CN115642614B - Day-ahead and day-in combined scheduling method and system for high-proportion wind power system - Google Patents

Day-ahead and day-in combined scheduling method and system for high-proportion wind power system Download PDF

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CN115642614B
CN115642614B CN202211215507.XA CN202211215507A CN115642614B CN 115642614 B CN115642614 B CN 115642614B CN 202211215507 A CN202211215507 A CN 202211215507A CN 115642614 B CN115642614 B CN 115642614B
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thermal power
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disturbance
wind
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CN115642614A (en
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苗世洪
王廷涛
姚福星
严道波
赵红生
蔡杰
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Huazhong University of Science and Technology
Economic and Technological Research Institute of State Grid Hubei Electric Power Co Ltd
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Economic and Technological Research Institute of State Grid Hubei Electric Power Co Ltd
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Abstract

The invention discloses a day-ahead and day-ahead joint scheduling method and system for a high-proportion wind power system, which respectively construct a system dynamic frequency response model under expected low-power disturbance and high-power disturbance by considering the frequency modulation effect of thermal power units and battery energy storage, and provides a day-ahead and day-ahead joint scheduling strategy considering dynamic frequency response constraint on the basis. Compared with the prior art, the invention has the main advantages that: 1) The standby stepped method for the slope of the thermal power generating unit can achieve the reduction of the standby response function, and the accuracy of the dynamic frequency response model of the system is not affected basically after simplification. 2) The dynamic frequency response index calculation method comprehensively describes the frequency response characteristics of the high-proportion wind power system under various power disturbances; 3) And the day-before-day joint scheduling strategy can reasonably arrange an operation plan of the thermal power unit and the battery energy storage, so that the system has the capability of maintaining the frequency safety level under the condition of low-power disturbance and high-power disturbance.

Description

Day-ahead and day-in combined scheduling method and system for high-proportion wind power system
Technical Field
The invention belongs to the field of power system optimization scheduling strategies, and particularly relates to a day-to-day joint scheduling method and system for a high-proportion wind power system.
Background
Promote the large-scale and high-quality development of renewable energy sources such as wind power and the like, and is a key measure for constructing an energy safety barrier and promoting low-carbon green transformation of energy sources in China. For a high-proportion wind power system (namely a power system with the installed proportion of wind power reaching 30% -50%), on one hand, the number of traditional synchronous generators is reduced, so that inertial response sources and primary frequency modulation sources of the system are more scarce; on the other hand, wind power has the characteristics of strong randomness, large volatility, low inertia and the like, and the large-scale grid connection of the wind power aggravates the power disturbance of the system.
Therefore, frequency safety constraint is considered in the process of combining and optimizing scheduling of the high-proportion wind power system units, and by reasonably making a unit start-stop and output plan, the system is ensured to have sufficient inertia support and primary frequency modulation resources in the operation stage, so that the system has the capability of maintaining the frequency index within a safety range under the expected power disturbance effect, and the method has important significance for improving the frequency safety level of the high-proportion wind power system.
Disclosure of Invention
Aiming at the defects and improvement demands of the prior art, the invention provides a day-to-day joint scheduling method and system for a high-proportion wind power system, and aims to solve the problems that the high-proportion wind power system has the characteristics of low moment of inertia, weak frequency modulation capability, easiness in disturbance and the like, and frequency safety is easy to cause.
In order to achieve the above purpose, in a first aspect, the present invention provides a day-to-day joint scheduling method for a high-ratio wind power system, comprising the following steps:
step A: constructing a system dynamic frequency response model under low-power disturbance and high-power disturbance and solving a dynamic frequency response index; the low-power disturbance forms are the maximum error step power disturbance of the load and wind power in the system, the high-power disturbance forms are the superposition of the maximum error step power disturbance of the load, the maximum error step power disturbance of the wind power and the single machine fault step power disturbance of the thermal power unit, and the frequency response indexes comprise an initial frequency change rate, a steady-state frequency difference and a maximum frequency difference;
and (B) step (B): taking thermal power unit operation constraint, battery energy storage operation constraint and system operation constraint into consideration, and constructing a day-ahead scheduling model by taking the minimum sum of thermal power unit operation cost, thermal power unit starting cost and waste wind punishment cost as an optimization target; taking thermal power unit operation constraint, battery energy storage operation constraint and system operation constraint into consideration, and constructing an intra-day scheduling model by taking the minimum sum of thermal power unit operation cost, thermal power unit standby cost and abandoned wind punishment cost as an optimization target;
step C: and solving the day-ahead scheduling model and the day-in scheduling model to obtain a high-proportion wind power system optimization scheduling result meeting an optimization target.
In a second aspect, the present invention provides a day-ahead-day joint scheduling system for a high-proportion wind power system, including: a computer readable storage medium and a processor;
the computer-readable storage medium is for storing executable instructions;
the processor is configured to read executable instructions stored in the computer readable storage medium, and execute the method for joint scheduling in the day-ahead and day-ahead of the high-ratio wind power system according to the first aspect.
Aiming at the problem that the system frequency safety level is reduced due to the characteristics of low rotational inertia, weak frequency modulation capability, easy disturbance and the like of a high-proportion wind power system, the invention respectively builds a system dynamic frequency response model under the expected low-power disturbance and high-power disturbance by considering the frequency modulation effect of a thermal power unit and battery energy storage, and provides a day-to-day joint scheduling strategy considering dynamic frequency response constraint on the basis. Compared with the prior art, the invention has the main advantages that:
1) The standby stair-stepping method for the slope of the thermal power generating unit can realize the reduction of the standby response function, and the accuracy of the simplified dynamic frequency response model of the system is not affected basically, so that a foundation is laid for deriving the dynamic frequency response index under high-power disturbance.
2) The method for calculating the dynamic frequency response index of the system under the low-power disturbance and the high-power disturbance provided by the invention comprehensively describes the frequency response characteristics of the high-proportion wind power system under various power disturbances, and can be used as an index for evaluating the capability of the system for resisting the frequency fluctuation risk.
3) The day-ahead and day-ahead joint scheduling strategy considering dynamic frequency response constraint can reasonably arrange an operation plan of a thermal power unit and battery energy storage, so that the system has the capability of maintaining the frequency safety level under low-power disturbance and high-power disturbance.
