CN113078678A - DG and SOP active-reactive collaborative planning method and device - Google Patents

DG and SOP active-reactive collaborative planning method and device Download PDF

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CN113078678A
CN113078678A CN202110395633.7A CN202110395633A CN113078678A CN 113078678 A CN113078678 A CN 113078678A CN 202110395633 A CN202110395633 A CN 202110395633A CN 113078678 A CN113078678 A CN 113078678A
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sop
reactive
active
power
constraint
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CN113078678B (en
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李勇
乔学博
姚天宇
马俊杰
罗隆福
曹一家
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Hunan University
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Hunan University
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/007—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources
    • H02J3/0073—Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing alternative feeding paths between load and source when the main path fails, e.g. transformers, busbars
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
    • H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]

Abstract

The embodiment of the invention provides a DG and SOP active-reactive collaborative planning method and a device, aiming at the distribution network distributed power supply planning, the method and the device can effectively utilize various active management measures, plan the installation position and the capacity of the SOP, improve the utilization rate of each device in a distribution system and improve the consumption capacity of the distribution network to the distributed power supply; by adopting the rural power grid safety boundary model, the planning capacity and the position of a distributed power supply in the power distribution network can be effectively restrained, the normal power supply of the power distribution system can be ensured in an N-1 state, and the reliability of the power distribution network is improved; by utilizing the linearization processing of the model, the calculation efficiency of the model can be greatly improved on the premise of reducing the error as much as possible.

Description

DG and SOP active-reactive collaborative planning method and device
Technical Field
The embodiment of the invention relates to the field of planning of a high-permeability renewable energy power distribution network, in particular to a DG and SOP active-reactive collaborative planning method and device.
Background
The access of high permeability renewable energy sources presents significant challenges to power distribution system planning and operation. On one hand, access of a large number of Distributed Generators (DG) can cause safety problems such as voltage fluctuation and voltage out-of-limit; on the other hand, the consumption of the DGs is severely limited by unreasonable DG planning configuration, lack of power distribution network regulation capacity, low utilization rate of power distribution equipment and the like. And the massive access of power electronic equipment makes the distribution network present the development trend of power electronization, and its rapid development provides new thinking for solving above-mentioned problem.
The intelligent Soft Switch (SOP) is used as a novel power electronic device to replace a tie switch of a multi-section distribution line, the power continuous non-differential regulation characteristic of the intelligent Soft switch can realize real-time power regulation among feeders, the power flow distribution of a system is changed, and the flexibility of a distribution network is improved. The SOP is based on a full-control power electronic device, has no mechanical operation, has higher action speed and can respond to a control command in real time. And a direct current isolation link is arranged between two SOP connected feeders, so that fault current is cut off more easily when a fault occurs, and the fault influence can be reduced. The technical advantages enable the SOP to have great development potential in the power distribution network. Therefore, the research on the collaborative planning method of the distributed power supply and the intelligent soft switch active and reactive power system has important engineering significance.
The existing distribution network planning method considering the safety boundary theory of the distribution network comprises the following steps: the method is based on a random planning method of a power distribution network with a safety distance, and multi-target DG (distributed generation) locating and sizing planning considering N-1 safety. The safety boundary model is an approximately linearized safety boundary in a direct current distribution network, and is more applied to urban distribution networks. The line loss in the rural power distribution network is serious, and particularly, when a large number of distributed power sources are applied to the rural power distribution network, the line loss has certain influence on the safety of the system.
The difference between the rural power network and the urban power network provides a new idea for DG planning in the rural power distribution network, as shown in FIG. 1. A DG and an active control means are not provided in a traditional power distribution network, so that the planning method only considers the voltage and current constraints of the power distribution network. With the change of the structure and the operation mode of the power grid, the planning mode becomes complicated, but the planning method only considers the consumption capability of the distribution network to the DG under the normal operation state.
Disclosure of Invention
The embodiment of the invention provides a DG and SOP active-reactive collaborative planning method and device, and aims to solve the problems of low DG consumption capability and poor safety and reliability of a power distribution network caused by neglecting the influence of power electronic equipment and a safety boundary in the power distribution network on planning in the planning process of the conventional distributed power supply.
In a first aspect, an embodiment of the present invention provides a DG and SOP active-reactive collaborative planning method, including:
step S1, determining typical time sequence correlation scenes of a plurality of preset time scales of the distributed power supply;
step S2, establishing a DG and SOP active-reactive collaborative planning model which takes the maximum allowable capacity of a distributed power supply DG as an objective function and takes power flow equality constraint, voltage and current constraint, intelligent soft switch SOP operation constraint, DG reactive power output constraint, safety boundary constraint and reactive power compensation device constraint as constraint conditions;
step S3, linearizing the nonlinear part of the DG and SOP active-reactive collaborative planning model based on a linear approximation method;
and S4, solving the DG and SOP active-reactive collaborative planning model in the step S3 based on the typical time sequence correlation scene in the step S1 to obtain DG planning capacity, SOP access position and corresponding SOP planning capacity.
