the superscript n representing the node power,
Figure BDA00037716219500000819
is represented by
Figure BDA00037716219500000820
And forming a T-dimensional column vector.
In the case of the accurate model, the model,
Figure BDA00037716219500000821
any non-empty subset of (a) corresponds to a pair of effective upper and lower bound constraints, and when T is larger, the model complexity is higher, and here, an approximate model named as a second-order approximate feasible domain is given, which can be expressed as:
Figure BDA00037716219500000822
it can be seen that the second order approximation feasible domain corresponds to those defined by any two time periods t 1 And t 2 All time periods in between, this is the set of
Figure BDA00037716219500000823
A fraction of the subset of (1), a parameter
Figure BDA00037716219500000824
And
Figure BDA00037716219500000825
is also that
Figure BDA00037716219500000826
And
Figure BDA00037716219500000827
corresponding to the portion of the subset described above.
It should be noted that, the embodiments of the present application can also be selected by selecting
Figure BDA00037716219500000828
Other parts of the subset are used to construct the approximate model, which will not be described in detail here, but only by selection
Figure BDA0003771621950000091
Are within the scope of the claims of the present application.
In step S103, at least one security constraint parameter of the feasible region aggregation model is calculated according to the expected target of the linear power flow constraint, and the feasible region aggregation model is optimized based on the at least one security constraint parameter, so as to perform the linear power flow security constraint on the power distribution network by using the optimized feasible region aggregation model.
In one embodiment of the present application, the desired targets for the linear power flow constraint include a first linear power flow constraint target and a second linear power flow constraint target.
The first linear power flow constraint target can be suitable for power flow safety constraint of any linear distribution network, and the second linear power flow constraint target can be suitable for linear power flow safety constraint described by a power flow transfer distribution factor.
According to the method and the device, the safety constraint parameters of the flexible resource feasible region aggregation model in the distribution network can be accurately calculated under the linear distribution network flow constraint, the model is optimized, the optimized line region aggregation model is used for carrying out linear flow safety constraint on the distribution network, the flexibility of flexible resources can be utilized to the maximum extent while the distribution network flow safety and the power distribution feasibility are guaranteed, and the economy and the safety of the whole network operation are improved.
In one embodiment of the present application, when the desired target of the linear power flow constraint is the first linear power flow constraint target, at least one safety constraint parameter of the feasible domain aggregation model is calculated according to the desired target of the linear power flow constraint, and the feasible domain aggregation model is optimized based on the at least one safety constraint parameter, including:
all the feasible domains of all the variables in the distribution network are converted into
Figure BDA0003771621950000092
Wherein n is the number of the variable, x n,t Is the value of the nth variable in the power flow equation in the time period t, x n Is represented by x n,t Forming a T-dimensional column vector; for a target set
Figure BDA0003771621950000093
Is not empty
Figure BDA0003771621950000094
So that
Figure BDA0003771621950000095
Figure BDA0003771621950000096
And (3) satisfying the constraint:
Figure BDA0003771621950000097
and current constraints
Figure BDA0003771621950000098
Where m is the number of the equation, a m,n Is x n,t Coefficients in the m-th equation;
calculating security constraint parameters according to a first optimization formula
Figure BDA0003771621950000099
And
Figure BDA00037716219500000910
the first optimization formula is:
Figure BDA00037716219500000911
Figure BDA00037716219500000912
Figure BDA00037716219500000913
Figure BDA00037716219500000914
Figure BDA00037716219500000915
Figure BDA00037716219500000916
wherein,
Figure BDA00037716219500000917
is that
Figure BDA00037716219500000918
The minimum value of (a) is determined,
Figure BDA00037716219500000919
is that
Figure BDA00037716219500000920
S.t. represents a constraint condition; according to safety constraint parameters
Figure BDA0003771621950000101
And
Figure BDA0003771621950000102
optimizing the feasible domain aggregation model.
