CN115642592A - Multi-terminal SOP-based flexible interconnected power distribution network multistage dynamic reconstruction method - Google Patents

Multi-terminal SOP-based flexible interconnected power distribution network multistage dynamic reconstruction method Download PDF

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CN115642592A
CN115642592A CN202211356798.4A CN202211356798A CN115642592A CN 115642592 A CN115642592 A CN 115642592A CN 202211356798 A CN202211356798 A CN 202211356798A CN 115642592 A CN115642592 A CN 115642592A
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reconstruction
sop
terminal
level
transformer
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马望
许典
蔡德福
万黎
陈汝斯
刘海光
王涛
董航
王文娜
张良一
孙冠群
王尔玺
尹斌鑫
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Electric Power Research Institute of State Grid Hubei Electric Power Co Ltd
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Electric Power Research Institute of State Grid Hubei Electric Power Co Ltd
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Abstract

The invention provides a multi-stage dynamic reconstruction method for a flexible interconnected power distribution network based on multi-terminal SOP, which considers the power flow distribution improvement capability of the multi-terminal SOP, establishes a reconstruction level decision model considering the multi-terminal SOP and carries out optimization decision on the reconstruction level variables of each transformer substation and each transformer subregion system; establishing a multi-stage dynamic reconstruction model by taking minimum light abandoning, load loss, network loss and switching action cost as an optimization target based on a level identification result; the method comprises the steps of carrying out network frame topology updating aiming at multi-stage reconstruction participated by a multi-terminal SOP flexible interconnection feeder line, providing an SOP multi-terminal multi-stage dynamic reconstruction distributed optimization framework, coordinating each terminal through multi-terminal SOP active power transmission constraint, carrying out global coordination and iterative solution by using an alternative direction multiplier method, and realizing distributed optimization solution of SOP multi-terminal multi-stage dynamic reconstruction. By the method and the device, the solving difficulty of the centralized dynamic reconstruction model of the flexible interconnected power distribution network can be reduced.

Description

Multi-terminal SOP-based flexible interconnected power distribution network multistage dynamic reconstruction method
Technical Field
The invention relates to the field of dynamic reconfiguration of a power distribution network, in particular to a multi-terminal SOP-based flexible interconnected power distribution network multi-stage dynamic reconfiguration method.
Background
Under "two carbon" targets and novel electric power system construction background, tradition distribution network spatial grid structure has been unable to satisfy the form characteristic demand of the nimble interconnection of novel distribution system, and the coexistence of the multiterminal SOP and the contact switch of connecting different transformer substation's power supply feeder is the inevitable development stage of traditional distribution network to the high-grade form evolution of novel distribution system. The multi-terminal SOP can accurately control feeder lines from different transformer substations to transmit active power and provide reactive support in real time, and compared with a traditional transformer substation cascading network switch, the multi-terminal SOP has the advantages that transformer substation-level power flow transfer capacity is improved remarkably, and flexibility of a grid structure is enhanced. Meanwhile, due to low-carbonization development of the source side, a large number of distributed photovoltaic power is connected to the power distribution network in a scattered mode. However, the differentiated distribution of high-proportion distributed photovoltaic and load demands leads to the development of source-load imbalance of the power distribution network, and the problems of light abandonment and load loss are caused. The flow distribution improving capability of the multi-terminal SOP and the switch reconstruction is an effective path for solving the challenges, but the global dynamic reconstruction of the large-scale power distribution network containing the multi-terminal SOP still faces the problem of coexistence of time complexity and space complexity, and flexible interconnection of a plurality of feeder lines cannot be matched with the reconstruction model dimension reduction of the traditional multi-stage dynamic reconstruction method at the transformer substation level. Therefore, the method has important significance for carrying out coordinated optimization on the feeder line interconnection switch, the transformer interconnection switch and the multi-terminal SOP and researching the multi-stage dynamic reconstruction method of the large-scale power distribution network suitable for multi-terminal SOP flexible interconnection.
Disclosure of Invention
The invention aims to solve the technical problem of a flexible interconnected power distribution network multi-stage dynamic reconstruction method, which responds to the flexibility requirement of each level of net load through the coordinated optimization of a multi-terminal SOP and a tie switch, realizes the dimension reduction solution of a global dynamic reconstruction model through the distributed optimization of SOP multi-terminal multi-stage reconstruction, and can be applied to the optimized operation of the flexible interconnected power distribution network under the source-load imbalance development.
The technical scheme for solving the technical problems is as follows:
a multi-stage dynamic reconstruction method for a flexible interconnected power distribution network based on multi-terminal SOP comprises the following steps:
(1) Considering the power flow distribution improvement capability of the multi-terminal SOP, establishing a reconstruction level decision model considering the multi-terminal SOP, performing optimization decision on reconstruction level variables of each transformer substation and each transformer sub-area system, and dividing based on a reconstruction period to obtain a time-period reconstruction level identification result;
(2) Establishing a multi-stage dynamic reconstruction model by taking the minimum light abandoning, load loss, network loss and switching action cost as an optimization target based on the time-interval reconstruction level identification result obtained in the step (1);
(3) Aiming at a sub-region multistage dynamic reconstruction model with participation of a non-multi-terminal SOP flexible interconnection feeder line, a commercial solver CPLEX is adopted to directly solve to obtain a switching action scheme corresponding to a sub-region;
(4) Carrying out grid topology updating aiming at a multistage dynamic reconstruction model participated by a multi-terminal SOP flexible interconnection feeder line, establishing a large-scale sub-area system dynamic reconstruction distributed optimization problem containing a multi-terminal SOP, providing an SOP multi-terminal multistage dynamic reconstruction distributed optimization frame, coordinating each terminal through multi-terminal SOP active power transmission constraint, and carrying out global coordination and iterative solution on SOP multi-terminal multistage dynamic reconstruction by using an alternating direction multiplier method, thereby realizing the distributed optimization solution of the SOP multi-terminal multistage dynamic reconstruction problem and obtaining a switch action scheme of a corresponding area;
(5) And (5) integrating the optimization results of the step (3) and the step (4) to obtain a full-time switch action scheme of the whole network, and reducing light abandon and load loss under the development of source-load imbalance through coordination optimization of the interconnection switch and the multi-terminal SOP.
