CN114156869A - Control method for participating in frequency adjustment of power system by electrified railway - Google Patents

Control method for participating in frequency adjustment of power system by electrified railway Download PDF

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CN114156869A
CN114156869A CN202111368431.XA CN202111368431A CN114156869A CN 114156869 A CN114156869 A CN 114156869A CN 202111368431 A CN202111368431 A CN 202111368431A CN 114156869 A CN114156869 A CN 114156869A
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frequency
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frequency modulation
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CN114156869B (en
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万灿
何子涵
宋永华
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Zhejiang University ZJU
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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
    • H02J3/002—Flicker reduction, e.g. compensation of flicker introduced by non-linear load
    • 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
    • H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
    • H02J3/241—The oscillation concerning frequency
    • 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
    • H02J2203/10—Power transmission or distribution systems management focussing at grid-level, e.g. load flow analysis, node profile computation, meshed network optimisation, active network management or spinning reserve management
    • 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]

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Abstract

The invention discloses a control method for participating in frequency regulation of an electric power system by an electrified railway, and belongs to the field of load side management and frequency control of the electric power system. Firstly, establishing a kinematic model of a train under frequency modulation control, then providing a multi-train cooperative control method to meet the frequency modulation specification of a power system, and finally constructing an electrified railway frequency control framework comprising day-ahead capacity estimation, intra-day frequency modulation parameter distribution and real-time frequency response; in addition, a sequence secant plane algorithm is provided to effectively solve the nonlinear integer optimization problem constructed in the day-ahead capacity estimation and day-wide frequency modulation parameter distribution stage. The method utilizes the characteristic that the train can change the running state in a short time, jointly regulates and controls a plurality of trains to jointly provide frequency regulation auxiliary service meeting requirements, can effectively improve the frequency response dynamics of the power system, and has an obvious supporting effect on the running control of the high-proportion renewable energy power system.

Description

Control method for participating in frequency adjustment of power system by electrified railway
Technical Field
The invention relates to a control method for participating in frequency regulation of an electric power system by an electrified railway, and belongs to the field of load side management and frequency control of the electric power system.
Background
The frequency of the power system reflects the source-to-load power balance and is one of the most important parameters of the power system. As more and more renewable energy sources are connected to the grid instead of traditional generator sets, frequency control of power systems is facing a huge challenge. Traditional methods that rely entirely on generator sets for frequency regulation become inadequate and uneconomical in the case of high-volatility, highly intermittent, renewable energy mass access. In recent years, the participation of the load side in the frequency control of the power system is one of the hot problems in the field of load side management and power system frequency. A great deal of research shows that flexible loads such as air conditioners, heat pumps, electric vehicles and the like have the capacity of participating in frequency control of an electric power system. Compared with an air conditioner, a heat pump and an electric automobile, the dynamic process of the electrified railway is relatively fast, a single train cannot maintain and regulate power for a long time, and currently, no published research on the participation of the electrified railway in frequency regulation is published. In fact, the train has the capability of adjusting the motion state in a short time on the premise of not influencing the accurate arrival of the train, so that the electrified railway has the theoretical potential of participating in frequency regulation. In addition, the modern electrified railway has a natural train dispatching center and a layered structure and also has a train-ground bidirectional communication device, which is very beneficial to centralized management and provides a practical foundation for the electrified railway to participate in frequency regulation and control.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide a control method for participating in frequency adjustment of an electric power system by an electrified railway.
In order to achieve the purpose, the invention adopts the following technical scheme:
a control method for an electrified railway to participate in frequency adjustment of a power system comprises the steps of firstly establishing a kinematic model of a train under frequency modulation control; on the basis, an electrified railway frequency control framework comprising day-ahead capacity estimation, day-in frequency modulation parameter distribution and real-time frequency response is provided; in order to effectively solve the problem of nonlinear integer optimization constructed in the day-ahead capacity estimation and day-interior frequency modulation parameter distribution stage, a sequence secant plane algorithm is provided.
The specific method comprises the following steps:
(1) establishing a kinematic model of a train under frequency modulation control
The dynamic model of the train moving under the traction gear u is as follows:
Figure BDA0003361716680000021
Figure BDA0003361716680000022
where M is train mass, gamma is coefficient of gyration, theta is rail slope, g is gravitational acceleration, a0,a1,a2Is the coefficient of air resistance, PmThe maximum traction power of the train. And solving the value of the differential equation at the time T by taking the current speed V and the current position X as initial conditions to obtain a speed function V (X, V, u, T) and a position function X (X, V, u, T) of the train movement.
