CN112952919A - Dynamic economic dispatching method and device for multi-region power grid, electronic equipment and medium - Google Patents

Dynamic economic dispatching method and device for multi-region power grid, electronic equipment and medium Download PDF

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CN112952919A
CN112952919A CN202110389224.6A CN202110389224A CN112952919A CN 112952919 A CN112952919 A CN 112952919A CN 202110389224 A CN202110389224 A CN 202110389224A CN 112952919 A CN112952919 A CN 112952919A
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stage
power
risk
power grid
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CN112952919B (en
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陈哲
郭创新
张通
张静
章姝俊
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Zhejiang University ZJU
State Grid Zhejiang Electric Power Co Ltd
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State Grid Zhejiang Electric Power Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • 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
    • H02J3/008—Circuit arrangements for ac mains or ac distribution networks involving trading of energy or energy transmission rights
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/76—Power conversion electric or electronic aspects

Abstract

The invention discloses a dynamic economic dispatching method and device for a multi-region power grid, electronic equipment and a medium, belonging to the field of research on optimized operation of a power system, wherein the method comprises the following steps: evaluating the operation risk of the power grid according to the condition risk value and defining a consumable wind power domain; establishing a two-stage three-layer multi-area power grid dynamic economic dispatching model according to the operation risk and the wind power area capable of being absorbed; and solving the dynamic economic dispatching model of the multi-region power grid by adopting a column constraint generation algorithm in a main and sub problem iteration mode to obtain a dispatching scheme and a reasonable wind power domain capable of being consumed. Compared with the existing research, the method provided by the invention can evaluate the operation risk of the power grid while formulating the dynamic economic dispatching plan of the multi-region power grid, obtain a reasonable wind power domain which can be consumed, and realize the standby sharing among the regions. The method is reliable, easy to implement and convenient to popularize.

Description

Dynamic economic dispatching method and device for multi-region power grid, electronic equipment and medium
Technical Field
The invention belongs to the field of electric power system optimization operation research, and particularly relates to a dynamic economic dispatching method and device for a multi-region power grid, electronic equipment and a medium.
Background
With the continuous expansion of the power grid scale, modern power systems are usually formed by interconnecting a plurality of subsystems. Because the wind power development and the load development in China are unbalanced, a large amount of electric power is transmitted from the northwest area to the east area through a cross-regional tie line. With the closer and closer connection between the sending end system and the receiving end system, in order to improve the operation economy and reliability of the whole system, the power generation resources of the power grids in each area are required to be coordinated and scheduled.
Scholars at home and abroad successively develop related researches including a multi-region optimal power flow problem, a multi-region economic dispatching problem, a multi-region dynamic economic dispatching problem and a multi-region unit combination problem. In order to consider the uncertainty of wind power in the multi-region collaborative optimization operation problem, a commonly used method at present is robust optimization.
However, there are still two problems to be solved. First, conventional robust optimization models have difficulty determining a suitable uncertainty set. When the set indeterminate set in advance is too large, the scheduling strategy is very conservative; otherwise, the reaction will be too radical. Second, due to the large uncertainty of the wind power output, the actual output may deviate significantly from the predicted value. However, the current work only arranges the power of the tie line according to the predicted wind power output, and the transmission power of the tie line cannot be adjusted in real time according to the actual wind power output. Due to the acceptance of large-scale external power sources, the peak shaving difficulty of the receiving-end power grid with insufficient local power generation resources is increasingly prominent. With the development of the flexible direct current technology, the advantage of flexibly adjusting the power of the tie line is fully exerted, and the regional standby sharing is promoted.
Disclosure of Invention
In order to solve the above problems, the invention provides a dynamic economic dispatching method and device for a multi-region power grid, an electronic device and a medium.