Further, in the multi-terminal SOP considered reconstruction level decision model in step (1), the reconstruction levels required by the transformer substation sub-regions and the transformer sub-regions in each time period are decided according to the characteristics of the net loads of the transformer substation sub-regions and the transformer sub-regions, so that the actual reconstruction levels of different transformer substations and transformers have certain differences, and the shortage of SOP load flow adjustment capability is made up by preferentially implementing feeder level reconstruction according to the space flexibility requirement of the net loads.
Further, the objective function of the multi-terminal SOP considered reconstruction level decision model is as follows:
1) Feeder level reconfiguration precedence
Carrying out cost quantification on implementation of transformer level reconstruction of the transformer substation sub-area system and implementation of feeder level reconstruction of the transformer sub-area system, and carrying out single-level cost c of the feeder level reconstruction FR Less than transformer level reconstruction c TR The reconstruction level cost is as follows:
Figure BDA0003920216590000021
in the formula:
Figure BDA0003920216590000022
representing subordinate substation sectionsCarrying out state identification of feeder level reconstruction by a transformer f at the point j;
Figure BDA0003920216590000023
representing the state identification of the transformer substation at the j node for transformer level reconstruction;
2) The light loss load of the multilevel reconstruction subregion system is minimum.
4. The multi-stage dynamic reconstruction method for the flexible interconnected power distribution network based on the multi-terminal SOP as claimed in claim 1, wherein the constraint conditions of the decision model for the reconstruction level considering the multi-terminal SOP are as follows:
1) Multi-terminal SOP operation constraints
Three-port SOP based on voltage source type converter is taken as a research object, and PQ-PQ-U is considered to be adopted dc The Q control mode provides active transmission regulation and reactive support functions, neglecting internal losses, and its operating constraints applicable to power distribution network optimization include active transmission constraints and capacity constraints, as follows:
Figure BDA0003920216590000024
Figure BDA0003920216590000025
Figure BDA0003920216590000026
Figure BDA0003920216590000027
in the formula:
Figure BDA0003920216590000028
and
Figure BDA0003920216590000029
respectively representing three-port SOP at nodes i and jThe active transmission value and the reactive injection value of the VSC at the k position;
Figure BDA00039202165900000210
and
Figure BDA00039202165900000211
respectively representing the installation capacities of three VSCs;
in order to quickly decide the reconstruction level requirements of each transformer substation and each transformer, the level decision model ignores network loss and SOP internal loss, and the subsequent decision level-based distributed SOP multi-terminal multi-level dynamic reconstruction ensures the effectiveness of a final switch action scheme;
the three-port SOP considers only the active transmission constraints as follows:
Figure BDA00039202165900000212
2) Reconstruction level decision constraints
The transformer level decision reconstructed by the sub-region of the transformer substation and the feeder level decision reconstructed by the sub-region of the transformer have coupling constraint, namely
Figure BDA00039202165900000213
When the temperature of the water is higher than the set temperature,
Figure BDA00039202165900000214
the value of f can only be 0 for any transformer belonging to the substation node j;
Figure BDA00039202165900000215
in the formula:
Figure BDA00039202165900000216
representing the total number of transformers belonging to the substation node j;
3) Multilevel reconstruction constraints
The transformer level reconstruction of the transformer substation sub-region system and the feeder level reconstruction of the transformer sub-region system are implemented by limiting action switch sets of transformer tie switches, feeder tie switches and section switches of all sub-regions through level decision variables, and simultaneously node power balance constraint, network reconstruction constraint, PV output constraint and loss load constraint are required to be met:
Figure BDA0003920216590000031
in the formula:
Figure BDA0003920216590000032
respectively representing the branch set and the total number of transformer interconnection switches of the j transformer substation;
Figure BDA0003920216590000033
and representing the branch set and the total number of feeder tie switches of the ith transformer of the j substation.
Further, the grid topology updating is performed on the multi-stage dynamic reconstruction model involving the multi-port SOP flexible interconnection feeder in step (4), that is, the grid topologies of the SOP multi-port multi-stage reconstruction are merged, the SOP operation constraint is increased, and the sub-region dynamic reconstruction model including the multi-port SOP is established, which specifically includes:
by taking a subregion system comprising a multi-terminal SOP and a level reconstruction region identified by each terminal as a reconstruction research object, photovoltaic high-proportion consumption and reliable load power supply are realized by optimizing the state combination of various tie switches and section switches in the region, and the objective function is as follows:
Figure BDA0003920216590000034
Figure BDA0003920216590000035
Figure BDA0003920216590000036
Figure BDA0003920216590000037
Figure BDA0003920216590000038
in the formula:
Figure BDA0003920216590000039
an objective function, T, representing the dynamic reconstruction of a sub-region of class c time-segments containing multi-terminal SOPs C Represents a set of periods belonging to class c; e SW,Feed 、E SW,Trans 、E、B、B PV Correspondingly adjusting according to the differential reconstruction level requirements of the flexible interconnection feeder line at each end of the SOP;
Figure BDA00039202165900000310
and
Figure BDA00039202165900000311
the single operation cost of the feeder line connection switch, the transformer connection switch and the section switch respectively,
Figure BDA00039202165900000312
a switch state change flag representing branch ij;
the constraint conditions comprise second-order cone current constraint, safety constraint, network reconstruction constraint, PV output constraint, power supply constraint of a transformer substation and loss load constraint.