In order to ensure that the train can arrive at the station accurately after providing frequency regulation service, a boundary driving strategy for enabling the train to arrive at the station as soon as possible is provided, and under the boundary driving strategy, the train only runs under the limitation of road speed limit and traction force per se. As long as the train can be quasi-point-to-station under the boundary driving strategy, a better driving strategy can be provided to make the train be quasi-point-to-station after frequency modulation service is provided, and the better driving strategy can be calculated by an automatic driving system of the train. The boundary driving strategy is described as follows:
a) the train is first accelerated in maximum traction gear;
b) if the speed of the train before the braking point reaches the road speed limit, the constant-speed cruising is started, otherwise, the train still runs in the maximum traction gear;
c) after the train reaches the braking point, braking is started with the common braking force until the train arrives at the station.
If the current speed of the train is v, the current position is x, the current time is t, and the train is on the sideThe arrival time under the boundary driving strategy is marked as Tarr(x,v,t)。
(2) Provides a frequency control framework of the electrified railway comprising day-ahead capacity estimation, day-in frequency modulation parameter distribution and real-time frequency response
The frequency control framework of the electrified railway mainly comprises day-ahead capacity estimation, day-time frequency modulation parameter distribution and real-time frequency response as shown in figure 1. Day-ahead capacity estimation: estimating maximum frequency modulation capacity of train according to planned operation information of train
Figure BDA0003361716680000031
Capacity P accepted by return of power systemup(ii) a And (3) intra-day frequency modulation parameter distribution: assigning a trigger frequency f of the next time period to each train in each time periodtri(uz) And traction gear u of the triggering frequencyz(ii) a Real-time frequency response: train according to trigger frequency ftri(uz) And traction gear u of the triggering frequencyzAnd responding to the frequency change of the power system in real time to assist the frequency adjustment of the power system. The overall flow of the electrified railway participating in the frequency regulation of the power system is shown in figure 2.
Because the running time of the train between two stations is only dozens of minutes to dozens of minutes in total, the duration time of the primary frequency modulation power specified by the power system is also dozens of minutes to dozens of minutes, and a single train possibly cannot maintain the primary frequency modulation power according to the specified duration time of the power system, a multi-train cooperative control strategy is provided, and a plurality of trains are coordinated and controlled to jointly provide the frequency modulation service meeting the requirements by constructing a day-ahead capacity estimation optimization problem and a day-time frequency modulation power distribution problem. Firstly, discretizing a time interval, wherein the duration of each interval is T0Each train can choose to provide frequency response at certain power in continuous time intervals, and a plurality of trains are combined to provide the frequency modulation service meeting the requirement, and the specific details are as follows:
a) day-ahead capacity estimation: the driving schedule of the train i is as follows: position-time relationship
Figure BDA0003361716680000032
And speed-time relationship
Figure BDA0003361716680000041
Train i slave time period
Figure BDA0003361716680000042
To the time period
Figure BDA0003361716680000043
Providing frequency control service, the train being in time period
Figure BDA0003361716680000044
At an initial time and for a period of time
Figure BDA0003361716680000045
Respectively, the position and the speed of the end time of (2) are recorded as
Figure BDA0003361716680000046
Figure BDA0003361716680000047
The calculation method is as follows:
Figure BDA0003361716680000048
Figure BDA0003361716680000049
Figure BDA00033617166800000410
Figure BDA00033617166800000411
to reduce the speed fluctuations of the train, the speed of the train should vary within a certain range:
Figure BDA00033617166800000412
wherein,
Figure BDA00033617166800000413
is the lower limit of the speed and,
Figure BDA00033617166800000414
is the railway speed limit. In order to guarantee the train to arrive at the station at the correct point, the arrival time of the train under the boundary driving strategy should be earlier than the specified arrival time:
Figure BDA00033617166800000415
wherein
Figure BDA00033617166800000416
Is the time of arrival at the station as specified,
Figure BDA00033617166800000417
is the reserved time margin. The frequency modulation power provided by the train i in the nth time period can be represented as:
Figure BDA00033617166800000418
wherein,
Figure BDA00033617166800000419
is the difference between the current traction gear and the lowest frequency modulated traction gear;
Figure BDA00033617166800000420
representing the characteristic function: if it is not
Figure BDA00033617166800000421
Otherwise
Figure BDA00033617166800000422
In order to jointly control a plurality of trains to jointly meet the requirements of the power system on the frequency modulation power and the duration, the estimation problem of the frequency modulation capacity of the trains can be expressed as an optimization problem, and the objective function is capacity maximization:
Figure BDA00033617166800000423
wherein N isETIs the total number of trains.