According to a first aspect of an embodiment of the present invention, a method for dynamic economic dispatching of a multi-region power grid is provided, which includes: evaluating the operation risk of the power grid according to the condition risk value and defining a consumable wind power domain; establishing a two-stage three-layer multi-area power grid dynamic economic dispatching model according to the operation risk and the wind power area capable of being absorbed; and solving the dynamic economic dispatching model of the multi-region power grid by adopting a column constraint generation algorithm in a main and sub problem iteration mode to obtain a dispatching scheme and a reasonable wind power domain capable of being consumed.
According to a second aspect of the embodiments of the present invention, there is provided a multi-region power grid dynamic economic dispatching device, including:
the risk evaluation module is used for evaluating the operation risk of the power grid according to the condition risk value and defining a digestible wind power domain;
the model generation module is used for establishing a two-stage three-layer multi-area power grid dynamic economic dispatching model according to the operation risk and the wind power domain capable of being absorbed;
and the model solving module is used for solving the dynamic economic dispatching model of the multi-region power grid in a main and sub problem iteration mode by adopting a column constraint generation algorithm so as to obtain a dispatching scheme and a reasonable wind power domain capable of being consumed.
According to a third aspect of embodiments of the present invention, there is provided an electronic apparatus, including: one or more processors; a memory for storing one or more programs; when executed by the one or more processors, cause the one or more processors to implement a method as described in the first aspect.
According to a fourth aspect of embodiments of the present invention, there is provided a computer-readable storage medium having stored thereon computer instructions, characterized in that the instructions, when executed by a processor, implement the steps of the method according to the first aspect.
The technical scheme provided by the embodiment of the application can have the following beneficial effects:
according to the embodiment, the multi-region power grid dynamic economic dispatching model adopts the adjustable uncertain set and wind power uncertainty and evaluates the power grid operation risk, the uncertain set boundary is optimized in the process of solving the multi-region power grid dynamic economic dispatching model, the balance of operation cost and operation risk can be realized, and meanwhile, a reasonable wind power domain can be obtained, namely, the wind power output range bringing risks to the power grid operation is avoided. In addition, by optimizing the transmission power of the tie line and the adjustable range of the tie line in each time interval in the multi-region power grid dynamic economic dispatching model, the standby sharing among the regions can be realized, and the economical efficiency and the reliability of the operation of the interconnected power grid are improved. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
Fig. 1 is a flowchart illustrating a method for dynamic economic dispatch of a multi-region power grid according to an exemplary embodiment.
FIG. 2 is a wind power output probability density curve shown in accordance with an exemplary embodiment.
Fig. 3 is a block diagram illustrating a multi-region grid dynamic economic dispatch device according to an exemplary embodiment.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
Fig. 1 is a flowchart illustrating a method for dynamic economic dispatching of a multi-region power grid according to an exemplary embodiment, and referring to fig. 1, an embodiment of the present invention provides a method for dynamic economic dispatching of a multi-region power grid, where the method may include the following steps:
step S11, evaluating the operation risk of the power grid according to the condition risk value and defining a digestible wind power domain;
step S12, establishing a two-stage three-layer multi-area dynamic economic dispatching model according to the power grid operation risk and the acceptable wind power domain;
and step S13, solving the multi-region dynamic economic dispatching model in a main and sub problem iteration mode by adopting a column constraint generation algorithm to obtain a dispatching scheme and a reasonable wind power domain capable of being absorbed.
According to the embodiment, the wind power uncertainty is calculated by adopting the adjustable uncertain set, the power grid operation risk is evaluated, the uncertain set boundary is optimized in the process of solving the multi-region power grid dynamic economic dispatching model, the balance between the operation cost and the operation risk can be realized, and meanwhile, a reasonable wind power domain can be obtained, namely, the wind power output range which can not bring risks to the power grid operation can be obtained. In addition, by optimizing the transmission power of the tie line and the adjustable range of the tie line in each time interval in the multi-region power grid dynamic economic dispatching model, the standby sharing among the regions can be realized, and the economical efficiency and the reliability of the operation of the interconnected power grid are improved.
In the specific implementation of step S11, the grid operation risk is evaluated according to the condition risk value and a wind power domain is defined.