Drawings
Fig. 1 is a flowchart of a day-to-day joint scheduling method of a high-ratio wind power system provided in embodiment 1 of the present invention.
FIG. 2 is a dynamic frequency response model of the system under low power disturbance of step A of example 1 of the present invention.
FIG. 3 is a dynamic frequency response model of the system under high power disturbance of step A of example 1 of the present invention.
Fig. 4 is a positive standby response curve of the thermal power generating unit in step a of embodiment 1 of the present invention.
Fig. 5 is a system topology diagram of step B of embodiment 2 of the present invention.
FIG. 6 is a daily load prediction curve of step B of example 2 of the present invention.
FIG. 7 is a daily load prediction curve of step B of example 2 of the present invention.
Fig. 8 is a graph showing a 1 day front power prediction curve of the wind farm according to step B of embodiment 2 of the present invention.
Fig. 9 is a graph showing the 1 day internal power prediction of the wind farm in step B of example 2 of the present invention.
FIG. 10 is a graph showing the predicted 2 day-ahead power of a wind farm according to step B of example 2 of the present invention.
FIG. 11 is a graph showing the predicted 2-day power for a wind farm according to step B of example 2 of the present invention.
Fig. 12 is a thermal power generating unit start-stop plan in step C of embodiment 2 of the present invention.
Fig. 13 is a thermal power generating unit output and standby plan in step C of embodiment 2 of the present invention, wherein (a), (b), and (C) respectively represent unit output, unit positive standby, and unit negative standby.
Fig. 14 shows the battery power and standby schedule of step C of example 2 of the present invention.
Fig. 15 is a scenario a battery energy storage emergency power support plan of example 2, step C, of the present invention.
FIG. 16 is a comparison of dynamic frequency response indexes of step C of embodiment 2 of the present invention, wherein (a), (b) and (C) respectively represent the initial frequency change rate, the steady-state frequency difference and the maximum frequency difference.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. In addition, the technical features of the embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
In the present invention, the terms "first," "second," and the like in the description and in the drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order.
Example 1
Referring to fig. 1, in combination with fig. 2 to 4, the invention provides a day-day joint scheduling method for a high-proportion wind power system. The method comprises the following steps:
in order to achieve the above object, the present invention mainly comprises the steps of:
step A: constructing a system dynamic frequency response model under low-power disturbance and high-power disturbance and solving a dynamic frequency response index; the low-power disturbance forms are the maximum error step power disturbance of the load and wind power in the system, the high-power disturbance forms are the superposition of the maximum error step power disturbance of the load, the maximum error step power disturbance of the wind power and the single machine fault step power disturbance of the thermal power unit, and the frequency response indexes comprise an initial frequency change rate, a steady-state frequency difference and a maximum frequency difference;
and (B) step (B): taking thermal power unit operation constraint, battery energy storage operation constraint and system operation constraint into consideration, and constructing a day-ahead scheduling model by taking the minimum sum of thermal power unit operation cost, thermal power unit starting cost and waste wind punishment cost as an optimization target; taking thermal power unit operation constraint, battery energy storage operation constraint and system operation constraint into consideration, and constructing an intra-day scheduling model by taking the minimum sum of thermal power unit operation cost, thermal power unit standby cost and abandoned wind punishment cost as an optimization target;
step C: and solving the day-ahead scheduling model and the day-in scheduling model to obtain a high-proportion wind power system optimization scheduling result meeting an optimization target.
The invention envisions that the small power disturbance is the maximum error step power disturbance of the load and wind power in the system, when the disturbance occurs, the inertia response and primary frequency modulation resource in the system are usually used for adjusting, so that the frequency index of the system is kept in a safe range. The dynamic frequency response model of the system at low power disturbances is shown in fig. 2. In the view of figure 2,
Figure BDA0003875889770000051
for the system frequency variation under low power disturbance, the angle marks (x) represent per unit value, and the same applies below; k (k) Ld Is the load frequency response coefficient; />
Figure BDA0003875889770000052
Load power at rated frequency; ΔP Ld (s) is a load maximum error step power disturbance at nominal frequency; ΔP W (s) wind power maximum error step power disturbance; g I (s) is a system inertial response transfer function; h G (s)、H E And(s) the transfer functions of the group of speed regulators for thermal power units and battery energy storage respectively. G I (s)、ΔP Ld (s)+ΔP W (s)、H G (s)、H E The specific expression of(s) is as follows:
Figure BDA0003875889770000053
Figure BDA0003875889770000054
wherein N is G The number of thermal power generating units in the system is the number;
Figure BDA0003875889770000055
the starting and stopping state of the thermal power generating unit i is 1 when the power is started and 0 when the power is stopped; />
Figure BDA0003875889770000056
Rated output of the thermal power unit i; t (T) i G The inertia time constant of the thermal power unit i; d (D) i The damping coefficient of the thermal power unit i is assumed to be 0; p (P) Lde Predicting a maximum error for the load; n (N) W The number of wind farms in the system; />
Figure BDA0003875889770000057
Predicting the maximum error for the output of the wind farm n; mu (mu) i The difference adjustment coefficient of the thermal power unit i; />
Figure BDA0003875889770000058
The dynamic frequency response proportion coefficient and the integral coefficient of the thermal power unit i are respectively; n (N) E The energy storage quantity of the battery in the system; />
Figure BDA0003875889770000059
Rated power for storing energy r for the battery;
Figure BDA00038758897700000510
the virtual inertia coefficient and the frequency droop coefficient of the battery energy storage r are respectively. Above H G The expression(s) has higher order, and the invention carries out equivalent transformation treatment to obtain the equivalent expression +.>
Figure BDA00038758897700000511
The following are provided:
Figure BDA0003875889770000061
wherein mu is equ 、
Figure BDA0003875889770000062
Respectively equivalent adjustment difference, proportion and integral coefficient of the thermal power generating unit in the system; τ mid Half of the steady time weighted average value of the speed regulator of each thermal power generating unit in the system; />
Figure BDA0003875889770000063
The time for stabilizing the speed regulator of the thermal power generating unit i.