b) And (3) intra-day frequency modulation parameter distribution: in the day fm parameter allocation stage, the frequency control parameter of the next time slot needs to be determined in each time slot. Firstly, the train i participating in frequency modulation in the next time period and the lowest frequency modulation gear are determined
Figure BDA0003361716680000051
Suppose that the power system accepts a frequency modulation capacity of PupIn order to fully fulfill the frequency modulation task, the total modulation power per time period is required to be greater than Pup：
Figure BDA0003361716680000052
In addition to this, the constraints described in a) to ensure train waypoint to station and the constraints on the range of train speed fluctuations should still be met.
The cost of the train participating in frequency modulation can be the cost coefficient q of the trainiRiding on the energy representation of train participating in frequency modulation:
Figure BDA0003361716680000053
wherein N isPDTIs the duration of the frequency modulated power required by the power system. The train i participating in the frequency modulation in the next time slot and the maximum frequency modulation gear are then
Figure BDA0003361716680000054
Can be expressed as an optimization problem with an objective function of:
Figure BDA0003361716680000055
solving the optimization problem to obtain the train i participating in frequency modulation in the next time period and the lowest frequency modulation gear
Figure BDA0003361716680000056
Trains participating in the frequency modulation in the next time period are ranked from low to high according to their cost factors, in order to provide a more linear primary frequency modulation droop curve, if in the current traction gear and the lowest frequency modulation gear
Figure BDA0003361716680000057
There are other traction gears in between
Figure BDA0003361716680000058
The triggering frequencies are also assigned to these traction gears:
Figure BDA0003361716680000061
wherein, OiRepresenting a set of trains ranked before train i, f0Is the system normal frequency,. DELTA.fdbIs the primary frequency modulation dead zone, Δ fmaxIs the maximum frequency deviation.
c) Real-time frequency response: in the real-time frequency response stage, the train controls parameters according to the allocated frequency: trigger frequency ftri i(uz i) And traction gear u of the triggering frequencyz iAnd responding to the system frequency deviation in real time. Specifically, the train monitors the power grid frequency in real time, and if the power grid frequency is lower than the trigger frequency ftri i(uz i) Then the train adjusts the traction gear to uz i。
(3) In order to effectively solve the problem of nonlinear integer optimization constructed in the day-ahead capacity estimation and day-interior frequency modulation parameter distribution stage, a sequence secant plane algorithm is provided
Since the capacity estimation problem and the power distribution problem in the flow of the electrified railway participating in the frequency adjustment relate to the solution of the nonlinear integer optimization problem, a sequence secant plane algorithm is provided to effectively solve the two optimization problems.
a) Set of individual feasible points: firstly, an independent feasible point set of each train is solved, namely, a set of regulation and control points which can ensure that the train is in a quasi-point arrival state and meet the speed fluctuation limit is obtained:
Figure BDA0003361716680000062
b) linear relaxation: get omegaiAnd is expressed by a linear inequality:
Figure BDA0003361716680000063
wherein L isi,liRespectively, a coefficient matrix and a right-hand vector of the linear inequality.
c) Cutting a plane: directly by
Figure BDA0003361716680000064
Solving the optimization problem for constraints, if the solution of the problem is relaxed
Figure BDA0003361716680000065
Is not a feasible solution to the original problem, i.e. not at ΩiIn this case, one can find a value in ΩiPoint of (5)
Figure BDA0003361716680000066
So that
Figure BDA0003361716680000067
And max. By a cutting plane
Figure BDA0003361716680000068
Cut off and remain
Figure BDA0003361716680000071
While retaining as much omega as possibleiIs a feasible point in (1). Let the secant plane equation be:
Ax+By+Cz+D≤0
if with b j1 represents ΩiThe point in (b) is not cut by the cutting plane, and the coefficients of the cutting plane can be determined by the following optimization problem:
Figure BDA0003361716680000072
Figure BDA0003361716680000073
Figure BDA0003361716680000074
this is a small scale mixed integer linear programming problem that can be solved using conventional mixed integer linear programming solvers.
d) Iteration: the variable beta is set to store the upper bound of the optimization problem and the variable alpha is set to store the lower bound of the optimization problem. The processes b) and c) are continued.
