CN111525568B - Modeling method and system suitable for electric power system rescheduling - Google Patents
Modeling method and system suitable for electric power system rescheduling Download PDFInfo
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Abstract
The invention provides a modeling method and a modeling system suitable for electric power system re-scheduling, which realize a method for replying and analyzing the effect of a power grid scheduling actual operation scheme from the 'after-the-fact' perspective, thereby promoting the closed-loop control of electric power scheduling. The method comprises the following steps: acquiring a power grid model and an operation mode in an analysis time period; solving a sensitivity matrix of branch active power to node injection; and establishing a post ideal scheduling operation scheme model.
Description
Technical Field
The invention relates to the field of operation and analysis of power systems, in particular to a method suitable for rescheduling of a power system and a power scheduling system.
Background
The power grid dispatching mechanism is used as a power system operation command center, and how to improve the economical efficiency and the energy-saving and environment-friendly level of power grid operation on the premise of considering the safe operation of a power grid becomes an important task of current power grid dispatching work. In order to improve the system operation ideality level, the current scheduling operation manager starts from links such as mode formulation, plan arrangement, real-time control and the like in the actual scheduling production process, and researches and adopts a large number of technical means and management measures. However, such scheduling operation promotion measures mostly focus on the "in advance" or "in the middle" link of scheduling production, and cannot accurately calculate the multi-balancing machine mode and the additional error caused by the node network loss linearization process.
Disclosure of Invention
In view of this, the embodiment of the present invention provides a modeling method and system suitable for electric power system re-scheduling, which implement a method for replicating and analyzing the effect of the actual operation scheme of power grid scheduling from a "post" perspective, thereby promoting closed-loop management and control of electric power scheduling, and effectively improving accuracy and practicability of the model.
An embodiment of the present invention provides a modeling method suitable for electric power system rescheduling, including: acquiring a power grid structure model and an operation data section in an analysis time period; solving a sensitivity matrix of branch active power to node injection according to the power grid structure model and the operation data section; correcting the sensitivity matrix; and establishing a post ideal scheduling operation scheme model according to the correction result of the sensitivity matrix.
In one embodiment, the correcting the sensitivity matrix includes: correcting the sensitivity matrix by adopting a power regulation coefficient matrix; and correcting the sensitivity matrix by adopting the network loss rate.
In one embodiment, the modifying the sensitivity matrix with the power adjustment coefficient matrix includes: constructing a frequency modulation characteristic coefficient matrix according to an actual frequency modulation distribution strategy of the unit; and correcting the sensitivity matrix by adopting the frequency modulation characteristic coefficient matrix.
In one embodiment, obtaining a model of a power grid structure over an analysis period comprises: power grid equipment parameters; obtaining an operating data section in an analysis time period, comprising: the operation mode of the power grid and the unit power at different moments. .
In one embodiment, the solving of the sensitivity matrix of branch active power injection to the node includes: obtaining a branch power flow equation according to the direct current power flow equation; writing the branch power flow equation into a branch power flow matrix; and obtaining a sensitivity matrix of branch active power to node injection according to the branch node incidence matrix of the power grid to be analyzed.
In an embodiment, after obtaining a sensitivity matrix of branch active power injection to a node injection according to a branch node incidence matrix of a power grid to be analyzed, the method includes: and obtaining the active sensitivity of the calculation branch according to the sensitivity matrix of the active power of the path to the node injection.
In one embodiment, the establishing the post-ideal scheduling operation scheme model includes: and obtaining the post ideal scheduling operation scheme model by taking the operation cost as a target.
In one embodiment, a commercial mathematical solver is used to solve the optimization model of the post-hoc ideal scheduling operating scenario model.
A system adapted for power system rescheduling, comprising:
the data acquisition module is used for acquiring a power grid structure model and an operation data section in an analysis time period;
the calculation module is used for solving a sensitivity matrix of branch active power to node injection according to the power grid structure model and the operation data section;
the correction module is used for correcting the sensitivity matrix; and
and the rescheduling module is used for establishing a post ideal scheduling operation scheme model for rescheduling the power system according to the correction result of the sensitivity matrix.