Further, the SOP multi-end multi-stage dynamic reconstruction distributed optimization framework of step (4) specifically includes:
the three-port SOP terminal area system may have differentiated net load transfer requirements under the condition that the connected feeders are flexibly interacted, assuming that the reconstruction level identification results of the sub-areas 1, 2 and 3 are respectively transformer level, feeder level and no reconstruction is needed, the active transmission is adjusted through the SOP to further expand the power flow distribution regulation range so as to ensure that no light abandoning and no load losing of the sub-areas 1, 2 and 3 occur; distributed optimization is carried out on dynamic reconstruction of a large-scale sub-region system containing a multi-terminal SOP, required level reconstruction is carried out on each terminal region, and global information updating is carried out through VSC transmission active power of the SOP until active power transmission meets a convergence condition;
when distributed optimization is carried out, the reconstruction scheme of the corresponding level requirement is made respectively in the minimum objective function in the region in each terminal region of the SOP, coupling consistency constraint is carried out between each level reconstruction of the end through VSC active transmission power, only VSC transmission active power on respective boundaries needs to be exchanged between the regions, multi-terminal multi-level reconstruction scheme decision under the SOP active balance constraint can be met, and a multi-level reconstruction model under a distributed optimization framework is expressed as follows:
Figure BDA0003920216590000041
s.t.G e (x e )≤0 (7)
H e (x e )＝0 (8)
Figure BDA0003920216590000042
wherein: expression (6) represents an objective function of level reconstruction corresponding to each terminal area, wherein the objective function comprises abandoned light, lost load, network loss and switching operation cost, and is similar to expressions (2) to (5); equations (7) and (8) are feasible fields of decision variables; equation (9) represents the consistency constraint of the reconstruction scheme of each terminal region, which is applied to global variable update of the following alternative direction multiplier method, and the left side of the equation is the local optimization variable of each sub-region, namely the active power flowing through the VSC where each sub-region is connected with the SOP
Figure BDA0003920216590000043
To the right of the equation is the global variable updated by iteration, for each terminal region of the SOP
Figure BDA0003920216590000044
And at the same time.
Further, the step (4) performs global coordination and iterative solution on the SOP multi-terminal multi-stage dynamic reconstruction by using an alternating direction multiplier method, so as to implement distributed optimal solution of the SOP multi-terminal multi-stage dynamic reconstruction problem, specifically including:
using said distributed optimization framework to reconstruct the model in multiple stages
Figure BDA0003920216590000045
By addition of lagrange multipliers to
Figure BDA0003920216590000046
In the method, the obtained augmented Lagrange function is as follows:
Figure BDA0003920216590000047
wherein λ is e,t Representing penalty factors for dual variables and rho, and obtaining SOP transmission active x by multilevel reconstruction optimization decision of each subarea e,t Providing a consistent variable updating basis for the exchange variable in the optimization process and the next iteration of the alternative direction multiplier method, wherein the global variable is
Figure BDA0003920216590000048
The updates of (2) are as follows:
Figure BDA0003920216590000049
with the gradual convergence of the original residual error and the dual residual error, the multi-stage reconstruction optimization at each end of the SOP gradually meets the SOP active power balance constraint, and the original residual error and the dual residual error after the nth iteration are respectively as follows:
Figure BDA0003920216590000051
Figure BDA0003920216590000052
the SOP multi-terminal multi-stage reconstruction distributed optimization solving method based on the alternating direction multiplier method comprises the following steps:
1) Initialization: setting the number of iterations n =0, given each sub-region λ e,t And global variable
Figure BDA0003920216590000053
And setting the maximum iteration number N and the convergence error epsilon;
2) Information exchange and update: each sub-region e receives the exchange variables of other sub-regions connected with the SOP and updates the consistency constraint variables;
3) And (3) multi-level reconstruction scheme decision: based on
Figure BDA0003920216590000054
Carrying out parallel decision on the multi-stage reconstruction optimization scheme of each terminal area of the SOP to obtain a new exchange variable x e,t ；
4) Checking whether convergence occurs: calculating the original residual error and the dual residual error of each sub-region based on the above formula if delta n,max If the number is less than epsilon, stopping iteration and outputting a decision result of each sub-region reconstruction scheme; otherwise, turning to the step 5);
5) Updating dual variables: each sub-area is updated simultaneously:
Figure BDA0003920216590000055
6) n = n +1, return to step 2).
The invention has the beneficial effects that: the invention explores a multi-stage dynamic reconstruction method of a flexible interconnected power distribution network, preferentially considers the real-time adjustment capability of the flow distribution of a multi-terminal SOP in a transformer substation level, identifies the reconstruction level of each transformer substation and a transformer sub-area, updates the network frame topology of the multi-stage reconstruction in which the flexible interconnected feeder participates, finally realizes the distributed optimization solution of the multi-stage dynamic reconstruction of the SOP based on an alternative direction multiplier method, and obviously reduces the difficulty of solving the flexible interconnected power distribution network by adopting a traditional centralized dynamic reconstruction model.
Drawings
FIG. 1 is a schematic flow chart of a flexible interconnected power distribution network multi-stage dynamic reconstruction method of the invention;
FIG. 2 is a SOP multi-terminal multi-level dynamic reconfiguration distributed optimization framework diagram of the present invention;
FIG. 3 is a reconstruction level recognition result considering multi-terminal SOP according to the present invention;
FIG. 4 is a time-phased reconstruction level recognition result considering multi-terminal SOP according to the present invention;
FIG. 5 shows the optimization result of multi-terminal SOP active power transmission according to the present invention;
FIG. 6 is a graph of error versus iteration number for the present invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth to illustrate, but are not to be construed to limit the scope of the invention.