(1.1) the present invention defines operational risks including wind curtailment risks (CVaR) according to the concept of conditional risk value (CVaR)+) And risk of loss of load (CVaR)-) Two aspects are provided. And meanwhile, a wind power output range which can take up a wind power domain, namely, the wind power output range can not bring risks to the operation of a power grid is defined. Fig. 2 shows a general wind power output probability density curve. Wherein A isw,tRepresenting the predicted value of the output of the wind power plant w at the moment t,
Figure BDA0003015883560000041
and
Figure BDA0003015883560000042
respectively an upper bound and a lower bound of a digestible wind power domain. It can be seen from the figure that when the actual wind power output is greater than the upper bound of the acceptable wind power domain, the lower reserve capacity of the system is insufficient, and the risk of wind abandonment exists. On the contrary, when the actual wind power output is smaller than the lower bound of the acceptable wind power domain, the up-regulation reserve capacity of the system is insufficient, and the load loss risk is caused. If the actual output of the wind power is in the digestible wind power domain, the wind power plant does not bring risks to the operation of the system at the moment.
Based on CVaR, the wind abandoning risk and the load losing risk can be calculated by the formulas (1) and (2) respectively:
Figure BDA0003015883560000051
Figure BDA0003015883560000052
in the formula (I), the compound is shown in the specification,
Figure BDA0003015883560000053
representing the maximum value of wind power output; x and Pr (x) respectively represent wind power output and probability density functions thereof.
(1.2) in order to improve the calculation efficiency of the model, the operation risk is linearized, which is specifically as follows:
Figure BDA0003015883560000054
Figure BDA0003015883560000055
in the formula, s is the number of sections of piecewise linearization; m and n are coefficients of the linearization constraint.
In the specific implementation of step S12, a two-stage three-layer multi-region grid dynamic economic dispatching model is established according to the operational risk and the acceptable wind power region.
For the two-stage three-layer multi-area power grid dynamic economic dispatching model provided by the invention, the first stage is used for dispatching the output of the unit and the transmission power plan of the connecting line in the area according to the wind power prediction output value, and determining the standby capacity of the unit and the connecting line and the wind power domain capable of being consumed so as to deal with the wind power uncertainty; and in the second stage, rescheduling is carried out according to the actual wind power output and the running standby arranged in the first stage, so that wind abandonment and load loss of all scenes in a digestible wind power domain are avoided. Meanwhile, the scheduling models of the two phases are not isolated but unified. The scheduling plan made in the first stage is to ensure that there is enough adjustment space to meet the operation constraint in the worst scene in the second stage. The two-stage problem is solved in a synergistic manner, so that the system operation cost, the standby cost and the operation risk can be minimized, and a reasonable wind power domain can be obtained.
(2.1) first stage objective function construction
The model provided by the invention divides a multi-region interconnected power system into a power transmitting terminal subsystem and a power receiving terminal subsystem, and the target function formula of the model minimizes the total operation cost, the standby cost and the operation risk of each subsystem, as shown in a formula (5).
Figure BDA0003015883560000061
In the formula, T, G and W are respectively a time set, a generator set and a wind power plant set of the dynamic economic dispatching problem to be researched; superscripts se and re respectively represent a sending-end subsystem and a receiving-end subsystem; superscript 0 represents the first stage problem variable; pg,tRepresenting the output of the traditional generator g at the moment t; fg(. h) is a fuel cost function;
Figure BDA0003015883560000062
and
Figure BDA0003015883560000063
upward and downward reserve capacities provided for the units respectively;
Figure BDA0003015883560000064
and
Figure BDA0003015883560000065
respectively punishment of unit wind abandon and unit load loss;
Figure BDA0003015883560000066
and
Figure BDA0003015883560000067
the standby cost, namely the opportunity cost of generating power by the unit. Since the operational constraints of the sending-end subsystem and the receiving-end subsystem are substantially the same, the superscripts se and re will be omitted below for brevity of the text, except for specific description.