According to the modeling method and system suitable for post-scheduling of the power system, provided by the embodiment of the invention, a power grid structure model and an operation data section in an analysis time period are obtained; solving a sensitivity matrix of branch active power to node injection according to a power grid structure model and an operation data section; correcting the sensitivity matrix; and according to the correction result of the sensitivity matrix, a post-event ideal scheduling operation scheme model is established, and the effect of the power grid scheduling actual operation scheme is copied and analyzed from the 'post' perspective, so that the closed-loop management and control of power scheduling are promoted, and the accuracy and the practicability of the model are effectively improved.
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The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic flowchart illustrating a modeling method for post-scheduling of an electric power system according to an embodiment of the present invention.
Fig. 2 is a schematic flowchart illustrating a modeling method for post-scheduling of an electric power system according to another embodiment of the present invention.
Fig. 3 is a schematic flowchart illustrating a modeling method for post-scheduling of an electric power system according to another embodiment of the present invention.
Detailed Description
The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
The following detailed description is exemplary in nature and is intended to provide further details of the invention. Unless otherwise defined, all technical terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention.
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 only a part of the embodiments of the present invention, and not all of the embodiments. 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.
Fig. 1 is a schematic flowchart illustrating a modeling method for post-scheduling of an electric power system according to an embodiment of the present invention.
As shown in fig. 1, the modeling method for electric power system rescheduling includes:
step 01: acquiring a power grid structure model and an operation data section in an analysis time period; and acquiring a power grid structure model and an actual operation data section from an EMS (energy management system) of a dispatching center, wherein the actual operation data section comprises power grid equipment parameters, a power grid operation mode, unit power measurement at different moments and the like. The SCADA and the state estimation module in the EMS system both store the operation modes of the system at all times, and in order to reduce the influence of phenomena such as measuring burrs on subsequent calculation, the invention adopts the power grid operation mode stored by state estimation as an analysis basis.
Step 02: solving a sensitivity matrix of branch active power to node injection according to a power grid structure model and an operation data section; because the stable section is the set of a group of branches, the sensitivity of the active power of the stable section to the active power of each generator can be converted into the sensitivity of the active power of the branches and the active power of the generators.
Step 03: the sensitivity matrix is corrected.
Step 04: and establishing a post ideal scheduling operation scheme model according to the correction structure of the sensitivity matrix. And establishing a post ideal scheduling operation scheme model by taking the lowest operation cost as a target.
By the modeling method, the effect of the actual operation scheme of the power grid dispatching can be copied and analyzed from the 'after affairs' perspective, so that the closed-loop control of the power dispatching is promoted. The method is used for analyzing the operation state of the power grid on the previous day. Compared with the traditional optimization scheduling model, the optimization scheduling method and the optimization scheduling model solve the defect that the traditional optimization model can only analyze a single balancing machine mode, take the influence of node grid loss change into consideration in the sensitivity model aiming at the characteristic of scheduling by using post optimization, reduce the linearization error in the traditional optimization scheduling model, and improve the calculation precision, so that the analysis result is more consistent with the actual operation characteristic of a power grid.
Fig. 2 is a schematic flow chart illustrating a process of correcting a sensitivity matrix according to another embodiment of the present invention.
As shown in fig. 2, the correcting the sensitivity matrix includes: correcting the sensitivity matrix by adopting a power regulation coefficient matrix; and further correcting the corrected sensitivity matrix by adopting the network loss rate. Wherein the adapting the sensitivity matrix by the power adjustment coefficient matrix may include:
step 031: and constructing a frequency modulation characteristic coefficient matrix according to an actual frequency modulation distribution strategy of the unit.
Step 032: and correcting the sensitivity matrix by adopting the frequency modulation characteristic coefficient matrix.
By adopting the method for correcting the sensitivity matrix by the power regulation coefficient matrix, the distribution of the unbalanced power of a plurality of generators participating in the system can be calculated. The setting of the frequency modulation coefficient parameters can be primary frequency modulation coefficients or secondary frequency modulation parameters according to the actual running state of the system. And during primary frequency modulation, the distribution coefficient is determined by the frequency modulation characteristic of the generator, and during secondary frequency modulation, the distribution coefficient is determined by an AGC (automatic gain control) regulation strategy.
The sensitivity matrix is corrected by adopting the network loss rate, the sensitivity matrix can be corrected according to the actual network loss rate of the system, and the problem that double errors are caused in the linearization process of the traditional sensitivity matrix to the network loss is solved. In the modeling process, generators and loads on the same node are distinguished, and the influence of the generator output and the load active power on the section power is converted by adopting different sensitivity matrixes, so that the accuracy of stable section power constraint is improved.