The transfer function of the dynamic frequency response model of fig. 2 is shown as follows:
Figure BDA0003875889770000064
wherein, kappa L 、λ L 、α L 、β L The method is characterized by comprising the following steps of:
Figure BDA0003875889770000065
wherein k is G Equivalent inertia coefficient of the system;
Figure BDA0003875889770000066
and the equivalent virtual inertia and the frequency droop coefficient of the battery energy storage in the system are respectively obtained.
Transfer function of dynamic frequency response model according to FIG. 2
Figure BDA0003875889770000067
The complex frequency domain expression of (2) can be obtained through Laplace inverse transformation, so that dynamic frequency response indexes of the system under low-power disturbance are obtained, wherein the dynamic frequency response indexes comprise 3 types of initial frequency change rate, steady-state frequency difference and maximum frequency difference, and the method comprises the following specific steps:
1) Initial rate of frequency change
Figure BDA0003875889770000071
2) Steady state frequency difference
Figure BDA0003875889770000072
3) Maximum frequency difference
Figure BDA0003875889770000073
The value is beta L And alpha is L 2 The size relationship between the two is affected, and the following is discussed:
①β L ＞α L 2 and is also provided with
Figure BDA0003875889770000074
Wherein->
Figure BDA0003875889770000075
Figure BDA0003875889770000076
Wherein τ os Is the time that passes from the onset of the disturbance to the time when the system frequency difference reaches a maximum.
②β L ＞α L 2 And is also provided with
Figure BDA0003875889770000077
Wherein->
Figure BDA0003875889770000078
Figure BDA0003875889770000079
③β L ＝α L 2
Figure BDA00038758897700000710
④β L ＜α L 2
Figure BDA00038758897700000711
In the step A, a dynamic frequency response model and a frequency index analysis expression of the high-proportion wind power system under high-power disturbance are as follows:
the invention envisions that the high-power disturbance form is superposition of the maximum error step power disturbance of the load in the system, the maximum error step power disturbance of wind power and the single machine fault step power disturbance of the thermal power generating unit. When such disturbance occurs, the system frequency is difficult to be stabilized in a safe range only through inertial response and primary frequency modulation, and measures such as rotation standby of a thermal power unit, emergency power support of battery energy storage, automatic low-frequency load shedding and the like are required to be matched to inhibit the system frequency reduction depth. The invention aims to reasonably configure standby and emergency power support quantity, so that under the action of high-power disturbance, the maximum frequency difference of a system is not caused to trigger the first-round low-frequency load shedding, and the steady-state frequency is not lower than 49.5Hz, therefore, the action of low-frequency load shedding is not considered in a dynamic frequency response model, and the model is shown in figure 3.
In the view of figure 3 of the drawings,
Figure BDA0003875889770000081
the system frequency variation under high-power disturbance is calculated; ΔP F (s) is a single machine fault step power disturbance of the thermal power generating unit; />
Figure BDA0003875889770000082
The sum of emergency power support amounts for all battery stored energy in the system is +.>
Figure BDA0003875889770000083
Takes the form of a delay-free step input opposite to the disturbance direction;
Figure BDA0003875889770000084
the sum of the positive and standby of the residual running thermal power generating units in the system is considered to be the slope input with time delay and amplitude limitation opposite to the disturbance direction.
Figure BDA0003875889770000085
The specific expression of (2) is as follows:
Figure BDA0003875889770000086
Figure BDA0003875889770000087
wherein, the subscript m is the number of the fault thermal power unit, and the value of the subscript m is 1 to N G The subscript m is adopted to represent the fault thermal power unit in the follow-up;
Figure BDA0003875889770000088
the output before the m faults of the thermal power unit; p (P) r E,em An emergency power support amount for the battery energy storage r; p (P) St,H The total step power of the system under high-power disturbance comprises various types of power disturbance and emergency power support quantity of battery energy storage; gamma ray i The climbing rate of the thermal power unit i; />
Figure BDA0003875889770000089
The standby starting time delay of the thermal power generating unit i is set; />
Figure BDA00038758897700000810
Is the full standby time of the thermal power generating unit i. />
Figure BDA00038758897700000811
The starting time of the two is the disturbance occurrence time.
Following fig. 2, the transfer function of the dynamic frequency response model of fig. 3 is shown as follows:
Figure BDA0003875889770000091
wherein, kappa H 、λ H 、α H 、β H Transformation coefficient of transfer function of dynamic frequency response model of system under high-power disturbance, calculation method and kappa L 、λ L 、α L 、β L The same, the only difference is kappa H 、λ H 、α H 、β H None of the parameters contains the relevant parameters of the fault thermal power unit m.
Because the thermal power generating unit is standby in a slope form, the thermal power generating unit is utilized
Figure BDA0003875889770000092
When the expression solves the maximum frequency difference of the system, the analytic expression cannot be obtained, so the system is simple in structure, convenient to use, and easy to use>
Figure BDA0003875889770000093
The slope part of (a) is equivalent to a step form, and is obtained +.>
Figure BDA0003875889770000094
Figure BDA0003875889770000095
In the method, in the process of the invention,
Figure BDA0003875889770000096
for the thermal power generating unit i, the number of rising edges after stepped is +.>
Figure BDA0003875889770000097
The number range is->
Figure BDA0003875889770000098
L i The height of a single-stage ladder is reserved for the i steps of the thermal power generating unit; />
Figure BDA0003875889770000099
The triggering time of the jth rising edge is reserved for the i steps of the thermal power generating unit, and the starting moment is the disturbance occurrence moment.
The standby response curves before and after the thermal power generating unit is equivalent are shown in fig. 4, the standby response curve of the thermal power generating unit before the equivalent is a simplified response curve, and the standby response curve of the thermal power generating unit after the equivalent is a stepped response curve.
Transfer function of dynamic frequency response model according to FIG. 3, namely
Figure BDA00038758897700000910
The complex frequency domain expression of (2) can be obtained through Laplace inverse transformation, so as to obtain the initial frequency change rate and steady-state frequency difference of the system under high-power disturbance; for->
Figure BDA00038758897700000911
Equivalent form of->
Figure BDA00038758897700000912
Performing Laplace inverse transformation to obtain a time domain expression, and further solving the maximum frequency difference of the system under high-power disturbance. The three frequency indexes are specifically as follows:
1) Initial rate of frequency change
Figure BDA00038758897700000913
2) Steady state frequency difference
Figure BDA00038758897700000914
Wherein->
Figure BDA00038758897700000915
Is the positive standby capacity of the thermal power generating unit i.