Preferably, the step S1 specifically includes:
determining historical data of DG output and load for n hours, determining a time sequence correlation clustering algorithm, and reducing the historical data into typical time sequence correlation scenes of a plurality of preset time scales; the time sequence correlation analysis algorithm is as follows:
Figure BDA0003018502840000021
in the above formula, the first and second carbon atoms are,
Figure BDA0003018502840000022
represents the load of DG for the t hour;
Figure BDA0003018502840000023
represents the output at the t hour of DG.
Preferably, in step S2, the objective function is:
Figure BDA0003018502840000024
wherein the content of the first and second substances,
Figure BDA0003018502840000031
to access node i's DG capacity size, omegaDGAnd the candidate node set is accessed to the distribution network DG.
Preferably, in step S2, the power flow constraint is a power flow constraint that describes the system by using a branch power flow model, and specifically includes the following steps:
Figure BDA0003018502840000032
Figure BDA0003018502840000033
Figure BDA0003018502840000034
Figure BDA0003018502840000035
Figure BDA0003018502840000036
Figure BDA0003018502840000037
wherein s represents a scene and t represents time;
Figure BDA0003018502840000038
and
Figure BDA0003018502840000039
respectively representing active power and reactive power flowing through the branch ij; r isijAnd xijRespectively representing the resistance and reactance of branch ij;
Figure BDA00030185028400000310
and
Figure BDA00030185028400000311
respectively representing the sum of the active power and the reactive power injected into the node j;
Figure BDA00030185028400000312
and
Figure BDA00030185028400000313
respectively representing active power and reactive power injected into a power grid by a generator node j;
Figure BDA00030185028400000314
and
Figure BDA00030185028400000315
respectively representing the active power and the reactive power of a DG injection node j;
Figure BDA00030185028400000316
and
Figure BDA00030185028400000317
respectively representing the active power and the reactive power of the SOP injection node j;
Figure BDA00030185028400000318
and
Figure BDA00030185028400000319
respectively representing the active power and the reactive power absorbed by the load connected with the node j;
Figure BDA00030185028400000320
represents the voltage of node i;
Figure BDA00030185028400000321
represents the current flowing through line ij; omega1、ΩGAnd ΩSOPRespectively representing a line set, a generator access node position set and a set for installing nodes at two ends of an SOP; qjThe variable is a 0-1 variable, when the variable is 1, the node j is accessed to the SOP, otherwise, the node j is not accessed to the SOP;
Figure BDA00030185028400000322
and
Figure BDA00030185028400000323
reactive power injected into node j for the switched virtual circuit SVC and the backup protection device SCB, respectively.
Preferably, in step S2, the constraint conditions that the branch currents and the node voltages satisfy are:
Figure BDA00030185028400000324
Figure BDA00030185028400000325
wherein:
Figure BDA00030185028400000326
represents the upper limit value of the current of branch ij;
Figure BDA00030185028400000327
and
Figure BDA00030185028400000328
respectively representing the upper limit value and the lower limit value of the voltage of the node i;
the DG reactive power output constraint conditions are as follows:
Figure BDA0003018502840000041
Figure BDA0003018502840000042
in the above formula, the first and second carbon atoms are,
Figure BDA0003018502840000043
a per unit value representing a DG output curve;
Figure BDA0003018502840000044
represents the minimum power factor at which the DG inverter operates;
the SOP operating constraints are:
Figure BDA0003018502840000045
Figure BDA0003018502840000046
Figure BDA0003018502840000047
Figure BDA0003018502840000048
Figure BDA0003018502840000049
Figure BDA00030185028400000410
Figure BDA00030185028400000411
wherein: the node numbers i, j are represented as feeders at two ends of the SOP;
Figure BDA00030185028400000412
and
Figure BDA00030185028400000413
respectively representing the active power loss of the current converter at nodes i and j at the time of t SOP;
Figure BDA00030185028400000414
and
Figure BDA00030185028400000415
representing the loss coefficient of the converter at two ends of the SOP;
Figure BDA00030185028400000416
represents the installation capacity of SOP on the road of ij;
the reactive power compensation device is restricted as follows:
Figure BDA00030185028400000417
Figure BDA00030185028400000418
wherein:
Figure BDA00030185028400000419
representing the number of SCB groups used by the j node at the scene s and the time t;
Figure BDA00030185028400000420
to representCapacity for a single set of SCBs;
Figure BDA00030185028400000421
expressed as the maximum number of SCB groups that the j node can invest;
Figure BDA00030185028400000422
and
Figure BDA00030185028400000423
respectively expressed as the upper and lower limits of the reactive power that the SVC is capable of delivering.
Preferably, in step S2, the safety boundary constraints include urban distribution network safety boundaries and rural distribution network safety boundaries; the safety boundary of the urban distribution network is as follows:
Figure BDA00030185028400000424
wherein the content of the first and second substances,
Figure BDA0003018502840000051
is a feeder FkThe load of (2);
Figure BDA0003018502840000052
presentation and feeder FkFeeder F with connection relationlOutlet power of (d);
Figure BDA0003018502840000053
is a feeder FlThe capacity of (a);
Figure BDA0003018502840000054
is a feeder FlThe capacity of a main transformer; fmPresentation and feeder FlA feeder line connected to the same main transformer;
Figure BDA0003018502840000055
is a feeder FlThe main transformer is a set of all feeders; fnPresentation and feeder FkConnected to the same main transformer and following F after faultkTogether withA feeder line for transfer;
Figure BDA0003018502840000056
to and the feeder FkOn the same main transformer and with loads after fault
Figure BDA0003018502840000057
Transferred to a main transformer together;
the rural power distribution network safety boundary is as follows:
Figure BDA0003018502840000058
Figure BDA0003018502840000059
wherein the content of the first and second substances,
Figure BDA00030185028400000510
is a feeder FlTotal power loss generated above;
Figure BDA00030185028400000511
represents the loss on line ij; z is a radical ofijRepresenting the impedance value on line ij.