In an embodiment of the present invention, acquiring a power grid model and an operation mode in an analysis period includes: and acquiring a power grid structure model and an actual operation data section from an energy management system of the dispatching center, wherein the actual operation data section comprises power grid equipment parameters, a power grid operation mode, unit power measurement at different moments and the like.
Fig. 3 is a schematic flow chart illustrating a process of solving a sensitivity matrix of branch active power injection to node injection according to another embodiment of the present invention.
As shown in fig. 3, solving the sensitivity matrix of branch active power injection to the node includes:
step 0211: obtaining a branch power flow equation according to the direct current power flow equation;
step 0212: writing a branch power flow equation into a branch power flow matrix;
step 0213: obtaining a sensitivity matrix of branch active power to node injection according to a branch node incidence matrix of a power grid to be analyzed; and
step 0214: and calculating the active sensitivity of the branch according to the sensitivity matrix of the active of the branch to the node injection.
In one embodiment of the invention, the 'after-the-fact' optimization re-scheduling is carried out according to the actual operation data of the power grid, and the following technical scheme is adopted for realizing the following steps:
firstly, a power grid model and an operation mode in an analysis time period are obtained. And acquiring a power grid structure model and an actual operation data section from an EMS (energy management system) of a dispatching center, wherein the actual operation data section comprises power grid equipment parameters, a power grid operation mode, unit power measurement at different moments and the like. The SCADA and the state estimation module in the EMS system both store the operation modes of the system at all times, and in order to reduce the influence of phenomena such as measuring burrs on subsequent calculation, the invention adopts the power grid operation mode stored by state estimation as an analysis basis.
Secondly, solving a sensitivity matrix of the branch to node injection. Because the stable section is the set of a group of branches, the sensitivity of the active power of the stable section to the active power of each generator can be converted into the sensitivity of the active power of the branches and the active power of the generators. The method for solving the branch active power and the generator active power sensitivity comprises the following steps:
firstly, a direct current power flow equation is briefly recorded:
P＝Bθ (2)
in the formula (2), P is a node injection power vector, theta is a point voltage phase angle vector, and B is an imaginary part of a node admittance matrix. Similarly, according to the simplified conditions of the P-Q decomposition method, the branch power flow equation can be obtained as follows:
in the formula (3), the subscript i is the number of the head end of the branch, j is the number of the tail end of the branch, PijFor active power flow at the beginning of the branch, BijFor branch admittance, θijIs the phase angle difference between the head and the tail of the branch, thetaiIs the phase angle of the head end, thetajIs the terminal phase angle, xijIs the branch reactance. The branch tide equation is written in a matrix form as follows:
Pl＝BlΦ (4)
in the formula (4), PlVector formed for active power flow of each branch, BlAnd phi is a phase angle difference vector at two ends of each branch.
A branch node incidence matrix of a power grid to be analyzed is A, A is a matrix with m rows and n columns, wherein m is the number of branches, and n is the number of nodes. In the row element corresponding to the branch ij, the ith column is 1, the jth column is-1, and other elements are all 0. Then there are:
Pl＝BlΦ＝BlAθ＝BlAB-1P (5)
from formula (5):
ΔPl＝BlAB-1ΔP (6)
as shown in formula (6), if F is equal to BlAB-1Then there is Δ PlF Δ P, i.e. the matrix F is the sensitivity matrix of branch active power injection to the node.
And thirdly, correcting the sensitivity matrix and solving the unit sensitivity of the fault plane. Consider first the situation where multiple generators are responsible for system imbalance power. The obtained F is a sensitivity matrix under the condition of only considering a single balancing machine according to the formula (6), and a plurality of generators share the unbalanced power of the system according to a certain control strategy in the actual operation process of the power system. The active power distribution strategy of each node is assumed as follows:
in the formula (7), Δ PgiUnbalanced power, k, borne by the generator at node iiTo the distribution coefficient, Δ PΣThe power unbalance of the whole network. According to this allocation strategy, a new sensitivity matrix F1The calculation method is as follows:
F1＝KF (8)
in the formula (8), the K matrix is a modification matrix formed according to the active power distribution coefficients of the nodes in the formula (7), and the specific form is as follows:
after the sensitivity matrix of the branch active power to the node injection is obtained, the sensitivity of the stable section to the unit can be conveniently obtained. If the stable section m consists of the j-th branch and the k-th branch, the sensitivity of the stable section m to the active power injection of the unit on the node i
Comprises the following steps:
in the formula, F1jiIs a matrix F1Element of jth row, ith column, F1kiIs a matrix F1Line k, column i.