3) Maximum frequency difference
Figure BDA00038758897700000916
Assume that the system frequency falls to a minimum point at time τ os Just in step of thermal power generating unit iLadder standby curve
Figure BDA0003875889770000101
On the step ladder. If τ os Just at a rising edge of the step back-up curve, it is considered to be on the step in the left neighborhood of the rising edge. The above timing relationship can be written as the following expression:
Figure BDA0003875889770000102
Figure BDA0003875889770000103
is subject to beta H And alpha is H 2 The size relationship between the two is affected, and the following is discussed:
①β H ＞α H 2 time, order
Figure BDA0003875889770000104
q i ＝sgn(p i ). Wherein sgn (p) is a sign function; epsilon ∑ 、σ ∑ For the maximum frequency difference conversion coefficient, the calculation method is as follows:
Figure BDA0003875889770000105
according to the value of theta, beta H ＞α H 2 Maximum frequency difference in case
Figure BDA0003875889770000106
The calculation formula of (2) can be further subdivided:
a)θ≤0
Figure BDA0003875889770000107
b)θ＞0
Figure BDA0003875889770000108
②β H ＝α H 2 time, let q i ＝sgn(p i ) Maximum frequency difference conversion coefficient epsilon ∑ 、σ ∑ The calculation method comprises the following steps:
Figure BDA0003875889770000109
maximum frequency difference
Figure BDA0003875889770000111
The following formula is shown:
Figure BDA0003875889770000112
③β H ＜α H 2 time, order
Figure BDA0003875889770000113
q i ＝sgn(p i ) Maximum frequency difference conversion coefficient epsilon ∑ 、σ ∑ The calculation method comprises the following steps:
Figure BDA0003875889770000114
maximum frequency difference
Figure BDA0003875889770000115
The following formula is shown:
Figure BDA0003875889770000116
in the step B, a high-proportion wind power system day-ahead-day joint scheduling architecture considering dynamic frequency response constraint is as follows:
the step A of the invention shows that the dynamic frequency response capability of the system under the low-power disturbance is determined by the inertial response and primary frequency modulation capability of the system, namely the starting-up quantity of the thermal power generating unit; the dynamic frequency response capability of the system under high-power disturbance is influenced by the start-stop state of the thermal power unit, and is related to the output and standby conditions of the thermal power unit, the battery energy storage charge-discharge power and the emergency power supporting conditions. Usually, the day-ahead scheduling is responsible for making a start-stop plan of the thermal power generating unit, and the specific operation plans of various scheduling resources such as the thermal power generating unit, the battery energy storage, the wind turbine unit and the like are made and executed by the day-ahead scheduling. The present invention therefore devised a day-to-day joint scheduling architecture that accounts for dynamic frequency response constraints, as shown in table 1.
Table 1 day-ahead-day joint scheduling architecture
Figure BDA0003875889770000117
Figure BDA0003875889770000121
As can be seen from Table 1, the dynamic frequency response constraint under low-power disturbance is considered in the day-ahead scheduling, so that the start-stop plan of the thermal power generating unit is reasonably arranged, and the system is ensured to have enough inertial response and primary frequency modulation capability to cope with random fluctuation of load and wind power. The intra-day scheduling is performed in a rolling mode based on the day-ahead scheduling result, and the scheduling plan of the 1 st hour in the total scheduling duration is selected for each time of intra-day scheduling. The dynamic frequency response constraint under high-power disturbance is increased by the intra-day scheduling, so that the operation plans of each scheduling resource are reasonably arranged, and the system can resist the frequency collapse risk caused by single machine faults.
In the step B, a constructed day-ahead scheduling model of the high-proportion wind power system considering dynamic frequency response constraint is as follows:
1) Optimization objective
minF d-a ＝C G,run +C G,on +C wind
Wherein C is G,run Is formed by running a thermal power generating unitThe cost is high; c (C) G,on The starting cost of the thermal power generating unit is; c (C) wind Cost is punished for wind abandoning. The specific calculation method of each cost is shown as follows:
Figure BDA0003875889770000122
wherein T is d-a Scheduling a total time length for the day before;
Figure BDA0003875889770000123
the electricity purchasing cost coefficient of the thermal power generating unit i; />
Figure BDA0003875889770000124
The active output of the thermal power generating unit i in the t period; />
Figure BDA0003875889770000125
The method is the single starting cost of the thermal power unit i; />
Figure BDA0003875889770000126
Starting the thermal power generating unit i for a period t, wherein the starting-up state is 1, and the starting-up state is 0 otherwise; c pen Punishing a cost coefficient for the wind curtailment; />
Figure BDA0003875889770000127
The predicted output and the actual output of the wind power plant n in the t period are respectively.
2) Thermal power generating unit operation constraint
(1) Thermal power generating unit output constraint
Figure BDA0003875889770000128
In the method, in the process of the invention,
Figure BDA0003875889770000129
the rated output and the minimum technical output of the thermal power generating unit i are respectively obtained.
(2) Start-stop time constraint of thermal power generating unit
Figure BDA0003875889770000131
In the method, in the process of the invention,
Figure BDA0003875889770000132
respectively the duration and the minimum limit value of the time length which are kept in the starting state after the thermal power unit i is started;
Figure BDA0003875889770000133
the time length and the minimum limit value of the thermal power unit i which are kept in the stop state after the thermal power unit i stops.
(3) Thermal power generating unit climbing rate constraint
Figure BDA0003875889770000134
Wherein V is i G Is the climbing rate of the thermal power generating unit i.
(4) Primary frequency modulation power constraint of thermal power generating unit under low-power disturbance
Figure BDA0003875889770000135
In the method, in the process of the invention,
Figure BDA0003875889770000136
for the primary frequency modulation steady-state power variation of the thermal power unit i under the t-period low-power disturbance, the calculation method is as follows:
Figure BDA0003875889770000137
in the method, in the process of the invention,
Figure BDA0003875889770000138
is frequency modulation dead zone.