As shown in fig. 1, an embodiment of the present invention provides a multi-stage dynamic reconstruction method for a flexible interconnected power distribution network based on a multi-terminal SOP, which considers the power flow distribution improvement capability of the multi-terminal SOP, establishes a reconstruction level decision model considering the multi-terminal SOP, performs an optimization decision on reconstruction level variables of each substation and each transformer sub-area system, and obtains a time-period reconstruction level recognition result based on reconstruction time period division; establishing a multi-stage dynamic reconstruction model by taking the minimum light abandoning cost, the minimum load loss cost, the minimum network loss cost and the minimum switch action cost as optimization targets based on the level identification result; aiming at a sub-region multilevel dynamic reconstruction model with participation of a non-multi-terminal SOP flexible interconnection feeder line, a commercial solver CPLEX is adopted to directly solve to obtain a switching action scheme corresponding to a sub-region; carrying out network frame topology updating aiming at a multi-stage dynamic reconstruction model participated by a multi-terminal SOP flexible interconnected feeder line, establishing a large-scale sub-area system dynamic reconstruction distributed optimization problem containing a multi-terminal SOP, providing an SOP multi-terminal multi-stage dynamic reconstruction distributed optimization framework, coordinating each terminal through multi-terminal SOP active power transmission constraint, and carrying out global coordination and iterative solution on SOP multi-terminal multi-stage dynamic reconstruction by using an alternating direction multiplier method, thereby realizing distributed optimization solution of the SOP multi-terminal multi-stage dynamic reconstruction problem, and synthesizing the optimization results to obtain a full-time switch action scheme of the whole network; and verifying the effectiveness of the flexible interconnected power distribution network multistage dynamic reconstruction method based on an example system.
The reconstruction level decision model considering the multi-terminal SOP makes up the deficiency of the SOP load flow adjustment capability by preferentially implementing feeder level reconstruction.
The objective function of the multi-terminal SOP considered reconstruction level decision model is as follows:
1) Feeder level reconfiguration precedence
Carrying out cost quantification on implementation of transformer level reconstruction of the transformer substation sub-area system and implementation of feeder level reconstruction of the transformer sub-area system, and carrying out single-level cost c of the feeder level reconstruction FR Less than transformer level reconstruction c TR The reconstruction level cost is as follows:
Figure BDA0003920216590000061
in the formula:
Figure BDA0003920216590000062
the state identification of the feeder level reconstruction of the transformer f representing the node j of the subordinate transformer substation is represented;
Figure BDA0003920216590000063
and representing the state identification of the transformer substation at the j node for transformer level reconstruction.
2) Minimum light loss load of multistage reconstruction subregion system
The constraint conditions of the multi-terminal SOP considered reconstruction level decision model are as follows:
1) Multi-terminal SOP operation constraints
The three-port SOP based on the voltage source type converter is taken as a research object, and PQ-PQ-U is considered to be adopted dc The Q control mode provides active transmission regulation and reactive support functions, neglecting internal losses, and its operating constraints suitable for power distribution network optimization include active transmission constraints andcapacity constraints, respectively as follows:
Figure BDA0003920216590000064
Figure BDA0003920216590000065
Figure BDA0003920216590000066
Figure BDA0003920216590000067
in the formula:
Figure BDA0003920216590000068
and
Figure BDA0003920216590000069
respectively representing the active transmission value and the reactive injection value of VSC of the three-port SOP at nodes i, j and k;
Figure BDA00039202165900000610
and
Figure BDA00039202165900000611
representing the mounting capacity of three VSCs, respectively. In order to quickly decide the reconstruction level requirements of each transformer substation and each transformer, the level decision model ignores network loss and SOP internal loss, and the validity of a final switch action scheme is ensured through subsequent decision level-based distributed SOP multi-terminal multi-level dynamic reconstruction;
the three-port SOP considers only the active transmission constraints as follows:
Figure BDA00039202165900000612
2) Reconstruction level decision constraints
The transformer level decision reconstructed by the sub-region of the transformer substation and the feeder level decision reconstructed by the sub-region of the transformer have coupling constraint, namely
Figure BDA00039202165900000613
When the temperature of the water is higher than the set temperature,
Figure BDA00039202165900000614
the value of f can only be 0 for any transformer belonging to the substation node j;
Figure BDA0003920216590000071
in the formula:
Figure BDA0003920216590000072
representing the total number of transformers belonging to the substation node j;
3) Multilevel reconstruction constraints
The transformer level reconstruction of the transformer substation sub-region system and the feeder level reconstruction of the transformer sub-region system are implemented by limiting action switch sets of transformer tie switches, feeder tie switches and section switches of all sub-regions through level decision variables, and simultaneously node power balance constraint, network reconstruction constraint, PV output constraint and loss load constraint are required to be met:
Figure BDA0003920216590000073
in the formula:
Figure BDA0003920216590000074
respectively representing the branch set and the total number of transformer interconnection switches of the j transformer substation;
Figure BDA0003920216590000075
and representing the branch set and the total number of feeder tie switches of the ith transformer of the j substation.
And updating the net rack topology:
feeder loads connected to each end of the SOP may have different levels of power flow transfer requirements, and the precise power flow control function of the SOP cannot be exerted by performing distributed multi-level reconstruction, namely, flexible interaction of a plurality of feeder loads cannot be performed at a transformer substation level. Therefore, the grid topologies of the SOP multi-end multi-stage reconstruction need to be merged, SOP operation constraints are increased, and a sub-region dynamic reconstruction model including the multi-end SOP is established.