In the embodiments of the present application, for any given
Figure BDA0003771621950000103
Solving the optimization problem determination
Figure BDA0003771621950000104
And
Figure BDA0003771621950000105
then pass through 2 (2) T -1) after sub-optimal computation, all can be determined
Figure BDA0003771621950000106
And
Figure BDA0003771621950000107
this calculation by solving an optimization problem
Figure BDA0003771621950000108
And
Figure BDA0003771621950000109
is called a flexible optimization method. For
Figure BDA00037716219500001010
And
Figure BDA00037716219500001011
as described above
Figure BDA00037716219500001012
The selection of the method is not arbitrary, only T (T + 1)/2 types are adopted, all the types can be determined through T (T + 1) sub-optimization calculation by using a flexible optimization method
Figure BDA00037716219500001013
And
Figure BDA00037716219500001014
for the convenience of understanding, the embodiment of the present application is described in detail by a specific linear power flow equation and safety constraints, as follows:
Figure BDA00037716219500001015
Figure BDA00037716219500001016
Figure BDA00037716219500001017
Figure BDA00037716219500001018
Figure BDA00037716219500001019
Figure BDA00037716219500001020
Figure BDA00037716219500001021
Figure BDA00037716219500001022
Figure BDA00037716219500001023
Figure BDA00037716219500001024
V 0,t ＝1,θ 0,t ＝0
Figure BDA00037716219500001025
wherein i, j are the numbers of the nodes, 0 represents the root node,
Figure BDA00037716219500001026
a set of all the nodes is represented,
Figure BDA00037716219500001027
a set of nodes representing the removal of the balancing nodes,
Figure BDA00037716219500001028
representing a set of nodes containing flexible resources, ij representing a branch starting from node i and ending at node j,
Figure BDA00037716219500001029
is the set of all the branches of the tree,
Figure BDA00037716219500001030
and
Figure BDA00037716219500001031
respectively, indicate branches ij atActive and reactive power, V, of time period t i,t Representing the voltage at node i, θ i,t Denotes the phase angle, G, of node i ij And B ij Respectively representing the real part and the imaginary part of the ith row and the jth column in the nodal admittance matrix,
Figure BDA0003771621950000111
and
Figure BDA0003771621950000112
respectively representing the active and reactive power, gamma, of node i i Is the power factor angle of the node i,
Figure BDA0003771621950000113
the transmission capacity of the branch ij is indicated, i Vand
Figure BDA0003771621950000114
respectively represent the upper and lower limits of the voltage at node i,
Figure BDA0003771621950000115
and
Figure BDA0003771621950000116
respectively, the load values of the fixed load nodes i.
The first 5 constraints correspond to
Figure BDA0003771621950000117
The 6 th and 7 th constraints correspond to
Figure BDA0003771621950000118
The 8 th, 9 th and 10 th constraints correspond to
Figure BDA0003771621950000119
The last constraint then corresponds to
Figure BDA00037716219500001110
Therefore, the load flow equation, the safety constraint and the resource flexibility constraint in the embodiment of the application completely accord with the conditions of using the flexibility optimization method, and can be realizedAnd calculating the aggregation feasible domain of the flexible resources in the distribution network by using an over-flexibility optimization method.