3) Battery energy storage operation constraint
(1) Battery energy storage charge-discharge power constraint
Figure BDA0003875889770000139
Wherein M is a sufficiently large positive number;
Figure BDA00038758897700001310
the output power of the battery energy storage r in the period t is negative in charging, positive in discharging and 0 in hot standby; />
Figure BDA00038758897700001311
The working condition indicating variable of the battery energy storage r in the t period is 0 in the charging or hot standby process, and 1 in the discharging or hot standby process; />
Figure BDA00038758897700001312
The rated power of the battery energy storage r.
(2) Battery energy storage energy constraint
E min,r ≤E t,r ≤E max,r ，E 1,r ＝E ini,r
Figure BDA00038758897700001313
Figure BDA0003875889770000141
Wherein E is t,r Remaining energy of the battery energy storage r for a period t; e (E) max,r 、E min,r The upper and lower limits of the energy stored by the battery r are respectively; e (E) ini,r The initial energy of the battery energy storage r; η (eta) r Power conversion efficiency for the battery storage r.
(3) Battery energy storage primary frequency modulation power constraint under low-power disturbance
Figure BDA0003875889770000142
In the method, in the process of the invention,
Figure BDA0003875889770000143
for the primary frequency modulation steady-state power variation of the battery energy storage r under t-period low-power disturbance, the calculation method is as follows:
Figure BDA0003875889770000144
4) System operation constraints
(1) Power balance constraint
Figure BDA0003875889770000145
(2) Wind power output constraint
Figure BDA0003875889770000146
(3) System standby constraints
Figure BDA0003875889770000147
Figure BDA0003875889770000148
(4) System initial frequency change rate constraint under low power disturbance
Figure BDA0003875889770000149
In the method, in the process of the invention,
Figure BDA00038758897700001410
is the system initial frequency change rate limit under low power disturbance.
(5) System steady-state frequency difference constraint under low-power disturbance
Figure BDA00038758897700001411
In the method, in the process of the invention,
Figure BDA0003875889770000151
is the steady-state frequency difference limit value of the system under the condition of low power disturbance.
(6) System maximum frequency difference constraint under low power disturbance
Figure BDA0003875889770000152
In the method, in the process of the invention,
Figure BDA0003875889770000153
is the maximum frequency difference limit of the system under low power disturbance. />
In the step B, the constructed intra-day scheduling model of the high-proportion wind power system considering the dynamic frequency response constraint is as follows:
1) Optimization objective
minF i-d ＝C G,run +C G,res +C wind
Wherein C is G,res The method is a standby cost for the thermal power generating unit. The specific calculation method of each cost is shown as follows:
Figure BDA0003875889770000154
wherein T is i-d Scheduling a total time length for a day;
Figure BDA0003875889770000155
positive and negative standby capacities of the thermal power generating unit i in the t period are respectively set; />
Figure BDA0003875889770000156
Positive and negative standby cost systems of thermal power generating units iA number.
2) Thermal power generating unit operation constraint
(1) Thermal power generating unit output constraint
Figure BDA0003875889770000157
(2) Thermal power generating unit climbing rate constraint
Figure BDA0003875889770000158
(3) Spare capacity constraint for thermal power generating unit
Figure BDA0003875889770000159
(4) Primary frequency modulation power constraint of thermal power generating unit under low-power disturbance
Figure BDA00038758897700001510
(5) Primary frequency modulation power constraint of thermal power generating unit under high-power disturbance
Figure BDA0003875889770000161
In the method, in the process of the invention,
Figure BDA0003875889770000162
for the primary frequency modulation steady-state power variation of the thermal power unit i under the condition of the m fault of the thermal power unit in the t period, the calculation method is as follows:
Figure BDA0003875889770000163
3) Battery energy storage operation constraint
(1) Battery energy storage charge-discharge power constraint
Figure BDA0003875889770000164
(2) Battery energy storage energy constraint
E min,r ≤E t,r ≤E max,r ，E 1,r ＝E ini,r
Figure BDA0003875889770000165
Figure BDA0003875889770000166
Figure BDA0003875889770000167
(3) Battery energy storage reserve capacity constraint
Figure BDA0003875889770000168
Figure BDA0003875889770000169
Figure BDA00038758897700001610
In the method, in the process of the invention,
Figure BDA00038758897700001611
positive and negative standby capacities of the battery energy storage r at the t period respectively; />
Figure BDA00038758897700001612
As a positive standby auxiliary variable, if the battery energy storage r is at the current power in the period of t>
Figure BDA00038758897700001613
On the basis of (1) providing positive standby->
Figure BDA00038758897700001614
The rear output power is positive, then +.>
Figure BDA00038758897700001615
1, otherwise 0; />
Figure BDA00038758897700001616
For the negative standby auxiliary state variable, if the battery energy storage r is at the current power +.>
Figure BDA00038758897700001617
On the basis of (1) providing a negative reserve->
Figure BDA00038758897700001618
The rear output power is positive, then +.>
Figure BDA00038758897700001619
1, otherwise 0.
(4) Battery energy storage primary frequency modulation power constraint under low-power disturbance
Figure BDA0003875889770000171
(5) Battery energy storage primary frequency modulation power constraint under high-power disturbance
Figure BDA0003875889770000172
In the method, in the process of the invention,
Figure BDA0003875889770000173
for the primary frequency modulation steady-state power variation of the battery energy storage r under the m fault condition of the thermal power unit in the t period, the calculation method is as follows:
Figure BDA0003875889770000174
4) System operation constraints
(1) Power balance constraint
Figure BDA0003875889770000175
(2) Wind power output constraint
Figure BDA0003875889770000176
(3) System standby constraints
The standby cost of the thermal power unit is considered in the daily scheduling optimization target, and the standby of each unit needs to be accurately calculated at the moment, so that the system standby constraint of the daily scheduling is different from that of the daily scheduling, and the system standby constraint is shown in the following formula:
Figure BDA0003875889770000177
(4) system initial frequency change rate constraint under high power disturbance
Figure BDA0003875889770000178
In the method, in the process of the invention,
Figure BDA0003875889770000179
is the system initial frequency change rate limit under high power disturbance.