As shown in fig. 2, VSCs of three-port SOPs are respectively connected to nodes i, j, and k of feeders S1T11, S2T22, and S3T22, and under the development of source-load imbalance, the reconstruction level requirement of the substation S1 to which the feeder S1T11 belongs is a transformer level, the reconstruction level requirement of the transformer S2T2 to which the feeder S2T22 belongs is a feeder level, and the power supply reliability can be ensured without reconstructing the transformer S3T2 to which the feeder S3T22 belongs. Considering the substation-level real-time power flow transfer capability of the three-port SOP, the S1 transformer-level reconstruction, the S2T2 feeder-level reconstruction and the S3T22 non-reconstruction optimization after level decision are updated to a sub-area dynamic reconstruction optimization model containing the S2 sub-area, the S2T2 sub-area, the feeder S3T22 and the three-port SOP, namely a region 0 dynamic reconstruction model in the graph.
And with the area 0 as a reconstruction research object, photovoltaic high-proportion consumption and reliable load power supply are realized by optimizing the state combination of various tie switches and section switches in the area. The objective function is as follows:
Figure BDA0003920216590000076
Figure BDA0003920216590000077
Figure BDA0003920216590000078
Figure BDA0003920216590000081
Figure BDA0003920216590000082
in the formula:
Figure BDA0003920216590000083
target function, T, representing dynamic reconstruction of region 0 containing multi-terminal SOP in class c time period C Represents a set of periods belonging to class c; e SW,Feed 、E SW,Trans 、E、B、B PV Correspondingly adjusting according to the differential reconstruction level requirements of the flexible interconnection feeder line at each end of the SOP;
Figure BDA0003920216590000084
and
Figure BDA0003920216590000085
the single operation cost of the feeder line connection switch, the transformer connection switch and the section switch respectively,
Figure BDA0003920216590000086
indicating the switch state change flag for branch ij.
The constraint conditions include second-order cone current constraint, safety constraint, network reconstruction constraint, PV output constraint, power supply constraint of the transformer substation and loss load constraint, which are not described herein again.
The SOP multi-terminal multi-stage dynamic reconstruction distributed optimization framework comprises the following steps:
three-port SOP terminal area systems may still have differentiated payload transfer requirements under flexible interaction of connected feeders. Taking the reconstruction level identification results of the sub-regions 1, 2 and 3 as a transformer level, a feeder level and no need of reconstruction as an example, the active transmission is adjusted through SOP to further expand the power flow distribution regulation range, so that no light abandonment or load loss occurs in the sub-regions 1, 2 and 3. Because the feeder lines of the sub-regions 1, 2 and 3 are flexibly interconnected through the SOP, decoupling solution cannot be realized through multi-stage reconstruction, and the solution difficulty of the dynamically reconstructed model of the region 0 after topology updating is obviously increased. However, the SOP based on the fully-controlled power electronic device is decoupled on the direct current side, so that the circulating current caused by the closed-loop operation of the traditional switch is avoided, and the operation constraint of the SOP has no influence on the network radiation constraint of each terminal area. Therefore, distributed optimization can be carried out on the dynamic reconfiguration of a large-scale sub-region system containing the multi-terminal SOP, the required level reconfiguration is carried out on each terminal region, and global information updating is carried out through VSC transmission active power of the exchange SOP until the active power transmission meets the convergence condition.
When distributed optimization is carried out, reconstruction schemes corresponding to level requirements are made in each terminal area of the SOP according to the minimum objective function in the area, coupling consistency constraint is carried out between level reconstruction of each end through VSC active transmission power, only VSC transmission active power on each boundary needs to be exchanged between the areas, and multi-terminal multi-level reconstruction scheme decision under the SOP active power balance constraint can be met. The multilevel reconstruction model under the distributed optimization framework provided by the invention can be expressed as follows:
Figure BDA0003920216590000087
s.t.G e (x e )≤0 (7)
H e (x e )＝0 (8)
Figure BDA0003920216590000088
wherein: expression (6) represents an objective function of level reconstruction corresponding to each terminal area, wherein the objective function comprises abandoned light, lost load, network loss and switching operation cost, and is similar to expressions (2) to (5); equations (7) and (8) are feasible fields of decision variables; equation (9) represents the consistency constraint of the reconfiguration scheme of each terminal region, which is applied to the global variable update of the following alternating direction multiplier method, and the left side of the equation is the local optimization variable of each sub-region, that is, the active power flowing through the VSC where each sub-region is connected with the SOP
Figure BDA0003920216590000089
Equation right side is followingWith iteratively updated global variables, from terminal area to terminal area of SOP
Figure BDA00039202165900000810
And at the same time.