The invention adopts a piecewise linearization function to describe the unit operation cost, as shown in formulas (6) - (8).
Figure BDA0003015883560000068
Figure BDA0003015883560000069
Figure BDA00030158835600000610
In the formula, K represents a cost segment set;
Figure BDA00030158835600000611
and
Figure BDA00030158835600000612
and respectively representing the output value, the maximum value and the cost coefficient of each section of the unit.
(2.2) first-stage constraint construction
(2.2.1) node Power balance constraints
The power balance constraints of the sending-end subsystem and the receiving-end subsystem are respectively as follows.
Figure BDA00030158835600000613
Figure BDA00030158835600000614
In the formula, D represents a regional bus set; gd、WdAnd BdRespectively representing a generator, a wind power plant and a connecting line set which are connected with a bus d; l | to (l) ═ d and l | fr (l) ═ d represent the transmission lines for power injection and outflow of the bus bar d, respectively; pw,tRepresenting the wind power consumption of the wind power plant w at the time t; pb,tThe power of the tie line b at time t corresponds to a load for the transmitting-side subsystem and a power supply for the receiving-side subsystem;
Figure BDA0003015883560000071
represents the transmission power of line l at time t; pd,tThe load of node d at time t.
(2.2.2) line Power flow and Power Angle constraints
Figure BDA0003015883560000072
Figure BDA0003015883560000073
In the formula (I), the compound is shown in the specification,
Figure BDA0003015883560000074
and
Figure BDA0003015883560000075
respectively the voltage phase of the busbar connected to the transmission line lAn angle; x is the number oflIs the line reactance;
Figure BDA0003015883560000076
is the upper limit of the current of the line l;
Figure BDA0003015883560000077
andθthe upper limit value and the lower limit value of the voltage phase angle are respectively. And (3) calculating the direct current power flow and setting a line capacity limit by using a constraint (11), wherein the constraint (12) is a power angle constraint.
(2.2.3) Unit ramp restriction
Figure BDA0003015883560000078
Figure BDA0003015883560000079
In the formula, RU,gAnd RD,gThe maximum value of the upward and downward climbing of the unit g per hour is respectively. The unit climbing capacity under the worst operation scene is guaranteed through the constraints (13) - (14), and decoupling on the unit operation time is achieved.
(2.2.4) Unit output and Standby constraints
Figure BDA00030158835600000710
Figure BDA00030158835600000711
Figure BDA00030158835600000712
In the formula (I), the compound is shown in the specification,
Figure BDA00030158835600000713
and
Figure BDA00030158835600000714
the maximum and minimum output limits of the generator set g are respectively.
(2.2.5) wind power output restraint
Figure BDA00030158835600000715
Figure BDA00030158835600000716
(3)-(4) (20)
Equations (18) - (19) describe the wind farm ground state contribution and the digestible wind farm, and equation (20) calculates the corresponding operational risk.
(2.2.6) Link Power and Adjustable Capacity constraints
Figure BDA00030158835600000717
Figure BDA0003015883560000081
Figure BDA0003015883560000082
Figure BDA0003015883560000083
Figure BDA0003015883560000084
In the formula (I), the compound is shown in the specification,
Figure BDA0003015883560000085
and
Figure BDA0003015883560000086
the upward and downward adjustment capacities of the tie line b are respectively set;
Figure BDA0003015883560000087
is the tie line maximum power limit. Junctor transmission power
Figure BDA0003015883560000088
And its regulating capacity
Figure BDA0003015883560000089
Is the coupling variable between the sending terminal subsystem and the receiving terminal subsystem. Equations (21) - (22) are consistency constraints. Wherein, the formula (21) represents that the power transmitted by the ground state of the transmitting terminal system is equal to the power received by the receiving terminal system; equation (22) indicates that the link-adjusted capacity provided by the sending-end subsystem is equal to the adjusted capacity available to the receiving-end subsystem. Equations (23) - (24) are the same form as equations (15) - (17), describing the junctor ground state power and tunable capacity, reflecting the junctor power flow constraint.