Preferably, in step S3, the squared terms of variables in the DG and SOP active-reactive collaborative planning model are replaced with linear variables; substituting the product of the discrete variable and the continuous variable for an equality expression by using a linearized inequality constraint; and relaxing the quadratic constraint, and converting the quadratic expression into a plurality of inequality expression constraints by utilizing a polyhedral approximation method so as to linearize the nonlinear part of the DG and SOP active-reactive collaborative planning model.
In a second aspect, an embodiment of the present invention provides a DG and SOP active-reactive collaborative planning apparatus, including:
the acquisition module is used for determining typical time sequence correlation scenes of a plurality of preset time scales of the distributed power supply;
the modeling module is used for establishing a DG and SOP active-reactive collaborative planning model which takes the maximum access capacity of a distributed power supply DG as an objective function and takes power flow equality constraint, voltage current constraint, intelligent soft switch SOP operation constraint, DG reactive power output constraint, safety boundary constraint and reactive power compensation device constraint as constraint conditions;
the linear processing module is used for linearizing the nonlinear part of the DG and SOP active-reactive collaborative planning model based on a linear approximation method;
and the planning module is used for solving the DG and SOP active-reactive collaborative planning model based on the typical time sequence correlation scene in the acquisition module to obtain DG planning capacity, an SOP access position and corresponding SOP planning capacity.
In a third aspect, an embodiment of the present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the steps of the DG and SOP active-reactive collaborative planning method according to the embodiment of the first aspect of the present invention when executing the program.
In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the DG and SOP active-reactive collaborative planning method according to an embodiment of the first aspect of the present invention.
According to the DG and SOP active-reactive collaborative planning method and device provided by the embodiment of the invention, aiming at the distribution network distributed power supply planning, various active management measures can be effectively utilized, the installation position and the capacity of the SOP are planned, the utilization rate of each device in a distribution system is improved, and the consumption capacity of the distribution network to the distributed power supply is improved; by adopting the rural power grid safety boundary model, the planning capacity and the position of a distributed power supply in the power distribution network can be effectively restrained, the normal power supply of the power distribution system can be ensured in an N-1 state, and the reliability of the power distribution network is improved; by utilizing the linearization processing of the model, the calculation efficiency of the model can be greatly improved on the premise of reducing the error as much as possible.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a flexible power distribution network planning idea considering rural power grid safety boundaries in an embodiment of the present invention;
fig. 2 is a flow chart of an active-reactive collaborative planning method for DG and SOP according to an embodiment of the present invention;
FIG. 3 is a specific flowchart of a distributed power supply and SOP active-reactive collaborative planning method related to a safety boundary according to an embodiment of the present invention;
FIG. 4 is a typical scenario generation curve according to an embodiment of the present invention;
FIG. 5 is a diagram illustrating a structure of a rack according to an embodiment of the present invention;
fig. 6 is a graph of the average voltage deviation of each scene node in the result of considering the rural power grid safety boundary planning according to the embodiment of the present invention;
fig. 7 is a schematic physical structure diagram according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the embodiment of the present application, the term "and/or" is only one kind of association relationship describing an associated object, and means that three relationships may exist, for example, a and/or B may mean: a exists alone, A and B exist simultaneously, and B exists alone.
The terms "first" and "second" in the embodiments of the present application 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, the terms "comprise" and "have", as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a system, product or apparatus that comprises a list of elements or components is not limited to only those elements or components but may alternatively include other elements or components not expressly listed or inherent to such product or apparatus. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless explicitly specifically limited otherwise.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
A DG and an active control means are not provided in a traditional power distribution network, so that the planning method only considers the voltage and current constraints of the power distribution network. With the change of the structure and the operation mode of the power grid, the planning mode becomes complicated, but the planning method only considers the consumption capability of the distribution network to the DG under the normal operation state.
Therefore, the embodiment of the invention provides a DG and SOP active-reactive collaborative planning method and device, aiming at the distribution network distributed power supply planning, a plurality of active management measures can be effectively utilized to plan the installation position and the capacity of the SOP, the utilization rate of each device in a distribution system is improved, and the consumption capacity of the distribution network to the distributed power supply is improved. The following description and description will proceed with reference being made to various embodiments.
Fig. 1 provides a DG and SOP active-reactive collaborative planning method according to an embodiment of the present invention, as shown in fig. 2 and fig. 3, including:
step S1, determining typical time sequence correlation scenes of a plurality of preset time scales of the distributed power supply;
historical data of distributed power output and load 8760 hours are imported, time sequence correlation is used as a formula (1), a clustering algorithm considering the time sequence correlation is adopted, original data are reduced, and a plurality of typical time sequence correlation scenes with 24 as a time scale are generated, as shown in fig. 4.