The SOP multi-terminal multi-stage dynamic reconstruction distributed optimization solving method based on the alternating direction multiplier method comprises the following steps:
the model is reconstructed in multiple stages under the distributed optimization framework
Figure BDA00039202165900000811
By addition of lagrange multipliers to
Figure BDA0003920216590000091
In the method, the obtained augmented Lagrange function is as follows:
Figure BDA0003920216590000092
wherein λ is e,t Representing a penalty factor for dual variables and rho, and obtaining SOP transmission active x by multilevel reconstruction optimization decision of each subarea e,t Providing a consistent variable updating basis for the exchange variable in the optimization process and the next iteration of the alternative direction multiplier method, wherein the global variable is
Figure BDA0003920216590000093
The updates of (2) are as follows:
Figure BDA0003920216590000094
with the gradual convergence of the original residual error and the dual residual error, the multi-stage reconstruction optimization at each end of the SOP gradually meets the SOP active power balance constraint, and the original residual error and the dual residual error after the nth iteration are respectively as follows:
Figure BDA0003920216590000095
Figure BDA0003920216590000096
the SOP multi-terminal multi-stage reconstruction distributed optimization solving method based on the alternating direction multiplier method comprises the following steps:
1) Initialization: setting the number of iterations n =0, given each sub-region λ e,t And global variable
Figure BDA0003920216590000097
And setting the maximum iteration number N and the convergence error epsilon;
2) Information exchange and update: each sub-region e receives the exchange variables of other sub-regions connected with the SOP and updates the consistency constraint variables;
3) And (3) multi-level reconstruction scheme decision: based on
Figure BDA0003920216590000098
Carrying out parallel decision on the multi-stage reconstruction optimization scheme of each terminal area of the SOP to obtain a new exchange variable x e,t ；
4) Checking whether convergence occurs: calculating the original residual error and the dual residual error of each sub-region based on the above formula if delta n,max If the number is less than epsilon, stopping iteration and outputting a decision result of each sub-region reconstruction scheme; otherwise, turning to the step 5);
5) Updating dual variables: each sub-area is updated simultaneously:
Figure BDA0003920216590000099
6) n = n +1, return to step 2).
Example verification analysis:
based on an improved actual 330 node system, a multi-stage dynamic reconstruction method of the flexible interconnected power distribution network is verified and analyzed on an MATLAB 2016a simulation platform with a CPLEX commercial solver and a YALMIP toolbox. The calculation system consists of three substations, six transformers, twelve feeders and a three-terminal SOP.
And (3) considering the reconstruction level optimization decision of the multi-terminal SOP flow distribution improvement capacity:
as shown in fig. 3, in an original single network topology, a three-port SOP can effectively reduce the light abandoning amount in 9 to 15 periods by controlling the active transmission of a feeder line connected to each port in real time, but the light abandoning and load losing phenomena cannot be completely avoided only by the flexible adjustment function of the three-port SOP, and load balancing needs to be performed by power flow transfer of a feeder line level and a transformer level. And (4) considering the load balancing capability of the three-port SOP at the substation level, and performing optimization decision on the reconstruction level variables of each substation and each transformer subregion system. Therefore, only the transformer substations S2 and S3 have the requirement of transformer level reconstruction in the period of 8-9 in the whole period. The level requirement after time interval division is shown in fig. 4, and the solving difficulty is further reduced for distributed SOP multi-terminal multi-level dynamic reconstruction.
SOP multi-end multi-stage dynamic reconstruction distributed optimization results:
under the time-interval reconstruction level identification result shown in fig. 4, distributed optimization solution needs to be performed on the SOP multi-terminal multi-level dynamic reconstruction in all the 2 nd, 3 rd and 4 th time intervals. Taking the 4 th class of time period as an example, the SOP multi-terminal multi-stage dynamic reconstruction adopts the alternate direction multiplier method to solve the SOP three-port active power transmission optimization result as shown in fig. 5, with the increase of the iteration times, each sub-region continuously updates the boundary transmission active power, finally meets the SOP active power balance constraint within the error allowable range, and realizes the respective reconstruction scheme optimization decision. A class 4 time-segment distributed optimization residual iteration curve at penalty factor ρ =2 is shown in fig. 6. It can be seen that, as the number of iterations increases, the original residual and the dual residual converge gradually, and the convergence accuracy requirement of 1e-4 is reached within 30 times.
The full-time switch action scheme is as follows:
the full-time switch action scheme is shown in the following table 1, the light rejection and load loss level under the source-load imbalance development can be remarkably reduced through the coordinated optimization of the multi-terminal SOP and the traditional interconnection switch, and the light rejection and load loss are respectively reduced to 0.2094MWh and 0MWh from the original 14.3267MWh and 5.4334 MWh.
TABLE 1 switching scheme
Figure BDA0003920216590000101
The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims (7)

1. A multi-stage dynamic reconstruction method for a flexible interconnected power distribution network based on multi-terminal SOP is characterized by comprising the following steps:
(1) Considering the power flow distribution improvement capacity of the multi-terminal SOP, establishing a reconstruction level decision model considering the multi-terminal SOP, performing optimization decision on reconstruction level variables of each transformer substation and each transformer subregion system, and dividing based on reconstruction time periods to obtain a time-period reconstruction level identification result;
(2) Establishing a multi-stage dynamic reconstruction model by taking the minimum light abandoning, load loss, network loss and switching action cost as an optimization target based on the time-interval reconstruction level identification result obtained in the step (1);
(3) Aiming at a sub-region multilevel dynamic reconstruction model with participation of a non-multi-terminal SOP flexible interconnection feeder line, a commercial solver CPLEX is adopted to directly solve to obtain a switching action scheme corresponding to a sub-region;
(4) Carrying out grid topology updating aiming at a multistage dynamic reconstruction model participated by a multi-terminal SOP flexible interconnection feeder line, establishing a large-scale sub-area system dynamic reconstruction distributed optimization problem containing a multi-terminal SOP, providing an SOP multi-terminal multistage dynamic reconstruction distributed optimization frame, coordinating each terminal through multi-terminal SOP active power transmission constraint, and carrying out global coordination and iterative solution on SOP multi-terminal multistage dynamic reconstruction by using an alternating direction multiplier method, thereby realizing the distributed optimization solution of the SOP multi-terminal multistage dynamic reconstruction problem and obtaining a switch action scheme of a corresponding area;
(5) And (4) integrating the optimization results of the step (3) and the step (4) to obtain a full-time switch action scheme of the whole network, and reducing light abandon and load loss under the source-load imbalance development through coordinated optimization of the interconnection switch and the multi-terminal SOP.