In each iteration, if the solution of the relaxation problem is feasible: the iteration is ended.
If the solution to the relaxation problem is not feasible: the objective function value of the solution is used as an upper bound of the original optimization problem, and the minimum upper bound variable beta is updated to form a cutting plane, so that the objective function value of the solution is obtained
Figure BDA0003361716680000075
Taking the objective function value corresponding to the feasible solution as the lower bound of the original optimization problem, and updating the maximum lower bound variable alpha; if the difference between the upper and lower bounds is toleratedIn the range δ:
(β-α)/α＜δ
ending the iteration, otherwise, adding the cutting plane into the constraint of the relaxation problem and continuing the iteration process.
The invention has the beneficial effects that:
the invention provides a control method for an electrified railway to participate in frequency adjustment of an electric power system, which considers the rapid and dynamic movement of a train and enables the train to be capable of providing primary frequency adjustment service for the electric power system on the premise of ensuring the arrival of the train at a destination; the multi-train combined response strategy coordinately controls a plurality of trains to provide frequency control service meeting the power system specification together, so that the problem of insufficient duration time of power regulation of a single train is solved; the frequency control framework of the electrified railway is provided, and the electrified railway participates in the frequency control of the power system under the condition of not increasing any new infrastructure investment; the sequence secant plane algorithm can effectively solve the nonlinear integer optimization problem constructed in the day-ahead capacity estimation and day-interior frequency modulation parameter distribution stage. The method can effectively improve the frequency response dynamic of the power system, and has an obvious supporting effect on the operation control of the high-proportion renewable energy power system.
Drawings
FIG. 1 is a diagram of an electrified railroad frequency control framework;
FIG. 2 is a flowchart of the overall frequency control of the electric power system involved in the electrified railway;
fig. 3 is a schematic diagram of a multi-vehicle cooperative control strategy.
Detailed Description
The invention is further described with reference to the accompanying drawings and examples.
Fig. 1 shows a frequency control framework of an electric railway including day-ahead capacity estimation, intra-day frequency modulation parameter allocation, and real-time frequency response according to the present invention.
Fig. 2 is a flowchart of the entire frequency control of the electric power system in which the electric railway participates. The specific execution flow is described below.
Calculating according to the proposed equation of motion of the train, off-line countingCalculating speed function V (X, V, u, T), position function X (X, V, u, T), and arrival time function T under boundary driving strategyarr(x,v,t)。
A schematic diagram of a multi-vehicle cooperative control strategy is shown in fig. 3: firstly, discretizing a time interval, wherein the duration of each interval is T0，T0In the range of 1 minute to 3 minutes. The dotted lines indicate the fm power and duration required by the power system, each small rectangle labeled ET indicates the fm service provided by an Electric Train (ET), the long bar indicates the duration of the fm power, and the high bar indicates the fm power provided. Each train can choose to provide frequency response at a certain power in continuous time intervals, and a plurality of trains are combined to provide frequency modulation service meeting requirements, and the frequency modulation service is represented by 12 small squares in the figure and covers the area enclosed by a dotted line.