Figure BDA0003018502840000081
In the above formula, the first and second carbon atoms are,
Figure BDA0003018502840000082
represents the load of DG for the t hour;
Figure BDA0003018502840000083
represents the output at the t hour of DG.
Step S2, establishing a DG and SOP active-reactive collaborative planning model which takes the maximum allowable capacity of a distributed power supply DG as an objective function and takes power flow equality constraint, voltage and current constraint, intelligent soft switch SOP operation constraint, DG reactive power output constraint, safety boundary constraint and reactive power compensation device constraint as constraint conditions;
step S21, enabling the objective function to be the maximum admission capacity of the distributed power supply of the power distribution network, as shown in formula (2):
Figure BDA0003018502840000084
wherein the content of the first and second substances,
Figure BDA0003018502840000085
to access node i's DG capacity size, omegaDGAnd the candidate node set is accessed to the distribution network DG.
S22, constructing each constraint condition of the planning model;
the power flow constraint is a power flow constraint adopting a branch power flow model description system, and specifically comprises the following steps:
Figure BDA0003018502840000086
Figure BDA0003018502840000087
Figure BDA0003018502840000088
Figure BDA0003018502840000089
Figure BDA00030185028400000810
Figure BDA00030185028400000811
wherein s represents a scene and t represents time;
Figure BDA00030185028400000812
and
Figure BDA00030185028400000813
respectively representing active power and reactive power flowing through the branch ij; r isijAnd xijRespectively representing the resistance and reactance of branch ij;
Figure BDA0003018502840000091
and
Figure BDA0003018502840000092
respectively representing the sum of the active power and the reactive power injected into the node j;
Figure BDA0003018502840000093
and
Figure BDA0003018502840000094
respectively representing active power and reactive power injected into a power grid by a generator node j;
Figure BDA0003018502840000095
and
Figure BDA0003018502840000096
respectively representing the active power and the reactive power of a DG injection node j;
Figure BDA0003018502840000097
and
Figure BDA0003018502840000098
respectively representing the active power and the reactive power of the SOP injection node j;
Figure BDA0003018502840000099
and
Figure BDA00030185028400000910
respectively representing the active power and the reactive power absorbed by the load connected with the node j;
Figure BDA00030185028400000911
represents the voltage of node i;
Figure BDA00030185028400000912
represents the current flowing through line ij; omega1、ΩGAnd ΩSOPRespectively representing a line set, a generator access node position set and a set for installing nodes at two ends of an SOP; qjThe variable is a 0-1 variable, when the variable is 1, the node j is accessed to the SOP, otherwise, the node j is not accessed to the SOP;
Figure BDA00030185028400000913
and
Figure BDA00030185028400000914
reactive power injected into node j for the switched virtual circuit SVC and the backup protection device SCB, respectively.
In order to ensure the safety and the electric energy quality of the system, the condition that the current of each branch and the voltage of each node meet the constraint conditions is as follows:
Figure BDA00030185028400000915
Figure BDA00030185028400000916
wherein:
Figure BDA00030185028400000917
represents the upper limit value of the current of branch ij;
Figure BDA00030185028400000918
and
Figure BDA00030185028400000919
respectively representing the upper limit value and the lower limit value of the voltage of the node i;
in order to fully utilize the reactive compensation function of the DG inverter, the DG reactive power output constraint condition is as follows, assuming that the DG inverter works in a maximum power point tracking mode:
Figure BDA00030185028400000920
Figure BDA00030185028400000921
in the above formula, the first and second carbon atoms are,
Figure BDA00030185028400000922
a per unit value representing a DG output curve;
Figure BDA00030185028400000923
represents the minimum power factor at which the DG inverter operates;
meanwhile, the SOP operation constraints are:
Figure BDA00030185028400000924
Figure BDA00030185028400000925
Figure BDA00030185028400000926
Figure BDA00030185028400000927
Figure BDA0003018502840000101
Figure BDA0003018502840000102
Figure BDA0003018502840000103
wherein: the node numbers i, j are represented as feeders at two ends of the SOP;
Figure BDA0003018502840000104
and
Figure BDA0003018502840000105
respectively representing the active power loss of the current converter at nodes i and j at the time of t SOP;
Figure BDA0003018502840000106
and
Figure BDA0003018502840000107
representing the loss coefficient of the converter at two ends of the SOP;
Figure BDA0003018502840000108
represents the installation capacity of SOP on the road of ij;
the reactive power compensation device is restricted as follows:
Figure BDA0003018502840000109
Figure BDA00030185028400001010
wherein:
Figure BDA00030185028400001011
representing the number of SCB groups used by the j node at the scene s and the time t;
Figure BDA00030185028400001012
capacity represented as a single set of SCBs;
Figure BDA00030185028400001013
expressed as the maximum number of SCB groups that the j node can invest;
Figure BDA00030185028400001014
and
Figure BDA00030185028400001015
respectively expressed as the upper and lower limits of the reactive power that the SVC is capable of delivering.