In one embodiment of the present application, when the desired target of the linear power flow constraint is the second linear power flow constraint target, at least one safety constraint parameter of the feasible domain aggregation model is calculated according to the desired target of the linear power flow constraint, and the feasible domain aggregation model is optimized based on the at least one safety constraint parameter, including:
calculating the distribution network power flow constraint described by the power flow transfer distribution factor according to the following formula:
Figure BDA00037716219500001111
Figure BDA00037716219500001112
Figure BDA00037716219500001113
Figure BDA00037716219500001114
wherein,
Figure BDA00037716219500001115
is the active increment of branch i over time period t,
Figure BDA00037716219500001116
is the active increment of the node i and,
Figure BDA00037716219500001117
is the reference power of the branch i,
Figure BDA00037716219500001118
is the reference power, s, of node i l,i Is the power flow transfer distribution factor of the branch l relative to the node i, meaning the node iIncreases the power of branch l by 1 unit causes an increase in the power of branch l,
Figure BDA00037716219500001119
is the set of all nodes in the distribution network,
Figure BDA00037716219500001120
is the set of nodes after the balancing nodes are removed,
Figure BDA00037716219500001121
is a collection of nodes that contains a flexible resource aggregator,
Figure BDA00037716219500001122
is a collection of distribution network branches,
Figure BDA00037716219500001123
and
Figure BDA00037716219500001124
are respectively composed of
Figure BDA00037716219500001125
And
Figure BDA00037716219500001126
the formed T-dimensional column vector is processed,
Figure BDA00037716219500001127
representing a power feasible domain at a flexible resource aggregator node;
according to distribution network power flow constraint described by the power flow transfer distribution factor, continuously correcting a feasible region from a leaf node along a road to a root node according to the transmission capacity of a branch to obtain a safety constraint parameter, wherein each correction is compared and summed; and optimizing the feasible domain aggregation model based on the security constraint parameters.
In the examples of the present application, let us note
Figure BDA00037716219500001128
The matrix is S, and in the radial distribution networkIn the above description, assuming that all the power unbalance amounts are balanced by the balancing node (i.e. the root node provides balance), S is equivalent to the branch-road association matrix of the radial grid, and the physical meaning of this conclusion is: when the load of a certain node increases by 1, the power of the branch on its road increases by 1.
Note the book
Figure BDA0003771621950000121
Is operable as
Figure BDA0003771621950000122
Wherein
Figure BDA0003771621950000123
Figure BDA0003771621950000124
Note the book
Figure BDA0003771621950000125
Is a field of
Figure BDA0003771621950000126
The flexible resource aggregation feasible domain in the distribution network is the solution
Figure BDA0003771621950000127
The feasible region of (2) is accurate under the linear power flow constraint of the distribution network described by the power flow transfer distribution factor
Figure BDA0003771621950000128
Parameters in the feasible domain model may be computed using a backtracking elimination method, comprising the steps of:
inputting: node set
Figure BDA0003771621950000129
Branch collection
Figure BDA00037716219500001210
Power feasible region of each node
Figure BDA00037716219500001211
Power feasible region Y of each branch l Δ ；
And (3) outputting:
Figure BDA00037716219500001212
can field of
Figure BDA00037716219500001213
1、while
Figure BDA00037716219500001214
do
2. Find out a leaf node i, its branch l and its father node j
3、for
Figure BDA00037716219500001215
do
4. Assignment of value
Figure BDA00037716219500001216
5、end for
6. From
Figure BDA00037716219500001217
Delete node i from
Figure BDA00037716219500001218
Middle deletion branch l
7、end while
8、return
Figure BDA00037716219500001219
According to the embodiment of the application, the distribution network power flow constraint described by the power flow transfer distribution factor is continuously corrected from the leaf node to the root node along the road according to the transmission capacity limit of the branch, only comparison and summation operation are needed for correction each time, the problem of calculation optimization is not needed, and the calculation complexity is greatly simplified.
According to the flexibility aggregation method for the adjustable resources in the power distribution network, the aggregation feasible region of the flexible resources of the power distribution network considering the power flow safety constraint of the power distribution network is calculated according to the aggregation feasible region model of the flexible resources on each node, and the power flexibility of the flexible resources can be utilized to the maximum extent on the premise that the power flow safety and the power distribution feasibility of the power distribution network are guaranteed. Therefore, the problems that the aggregation feasible region of the flexible resources in the distribution network is not comprehensively considered, the flexibility of the flexible resources cannot be utilized to the maximum extent, the economy and the safety of the whole network operation are reduced and the like in the related technology are solved.
Next, a flexible aggregation apparatus for tunable resources in a power distribution network according to an embodiment of the present application is described with reference to the accompanying drawings.
Fig. 2 is a schematic block diagram of a flexible aggregation apparatus for tunable resources in a power distribution network according to an embodiment of the present application.