Day-ahead capacity estimation: according to planned train movement information, i.e. position-time relationship
Figure BDA0003361716680000091
And speed-time relationship
Figure BDA0003361716680000092
Designating areas of the train capable of providing frequency control as slave locations
Figure BDA0003361716680000093
To
Figure BDA0003361716680000094
Calculating the time of arrival and departure of the train to and from the FM control area as
Figure BDA0003361716680000095
And
Figure BDA0003361716680000096
calculating the discrete time segment in which it is located
Figure BDA0003361716680000097
And
Figure BDA0003361716680000098
constructing a day-ahead capacity estimation optimization problem, wherein an objective function is as follows:
Figure BDA0003361716680000099
the constraints are:
Figure BDA00033617166800000910
Figure BDA00033617166800000911
Figure BDA00033617166800000912
Figure BDA00033617166800000913
Figure BDA00033617166800000914
Figure BDA00033617166800000915
Figure BDA00033617166800000916
Figure BDA00033617166800000917
setting the target function at the end of iteration according to the proposed sequence plane-cutting algorithmThe tolerance range delta of the lower bound gap is about 0.5 to 5 percent, and the maximum frequency modulation capacity is obtained by iteratively solving the optimization problem
Figure BDA00033617166800000918
Maximum capacity of frequency modulation
Figure BDA00033617166800000919
Submitted to the power system, which returns the received FM capacity Pup。
And (3) intra-day frequency modulation parameter distribution: from real-time train information, i.e. position-time relationship
Figure BDA0003361716680000101
And speed-time relationship
Figure BDA0003361716680000102
Constructing a power distribution problem, wherein an objective function is as follows:
Figure BDA0003361716680000103
the constraints are:
Figure BDA0003361716680000104
Figure BDA0003361716680000105
Figure BDA0003361716680000106
Figure BDA0003361716680000107
Figure BDA0003361716680000108
Figure BDA0003361716680000109
Figure BDA00033617166800001010
Figure BDA00033617166800001011
Figure BDA00033617166800001012
Figure BDA00033617166800001013
setting the tolerance range delta of the difference between the upper and lower bounds of the objective function at the end of iteration to be between 0.5 and 5 percent according to the proposed sequence secant plane algorithm, and solving the optimization problem in an iteration mode to obtain the train i and the lowest frequency modulation gear which participate in frequency modulation in the next time period
Figure BDA00033617166800001014
The trains participating in frequency modulation in the next time period are ranked from low to high according to cost coefficients, and if the trains are in the current traction gear and the lowest frequency modulation gear
Figure BDA00033617166800001015
There are other traction gears in between
Figure BDA00033617166800001016
The triggering frequency is allocated to these traction gears:
Figure BDA0003361716680000111
real-time frequency response: monitoring the power grid frequency in real time by the train, and if the power grid frequency is lower than the trigger frequency ftri i(uz i) Then the train adjusts the traction gear to uz i。
The above description of the embodiments of the present invention is provided in conjunction with the accompanying drawings, and not intended to limit the scope of the present invention, and all equivalent models or equivalent algorithm flows made by using the contents of the present specification and the accompanying drawings are within the scope of the present invention by applying directly or indirectly to other related technologies.

Claims (4)

1. A control method for participating in frequency adjustment of an electric power system by an electrified railway is characterized by comprising the following steps: establishing a kinematic model of the train under the control of frequency modulation; on the basis, a framework for participating in the frequency control of the power system by the electrified railway is provided, wherein the framework comprises day-ahead capacity estimation, day-time frequency modulation parameter distribution and real-time frequency response; a sequence secant plane algorithm is provided to effectively solve the nonlinear integer optimization problem constructed in the day-ahead capacity estimation and day-interior frequency modulation parameter distribution stage.
2. The method of claim 1, wherein the established kinematic model of the train under the fm control comprises a velocity function V (X, V, u, T), a position function X (X, V, u, T), and a time to arrival function T under a boundary driving strategyarr(x, v, t); wherein v represents the current speed, x represents the current position, T represents the current time, u represents the traction gear, and T represents the traction time; the speed function V (X, V, u, T) and the position function X (X, V, u, T) are directly obtained by solving a train dynamics equation; the construction process of the boundary driving strategy is as follows:
a) the train is first accelerated in the maximum traction gear,
b) if the speed of the train before the braking point reaches the road speed limit, constant speed cruising is started, otherwise the train still runs at the maximum traction gear,
c) after the train reaches a braking point, the train starts braking with the common braking force until arriving at the station;
arrival time function T under boundary driving strategyarr(x, v, t) is directly calculated according to the driving process.