The safety boundary constraint comprises a city power distribution network safety boundary and a rural power distribution network safety boundary; the safety boundary based on the direct current flow is approximately linear, and the error between the result and the accurate boundary is very small, so the network loss is ignored by the safety boundary of the urban distribution network, and the safety boundary of the urban distribution network is as follows:
Figure BDA00030185028400001016
wherein the content of the first and second substances,
Figure BDA00030185028400001017
is a feeder FkThe load of (2);
Figure BDA00030185028400001018
presentation and feeder FkFeeder F with connection relationlOutlet power of (d);
Figure BDA00030185028400001019
is a feeder FlThe capacity of (a);
Figure BDA00030185028400001020
is a feeder FlThe capacity of a main transformer; fmPresentation and feeder FlA feeder line connected to the same main transformer;
Figure BDA00030185028400001021
is a feeder FlThe main transformer is a set of all feeders; fnPresentation and feeder FkConnected to the same main transformer and following F after faultkA feed line for supplying together;
Figure BDA00030185028400001022
to and the feeder FkOn the same main transformer and with loads after fault
Figure BDA00030185028400001023
Transferred to a main transformer together;
however, in a rural power distribution network, due to the characteristics of long lines, large voltage drop and the like, line loss in the rural power network is serious, and the problem of line loss cannot be ignored. Therefore, adding the above safety margin improvement to the network loss, the safety margin equation associated with the feeder in the rural network may be:
Figure BDA0003018502840000111
Figure BDA0003018502840000112
wherein the content of the first and second substances,
Figure BDA0003018502840000113
is a feeder FlTotal power loss generated above;
Figure BDA0003018502840000114
represents the loss on line ij; z is a radical ofijRepresenting the impedance value on line ij.
Step S3, linearizing the nonlinear part of the DG and SOP active-reactive collaborative planning model based on a linear approximation method;
a large number of variables exist in a planning model, and nonlinear constraints such as power flow constraint, SOP operation constraint and the like cause the problem that the model is a non-convex nonlinear NP difficult problem, and an optimal solution is difficult to obtain. Therefore, the second-order cone relaxation and linearization are carried out on the power flow constraint and the SOP constraint, and the linearization processing is carried out on the other constraint conditions, so that the model can rapidly obtain the optimal solution;
step S31, square term variable replacement. The power flow equation is constrained to the voltage-current square terms contained in equations (2) - (3), (7) - (8):
Figure BDA0003018502840000115
by using
Figure BDA0003018502840000116
And
Figure BDA0003018502840000117
instead, the conversion is:
Figure BDA0003018502840000118
Figure BDA0003018502840000119
Figure BDA00030185028400001110
Figure BDA00030185028400001111
step S32, linearization of discrete/continuous variable product. Multiplying discrete variables and continuous variables appearing in the power flow constraints (4) - (5):
Figure BDA00030185028400001112
by means of variables
Figure BDA00030185028400001113
Equivalently, then:
Figure BDA00030185028400001114
Figure BDA00030185028400001115
Figure BDA00030185028400001116
Figure BDA0003018502840000121
and step S33, performing second-order cone relaxation processing on the power flow constraint and the SOP constraint. The operating constraints (14) to (15) of the SOP are transformed to obtain:
Figure BDA0003018502840000122
Figure BDA0003018502840000123
substituting the above equations for equations (16) - (17), the linear constraint expression of the loss on the extrapolated SOP is:
Figure BDA0003018502840000124
Figure BDA0003018502840000125
then, the formulas (32), (33) and (27) are relaxed to obtain:
Figure BDA0003018502840000126
Figure BDA0003018502840000127
Figure BDA0003018502840000128
step S34: and carrying out linearization processing on the constraint condition after the relaxation processing. After relaxation, formulae (36) - (38) have the same expression pattern as follows:
α2+β2≤χρ (40)
for quadratic constraint of the form of the formula (39), and uniformly processing the quadratic constraint into a linearized expression by using a polyhedral approximation method, the constraint should satisfy:
Figure BDA0003018502840000129
Figure BDA0003018502840000131
Figure BDA0003018502840000132
wherein: xiωAnd muωExpressed as linearized intermediate variables; κ denotes the number of linearization approximations.
Step S35: the security boundary model linearization process will be improved. Because the power flow constraint is a branch power flow expression form and the network loss is considered, the line loss can be indirectly calculated according to a power flow linearization formula, and the safety boundary model is equivalent. Wherein:
Figure BDA0003018502840000133
ij＝Floutlet line (44)
Figure BDA0003018502840000134
ij＝FlOutlet line (45)
Because of having:
Figure BDA0003018502840000135
then:
Figure BDA0003018502840000136
ij＝Floutlet line (47)
Through the above conversion, the rural power grid safety boundary model can be converted into:
Figure BDA0003018502840000137
and S4, solving the DG and SOP active-reactive collaborative planning model in the step S3 based on the typical time sequence correlation scene in the step S1 to obtain DG planning capacity, SOP access position and corresponding SOP planning capacity.
Take a 10kV system of a certain rural power grid 51 node as an example, as shown in fig. 5. The total load in the system is 6875+ j2440kVA, and three feeders are shared. Let DG (here DG is distributed photovoltaic, DPV) access locations be nodes 32, 34, 43, 47; the SOP positions to be selected are 5 traditional contact line positions; the lower limit of the power factor of the inverter is 0.9; the SVC is installed at the nodes 14 and 48, and the adjustable range is-500 kVA-500 kVar; the SCB is installed at nodes 9 and 31, and 5 groups are installed. The influence of the rural power grid safety boundary on the DPV planning result is researched, and the planning result is shown in table 1. The average deviation of the voltage of the nodes of the whole scene is shown in fig. 6, and the average deviation of the voltage of each scene is smaller than that of the voltage of an unconsidered security boundary after the security boundary is considered, which indicates that the rural power grid security boundary is considered to be beneficial to improving the voltage distribution of the power distribution network, and further, the validity of the rural power grid security boundary is verified.