2. The multi-stage dynamic reconfiguration method for the flexible interconnected power distribution network based on the multi-terminal SOP is characterized in that,
in the multi-terminal SOP considered reconstruction level decision model in the step (1), the reconstruction levels required by the transformer substation sub-regions and the transformer sub-regions in each period are decided according to the characteristics of the net loads of the transformer substation sub-regions and the transformer sub-regions, so that the actual reconstruction levels of different transformer substations and transformers have certain difference, and the shortage of the SOP load flow adjustment capacity is made up by preferentially implementing feeder level reconstruction aiming at the space flexibility requirement of the net loads.
3. The multi-terminal SOP-based flexible interconnected power distribution network multi-level dynamic reconstruction method according to claim 1, wherein an objective function of the multi-terminal SOP-considering reconstruction level decision model is as follows:
1) Feeder level reconfiguration precedence
Carrying out cost quantification on implementation of transformer level reconstruction of the transformer substation sub-area system and implementation of feeder level reconstruction of the transformer sub-area system, and carrying out single-level cost c of the feeder level reconstruction FR Less than transformer level reconstruction c TR The reconstruction level cost is as follows:
Figure FDA0003920216580000011
in the formula:
Figure FDA0003920216580000012
the state identification of the feeder level reconstruction of the transformer f representing the node j of the subordinate transformer substation is represented;
Figure FDA0003920216580000013
representing transformer level reconstruction at j-node substationThe status of (2);
2) The light loss load of the multilevel reconstruction subregion system is minimum.
4. The multi-terminal SOP-based flexible interconnected power distribution network multi-level dynamic reconstruction method according to claim 1, wherein the constraint conditions of the multi-terminal SOP-considering reconstruction level decision model are as follows:
1) Multi-terminal SOP operation constraints
The three-port SOP based on the voltage source type converter is taken as a research object, and PQ-PQ-U is considered to be adopted dc The Q control mode provides active transmission regulation and reactive support functions, neglecting internal losses, and its operating constraints applicable to power distribution network optimization include active transmission constraints and capacity constraints, as follows:
Figure FDA0003920216580000014
Figure FDA0003920216580000021
Figure FDA0003920216580000022
Figure FDA0003920216580000023
in the formula: p i SOP 、
Figure FDA0003920216580000024
And
Figure FDA0003920216580000025
respectively representing the active transmission value and the reactive injection value of VSC of the three-port SOP at nodes i, j and k;
Figure FDA0003920216580000026
and
Figure FDA0003920216580000027
respectively representing the installation capacities of three VSCs;
in order to quickly decide the reconstruction level requirements of each transformer substation and each transformer, the level decision model ignores network loss and SOP internal loss, and the subsequent decision level-based distributed SOP multi-terminal multi-level dynamic reconstruction ensures the effectiveness of a final switch action scheme;
the three-port SOP considers only the active transmission constraints as follows:
Figure FDA0003920216580000028
2) Reconstruction level decision constraints
The transformer level decision reconstructed by the sub-region of the transformer substation and the feeder level decision reconstructed by the sub-region of the transformer have coupling constraint, namely
Figure FDA0003920216580000029
When the temperature of the water is higher than the set temperature,
Figure FDA00039202165800000210
the value of f can only be 0 for any transformer belonging to the substation node j;
Figure FDA00039202165800000211
in the formula:
Figure FDA00039202165800000212
representing the total number of transformers belonging to the substation node j;
3) Multilevel reconstruction constraints
The transformer level reconstruction of the transformer substation sub-region system and the feeder level reconstruction of the transformer sub-region system are implemented by limiting action switch sets of transformer tie switches, feeder tie switches and section switches of all sub-regions through level decision variables, and simultaneously node power balance constraint, network reconstruction constraint, PV output constraint and loss load constraint are required to be met:
Figure FDA00039202165800000213
in the formula:
Figure FDA00039202165800000214
respectively representing the branch set and the total number of transformer interconnection switches of the j transformer substation;
Figure FDA00039202165800000215
and representing the branch set and the total number of feeder tie switches of the ith transformer of the j substation.
5. The multi-stage dynamic reconfiguration method for the flexible interconnected power distribution network based on the multi-terminal SOP is characterized in that,
the grid topology updating is performed on the multi-stage dynamic reconstruction model involving the multi-terminal SOP flexible interconnection feeder line in the step (4), the grid topologies of the SOP multi-terminal multi-stage reconstruction are merged, SOP operation constraints are increased, and a sub-region dynamic reconstruction model containing the multi-terminal SOP is established, and the method specifically comprises the following steps:
by taking a subregion system comprising a multi-terminal SOP and a level reconstruction region identified by each terminal as a reconstruction research object, photovoltaic high-proportion consumption and reliable load power supply are realized by optimizing the state combination of various tie switches and section switches in the region, and the objective function is as follows:
Figure FDA0003920216580000031
Figure FDA0003920216580000032
Figure FDA0003920216580000033
Figure FDA0003920216580000034
Figure FDA0003920216580000035
in the formula:
Figure FDA0003920216580000036
an objective function, T, representing the dynamic reconstruction of a sub-region of class c time-segments containing multi-terminal SOPs C Represents a set of periods belonging to class c; e SW,Feed 、E SW,Trans 、E、B、B PV Correspondingly adjusting according to the differential reconstruction level requirements of the flexible interconnection feeder line at each end of the SOP;
Figure FDA0003920216580000037
and
Figure FDA0003920216580000038
the single operation cost of the feeder line connection switch, the transformer connection switch and the section switch respectively,
Figure FDA0003920216580000039
a switch state change flag representing branch ij;
the constraint conditions comprise second-order cone current constraint, safety constraint, network reconstruction constraint, PV output constraint, power supply constraint of a transformer substation and loss load constraint.