And then, further perfecting the error of the conventional sensitivity matrix to the network loss change part, and solving the sensitivity of the section to the load. Assuming that the network loss rate of the whole system at the time t is loss (t), loss (t) can be directly obtained from the state estimation result in the step 1. After considering the net loss factor, the new sensitivity matrix F2The calculation method is as follows:
F2＝(1+Loss(t))F1 (11)
obtaining F2Then, the stable cross section sensitivity to load can be further obtained. If the stable section m is formed by the j-th and k-th branches, the sensitivity of the stable section m to the active injection of the load on the node i
Comprises the following steps:
F2jiis a matrix F2Element of jth row, ith column, F2kiIs a matrix F2Line k, column i.
And finally, establishing a post ideal scheduling operation scheme model. With the lowest operating cost as the target, the detailed model is as follows:
Pimin≤pi(t)≤Pimax
-ΔPi_down≤(pi(t+1)-pi(t))≤ΔPi_up (13)
in the formula:
t is the number of time segments in the analysis period; i is the number of system units; p is a radical ofi(t) is a variable to be solved, and means the active power of the unit i at the moment t; di(t) is the load active power state estimated value of the node i at the moment t; x is the number ofi(t) is the continuous start-up and shut-down time of the unit i at t; x is the number ofi(t)>0 denotes the continuous boot time, xi(t)<0 represents continuous down time; u. ofi(t) is the state of the unit i at t, ui(t) < 1 > indicates power-on, uiAnd (t) ═ 0 indicates shutdown. DNi(pi(t)) is the operating cost of unit i at t; DS (direct sequence)i(xi(t-1),ui(t)) is the starting cost from the time period t-1 to the time period t when the state of the unit i changes; pm_tdmaxThe power control limit value of the d-th stable section at the time t is set; piminThe active lower limit of the ith generator is set; pimaxThe active upper limit of the ith generator is set; delta Pi_downThe landslide capability of the g-th generator; delta Pi_upThe climbing capability of the ith generator.
The optimization model in equation (13) is solved using a general commercial mathematical solver.
In an embodiment of the invention, the post-scheduling model of the power system is established by using the modeling method suitable for the post-scheduling of the power system. Obtaining a power grid structure model and an operation data section in an analysis time period; solving a sensitivity matrix of branch active power to node injection according to a power grid structure model and an operation data section; correcting the sensitivity matrix; and according to the correction result of the sensitivity matrix, a post-incident ideal scheduling operation scheme model is established, and the effect of the actual operation scheme of the power grid scheduling can be copied and analyzed from the 'post' perspective by the method, so that the closed-loop control of the power scheduling is promoted. The invention is provided for analyzing the operation state of the power grid on the previous day. Compared with the traditional optimization scheduling model, the optimization scheduling method and the optimization scheduling model solve the defect that the traditional optimization model can only analyze a single balancing machine mode, take the influence of node grid loss change into consideration in the sensitivity model aiming at the characteristic of scheduling by using post optimization, reduce the linearization error in the traditional optimization scheduling model, and improve the calculation precision, so that the analysis result is more consistent with the actual operation characteristic of a power grid.
The electric power system is rescheduled by adopting the electric power system post-scheduling model established by the invention; according to the actual operation data of the power grid acquired afterwards, optimization and rescheduling are carried out, and an optimal adjustment strategy is solved; the effect of the previous actual operation scheme of power grid dispatching is analyzed and decision-making is assisted from the 'after-the-fact' perspective, and the defects in the daily dispatching process can be found by power dispatching operation personnel through the given after-the-fact adjustment suggestion.
In an embodiment of the present invention, a system for rescheduling an electrical power system includes:
the data acquisition module is used for acquiring a power grid structure model and an operation data section in an analysis time period;
the calculation module is used for solving a sensitivity matrix of branch active power to node injection according to the power grid structure model and the operation data section;
the correction module is used for correcting the sensitivity matrix; and
and the rescheduling module is used for establishing a post ideal scheduling operation scheme model for rescheduling the power system according to the correction result of the sensitivity matrix.
In this embodiment, the steps executed by each module are the same as those of each method in the method for re-scheduling the power system, and are not described herein again.