TABLE 1
Figure BDA0003018502840000141
In the embodiment of the invention, the DPV planning result considering the safety boundary of the rural power grid is slightly smaller than the DPV planning result not considering the safety boundary, because the feasible domain of the original mathematical model is reduced by adding the constraint of the safety boundary of the rural power grid. The rural power grid safety boundary is a constraint considering N-1 safety, the planning result can be ensured to be in a safe operation range under the full scene operation, and compared with a model not considering the safety boundary, the solution result is more accurate and reliable. In addition, the SOP planning positions are consistent but the planning capacities are slightly different, which shows that the addition of the rural power grid safety boundary also has certain influence on the SOP planning.
Various planning schemes are considered, and planning results are obtained as shown in table 2, which shows that the consumption capacity of the distribution network to the DGs can be improved by the active management measures and the access of the SOP. The active management measures are close to the improvement effect of the SOP on the DG consumption, but include SVC, SCB, DG reactive support and other measures. The influence of SOP on the DG allowed access to the maximum capacity is most pronounced compared to single approach. The planning model is more beneficial to improving the DG consumption capability of the power distribution network.
TABLE 2
Figure BDA0003018502840000142
Figure BDA0003018502840000151
In step S3, replacing a square term of a variable in the DG and SOP active-reactive collaborative planning model with a linear variable; substituting the product of the discrete variable and the continuous variable for an equality expression by using a linearized inequality constraint; and relaxing the quadratic constraint, and converting the quadratic expression into a plurality of inequality expression constraints by utilizing a polyhedral approximation method so as to linearize the nonlinear part of the DG and SOP active-reactive collaborative planning model.
The embodiment of the invention also provides a DG and SOP active-reactive collaborative planning device, which is based on the DG and SOP active-reactive collaborative planning method in the embodiments and comprises an acquisition module, a modeling module, a linear processing module and a planning module, wherein:
the acquisition module is used for determining typical time sequence correlation scenes of a plurality of preset time scales of the distributed power supply;
the modeling module is used for establishing a DG and SOP active-reactive collaborative planning model which takes the maximum access capacity of a distributed power supply DG as an objective function and takes power flow equality constraint, voltage current constraint, intelligent soft switch SOP operation constraint, DG reactive power output constraint, safety boundary constraint and reactive power compensation device constraint as constraint conditions;
the linear processing module is used for linearizing the nonlinear part of the DG and SOP active-reactive collaborative planning model based on a linear approximation method;
and the planning module is used for solving the DG and SOP active-reactive collaborative planning model based on the typical time sequence correlation scene in the acquisition module to obtain DG planning capacity, an SOP access position and corresponding SOP planning capacity.
Based on the same concept, an embodiment of the present invention further provides an entity structure schematic diagram, as shown in fig. 7, the server may include: a processor (processor)810, a communication Interface 820, a memory 830 and a communication bus 840, wherein the processor 810, the communication Interface 820 and the memory 830 communicate with each other via the communication bus 840. The processor 810 may call logic instructions in the memory 830 to perform the steps of the DG and SOP active-reactive co-planning method as described in the various embodiments above. Examples include:
step S1, determining typical time sequence correlation scenes of a plurality of preset time scales of the distributed power supply;
step S2, establishing a DG and SOP active-reactive collaborative planning model which takes the maximum allowable capacity of a distributed power supply DG as an objective function and takes power flow equality constraint, voltage and current constraint, intelligent soft switch SOP operation constraint, DG reactive power output constraint, safety boundary constraint and reactive power compensation device constraint as constraint conditions;
step S3, linearizing the nonlinear part of the DG and SOP active-reactive collaborative planning model based on a linear approximation method;
and S4, solving the DG and SOP active-reactive collaborative planning model in the step S3 based on the typical time sequence correlation scene in the step S1 to obtain DG planning capacity, SOP access position and corresponding SOP planning capacity.
In addition, the logic instructions in the memory 830 may be implemented in software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Based on the same concept, embodiments of the present invention further provide a non-transitory computer-readable storage medium, where the computer-readable storage medium stores a computer program, where the computer program includes at least one code, and the at least one code is executable by a master control device to control the master control device to implement the steps of the DG and SOP active-reactive collaborative planning method according to the embodiments. Examples include:
step S1, determining typical time sequence correlation scenes of a plurality of preset time scales of the distributed power supply;
step S2, establishing a DG and SOP active-reactive collaborative planning model which takes the maximum allowable capacity of a distributed power supply DG as an objective function and takes power flow equality constraint, voltage and current constraint, intelligent soft switch SOP operation constraint, DG reactive power output constraint, safety boundary constraint and reactive power compensation device constraint as constraint conditions;
step S3, linearizing the nonlinear part of the DG and SOP active-reactive collaborative planning model based on a linear approximation method;
and S4, solving the DG and SOP active-reactive collaborative planning model in the step S3 based on the typical time sequence correlation scene in the step S1 to obtain DG planning capacity, SOP access position and corresponding SOP planning capacity.