As shown in fig. 2, the flexible aggregation apparatus 10 for tunable resources in the power distribution network includes: a determination module 100, a construction module 200 and a constraint module 300.
The determining module 100 is configured to determine flexible resources on each node in the power distribution network; the building module 200 is used for building a feasible region aggregation model of the power distribution network according to preset safety constraint conditions of the power distribution network and flexible resources on each node; the constraint module 300 is configured to calculate at least one security constraint parameter of the feasible region aggregation model according to an expected target of linear power flow constraint, and optimize the feasible region aggregation model based on the at least one security constraint parameter, so as to perform linear power flow security constraint on the power distribution network by using the optimized feasible region aggregation model.
Optionally, in an embodiment of the present application, the constructing module 200 is further configured to divide a preset time window into a plurality of time periods according to a preset time interval, and construct an aggregation feasible region of the flexible resources on each node according to boundary parameters of the flexible resources on each node in each time period; and aggregating the aggregation feasible region of the flexible resources on each node according to the preset distribution network safety constraint and the preset linear distribution network flow equation to obtain a feasible region aggregation model of the distribution network.
Optionally, in an embodiment of the present application, the expression formula of the feasible domain aggregation model is:
Figure BDA0003771621950000131
wherein, X 0 Representing the feasible domain aggregation model, t is a time period index,
Figure BDA0003771621950000132
representing the set of all time periods, T representing the total number of time periods,
Figure BDA0003771621950000133
representing the active power at the root node,
Figure BDA0003771621950000134
is that
Figure BDA0003771621950000135
Any subset of the number of the first and second subsets of,
Figure BDA0003771621950000136
and
Figure BDA0003771621950000137
respectively representing power
Figure BDA0003771621950000138
Set of time periods
Figure BDA0003771621950000139
The upper and lower bounds of the upper integral, the superscript n representing the node power,
Figure BDA00037716219500001310
is represented by
Figure BDA00037716219500001311
And forming a T-dimensional column vector.
Optionally, in one embodiment of the present application, the desired targets of the linear power flow constraint include a first linear power flow constraint target and a second linear power flow constraint target.
Optionally, in an embodiment of the present application, when the desired target of the linear power flow constraint is the first linear power flow constraint target, the constraint module 300 is further configured to convert all the feasible domains of all the variables in the distribution network into the first linear power flow constraint target
Figure BDA00037716219500001312
Wherein x is n,t Is the value of the nth variable in the power flow equation in the time period t, x n Is represented by x n,t A constructed T-dimensional column vector;
for a target set
Figure BDA00037716219500001313
Is not empty
Figure BDA00037716219500001314
So that
Figure BDA00037716219500001315
Figure BDA00037716219500001316
And satisfying the constraint:
Figure BDA00037716219500001317
and current constraints
Figure BDA00037716219500001318
Where m is the number of the equation, a m,n Is x n,t Coefficients in the mth equation;
calculating security constraint parameters according to a first optimization formula
Figure BDA00037716219500001319
And
Figure BDA00037716219500001320
the first optimization formula is:
Figure BDA0003771621950000141
wherein,
Figure BDA0003771621950000142
is that
Figure BDA0003771621950000143
The minimum value of (a) is calculated,
Figure BDA0003771621950000144
is that
Figure BDA0003771621950000145
S.t. represents a constraint;
according to security constraint parameters
Figure BDA0003771621950000146
And
Figure BDA0003771621950000147
optimizing the feasible domain aggregation model.