6. The multi-stage dynamic reconfiguration method for the flexible interconnected power distribution network based on the multi-terminal SOP is characterized in that,
the SOP multi-end multi-stage dynamic reconstruction distributed optimization framework in the step (4) specifically comprises the following steps:
under the condition that the feeder lines connected to the terminal area systems of the three-port SOP are flexibly interacted, the requirement for differential net load transfer possibly exists, the reconstruction level identification results of the sub-areas 1, 2 and 3 are respectively transformer level, feeder line level and no reconstruction is needed, the active transmission is adjusted through the SOP to further expand the power flow distribution adjusting range, and therefore the sub-areas 1, 2 and 3 are guaranteed not to have light abandoning and load losing; distributed optimization is carried out on dynamic reconstruction of a large-scale sub-region system containing a multi-terminal SOP, required level reconstruction is carried out on each terminal region, and global information updating is carried out through VSC transmission active power of the SOP until active power transmission meets a convergence condition;
when distributed optimization is carried out, the reconstruction scheme of the corresponding level requirement is made respectively in the minimum objective function in the region in each terminal region of the SOP, coupling consistency constraint is carried out between each level reconstruction of the end through VSC active transmission power, only VSC transmission active power on respective boundaries needs to be exchanged between the regions, multi-terminal multi-level reconstruction scheme decision under the SOP active balance constraint can be met, and a multi-level reconstruction model under a distributed optimization framework is expressed as follows:
Figure FDA00039202165800000310
s.t.G e (x e )≤0 (7)
H e (x e )＝0 (8)
Figure FDA0003920216580000041
wherein: expression (6) represents an objective function of level reconstruction corresponding to each terminal area, wherein the objective function comprises abandoned light, lost load, network loss and switching operation cost, and is similar to expressions (2) to (5); formula (7) and formula (8) Is a feasible field of decision variables; equation (9) represents the consistency constraint of the reconstruction scheme of each terminal region, which is applied to global variable update of the following alternative direction multiplier method, and the left side of the equation is the local optimization variable of each sub-region, namely the active power flowing through the VSC where each sub-region is connected with the SOP
Figure FDA0003920216580000042
To the right of the equation is the global variable updated by iteration, for each terminal region of the SOP
Figure FDA0003920216580000043
And at the same time.
7. The multi-stage dynamic reconfiguration method for the flexible interconnected power distribution network based on the multi-terminal SOP is characterized in that,
the step (4) utilizes an alternating direction multiplier method to carry out global coordination and iterative solution on the SOP multi-terminal multi-stage dynamic reconstruction, so that the distributed optimization solution of the SOP multi-terminal multi-stage dynamic reconstruction problem is realized, and the method specifically comprises the following steps:
using said distributed optimization framework to reconstruct the model in multiple stages
Figure FDA0003920216580000044
By addition of lagrange multipliers to
Figure FDA0003920216580000045
In the method, the obtained augmented Lagrange function is as follows:
Figure FDA0003920216580000046
wherein λ is e,t Representing a penalty factor for dual variables and rho, and obtaining SOP transmission active x by multilevel reconstruction optimization decision of each subarea e,t Providing a consistent variable updating basis for the exchange variable in the optimization process and the next iteration of the alternative direction multiplier method, and obtaining a global variable
Figure FDA0003920216580000047
The updates of (2) are as follows:
Figure FDA0003920216580000048
with the gradual convergence of the original residual error and the dual residual error, the multi-stage reconstruction optimization at each end of the SOP gradually meets the SOP active power balance constraint, and the original residual error and the dual residual error after the nth iteration are respectively as follows:
Figure FDA0003920216580000049
Figure FDA00039202165800000410
the SOP multi-terminal multi-stage reconstruction distributed optimization solving method based on the alternating direction multiplier method comprises the following steps:
1) Initialization: setting the number of iterations n =0, given each sub-region λ e,t And global variable
Figure FDA00039202165800000411
And setting the maximum iteration number N and the convergence error epsilon;
2) Information exchange and update: each sub-region e receives the exchange variables of other sub-regions connected with the SOP and updates the consistency constraint variables;
3) And (3) multi-level reconstruction scheme decision: based on
Figure FDA00039202165800000412
Carrying out parallel decision on the multi-stage reconstruction optimization scheme of each terminal area of the SOP to obtain a new exchange variable x e,t ；
4) Checking whether convergence occurs: calculating the original residual error and the dual residual error of each sub-region based on the above formula if delta n,max If the number is less than epsilon, stopping iteration and outputting a decision result of each sub-region reconstruction scheme; otherwise, turning to the step 5);
5) Updating dual variables: each sub-area is updated simultaneously:
Figure FDA0003920216580000051
6) n = n +1, return to step 2).
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116054210A (en) * 2023-03-30 2023-05-02 湖南大学 F-SOP-based flexible interconnection low-voltage distribution transformer area three-phase imbalance optimization regulation and control method
CN116108322A (en) * 2023-04-10 2023-05-12 北京智中能源科技发展有限公司 Method for calculating maximum load transfer capacity of power distribution network

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116054210A (en) * 2023-03-30 2023-05-02 湖南大学 F-SOP-based flexible interconnection low-voltage distribution transformer area three-phase imbalance optimization regulation and control method
CN116054210B (en) * 2023-03-30 2023-06-20 湖南大学 F-SOP-based flexible interconnection low-voltage distribution transformer area three-phase imbalance optimization regulation and control method
CN116108322A (en) * 2023-04-10 2023-05-12 北京智中能源科技发展有限公司 Method for calculating maximum load transfer capacity of power distribution network

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