(2.3) second stage objective function construction
The second stage is to perform re-dispatching on the basis of the dispatching plan formulated in the first stage according to the actual wind power output. In order to deal with the uncertainty of wind power output and ensure the safety and reliability of a dispatching plan, the second stage problem requires that no abandoned wind and no load loss are generated under the worst operation condition in a wind power domain. The second stage objective function is shown in equation (26).
Figure BDA00030158835600000810
In the formula,. DELTA.Pw,tAnd Δ Ld,tRespectively is a wind curtailment variable and a load loss relaxation variable;
Figure BDA00030158835600000811
and
Figure BDA00030158835600000812
wind power output and delivery end grid tie-line is describedUncertainty in power regulation. The worst operation scene corresponding to the appointed dispatching plan can be found through the max-min double-layer optimization, and the safety and the reliability of the dispatching plan are guaranteed by optimizing the relaxation variable to 0.
(2.4) second stage constraint construction
(2.4.1) Power Balancing and line flow constraints
The second stage problem also includes node power balance and line flow constraint, and unlike the first stage, relaxation variables are introduced, specifically as shown in equations (27) - (30).
Figure BDA00030158835600000813
Figure BDA00030158835600000814
Figure BDA0003015883560000091
Figure BDA0003015883560000092
In the formula, superscript u denotes a second stage variable.
(2.4.2) relaxation of variable constraints
Figure BDA0003015883560000093
Figure BDA0003015883560000094
(2.4.3) Unit Regulation constraints
Figure BDA0003015883560000095
And the output of the unit at the second stage is adjusted by combining the reserved spare capacity on the basis of determining the operating point at the first stage.
(2.4.4) subject to end-subsystem tie-line adjustment constraints
Figure BDA0003015883560000096
In order to achieve backup sharing between zones, the receiver subsystem in the model created by the present invention treats the tie-line as an adjustable power source. As with the genset, the receiver subsystem tie power can be adjusted within the optimized tie reserve capacity.
(2.4.5) indeterminate concentration Beam
Figure BDA0003015883560000097
Figure BDA0003015883560000098
Figure BDA0003015883560000099
Figure BDA00030158835600000910
The present invention takes into account two types of uncertainty. Equations (35) - (36) describe the uncertainty in the wind power contribution in all subsystems using the box uncertainty set. In order to meet the demand of the receiver-side subsystem for the tie line power adjustment, the transmitter-side subsystem considers the tie line power as a load with uncertainty and is described by equations (37) - (38). After optimization, when the receiving end system adjusts the power of the connecting line in a planning range, the sending end system can normally operate. It should be noted that the boundaries of these two types of indeterminate sets need to be optimized, rather than being set in advance.
In the specific implementation of step S13, a column constraint generation algorithm is adopted, and the multi-region power grid dynamic economic scheduling model is solved in a main and sub-problem iteration form.
Solving the model by adopting a column constraint generation (C & CG) algorithm in a main and sub problem iteration mode; the models described in (5) to (38) are written in compact form as shown in equations (39) to (42):
Figure BDA0003015883560000101
s.t.F0x0≤f (40)
Figure BDA0003015883560000102
Figure BDA0003015883560000103
in the formula, x0、xuZ and s represent the first stage variables, the second stage variables, the auxiliary variables representing uncertainty and the slack variables, respectively; c. e, F, F, H, H, V and V are the corresponding coefficient matrices. Equation (39) represents the first-stage objective function, the first-stage constraints are (40) - (41), and the second-stage objective function and constraints are equation (42).
The sub-problem is the second stage of the two-tier rescheduling problem. The invention converts the inner layer problem into the dual problem and constructs an equivalent single-layer bilinear optimization problem. The sub-problems during the mth iteration are shown in equations (43) - (45).