In an embodiment of the present invention, a system for rescheduling an electrical power system includes: a processor and a memory coupled to the processor, the memory storing a computer program which, when executed by the processor, performs the method steps of a method for power system rescheduling.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (9)
1. A modeling method suitable for electric power system rescheduling,
acquiring a power grid structure model and an operation data section in an analysis time period;
solving a sensitivity matrix of branch active power to node injection according to the power grid structure model and the operation data section;
correcting the sensitivity matrix; and
establishing a post ideal scheduling operation scheme model according to the correction result of the sensitivity matrix;
the correcting the sensitivity matrix comprises:
correcting the sensitivity matrix by adopting a frequency modulation characteristic coefficient matrix;
and further correcting the corrected sensitivity matrix by adopting the network loss rate.
2. The modeling method suitable for electric power system rescheduling of claim 1, wherein said modifying the sensitivity matrix with the fm characteristic coefficient matrix comprises:
constructing a frequency modulation characteristic coefficient matrix according to an actual frequency modulation distribution strategy of the unit; and
and correcting the sensitivity matrix by adopting the frequency modulation characteristic coefficient matrix.
3. The modeling method for electric power system rescheduling of claim 1, wherein said grid structure model comprises: power grid equipment parameters; the operational data profile comprises: the operation mode of the power grid and the unit power at different moments.
4. The modeling method suitable for electric power system re-scheduling according to claim 1, wherein said solving the sensitivity matrix of branch active power to node injection comprises:
obtaining a branch power flow equation according to the direct current power flow equation;
writing the branch power flow equation into a branch power flow matrix;
and obtaining a sensitivity matrix of branch active power to node injection according to the branch node incidence matrix of the power grid to be analyzed.
5. The modeling method suitable for electric power system re-scheduling according to claim 4, wherein after obtaining the sensitivity matrix of branch active power to node injection according to the branch node incidence matrix of the electric network to be analyzed, the method comprises: and calculating to obtain the active sensitivity of the branch according to the sensitivity matrix of the active of the branch to the node injection.
6. The modeling method suitable for electric power system rescheduling of claim 1, wherein said establishing a post-hoc ideal scheduling operating scenario model comprises: and obtaining the post ideal scheduling operation scheme model by taking the operation cost as a target.
7. The modeling method applicable to electric power system re-scheduling of claim 6, wherein a commercial mathematical solver is used to solve the optimization model of the post-event ideal scheduling operating scenario model.
8. Modeling method applicable to power system re-scheduling in accordance with claim 1,
the established post ideal scheduling operation scheme model comprises the following steps:
Pimin≤pi(t)≤Pimax
-ΔPi_down≤(pi(t+1)-pi(t))≤ΔPi_up
in the formula: t is the number of time segments in the analysis period; i is the number of system units; p is a radical ofi(t) is a variable to be solved, and means the active power of the unit i at the moment t; di(t) is the load active power state estimated value of the node i at the moment t; x is the number ofi(t) is the continuous start-up and shut-down time of the unit i at t; x is the number ofi(t) > 0 denotes continuous boot time, xi(t) < 0 represents continuous down time; u. ofi(t) is the state of the unit i at t, ui(t) < 1 > indicates power-on, ui(t) ═ 0 indicates shutdown; DNi(pi(t)) is the operating cost of unit i at t; DS (direct sequence)i(xi(t-1),ui(t)) is the starting cost from the time period t-1 to the time period t when the state of the unit i changes; pm_tdmaxThe power control limit value of the d-th stable section at the time t is set; piminThe active lower limit of the ith generator is set; pimaxThe active upper limit of the ith generator is set; delta Pi_downThe landslide capability of the g-th generator; delta Pi_upThe climbing capability of the ith generator.
9. A system adapted for electric power system rescheduling, comprising:
the data acquisition module is used for acquiring a power grid structure model and an operation data section in an analysis time period;
the calculation module is used for solving a sensitivity matrix of branch active power to node injection according to the power grid structure model and the operation data section;
the correction module is used for correcting the sensitivity matrix; and
the rescheduling module is used for establishing a post ideal scheduling operation scheme model for rescheduling the power system according to the correction result of the sensitivity matrix;
the correcting the sensitivity matrix comprises:
correcting the sensitivity matrix by adopting a frequency modulation characteristic coefficient matrix;
and further correcting the corrected sensitivity matrix by adopting the network loss rate.
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