Based on the same technical concept, the embodiment of the present application further provides a computer program, which is used to implement the above method embodiment when the computer program is executed by the main control device.
The program may be stored in whole or in part on a storage medium packaged with the processor, or in part or in whole on a memory not packaged with the processor.
Based on the same technical concept, the embodiment of the present application further provides a processor, and the processor is configured to implement the above method embodiment. The processor may be a chip.
In summary, the method and the device for active-reactive collaborative planning of DG and SOP provided by the embodiments of the present invention can effectively utilize various active management measures to plan the installation position and the capacity of the SOP for the distribution network distributed power supply planning, improve the utilization rate of each device in the distribution system, and improve the consumption capability of the distribution network for the distributed power supply; by adopting the rural power grid safety boundary model, the planning capacity and the position of a distributed power supply in the power distribution network can be effectively restrained, the normal power supply of the power distribution system can be ensured in an N-1 state, and the reliability of the power distribution network is improved; by utilizing the linearization processing of the model, the calculation efficiency of the model can be greatly improved on the premise of reducing the error as much as possible.
The embodiments of the present invention can be arbitrarily combined to achieve different technical effects.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the procedures or functions described in accordance with the present application are generated, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (e.g., coaxial cable, fiber optic, digital subscriber line) or wirelessly (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid state disk), among others.
One of ordinary skill in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by hardware related to instructions of a computer program, which may be stored in a computer-readable storage medium, and when executed, may include the processes of the above method embodiments. And the aforementioned storage medium includes: various media capable of storing program codes, such as ROM or RAM, magnetic or optical disks, etc.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (10)

1. A DG and SOP active-reactive collaborative planning method is characterized by comprising the following steps:
step S1, determining typical time sequence correlation scenes of a plurality of preset time scales of the distributed power supply;
step S2, establishing a DG and SOP active-reactive collaborative planning model which takes the maximum allowable capacity of a distributed power supply DG as an objective function and takes power flow equality constraint, voltage and current constraint, intelligent soft switch SOP operation constraint, DG reactive power output constraint, safety boundary constraint and reactive power compensation device constraint as constraint conditions;
step S3, linearizing the nonlinear part of the DG and SOP active-reactive collaborative planning model based on a linear approximation method;
and S4, solving the DG and SOP active-reactive collaborative planning model in the step S3 based on the typical time sequence correlation scene in the step S1 to obtain DG planning capacity, SOP access position and corresponding SOP planning capacity.
2. The DG and SOP active-reactive collaborative planning method according to claim 1, wherein the step S1 specifically comprises:
determining historical data of DG output and load for n hours, determining a time sequence correlation clustering algorithm, and reducing the historical data into typical time sequence correlation scenes of a plurality of preset time scales; the time sequence correlation analysis algorithm is as follows:
Figure FDA0003018502830000011
in the above formula, the first and second carbon atoms are,
Figure FDA0003018502830000012
represents the load of DG for the t hour;
Figure FDA0003018502830000013
represents the output at the t hour of DG.
3. The DG and SOP active-reactive collaborative planning method according to claim 1, wherein in said step S2, said objective function is:
Figure FDA0003018502830000014
wherein the content of the first and second substances,
Figure FDA0003018502830000015
to access node i's DG capacity size, omegaDGAnd the candidate node set is accessed to the distribution network DG.
4. The DG and SOP active-reactive collaborative planning method according to claim 3, wherein in the step S2, the power flow constraint is a power flow constraint describing a system by using a branch power flow model, and the specific steps are as follows:
Figure FDA0003018502830000016
Figure FDA0003018502830000021
Figure FDA0003018502830000022
Figure FDA0003018502830000023
Figure FDA0003018502830000024
Figure FDA0003018502830000025
wherein s represents a scene and t represents time;
Figure FDA0003018502830000026
and
Figure FDA0003018502830000027
respectively representing active power and reactive power flowing through the branch ij; r isijAnd xijRespectively representing the resistance and reactance of branch ij;
Figure FDA0003018502830000028
and
Figure FDA0003018502830000029
respectively representing the sum of the active power and the reactive power injected into the node j;
Figure FDA00030185028300000210
and
Figure FDA00030185028300000211
respectively representing active power and reactive power injected into a power grid by a generator node j;
Figure FDA00030185028300000212
and
Figure FDA00030185028300000213
respectively representing the active power and the reactive power of a DG injection node j;
Figure FDA00030185028300000214
and
Figure FDA00030185028300000215
respectively representing the active power and the reactive power of the SOP injection node j;
Figure FDA00030185028300000216
and
Figure FDA00030185028300000217
respectively representing the active power and the reactive power absorbed by the load connected with the node j;
Figure FDA00030185028300000218
represents the voltage of node i;
Figure FDA00030185028300000219
represents the current flowing through line ij; omega1、ΩGAnd ΩSOPRespectively representing a line set, a generator access node position set and a set for installing nodes at two ends of an SOP; qjIs a variable from 0 to 1, and when the variable is 1, the node j is connectedEntering the SOP, otherwise, not accessing the SOP;
Figure FDA00030185028300000220
and
Figure FDA00030185028300000221
reactive power injected into node j for the switched virtual circuit SVC and the backup protection device SCB, respectively.