Figure BDA0003015883560000104
Figure BDA0003015883560000107
z∈[0,1] (45)
Where ξ is the dual variable of the inner layer problem. The bilinear terms contained in equation (43) can be linearized with precision using the large M method.
And identifying the worst operation scene after solving the sub-problem, and adding the corresponding constraint condition into the main problem. The main problems in the mth iteration are shown in equations (46) - (48).
Figure BDA0003015883560000105
s.t.F0x0≤f (47)
Figure BDA0003015883560000106
In the formula, xu(j)Is a newly added decision variable in the iterative process.
According to the main and sub problems, the C & CG algorithm solving steps are as follows:
1) initialization: setting the iteration number m to be 1;
2) solving the main problem of equations (46) - (48) to obtain the control variable xu(m)；
3) Solving the subproblems of the formulas (43) - (45) according to the main problem result to obtain the objective function value Vs and the worst operation working condition z*(m)；
4) And (3) convergence judgment: if Vs is 0, the problem converges and the iteration is stopped; otherwise, adding the worst operation condition constraint (48) to the main problem, continuing iteration, and returning to the step 2).
Corresponding to the embodiment of the multi-region power grid dynamic economic dispatching method, the application also provides an embodiment of a multi-region power grid dynamic economic dispatching device.
Fig. 3 is a block diagram illustrating a multi-region grid dynamic economic dispatch device according to an exemplary embodiment. Referring to fig. 3, the apparatus:
the risk evaluation module 31 is used for evaluating the operation risk of the power grid according to the condition risk value and defining a consumable wind power domain;
the model generation module 32 is used for establishing a two-stage three-layer multi-area power grid dynamic economic dispatching model according to the operation risk and the wind power domain capable of being absorbed;
and the model solving module 33 is used for solving the dynamic economic dispatching model of the multi-region power grid in a main and sub problem iteration mode by adopting a column constraint generation algorithm so as to obtain a dispatching scheme and a reasonable wind power domain capable of being consumed.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
For the device embodiments, since they substantially correspond to the method embodiments, reference may be made to the partial description of the method embodiments for relevant points. The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of the application. One of ordinary skill in the art can understand and implement it without inventive effort.
Correspondingly, the present application also provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors are enabled to implement the multi-region power grid dynamic economic dispatching method as described above.
Accordingly, the present application also provides a computer readable storage medium, on which computer instructions are stored, wherein the instructions, when executed by a processor, implement the multi-region power grid dynamic economic dispatching method as described above.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.

Claims (10)

1. A dynamic economic dispatching method for a multi-region power grid is characterized by comprising the following steps:
evaluating the operation risk of the power grid according to the condition risk value and defining a consumable wind power domain;
establishing a two-stage three-layer multi-area power grid dynamic economic dispatching model according to the operation risk and the wind power area capable of being absorbed;
and solving the dynamic economic dispatching model of the multi-region power grid by adopting a column constraint generation algorithm in a main and sub problem iteration mode to obtain a dispatching scheme and a reasonable wind power domain capable of being consumed.
2. The method of claim 1, wherein evaluating grid operational risk and defining a digestible wind domain as a function of conditional risk value comprises:
(1.1) defining operational risks including wind curtailment Risk (CVaR) in terms of a notion of conditional Risk values+) And risk of loss of load (CVaR)-)。
(1.2) defining the digestible wind power domain as a wind power output range which does not bring risks to the operation of the power grid.
3. The method of claim 1, wherein the two-stage three-layer multi-area grid dynamic economic dispatch model comprises the following four parts: a first stage objective function, a first stage constraint condition, a second stage objective function and a second stage constraint condition;
(2.1) first stage objective function
Dividing a multi-region interconnected power system into a power transmitting end subsystem and a power receiving end subsystem, wherein a target function formula of the multi-region interconnected power system minimizes the total operation cost, the standby cost and the operation risk of each subsystem;
(2.2) first stage constraints
The first stage constraints include: node power balance constraint, line tide and power angle constraint, unit climbing constraint, unit output and standby constraint, wind power output constraint, tie line power and adjustable capacity constraint and a feasible region defined by a second-stage problem;
(2.3) second stage objective function
The second stage objective function is to minimize the wind curtailment and the load loss under the worst operation condition to zero according to the dispatching plan of the first stage;
(2.4) second stage constraint Condition
The second stage constraints include: power balance and line power flow constraint, relaxation variable constraint, unit regulation constraint, receiving end subsystem tie line regulation constraint and uncertain set constraint.