Optionally, in an embodiment of the present application, when the desired target of the linear power flow constraint is a second linear power flow constraint target, the constraint module 300 is further configured to calculate a distribution network power flow constraint described by the power flow transfer distribution factor according to the following formula:
Figure BDA0003771621950000148
Figure BDA0003771621950000149
Figure BDA00037716219500001410
Figure BDA00037716219500001411
Figure BDA00037716219500001412
wherein,
Figure BDA00037716219500001413
is the active increment of branch i over time period t,
Figure BDA00037716219500001414
is the active increment of the node i,
Figure BDA00037716219500001415
is the reference power of the branch l,
Figure BDA00037716219500001416
is the reference power, s, of node i l,i Is the power flow transfer distribution factor of branch i with respect to node i, meaning that the power of node i is increased by 1 unit so that the power of branch i is increased by an increment,
Figure BDA00037716219500001417
is the set of all nodes in the distribution network,
Figure BDA00037716219500001418
is the set of nodes after the balancing nodes are removed,
Figure BDA00037716219500001419
is a collection of nodes that contains a flexible resource aggregator,
Figure BDA00037716219500001420
is a collection of distribution network branches,
Figure BDA00037716219500001421
and
Figure BDA00037716219500001422
are respectively composed of
Figure BDA00037716219500001423
And
Figure BDA00037716219500001424
the formed T-dimensional column vector is then,
Figure BDA00037716219500001425
representing a power feasible domain at a flexible resource aggregator node;
according to the distribution network power flow constraint described by the power flow transfer distribution factor, continuously correcting a feasible region from a leaf node to a root node along a road according to the transmission capacity of a branch, so as to obtain a safety constraint parameter, wherein comparison and summation operation are carried out on correction each time; and optimizing the feasible domain aggregation model based on the security constraint parameters.
It should be noted that the foregoing explanation of the embodiment of the method for flexibly aggregating tunable resources in a power distribution network is also applicable to the device for flexibly aggregating tunable resources in a power distribution network of this embodiment, and details are not repeated here.
According to the flexibility aggregation device for the adjustable resources in the power distribution network, the aggregation feasible region of the flexible resources of the power distribution network considering the power flow safety constraint of the power distribution network is calculated according to the aggregation feasible region model of the flexible resources on each node, and the power flexibility of the flexible resources can be utilized to the maximum extent on the premise of ensuring the power flow safety and the power distribution feasibility of the power distribution network. Therefore, the problems that the aggregation feasible domain of the flexible resources in the distribution network is not comprehensively considered, the flexibility of the flexible resources cannot be utilized to the maximum extent, the economical efficiency and the safety of the operation of the whole network are reduced, and the like in the related technology are solved.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device may include:
a memory 301, a processor 302, and a computer program stored on the memory 301 and executable on the processor 302.
The processor 302, when executing the program, implements the flexible aggregation method for tunable resources in a power distribution network provided in the above embodiments.
Further, the electronic device further includes:
a communication interface 303 for communication between the memory 301 and the processor 302.
A memory 301 for storing computer programs executable on the processor 302.
The Memory 301 may include a high-speed RAM (Random Access Memory) Memory, and may also include a non-volatile Memory, such as at least one disk Memory.
If the memory 301, the processor 302 and the communication interface 303 are implemented independently, the communication interface 303, the memory 301 and the processor 302 may be connected to each other through a bus and perform communication with each other. The bus may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 3, but that does not indicate only one bus or one type of bus.
Optionally, in a specific implementation, if the memory 301, the processor 302, and the communication interface 303 are integrated on one chip, the memory 301, the processor 302, and the communication interface 303 may complete mutual communication through an internal interface.
The processor 302 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement embodiments of the present Application.
Embodiments of the present application further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for flexible aggregation of tunable resources in a power distribution network as described above.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Moreover, various embodiments or examples and features of various embodiments or examples described in this specification can be combined and combined by one skilled in the art without being mutually inconsistent.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more N executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of implementing the embodiments of the present application.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a programmable gate array, a field programmable gate array, or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.

Claims (10)

1. A flexible aggregation method for adjustable resources in a power distribution network is characterized by comprising the following steps:
determining flexible resources on each node in the power distribution network;
constructing a feasible region aggregation model of the power distribution network according to preset safety constraint conditions of the power distribution network and flexible resources on each node;
calculating at least one safety constraint parameter of the feasible region aggregation model according to an expected target of linear power flow constraint, and optimizing the feasible region aggregation model based on the at least one safety constraint parameter so as to perform linear power flow safety constraint on the power distribution network by using the optimized feasible region aggregation model.