(5) System steady-state frequency difference constraint under high-power disturbance
Figure BDA00038758897700001710
In the method, in the process of the invention,
Figure BDA0003875889770000181
is the steady-state frequency difference limit value of the system under high-power disturbance.
(6) System maximum frequency difference constraint under high-power disturbance
Figure BDA0003875889770000182
In the method, in the process of the invention,
Figure BDA0003875889770000183
is the maximum frequency difference limit value of the system under high power disturbance.
In step C, the model solution results are as follows:
1) Thermal power generating unit: start-stop state, planned output, positive standby capacity, negative standby capacity, primary frequency modulation steady-state power variation under low power disturbance, and primary frequency modulation steady-state power variation under high power disturbance
2) And (3) energy storage of a battery: working state, charge and discharge power, residual energy, positive standby capacity, negative standby capacity, emergency power support, primary frequency modulation steady-state power variation under small power disturbance, and primary frequency modulation steady-state power variation under large power disturbance
3) Other: wind power plan output, system frequency index under small power disturbance (initial frequency change rate, steady-state frequency difference, maximum frequency difference), system frequency index under large power disturbance (initial frequency change rate, steady-state frequency difference, maximum frequency difference), system operation cost
Example 2
The embodiment is developed around a day-to-day joint scheduling strategy of the high-proportion wind power system considering dynamic frequency response constraint, and comprises the following specific steps:
step A: the model of this embodiment is constructed as follows.
1) And (3) taking thermal power unit operation constraint, battery energy storage operation constraint and system operation constraint into consideration, and constructing a daily scheduling model by taking the minimum sum of thermal power unit operation cost, thermal power unit starting cost and waste wind punishment cost as an optimization target.
2) And taking thermal power unit operation constraint, battery energy storage operation constraint and system operation constraint into consideration, and constructing an intra-day scheduling model by taking the minimum sum of thermal power unit operation cost, thermal power unit standby cost and abandoned wind punishment cost as an optimization target.
3) In the model, specific mathematical expressions are detailed in a day-ahead scheduling model and a day-in scheduling model of the high-proportion wind power system which are considered and constrained by dynamic frequency response and are described in the step B of the invention.
And (B) step (B): the parameters of the present embodiment are set as follows.
1) Embodiment operating environment: in the embodiment, the test is carried out on a computer with the CPU model of Intel Xeon Gold 2.70GHz and the memory of 256GB, the day-ahead scheduling model and the day-in scheduling model are both called by MATLAB R2022a to solve, and the solver selects Gurobi 9.1.
2) Embodiments optimize time scale: and B, a high-proportion wind power system day-to-day joint scheduling architecture which is described in the step B and takes dynamic frequency response constraints into consideration.
3) Embodiment topology: the topology is shown in fig. 5.
4) Embodiment thermal power generating unit parameters: the thermal power plant parameters are shown in table 2.
TABLE 2 thermal power generating unit parameters
Figure BDA0003875889770000191
5) Example battery energy storage parameters: the battery storage parameters are shown in table 3.
Table 3 battery energy storage parameters
Figure BDA0003875889770000192
6) Example load parameters: the daily load prediction curve is shown in fig. 6, and the daily load prediction curve is shown in fig. 7.
7) Example wind power parameters: the power prediction curve before 1 day of the wind farm is shown in fig. 8, and the power prediction curve in the day is shown in fig. 9. The power prediction curve before 2 days of the wind farm is shown in fig. 10, and the power prediction curve within the day is shown in fig. 11.
8) Example other parameters: other parameters of the system are shown in table 4.
TABLE 4 other parameters of the system
Figure BDA0003875889770000201
Step C: and carrying out optimization solution on the embodiment, and analyzing the result.
In order to verify the effectiveness of the day-to-day joint scheduling strategy of the high-proportion wind power system considering dynamic frequency response constraint, 3 groups of embodiment scenes are set: the day-ahead and day-in scheduling stages of the scene A consider dynamic frequency response constraints, namely a model constructed by the method; scene B is considered only in the day-ahead scheduling stage, and is not considered in the day; scene C was not considered until and during the day. Carrying out optimization solution on 3 groups of scenes, wherein the solution results mainly comprise: the cost of the 3 groups of scenes is shown in table 5, the start-stop plan of the thermal power generating unit is shown in fig. 12, and the output and standby plans are shown in fig. 13. The battery energy storage charge-discharge power and standby schedule are shown in fig. 14, the battery energy storage emergency power support schedule of scenario a is shown in fig. 15, and the dynamic frequency response index pairs of 3 sets of scenarios are shown in fig. 16.
TABLE 5 example 1 optimization results-System running cost
Figure BDA0003875889770000202
As can be seen from table 5, the cost of scene A, B was increased by 3.718% and 1.435%, respectively, based on scene C. In combination with the analysis in fig. 12 and fig. 13 (a), the scenario C follows the economy principle, and the large-capacity unit is preferably arranged to fully emit, and under the condition of meeting the load demand, the startup quantity of the thermal power unit is smaller than that of the scenario A, B. In contrast, in order to meet the constraint of dynamic frequency response of day-ahead scheduling, more medium-small capacity units are added to improve the inertial response and primary frequency modulation capability of the system, and the economy of the units is relatively poor, so that the cost of the scene B is improved. In order to avoid the frequency breakdown of the system caused by high-power disturbance, the output of the high-capacity unit is reduced on the basis of the scene B, so that the power shortage caused by the maximum single machine fault is reduced, and the cost of the scene A is further increased.
As can be seen from fig. 13 (a), all the thermal power units in the scenario a are not operated at the minimum technical output, and the scenario B, C arranges the medium-sized and small-sized units as the output supplements of the large-sized units to operate at the minimum technical output according to the economical principle. The method is characterized in that the design of the power output plan of the scene A machine set is required to meet the constraint of daily scheduling dynamic frequency response, and when power disturbance of sudden load drop or sudden wind power increase occurs in the system, the automatic speed regulation system of the machine set acts and controls the machine set to reduce the output, so that a load reduction space is required to be reserved for the machine set.