4. The method of claim 1, wherein the multi-region power grid dynamic economic dispatching model is solved in a main and sub problem iteration form by adopting a column constraint generation algorithm, and the method comprises the following steps:
(3.1) initialization: setting the iteration number m to be 1;
(3.2) solving the main problem to obtain a control variable of the main problem;
(3.3) solving the sub-problem according to the main problem result to obtain an objective function value Vs and the worst operation condition;
(3.4) convergence judgment: if Vs is 0, the problem converges and the iteration is stopped; otherwise, adding the worst operation condition constraint to the main problem, continuing iteration, and returning to (3.2) when m is m + 1.
5. A multi-region power grid dynamic economic dispatching device is characterized by comprising:
the risk evaluation module is used for evaluating the operation risk of the power grid according to the condition risk value and defining a digestible wind power domain;
the model generation module is used for establishing a two-stage three-layer multi-region dynamic economic dispatching model according to the power grid operation risk and the wind power domain capable of being absorbed;
and the model solving module is used for solving the multi-region dynamic economic dispatching model in a main and sub problem iteration mode by adopting a column constraint generation algorithm so as to obtain a dispatching scheme and a reasonable wind power domain capable of being consumed.
6. The apparatus of claim 5, wherein evaluating grid operational risk and defining a digestible wind domain as a function of conditional risk value comprises:
(1.1) defining operational risks according to the concept of conditional risk value, wherein the operational risks comprise wind curtailment risks and load loss risks.
(1.2) the digestible wind power domain is defined as a wind power output range which does not bring risks to the operation of a power grid.
7. The apparatus of claim 5, wherein the two-stage three-layer multi-area grid dynamic economic dispatch model comprises the following four parts: a first stage objective function, a first stage constraint condition, a second stage objective function and a second stage constraint condition;
(2.1) first stage objective function
Dividing a multi-region interconnected power system into a power transmitting end subsystem and a power receiving end subsystem, wherein a target function formula of the multi-region interconnected power system minimizes the total operation cost, the standby cost and the operation risk of each subsystem;
(2.2) first stage constraints
The first stage constraints include: node power balance constraint, line tide and power angle constraint, unit climbing constraint, unit output and standby constraint, wind power output constraint, tie line power and adjustable capacity constraint and a feasible region defined by a second-stage problem;
(2.3) second stage objective function
The second stage objective function is to minimize the wind curtailment and the load loss under the worst operation condition to zero according to the dispatching plan of the first stage;
(2.4) second stage constraint Condition
The second stage constraints include: power balance and line power flow constraint, relaxation variable constraint, unit regulation constraint, receiving end subsystem tie line regulation constraint and uncertain set constraint.
8. The apparatus of claim 5, wherein the multi-region power grid dynamic economic dispatch model is solved in a main and sub-problem iteration form by using a column constraint generation algorithm, and the method comprises:
(3.1) initialization: setting the iteration number m to be 1;
(3.2) solving the main problem to obtain a control variable of the main problem;
(3.3) solving the sub-problem according to the main problem result to obtain an objective function value Vs and the worst operation condition;
(3.4) convergence judgment: if Vs is 0, the problem converges and the iteration is stopped; otherwise, adding the worst operation condition constraint to the main problem, continuing iteration, and returning to (3.2) when m is m + 1.
9. An electronic device, comprising:
one or more processors;
a memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-4.
10. A computer-readable storage medium having stored thereon computer instructions, which, when executed by a processor, carry out the steps of the method according to any one of claims 1 to 4.
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