2. The method of claim 1, wherein the constructing the feasible domain aggregation model of the power distribution network according to the preset security constraints of the power distribution network and the flexible resources at the nodes comprises:
dividing a preset time window into a plurality of time periods according to a preset time interval;
constructing an aggregation feasible region of the flexible resources on each node according to the boundary parameters of the flexible resources on each node in each time period;
and aggregating the aggregated feasible domain of the flexible resources on each node according to preset distribution network safety constraints and a preset linear distribution network flow equation to obtain a feasible domain aggregation model of the distribution network.
3. The method of claim 2, wherein the expression formula of the feasible region aggregation model is:
Figure FDA0003771621940000011
wherein X 0 Representing the feasible domain aggregation model, t is a time period index,
Figure FDA0003771621940000012
representing the set of all time periods, T representing the total number of time periods,
Figure FDA0003771621940000013
representing the active power at the root node,
Figure FDA0003771621940000014
is that
Figure FDA0003771621940000015
Any subset of the number of the first and second subsets of,
Figure FDA0003771621940000016
and
Figure FDA0003771621940000017
respectively representing power
Figure FDA0003771621940000018
Set of time periods
Figure FDA0003771621940000019
The upper and lower bounds of the upper integral, the superscript n representing the node power,
Figure FDA00037716219400000110
is represented by
Figure FDA00037716219400000111
And forming a T-dimensional column vector.
4. The method of claim 1, wherein the desired objectives for the linear power flow constraint include a first linear power flow constraint objective and a second linear power flow constraint objective.
5. The method according to claim 4, wherein, when the desired objective of the linear power flow constraint is the first linear power flow constraint objective, the calculating at least one safety constraint parameter of the feasible domain aggregation model according to the desired objective of the linear power flow constraint, optimizing the feasible domain aggregation model based on the at least one safety constraint parameter, comprises:
all the feasible domains of all the variables in the distribution network are converted into
Figure FDA00037716219400000112
Wherein n is the number of the variable, x n,t Is the value of the nth variable in the power flow equation over a period t, x n Is represented by x n,t A constructed T-dimensional column vector;
for a target set
Figure FDA00037716219400000213
Is not an empty subset of
Figure FDA00037716219400000232
So that
Figure FDA0003771621940000021
Figure FDA0003771621940000022
And satisfying the constraint:
Figure FDA0003771621940000023
and current constraints
Figure FDA0003771621940000024
Where m is the number of the equation, a m,n Is x n,t Coefficients in the mth equation;
calculating security constraint parameters according to a first optimization formula
Figure FDA0003771621940000025
And
Figure FDA0003771621940000026
the first optimization formula is as follows:
Figure FDA0003771621940000027
wherein,
Figure FDA00037716219400000214
is that
Figure FDA00037716219400000215
The minimum value of (a) is determined,
Figure FDA00037716219400000216
is that
Figure FDA00037716219400000217
S.t. represents a constraint;
according to the safety constraint parameters
Figure FDA00037716219400000218
And
Figure FDA00037716219400000219
optimizing the feasible domain aggregation model.