3. The method for controlling the frequency regulation of the electric railway participating in the power system according to claim 1, wherein the framework of the electric railway participating in the power system frequency control is specifically as follows:
a) day-ahead capacity estimation: the day-ahead capacity estimation is based on the train schedule, i.e. the position-time relationship of the train
Figure FDA0003361716670000011
And speed-time relationship
Figure FDA0003361716670000012
The aim of guaranteeing the arrival of the train at the station is taken as constraint to start the frequency modulation time period
Figure FDA0003361716670000013
Ending the FM time period
Figure FDA0003361716670000014
Frequency modulation traction gear
Figure FDA0003361716670000015
An optimization problem is established by taking the maximum train frequency modulation capacity as an objective function as a decision variable:
the objective function is:
Figure FDA0003361716670000021
the constraints are:
Figure FDA0003361716670000022
Figure FDA0003361716670000023
Figure FDA0003361716670000024
wherein N isETIs the total number of the trains,
Figure FDA0003361716670000025
is the lower limit of the speed and,
Figure FDA0003361716670000026
is the speed limit of the railway,
Figure FDA0003361716670000027
is the time of arrival at the station as specified,
Figure FDA0003361716670000028
is a reserved time margin;
Figure FDA0003361716670000029
respectively time period
Figure FDA00033617166700000210
At an initial time and for a period of time
Figure FDA00033617166700000211
The position and speed of the end time of (2) are calculated as follows:
Figure FDA00033617166700000212
Figure FDA00033617166700000213
Figure FDA00033617166700000214
Figure FDA00033617166700000215
ΔPi(n) the modulated frequency power provided for train i in the nth time period may be represented as:
Figure FDA00033617166700000216
wherein,
Figure FDA00033617166700000217
is the difference between the current traction gear and the lowest frequency modulated traction gear;
Figure FDA00033617166700000218
representing the characteristic function: if it is not
Figure FDA00033617166700000219
Otherwise
Figure FDA00033617166700000220
b) And (3) intra-day frequency modulation parameter distribution: the day frequency modulation parameter distribution is to determine the frequency control parameter of the next time period in each time period; the distribution of day-to-day frequency modulation parameters is based on the real-time train operation information, i.e. the position-time relationship of the train
Figure FDA00033617166700000221
And speed-time relationship
Figure FDA00033617166700000222
The method takes the constraint of ensuring that the train arrives at the station at a standard point and meeting the frequency modulation requirement as the constraint to start the frequency modulation time period
Figure FDA0003361716670000031
Ending the FM time period
Figure FDA0003361716670000032
Frequency modulation traction gear
Figure FDA0003361716670000033
As a decision variable, an optimization problem is established by taking the minimum train frequency modulation cost as an objective function:
the objective function is:
Figure FDA0003361716670000034
the constraints are:
Figure FDA0003361716670000035
Figure FDA0003361716670000036
Figure FDA0003361716670000037
Figure FDA0003361716670000038
Figure FDA0003361716670000039
solving the optimization problem to obtain the train i participating in frequency modulation in the next time period and the lowest frequency modulation gear
Figure FDA00033617166700000310
If the current traction gear and the lowest frequency modulation gear are adopted
Figure FDA00033617166700000311
There are other traction gears in between
Figure FDA00033617166700000312
Then the triggering frequencies are also assigned to these traction gears:
Figure FDA00033617166700000313
wherein, OiRepresenting a set of trains ranked before train i, f0Is the system normal frequency,. DELTA.fdbIs the primary frequency modulation dead zone, Δ fmaxIs the maximum frequency deviation;
c) real-time frequency response: the real-time frequency response being the train's assigned trigger frequency ftri i(uz i) Traction gear u corresponding to the triggering frequencyz iResponding to the system frequency deviation; specifically, the train monitors the grid frequency in real time, and if the grid frequency is lower than the trigger frequency ftri i(uz i) Then the train adjusts the traction gear to uz i。
4. The method of claim 1, wherein the sequential secant plane algorithm comprises four steps of solving a set of single feasible points, linear relaxation, secant plane, and iteration:
a) solving a set of individual feasible points: solving a set of regulation and control points which can ensure that the train is in a quasi-point arrival state and meets the speed fluctuation limit:
Figure FDA0003361716670000041
b) linear relaxation: get omegaiAnd is expressed by a linear inequality:
Figure FDA0003361716670000042
wherein L isi,liIs a coefficient matrix and right-hand vector of the linear inequality;
c) cutting a plane: directly by
Figure FDA0003361716670000043