As can be seen from fig. 13 (b), (c) and fig. 14, the system standby in the 3-group scenario is preferentially borne by the battery energy storage with higher economy and faster response speed. For the positive standby of the thermal power generating unit, the thermal power generating unit is mainly provided by a small-capacity unit in operation, on one hand, the positive standby of the thermal power generating unit is more economical, and on the other hand, the large-capacity unit is basically in a full-power state. The negative standby of the thermal power generating unit in the scene B, C is opposite, and is mainly provided by a large-capacity unit because the small-capacity unit is mostly operated at the minimum technical output. The medium-small capacity unit in the scene A reserves a load-reducing space for meeting primary frequency modulation requirements, so that negative standby can be provided by the medium-small capacity unit, and the economy is higher.
As can be seen from fig. 15, for most of the time, when a high power disturbance occurs in the scene a system, the battery energy storage will operate in a full power discharge condition. The battery energy storage has the advantages of fast working condition conversion, high regulation rate, short response time delay and the like, and can provide a large amount of emergency power support in a short time. For a portion of the time, the battery energy storage does not provide emergency power support. In conjunction with the analysis of fig. 13 (a), the maximum single machine output is small in the above period, so that the frequency safety requirement can be met through the inertia response of the system and the primary frequency modulation link action.
As can be seen from fig. 16, under the low-power disturbance, the dynamic frequency response index of the scene A, B is the same, meets the safety requirement and is superior to the scene C, and the initial frequency change rate and the steady-state frequency difference of the scene C have a partial period exceeding the limit value. The scene A, B is used for scheduling in the future, so that the number of the thermal power generating units started is increased, and the inertial response and primary frequency modulation capacity of the system are improved. And the scene C arranges a start-stop plan of the thermal power generating unit according to an economy principle, so that the frequency safety requirement of the system is ignored, and the disturbance rejection capability of the system is poor.
Under high-power disturbance, the dynamic frequency response index is scene A, B, C from good to bad in sequence, each period of scene A meets the safety requirement, and part of the period of scene B, C exceeds the limit value. The method is characterized in that the dynamic frequency response constraint under high-power disturbance is considered in the daily scheduling of the scene A, and the system has the capability of bearing the high-power disturbance such as single machine fault without low-frequency load shedding and frequency collapse by reasonably arranging the means such as standby of a unit, emergency power support of battery energy storage, and low maximum single machine output.
Example 2 summary
By combining the steps of the embodiment 2, the day-to-day joint scheduling strategy of the high-proportion wind power system considering dynamic frequency response constraint can give consideration to the system operation economical requirement and the frequency safety requirement, and the system can maintain the initial frequency change rate, the steady-state frequency difference and the maximum frequency difference within a specified range under the expected low-power disturbance and high-power disturbance by reasonably arranging the start-stop, the output and the standby plans of the thermal power unit and the battery energy storage in the high-proportion wind power system.
It will be readily appreciated by those skilled in the art that the foregoing description is merely a preferred embodiment of the invention and is not intended to limit the invention, but any modifications, equivalents, improvements or alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.

Claims (4)

1. The day-day combined scheduling method of the high-proportion wind power system is characterized by comprising the following steps of:
step A: constructing a system dynamic frequency response model under low-power disturbance and high-power disturbance and solving a dynamic frequency response index; the low-power disturbance forms are the maximum error step power disturbance of the load and wind power in the system, the high-power disturbance forms are the superposition of the maximum error step power disturbance of the load, the maximum error step power disturbance of the wind power and the single machine fault step power disturbance of the thermal power unit, and the frequency response indexes comprise an initial frequency change rate, a steady-state frequency difference and a maximum frequency difference;
and (B) step (B): taking thermal power unit operation constraint, battery energy storage operation constraint and system operation constraint into consideration, and constructing a day-ahead scheduling model by taking the minimum sum of thermal power unit operation cost, thermal power unit starting cost and waste wind punishment cost as an optimization target; taking thermal power unit operation constraint, battery energy storage operation constraint and system operation constraint into consideration, and constructing an intra-day scheduling model by taking the minimum sum of thermal power unit operation cost, thermal power unit standby cost and abandoned wind punishment cost as an optimization target;
step C: solving the day-ahead scheduling model and the day-in scheduling model to obtain a high-proportion wind power system optimization scheduling result meeting an optimization target;
in the step A, the transfer function of the dynamic frequency response model of the system under the low-power disturbance is shown as follows:
Figure FDA0004191901150000011
wherein P is Lde Predicting a maximum error for the load; n (N) W The number of wind farms in the system;
Figure FDA0004191901150000012
predicting the maximum error for the output of the wind farm n; kappa (kappa) L 、λ L 、α L 、β L Specific calculation method for transformation coefficient of transfer function of dynamic frequency response model of system under low-power disturbanceThe following are provided:
Figure FDA0004191901150000013
wherein k is G Equivalent inertia coefficient of the system;
Figure FDA0004191901150000021
equivalent virtual inertia and frequency droop coefficients of battery energy storage in the system are respectively; mu (mu) equ 、/>
Figure FDA0004191901150000022
Respectively equivalent adjustment difference, proportion and integral coefficient of the thermal power generating unit in the system; k (k) Ld Is the load frequency response coefficient; />
Figure FDA0004191901150000023
Load power at rated frequency;
in the step A, the dynamic frequency response index of the system under the low-power disturbance is as follows:
1) Initial rate of frequency change
Figure FDA0004191901150000024
2) Steady state frequency difference
Figure FDA0004191901150000025
3) Maximum frequency difference
Figure FDA0004191901150000026
The value is beta L And alpha is L 2 The size relationship between the two is affected, and the following is discussed:
①β L ＞α L 2 and is also provided with