6. The method according to claim 4, wherein, when the desired objective of the linear power flow constraint is the second linear power flow constraint objective, the calculating at least one safety constraint parameter of the feasible domain aggregation model according to the desired objective of the linear power flow constraint, optimizing the feasible domain aggregation model based on the at least one safety constraint parameter, comprises:
calculating the distribution network power flow constraint described by the power flow transfer distribution factor according to the following formula:
Figure FDA0003771621940000028
Figure FDA0003771621940000029
Figure FDA00037716219400000210
Figure FDA00037716219400000211
Figure FDA00037716219400000212
wherein,
Figure FDA00037716219400000220
is the active increment of branch i during time period t,
Figure FDA00037716219400000221
is the active increment of the node i,
Figure FDA00037716219400000222
is the reference power of the branch l,
Figure FDA00037716219400000223
is the reference power, s, of node i l,i Is the power flow transfer distribution factor of branch i with respect to node i, meaning that the power of node i is increased by 1 unit so that the power of branch i is increased by an increment,
Figure FDA00037716219400000224
is the set of all nodes in the distribution network,
Figure FDA00037716219400000225
is the set of nodes after the balancing nodes are removed,
Figure FDA00037716219400000226
is a collection of nodes that contains a flexible resource aggregator,
Figure FDA00037716219400000227
is a set of distribution network branches, Δ P i n And
Figure FDA00037716219400000231
are respectively composed of
Figure FDA00037716219400000229
And
Figure FDA00037716219400000228
the formed T-dimensional column vector is then,
Figure FDA00037716219400000230
representing a power feasible domain at a flexible resource aggregator node;
according to the distribution network power flow constraint described by the power flow transfer distribution factor, continuously correcting a feasible region from a leaf node along a road to a root node according to the transmission capacity of a branch to obtain a safety constraint parameter, wherein each correction is compared and summed;
optimizing the feasible domain aggregation model based on the security constraint parameters.
7. A flexible aggregation device for tunable resources in a power distribution network, comprising:
the determining module is used for determining flexible resources on each node in the power distribution network;
the construction module is used for constructing a feasible region aggregation model of the power distribution network according to preset safety constraint conditions of the power distribution network and flexible resources on each node;
and the constraint module is used for calculating at least one safety constraint parameter of the feasible region aggregation model according to an expected target of linear power flow constraint, and optimizing the feasible region aggregation model based on the at least one safety constraint parameter so as to perform linear power flow safety constraint on the power distribution network by using the optimized feasible region aggregation model.
8. The apparatus of claim 7, wherein the build module is further configured to:
dividing a preset time window into a plurality of time periods according to a preset time interval, and constructing an aggregation feasible region of the flexible resources on each node according to the boundary parameters of the flexible resources on each node in each time period; and aggregating the aggregated feasible domain of the flexible resources on each node according to preset distribution network safety constraints and a preset linear distribution network flow equation to obtain a feasible domain aggregation model of the distribution network.
9. An electronic device, comprising: memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement a flexible aggregation method of tunable resources in an electrical distribution network according to any of claims 1-6.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the program is executable by a processor for implementing a method for flexible aggregation of tunable resources in a power distribution network according to any of claims 1-6.
CN202210903140.4A 2022-07-29 2022-07-29 Flexible aggregation method, device, equipment and medium for adjustable resources in power distribution network Pending CN115146872A (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116131259A (en) * 2023-02-09 2023-05-16 中国南方电网有限责任公司 Power resource scheduling method and device based on time aggregation and computer equipment
CN117077946A (en) * 2023-08-16 2023-11-17 国网山东省电力公司东营供电公司 Novel market subject identification method and system suitable for participating in power grid aggregation scheduling
CN117810995A (en) * 2024-02-29 2024-04-02 国网江西省电力有限公司电力科学研究院 Operation control method and system for electric automobile accessing power distribution network

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116131259A (en) * 2023-02-09 2023-05-16 中国南方电网有限责任公司 Power resource scheduling method and device based on time aggregation and computer equipment
CN116131259B (en) * 2023-02-09 2024-02-06 中国南方电网有限责任公司 Power resource scheduling method and device based on time aggregation and computer equipment
CN117077946A (en) * 2023-08-16 2023-11-17 国网山东省电力公司东营供电公司 Novel market subject identification method and system suitable for participating in power grid aggregation scheduling
CN117077946B (en) * 2023-08-16 2024-04-16 国网山东省电力公司东营供电公司 Novel market subject identification method and system suitable for participating in power grid aggregation scheduling
CN117810995A (en) * 2024-02-29 2024-04-02 国网江西省电力有限公司电力科学研究院 Operation control method and system for electric automobile accessing power distribution network
CN117810995B (en) * 2024-02-29 2024-07-05 国网江西省电力有限公司电力科学研究院 Operation control method and system for electric automobile accessing power distribution network

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