5. The DG and SOP active-reactive collaborative planning method according to claim 4, wherein in the step S2, the constraint conditions that the branch current and the node voltage satisfy are as follows:
Figure FDA00030185028300000222
Figure FDA00030185028300000223
wherein:
Figure FDA00030185028300000224
represents the upper limit value of the current of branch ij;
Figure FDA00030185028300000225
and
Figure FDA00030185028300000226
respectively representing the upper limit value and the lower limit value of the voltage of the node i;
the DG reactive power output constraint conditions are as follows:
Figure FDA00030185028300000227
Figure FDA00030185028300000228
in the above formula, the first and second carbon atoms are,
Figure FDA00030185028300000229
a per unit value representing a DG output curve;
Figure FDA00030185028300000230
represents the minimum power factor at which the DG inverter operates;
the SOP operating constraints are:
Figure FDA0003018502830000031
Figure FDA0003018502830000032
Figure FDA0003018502830000033
Figure FDA0003018502830000034
Figure FDA0003018502830000035
Figure FDA0003018502830000036
Figure FDA0003018502830000037
wherein: the node numbers i, j are represented as feeders at two ends of the SOP;
Figure FDA0003018502830000038
and
Figure FDA0003018502830000039
respectively representing the active power loss of the current converter at nodes i and j at the time of t SOP;
Figure FDA00030185028300000310
and
Figure FDA00030185028300000311
representing the loss coefficient of the converter at two ends of the SOP;
Figure FDA00030185028300000312
represents the installation capacity of SOP on the road of ij;
the reactive power compensation device is restricted as follows:
Figure FDA00030185028300000313
Figure FDA00030185028300000314
wherein:
Figure FDA00030185028300000315
representing the number of SCB groups used by the j node at the scene s and the time t;
Figure FDA00030185028300000316
capacity represented as a single set of SCBs;
Figure FDA00030185028300000317
representing j node capable of putting into maximum SCB groupCounting;
Figure FDA00030185028300000318
and
Figure FDA00030185028300000319
respectively expressed as the upper and lower limits of the reactive power that the SVC is capable of delivering.
6. The DG and SOP active-reactive collaborative planning method according to claim 5, wherein in step S2, the safety boundary constraints include city distribution network safety boundaries and rural distribution network safety boundaries; the safety boundary of the urban distribution network is as follows:
Figure FDA00030185028300000320
wherein the content of the first and second substances,
Figure FDA00030185028300000321
is a feeder FkThe load of (2);
Figure FDA00030185028300000322
presentation and feeder FkFeeder F with connection relationlOutlet power of (d);
Figure FDA00030185028300000323
is a feeder FlThe capacity of (a);
Figure FDA00030185028300000324
is a feeder FlThe capacity of a main transformer; fmPresentation and feeder FlA feeder line connected to the same main transformer;
Figure FDA00030185028300000325
is a feeder FlThe main transformer is a set of all feeders; fnPresentation and feeder FkConnected to the same masterVariable and fault followed by FkA feed line for supplying together;
Figure FDA0003018502830000041
to and the feeder FkOn the same main transformer and with loads after fault
Figure FDA0003018502830000042
Transferred to a main transformer together;
the rural power distribution network safety boundary is as follows:
Figure FDA0003018502830000043
Figure FDA0003018502830000044
wherein the content of the first and second substances,
Figure FDA0003018502830000045
is a feeder FlTotal power loss generated above;
Figure FDA0003018502830000046
represents the loss on line ij; z is a radical ofijRepresenting the impedance value on line ij.
7. The DG and SOP active-reactive collaborative planning method according to claim 6, wherein in step S3, the square terms of variables in the DG and SOP active-reactive collaborative planning model are replaced by linear variables; substituting the product of the discrete variable and the continuous variable for an equality expression by using a linearized inequality constraint; and relaxing the quadratic constraint, and converting the quadratic expression into a plurality of inequality expression constraints by utilizing a polyhedral approximation method so as to linearize the nonlinear part of the DG and SOP active-reactive collaborative planning model.
8. The utility model provides a DG and SOP active-reactive collaborative planning device which characterized in that includes:
the acquisition module is used for determining typical time sequence correlation scenes of a plurality of preset time scales of the distributed power supply;
the modeling module is used for establishing a DG and SOP active-reactive collaborative planning model which takes the maximum access capacity of a distributed power supply DG as an objective function and takes power flow equality constraint, voltage current constraint, intelligent soft switch SOP operation constraint, DG reactive power output constraint, safety boundary constraint and reactive power compensation device constraint as constraint conditions;
the linear processing module is used for linearizing the nonlinear part of the DG and SOP active-reactive collaborative planning model based on a linear approximation method;
and the planning module is used for solving the DG and SOP active-reactive collaborative planning model based on the typical time sequence correlation scene in the acquisition module to obtain DG planning capacity, an SOP access position and corresponding SOP planning capacity.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the DG and SOP active-reactive co-planning method of any one of claims 1 to 7.
10. A non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor implements the steps of the DG and SOP active-reactive co-planning method according to any one of claims 1 to 7.
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