Figure FDA0004191901150000027
Wherein->
Figure FDA0004191901150000028
Figure FDA0004191901150000029
②β L ＞α L 2 And is also provided with
Figure FDA00041919011500000210
Wherein->
Figure FDA00041919011500000211
Figure FDA00041919011500000212
③β L ＝α L 2
Figure FDA00041919011500000213
④β L ＜α L 2
Figure FDA0004191901150000031
Wherein τ os The time from the beginning of disturbance to the time when the system frequency difference reaches the maximum value;
in the step A, the transfer function of the dynamic frequency response model of the system under high-power disturbance is shown as follows:
Figure FDA0004191901150000032
wherein N is G For the number of thermal power units in the system, the subscript m is the number of the fault thermal power unit, and the value of the subscript m is 1-N G Between them;
Figure FDA0004191901150000033
for the thermal power generating unit i, the number of rising edges after stepped is +.>
Figure FDA0004191901150000034
The number range is->
Figure FDA0004191901150000035
L i The height of a single-stage ladder is reserved for the i steps of the thermal power generating unit; />
Figure FDA0004191901150000036
The method comprises the steps of (1) reserving the triggering time of the jth rising edge for a step i of the thermal power generating unit, wherein the starting time is the disturbance occurrence time; p (P) St,H The total step power of the system under high-power disturbance comprises various types of power disturbance and emergency power support quantity of battery energy storage; kappa (kappa) H 、λ H 、α H 、β H Transformation coefficient of transfer function of dynamic frequency response model of system under high-power disturbance, calculation method and kappa L 、λ L 、α L 、β L The same, the only difference is kappa H 、λ H 、α H 、β H None of the parameters contains the relevant parameters of the fault thermal power unit m;
in the step A, the dynamic frequency response index of the system under high-power disturbance is as follows:
1) Initial rate of frequency change
Figure FDA0004191901150000037
2) Steady state frequency difference
Figure FDA0004191901150000038
Wherein->
Figure FDA0004191901150000039
The positive standby capacity of the thermal power unit i;
3) Maximum frequency difference
Figure FDA00041919011500000310
Is subject to beta H And alpha is H 2 The size relationship between the two is affected, and the following is discussed:
①β H ＞α H 2 time, order
Figure FDA00041919011500000311
q i ＝sgn(p i ) The method comprises the steps of carrying out a first treatment on the surface of the Wherein sgn (p) is a sign function; epsilon ∑ 、σ ∑ For the maximum frequency difference conversion coefficient, the calculation method is as follows:
Figure FDA0004191901150000041
according to the value of theta, beta H ＞α H 2 Maximum frequency difference in case
Figure FDA0004191901150000042
Is further subdivided into the calculation formula:
a)θ≤0
Figure FDA0004191901150000043
τ os ＝(θ+π)/ω
b)θ＞0
Figure FDA0004191901150000044
τ os ＝θ/ω
②β H ＝α H 2 time, let q i ＝sgn(p i ) Maximum frequency difference conversion coefficient epsilon ∑ 、σ ∑ The calculation method comprises the following steps:
Figure FDA0004191901150000045
maximum frequency difference
Figure FDA0004191901150000046
The following formula is shown:
Figure FDA0004191901150000047
τ os ＝(1-ε ∑ /σ ∑ )/α H
③β H ＜α H 2 time, order
Figure FDA0004191901150000048
q i ＝sgn(p i ) Maximum frequency difference conversion coefficient epsilon ∑ 、σ ∑ The calculation method comprises the following steps:
Figure FDA0004191901150000049
maximum frequency difference
Figure FDA00041919011500000410
The following formula is shown:
Figure FDA0004191901150000051
wherein, gamma i The climbing rate of the thermal power unit i;
Figure FDA0004191901150000052
the standby starting time delay of the thermal power generating unit i is set; />
Figure FDA0004191901150000053
The full standby time of the thermal power generating unit i; />
Figure FDA0004191901150000054
Representing the step number corresponding to the step standby curve of the thermal power generating unit i when the frequency drops to the lowest point; τ os Is the time that passes from the onset of the disturbance to the time when the system frequency difference reaches a maximum.
2. The method for joint day-ahead and day-in scheduling of a high-ratio wind power system according to claim 1, wherein in the step B, the optimization objective of the day-ahead scheduling model is as follows:
minF d-a ＝C G,run +C G,on +C wind
wherein C is G,run The running cost of the thermal power generating unit is; c (C) G,on The starting cost of the thermal power generating unit is; c (C) wind Punishment of costs for wind curtailment; the specific calculation method of each cost is shown as follows:
Figure FDA0004191901150000055
wherein T is d-a Scheduling a total time length for the day before;
Figure FDA0004191901150000056
the electricity purchasing cost coefficient of the thermal power generating unit i; />
Figure FDA0004191901150000057
The active output of the thermal power generating unit i in the t period; />
Figure FDA0004191901150000058
The method is the single starting cost of the thermal power unit i; />
Figure FDA0004191901150000059
Starting the thermal power generating unit i for a period t, wherein the starting-up state is 1, and the starting-up state is 0 otherwise; c pen Punishing a cost coefficient for the wind curtailment; />
Figure FDA00041919011500000510
The predicted output and the actual output of the wind power plant n in the t period are respectively.
3. The method for joint daily-daily scheduling of a high-ratio wind power system according to claim 1, wherein in the step B, the optimization objective of the daily scheduling model is as follows:
minF i-d ＝C G,run +C G,res +C wind
wherein C is G,run The running cost of the thermal power generating unit is; c (C) G,res Standby cost for the thermal power generating unit; c (C) wind Punishment of costs for wind curtailment; the specific calculation method of each cost is shown as follows:
Figure FDA0004191901150000061
wherein T is i-d Scheduling a total time length for a day;
Figure FDA0004191901150000062
the electricity purchasing cost coefficient of the thermal power generating unit i; />
Figure FDA0004191901150000063
The active output of the thermal power generating unit i in the t period; />
Figure FDA0004191901150000064
Starting the thermal power generating unit i for a period t, wherein the starting-up state is 1, and the starting-up state is 0 otherwise; />
Figure FDA0004191901150000065
Positive and negative standby capacities of the thermal power generating unit i in the t period are respectively set; />
Figure FDA0004191901150000066
Figure FDA0004191901150000067
Positive and negative standby cost coefficients of the thermal power unit i are respectively; c pen Punishing a cost coefficient for the wind curtailment; />
Figure FDA0004191901150000068
Figure FDA0004191901150000069
The predicted output and the actual output of the wind power plant n in the t period are respectively.
4. A high-proportion wind power system day-ahead-day joint scheduling system, comprising: a computer readable storage medium and a processor;
the computer-readable storage medium is for storing executable instructions;
the processor is configured to read executable instructions stored in the computer readable storage medium and execute the method for joint day-ahead-day scheduling of the high-ratio wind power system according to any one of claims 1 to 3.
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