Solving the optimization problem for constraints, if the solution of the relaxation problem is obtained
Figure FDA0003361716670000044
Is not at omegaiIn (3), a feasible solution is found
Figure FDA0003361716670000045
So that
Figure FDA0003361716670000046
Maximum; by a cutting plane
Figure FDA0003361716670000047
Cut off and remain
Figure FDA0003361716670000048
While at the same time preserving omega as much as possibleiA feasible point of (1); let the secant plane equation be:
Ax+By+Cz+D≤0
by bj1 represents ΩiThe point in (b) is not cut by the cutting plane, and the coefficients of the cutting plane can be determined by the following optimization problem:
Figure FDA0003361716670000049
Figure FDA00033617166700000410
Figure FDA00033617166700000411
d) iteration: continuously carrying out the processes b) and c);
during each iteration:
if the solution of the relaxation problem is feasible, ending the iteration;
if the solution of the relaxation problem is not feasible, the solution is taken as an upper bound of the original optimization problem to form a cutting plane, and the cutting plane is obtained
Figure FDA0003361716670000051
Taking the objective function value corresponding to the maximum feasible solution as the lower bound of the original optimization problem; if the difference between the upper and lower boundaries is in the tolerance range, the iteration is ended, otherwise, the cutting plane is added into the constraint of the relaxation problem to continue the iteration process.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114597951A (en) * 2022-04-06 2022-06-07 西南交通大学 Optimization method for energy-saving operation of electric automobile participating in alternating-current urban rail power supply system
CN114937995A (en) * 2022-05-26 2022-08-23 浙江大学 Electrified railway self-adaptive frequency response method based on operation sag
CN117734646A (en) * 2023-05-06 2024-03-22 中车株洲电力机车研究所有限公司 Rail train, circulating air braking method, circulating air braking device, circulating air braking equipment and storage medium

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8831801B1 (en) * 2013-03-14 2014-09-09 Mitsubishi Electric Research Laboratories, Inc. System and method for optimizing energy consumption in railway systems
CN104917207A (en) * 2015-06-12 2015-09-16 国网天津市电力公司 Power system unit commitment optimization method based on branch-cut-plane algorithm
CN104933516A (en) * 2015-05-27 2015-09-23 华南理工大学 Multi-time-scale power system robustness scheduling system design method
CN108574303A (en) * 2018-04-17 2018-09-25 上海电力学院 A kind of multiple-energy-source coordination optimization dispatching method considering peak-frequency regulation demand
CN109038630A (en) * 2018-08-16 2018-12-18 洁电（北京）储能科技有限公司 A kind of ferroelectric power supply system and control method with energy storage ancillary service function
CN112909980A (en) * 2021-04-22 2021-06-04 大连理工大学 Virtual coefficient optimization method for simulating quick frequency response of thermal power generating unit by electrochemical energy storage

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8831801B1 (en) * 2013-03-14 2014-09-09 Mitsubishi Electric Research Laboratories, Inc. System and method for optimizing energy consumption in railway systems
CN104933516A (en) * 2015-05-27 2015-09-23 华南理工大学 Multi-time-scale power system robustness scheduling system design method
CN104917207A (en) * 2015-06-12 2015-09-16 国网天津市电力公司 Power system unit commitment optimization method based on branch-cut-plane algorithm
CN108574303A (en) * 2018-04-17 2018-09-25 上海电力学院 A kind of multiple-energy-source coordination optimization dispatching method considering peak-frequency regulation demand
CN109038630A (en) * 2018-08-16 2018-12-18 洁电（北京）储能科技有限公司 A kind of ferroelectric power supply system and control method with energy storage ancillary service function
CN112909980A (en) * 2021-04-22 2021-06-04 大连理工大学 Virtual coefficient optimization method for simulating quick frequency response of thermal power generating unit by electrochemical energy storage

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
TAKAYUKI WADA等: "Sequential randomized algorithms: A probabilistic cutting plane technique based on maximum volume ellipsoid center", 《2010 IEEE INTERNATIONAL SYMPOSIUM ON COMPUTER-AIDED CONTROL SYSTEM DESIGN》, pages 1533 - 1538 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114597951A (en) * 2022-04-06 2022-06-07 西南交通大学 Optimization method for energy-saving operation of electric automobile participating in alternating-current urban rail power supply system
CN114937995A (en) * 2022-05-26 2022-08-23 浙江大学 Electrified railway self-adaptive frequency response method based on operation sag
CN117734646A (en) * 2023-05-06 2024-03-22 中车株洲电力机车研究所有限公司 Rail train, circulating air braking method, circulating air braking device, circulating air braking equipment and storage medium
CN117734646B (en) * 2023-05-06 2024-10-11 中车株洲电力机车研究所有限公司 Rail train, circulating air braking method, circulating air braking device, circulating air braking equipment and storage medium

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